Isolation and identification of antiplasmodial N-alkylamides from Spilanthes acmella flowers using centrifugal partition chromatography and ESI-IT-TOF-MS

The development of new antiplasmodial drugs is of primary importance due to the growing problem of multi-drug resistance of malaria parasites. Spilanthes acmella, a plant traditionally used for the treatment of toothache, was targeted as a lead for its potential antiplasmodial activity. A systematic approach for investigating a suitable centrifugal partition chromatography (CPC) solvent system for N-alkylamides separation was reported. The partition behavior of three N-alkylamides has been studied using several biphasic solvent mixtures in search of an adequate CPC solvent system for this class of compounds. Major N-alkylamides in S. acmella were isolated from a methanolic crude extract of flowers by CPC with the solvent system heptanes-ethyl acetate-methanol-water (3:2:3:2, v/v/v/v). Four N-alkylamides were purified and the structures were illustrated by electrospray ionization-ion trap-time of flight-mass spectrometry (ESI-IT-TOF-MS), 1H nuclear magnetic resonance (1H NMR) and 13C nuclear magnetic resonance (13C NMR). The CPC fractions, which contained natural mixtures of phytochemicals, demonstrated significantly higher antiplasmodial activity compared to corresponding purified N-alkylamides, thus suggesting that interactions between these N-alkylamides may potentiate antiplasmodial bioactivity.     

Glycoside hydrolases as components of putative carbohydrate biosensor proteins in <Emphasis Type="Italic">Clostridium thermocellum</Emphasis>

The composition of the cellulase system in the cellulosome-producing bacterium, Clostridium thermocellum, has been reported to change in response to growth on different carbon sources. Recently, an extensive carbohydrate-sensing mechanism, purported to regulate the activation of genes coding for polysaccharide-degrading enzymes, was suggested. In this system, CBM modules, comprising extracellular components of RsgI-like anti-σ factors, were proposed to function as carbohydrate sensors, through which a set of cellulose utilization genes are activated by the associated σ^I-like factors. An extracellular module of one of these RsgI-like proteins (Cthe_2119) was annotated as a family 10 glycoside hydrolase, RsgI6-GH10, and a second putative anti-σ factor (Cthe_1471), related in sequence to Rsi24, was found to contain a module that resembles a family 5 glycoside hydrolase (termed herein Rsi24C-GH5). The present study examines the relevance of these two glycoside hydrolases as sensors in this signal-transmission system. The RsgI6-GH10 was found to bind xylan matrices but exhibited low enzymatic activity on this substrate. In addition, this glycoside hydrolase module was shown to interact with crystalline cellulose although no hydrolytic activity was detected on cellulosic substrates. Bioinformatic analysis of the Rsi24C-GH5 showed a glutamate-to-glutamine substitution that would presumably preclude catalytic activity. Indeed, the recombinant module was shown to bind to cellulose, but showed no hydrolytic activity. These observations suggest that these two glycoside hydrolases underwent an evolutionary adaptation to function as polysaccharide binding agents rather than enzymatic components and thus serve in the capacity of extracellular carbohydrate sensors.     

A secreted BMP antagonist, Cer1, fine tunes the spatial organization of the ureteric bud tree during mouse kidney development

The epithelial ureteric bud is critical for mammalian kidney development as it generates the ureter and the collecting duct system that induces nephrogenesis in dicrete locations in the kidney mesenchyme during its emergence. We show that a secreted Bmp antagonist Cerberus homologue (Cer1) fine tunes the organization of the ureteric tree during organogenesis in the mouse embryo. Both enhanced ureteric expression of Cer1 and Cer1 knock out enlarge kidney size, and these changes are associated with an altered three-dimensional structure of the ureteric tree as revealed by optical projection tomography. Enhanced Cer1 expression changes the ureteric bud branching programme so that more trifid and lateral branches rather than bifid ones develop, as seen in time-lapse organ culture. These changes may be the reasons for the modified spatial arrangement of the ureteric tree in the kidneys of Cer1+ embryos. Cer1 gain of function is associated with moderately elevated expression of Gdnf and Wnt11, which is also induced in the case of Cer1 deficiency, where Bmp4 expression is reduced, indicating the dependence of Bmp expression on Cer1. Cer1 binds at least Bmp2/4 and antagonizes Bmp signalling in cell culture. In line with this, supplementation of Bmp4 restored the ureteric bud tip number, which was reduced by Cer1+ to bring it closer to the normal, consistent with models suggesting that Bmp signalling inhibits ureteric bud development. Genetic reduction of Wnt11 inhibited the Cer1-stimulated kidney development, but Cer1 did not influence Wnt11 signalling in cell culture, although it did inhibit the Wnt3a-induced canonical Top Flash reporter to some extent. We conclude that Cer1 fine tunes the spatial organization of the ureteric tree by coordinating the activities of the growth-promoting ureteric bud signals Gndf and Wnt11 via Bmp-mediated antagonism and to some degree via the canonical Wnt signalling involved in branching.     

Cellulosomics, a gene-centric approach to investigating the intraspecific diversity and adaptation of Ruminococcus flavefaciens within the rumen

Background

The bovine rumen maintains a diverse microbial community that serves to break down indigestible plant substrates. However, those bacteria specifically adapted to degrade cellulose, the major structural component of plant biomass, represent a fraction of the rumen microbiome. Previously, we proposed scaC as a candidate for phylotyping Ruminococcus flavefaciens, one of three major cellulolytic bacterial species isolated from the rumen. In the present report we examine the dynamics and diversity of scaC-types both within and between cattle temporally, following a dietary switch from corn-silage to grass-legume hay. These results were placed in the context of the overall bacterial population dynamics measured using the 16S rRNA.

Principal Findings

As many as 117 scaC-types were estimated, although just nineteen were detected in each of three rumens tested, and these collectively accounted for the majority of all types present. Variation in scaC populations was observed between cattle, between planktonic and fiber-associated fractions and temporally over the six-week survey, and appeared related to scaC phylogeny. However, by the sixth week no significant separation of scaC populations was seen between animals, suggesting enrichment of a constrained set of scaC-types. Comparing the amino-acid translation of each scaC-type revealed sequence variation within part of the predicted dockerin module but strong conservation in the N-terminus, where the cohesin module is located.

Conclusions

The R. flavefaciens species comprises a multiplicity of scaC-types in-vivo. Enrichment of particular scaC-types temporally, following a dietary switch, and between fractions along with the phylogenetic congruence suggests that functional differences exist between types. Observed differences in dockerin modules suggest at least part of the functional heterogeneity may be conferred by scaC. The polymorphic nature of scaC enables the relative distribution of R. flavefaciens strains to be examined and represents a gene-centric approach to investigating the intraspecific adaptation of an important specialist population.     

On the botanic model of plant growth with intermediate vegetative-reproductive stage

The application of dynamic optimization to mathematical models of ontogenic biological growth has been the subject of much research [see e.g. . J. Theor. Biol. 33, 299-307]. Koz?owsky and Zió?ko [1988. Thor. Popul. Biol. 34, 118-129] and Zió?ko and Koz?owski [1995. IEEE Trans. Automat. Contr. 40(10), 1779-1783] presented a model with gradual transition from vegetative to reproductive growth. The central point of their model is a mixed state-control constraint on the rate of reproductive growth, which leads to a mixed vegetative-reproductive growth period. Their model is modified here in order to take into account the difference of photosynthesis use efficiency when energy is accumulated in the vegetative and in the reproductive organs of a plant, respectively. The simple assumption on correlation between photosynthesis and temperature permits us to modify the model in a form that is useful for changing climate. Unfortunately, the mathematical solution of the optimal control problem in Koz?owsky and Zió?ko (1988) and Zió?ko and Koz?owski (1995) is incorrect. The strict mathematical solution is presented here, the numerical example from is solved, and the results are compared. The influence of the length of the season and the relative photosynthesis use efficiency, as well as of the potential sink demand of the reproductive organs, on the location and duration of the mixed vegetative-reproduction period of growth is investigated numerically. The results show that the mixed growth period is increased and shifted toward the end of the season when the lengths of the season is increased. Additional details of the sensitivity analysis are also presented.     

Structural dynamics of nucleosome core particle: comparison with nucleosomes containing histone variants

The present study provides insights on the dominant mechanisms of motions of the nucleosome core particle and the changes in its functional dynamics in response to histone variants. Comparative analysis of the global dynamics of nucleosomes with native and variant H2A histones, using normal mode analysis revealed that the dynamics of the nucleosome is highly symmetric, and its interaction with the nucleosomal DNA plays a vital role in its regulation. The collective dynamics of nucleosomes are predicted to be dominated by two types of large-scale motions: (1) a global stretching-compression of nucleosome along the dyad axis by which the nucleosome undergoes a breathing motion with a massive distortion of nucleosomal DNA, modulated by histone-DNA interactions; and (2) the flipping (or bending) of both the sides of the nucleosome in an out-of-plane fashion with respect to the dyad axis, originated by the highly dynamic N-termini of H3 and (H2A.Z-H2B) dimer in agreement with the experimentally observed perturbed dynamics of the particular N-terminus under physiological conditions. In general, the nucleosomes with variant histones exhibit higher mobilities and weaker correlations between internal motions compared to the nucleosome containing ordinary histones. The differences are more pronounced at the L1 and L2 loops of the respective monomers H2B and H2A, and at the N-termini of the monomers H3 and H4, all of which closely interact with the wrapping DNA.     

The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging

The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.     

Feature selection and nearest centroid classification for protein mass spectrometry

Background  

The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard supervised classification algorithms can be employed, the "curse of dimensionality" needs to be solved. Due to the sheer amount of information contained within the mass spectra, most standard machine learning techniques cannot be directly applied. Instead, feature selection techniques are used to first reduce the dimensionality of the input space and thus enable the subsequent use of classification algorithms. This paper examines feature selection techniques for proteomic mass spectrometry.