570 Biowissenschaften; Biologie
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Knowledge discovery in biomedical data using supervised methods assumes that the data contain structure relevant to the class structure if a classifier can be trained to assign a case to the correct class better than by guessing. In this setting, acceptance or rejection of a scientific hypothesis may depend critically on the ability to classify cases better than randomly, without high classification performance being the primary goal. Random forests are often chosen for knowledge-discovery tasks because they are considered a powerful classifier that does not require sophisticated data transformation or hyperparameter tuning and can be regarded as a reference classifier for tabular numerical data. Here, we report a case where the failure of random forests using the default hyperparameter settings in the standard implementations of R and Python would have led to the rejection of the hypothesis that the data contained structure relevant to the class structure. After tuning the hyperparameters, classification performance increased from 56% to 65% balanced accuracy in R, and from 55% to 67% balanced accuracy in Python. More importantly, the 95% confidence intervals in the tuned versions were to the right of the value of 50% that characterizes guessing-level classification. Thus, tuning provided the desired evidence that the data structure supported the class structure of the data set. In this case, the tuning made more than a quantitative difference in the form of slightly better classification accuracy, but significantly changed the interpretation of the data set. This is especially true when classification performance is low and a small improvement increases the balanced accuracy to over 50% when guessing.
A Bayesian framework to estimate diversification rates and their variation through time and space
(2011)
Background: Patterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov chain Monte Carlo methods offer a promising framework to incorporate phylogenetic uncertainty when estimating rates of diversification.
Results: We introduce a new approach to estimate diversification rates in a Bayesian framework over a distribution of trees under various constant and variable rate birth-death and pure-birth models, and test it on simulated phylogenies. Furthermore, speciation and extinction rates and their posterior credibility intervals can be estimated while accounting for non-random taxon sampling. The framework is particularly suitable for hypothesis testing using Bayes factors, as we demonstrate analyzing dated phylogenies of Chondrostoma (Cyprinids) and Lupinus (Fabaceae). In addition, we develop a model that extends the rate estimation to a meta-analysis framework in which different data sets are combined in a single analysis to detect general temporal and spatial trends in diversification.
Conclusions: Our approach provides a flexible framework for the estimation of diversification parameters and hypothesis testing while simultaneously accounting for uncertainties in the divergence times and incomplete taxon sampling.
The Wood-Ljungdahl pathway of anaerobic CO(2) fixation with hydrogen as reductant is considered a candidate for the first life-sustaining pathway on earth because it combines carbon dioxide fixation with the synthesis of ATP via a chemiosmotic mechanism. The acetogenic bacterium Acetobacterium woodii uses an ancient version of the pathway that has only one site to generate the electrochemical ion potential used to drive ATP synthesis, the ferredoxin-fueled, sodium-motive Rnf complex. However, hydrogen-based ferredoxin reduction is endergonic, and how the steep energy barrier is overcome has been an enigma for a long time. We have purified a multimeric [FeFe]-hydrogenase from A. woodii containing four subunits (HydABCD) which is predicted to have one [H]-cluster, three [2Fe2S]-, and six [4Fe4S]-clusters consistent with the experimental determination of 32 mol of Fe and 30 mol of acid-labile sulfur. The enzyme indeed catalyzed hydrogen-based ferredoxin reduction, but required NAD(+) for this reaction. NAD(+) was also reduced but only in the presence of ferredoxin. NAD(+) and ferredoxin reduction both required flavin. Spectroscopic analyses revealed that NAD(+) and ferredoxin reduction are strictly coupled and that they are reduced in a 1:1 stoichiometry. Apparently, the multimeric hydrogenase of A. woodii is a soluble energy-converting hydrogenase that uses electron bifurcation to drive the endergonic ferredoxin reduction by coupling it to the exergonic NAD(+) reduction.
Anaerobic ammonium oxidation (anammox) is a major process in the biogeochemical nitrogen cycle in which nitrite and ammonium are converted to dinitrogen gas and water through the highly reactive intermediate hydrazine. So far, it is unknown how anammox organisms convert the toxic hydrazine into nitrogen and harvest the extremely low potential electrons (−750 mV) released in this process. We report the crystal structure and cryo electron microscopy structures of the responsible enzyme, hydrazine dehydrogenase, which is a 1.7 MDa multiprotein complex containing an extended electron transfer network of 192 heme groups spanning the entire complex. This unique molecular arrangement suggests a way in which the protein stores and releases the electrons obtained from hydrazine conversion, the final step in the globally important anammox process.
Since hyperactivity of the protein kinase DYRK1A is linked to several neurodegenerative disorders, DYRK1A inhibitors have been suggested as potential therapeutics for Down syndrome and Alzheimer’s disease. Most published inhibitors to date suffer from low selectivity against related kinases or from unfavorable physicochemical properties. In order to identify DYRK1A inhibitors with improved properties, a series of new chemicals based on [b]-annulated halogenated indoles were designed, synthesized, and evaluated for biological activity. Analysis of crystal structures revealed a typical type-I binding mode of the new inhibitor 4-chlorocyclohepta[b]indol-10(5H)-one in DYRK1A, exploiting mainly shape complementarity for tight binding. Conversion of the DYRK1A inhibitor 8-chloro-1,2,3,9-tetrahydro-4H-carbazol-4-one into a corresponding Mannich base hydrochloride improved the aqueous solubility but abrogated kinase inhibitory activity.
The German Working Group on Vegetation Databanks has held annual meetings since 2002 with financial support by the German Federal Agency for Nature Conservation. Ca. 215 members are regularly informed through a mailing-list. The 2008 meeting was hosted by University of Oldenburg’s Landscape Ecology Group and was attended by 72 participants from 15 countries. Software demonstrations of vegetation databanks Turboveg and VegetWeb as well as plant trait databanks LEDA and BiolFlor opened the workshop. There were lecture sessions on trait databanks, recalibration of ecological indicator values and new developments in the field of vegetation databanks. Working groups were devoted to an initiative to build a meta-databank of existing vegetation databanks in Germany and to mathematical modelling of species habitats. In 2009 the 8th workshop will be held on "Vegetation Databanks and Biodindication" at the University of Greifswald.
50 years of amino acid hydrophobicity scales : revisiting the capacity for peptide classification
(2016)
Background: Physicochemical properties are frequently analyzed to characterize protein-sequences of known and unknown function. Especially the hydrophobicity of amino acids is often used for structural prediction or for the detection of membrane associated or embedded β-sheets and α-helices. For this purpose many scales classifying amino acids according to their physicochemical properties have been defined over the past decades. In parallel, several hydrophobicity parameters have been defined for calculation of peptide properties. We analyzed the performance of separating sequence pools using 98 hydrophobicity scales and five different hydrophobicity parameters, namely the overall hydrophobicity, the hydrophobic moment for detection of the α-helical and β-sheet membrane segments, the alternating hydrophobicity and the exact ß-strand score.
Results: Most of the scales are capable of discriminating between transmembrane α-helices and transmembrane β-sheets, but assignment of peptides to pools of soluble peptides of different secondary structures is not achieved at the same quality. The separation capacity as measure of the discrimination between different structural elements is best by using the five different hydrophobicity parameters, but addition of the alternating hydrophobicity does not provide a large benefit. An in silico evolutionary approach shows that scales have limitation in separation capacity with a maximal threshold of 0.6 in general. We observed that scales derived from the evolutionary approach performed best in separating the different peptide pools when values for arginine and tyrosine were largely distinct from the value of glutamate. Finally, the separation of secondary structure pools via hydrophobicity can be supported by specific detectable patterns of four amino acids.
Conclusion: It could be assumed that the quality of separation capacity of a certain scale depends on the spacing of the hydrophobicity value of certain amino acids. Irrespective of the wealth of hydrophobicity scales a scale separating all different kinds of secondary structures or between soluble and transmembrane peptides does not exist reflecting that properties other than hydrophobicity affect secondary structure formation as well. Nevertheless, application of hydrophobicity scales allows distinguishing between peptides with transmembrane α-helices and β-sheets. Furthermore, the overall separation capacity score of 0.6 using different hydrophobicity parameters could be assisted by pattern search on the protein sequence level for specific peptides with a length of four amino acids.
5-Lipoxygenase contributes to PPAR [gamma] activation in macrophages in response to apoptotic cells
(2012)
Background: One hallmark contributing to immune suppression during the late phase of sepsis is macrophage polarization to an anti-inflammatory phenotype upon contact with apoptotic cells (AC). Taking the important role of the nuclear receptor PPARγ for this phenotype switch into consideration, it remains elusive how AC activate PPARγ in macrophages. Therefore, we were interested to characterize the underlying principle.
Methods: Apoptosis was induced by treatment of Jurkat T cells for 3 hours with 0.5 μg/ml staurosporine. Necrotic cells (NC) were prepared by heating cells for 20 minutes to 65°C. PPARγ activation was followed by stably transducing RAW264.7 macrophages with a vector encoding the red fluorescent protein mRuby after PPARγ binding to 4 × PPRE sites downstream of the reporter gene sequence. This readout was established by treatment with the PPARγ agonist rosiglitazone (1 μM) and AC (5:1). Twenty-four hours after stimulation, mRuby expression was analysed by fluorescence microscopy. Lipid rafts of AC, NC, as well as living cells (LC) were enriched by sucrose gradient centrifugation. Fractions were analysed for lipid raft-associated marker proteins. Lipid rafts were incubated with transduced RAW264.7 macrophages as described above. 5-Lipoxygenase (5-LO) involvement was verified by pharmacological inhibition (MK-866, 1 μM) and overexpression.
Results: Assuming that the molecule responsible for PPARγ activation in macrophages is localized in the cell membrane of AC, most probably associated to lipid rafts, we isolated lipid rafts from AC, NC and LC. Mass spectrometric analysis of lipid rafts of AC showed the expression of 5-LO, whereas lipid rafts of LC did not. Moreover, incubating macrophages with lipid rafts of AC induced mRuby expression. In contrast, lipid rafts of NC and LC did not. To verify the involvement of 5-LO in activating PPARγ in macrophages, Jurkat T cells were incubated for 30 minutes with the 5-LO inhibitor MK-866 (1 μM) before apoptosis induction. In line with our hypothesis, these AC did not induce mRuby expression. Finally, although living Jurkat T cells overexpressing 5-LO did not activate PPARγ in macrophages, mRuby expression was significantly increased when AC were generated from 5-LO overexpressing compared with wild-type Jurkat cells.
Conclusion: Our results suggest that induction of apoptosis activates 5-LO, localizing to lipid rafts, necessary for PPARγ activation in macrophages. Therefore, it will be challenging to determine whether 5-LO activity in AC, generated from other cell types, correlates with PPARγ activation, contributing to an immune-suppressed phenotype in macrophages.
This work aimed to investigate the regulation and activity of 5-lipoxygenase (5-LO), the central enzyme in leukotriene biosynthesis, in two colorectal cancer cell lines. The leukotriene pathway is positively correlated with the progression of several solid malignancies; however, factors regulating 5-LO expression and activity in tumors are poorly understood.
Cancer development, as well as cancer progression, are strongly dependent on the tumor microenvironment. In the conventional monolayer culture of cancer cell lines, cell-matrix and cell-cell interactions present in native tumors are absent. Furthermore, it is already known that various colon cancer cell lines dysregulate several important signaling pathways due to 3D growth. Therefore, the expression of the leukotriene cascade in HT-29 and HCT-116 colorectal cancer cells was investigated within a three-dimensional context using multicellular tumor spheroids to mimic a more physiological environment compared to conventional cell culture. Especially the expression of 5-LO, cPLA2α, and LTA4 hydrolase was altered due to threedimensional (3D) cell growth, which was investigated by qPCR and Western blot analysis. High cellular density in monolayer cultures led to similar results. The observed 5-LO upregulation was found inversely correlated with cell proliferation, determined by cell cycle analysis, and activation of PI3K/mTORC-2- and MEK-1/ERK-dependent pathways, determined using pharmacological pathway inhibition, stable shRNA knockdown cell lines, and analysis via qPCR and Western blot analysis. Following, the transcription factor E2F1 and its target gene MYBL2 were identified to play a role in the repression of 5-LO during cell proliferation. For this purpose, several stable MYBL2 over-expression and ALOX5 reporter cell lines were prepared and analyzed. Since 5-LO was already identified as a direct p53 target gene, the influence of p53, which is variably expressed in the cell lines (HT-29, p53 R273H mut; HCT-116 p53 wt; HCT-116 p53 KO), was investigated as well. Furthermore, HCT-116 cells carrying a p53 knockout were investigated. The PI3K/mTORC-2- and MEK-1/ERK-dependent suppression of 5-LO was also found in tumor cells from other origins (Capan-2, Caco-2, MCF-7), which was determined using pharmacological pathway inhibition and following analysis via qPCR. This suggests that the identified mechanism might apply to other tumor entities as well.
5-LO activity was previously described as attenuated in HT-29 and HCT-116 cells compared to polymorphonuclear leukocytes, which express a highly active 5-LO. However, the present study showed that the enzyme activity is indeed low but inducible in HT-29 and HCT-116 cells. Of note, the general lipid mediator profile and the mediator concentrations were comparable to those of M2 macrophages. Finally, the analysis of substrate availability in HT-29 and HCT-116 cells revealed a vast difference between formed metabolite concentrations and supplemented fatty acid concentrations, indicating that the substrates are either transformed into lipoxygenase-independent metabolites or are esterified into the cellular membrane.
In summary, the data presented in this work demonstrate that 5-LO expression and activity are tightly regulated in HT-29 and HCT-116 cells and fine-tuned due to environmental conditions. The cells suppress 5-LO during proliferation but upregulate the expression and activity of the enzyme under cellular stress-triggering conditions. This implies a possible role of 5-LO in manipulating the tumor stroma to support a tumor-promoting microenvironment.