Separating the wheat from the chaff: a prioritisation pipeline for the analysis of metabolomics datasets

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful and widely applied method for the study of biological systems, biomarker discovery and pharmacological interventions. LC-MS measurements are, however, significantly complicated by several technical challenges, including: (1) ionisation suppression/enhancement, disturbing the correct quantification of analytes, and (2) the detection of large amounts of separate derivative ions, increasing the complexity of the spectra, but not their information content. Here we introduce an experimental and analytical strategy that leads to robust metabolome profiles in the face of these challenges. Our method is based on rigorous filtering of the measured signals based on a series of sample dilutions. Such data sets have the additional characteristic that they allow a more robust assessment of detection signal quality for each metabolite. Using our method, almost 80% of the recorded signals can be discarded as uninformative, while important information is retained. As a consequence, we obtain a broader understanding of the information content of our analyses and a better assessment of the metabolites detected in the analyzed data sets. We illustrate the applicability of this method using standard mixtures, as well as cell extracts from bacterial samples. It is evident that this method can be applied in many types of LC-MS analyses and more specifically in untargeted metabolomics.

     

Taking into account water use impacts in the LCA of biofuels: an Argentinean case study

Purpose  

The assessment of biofuels has until now mainly focused on energy demand and greenhouse gas emissions. Only little attention has been given to other impacts, although the general importance of water use for the life cycle assessment (LCA) of agricultural products has been recognized in recent publications. The aim of this work is to assess in detail the water consumption along a biofuel production chain taking into account irrigation efficiencies, levels of water scarcity, and type of feedstock, and to integrate those results in a full LCA. Furthermore, we compare the results for biofuels from various feedstocks and regions with conventional petrol.     

Comparison of the adhesion and proliferation characteristics of HUVEC and two endothelial cell lines (CRL 2922 and CRL 2873) on various substrata

Endothelial cell coverage of blood-contacting devices is crucial to their eventual success in the clinic. Two established human cell lines derived from HUVEC (human umbilical vascular endothelial cells), CRL 2922 and CRL 2873, have been widely utilized to study and model endothelial cell biology. However, it is not clear if these two cell lines would be useful for modeling primary endothelial cell interaction with newly-formulated biomaterials in tissue engineering applications. Hence, this study was conducted to compare the adhesion and proliferation characteristics of HUVEC grown on seven different substrata, tissue culture polystyrene (TCPS), gelatin, chitosan, poly-L-lysine, hyaluronan, poly-L-lactic acid (PLLA), and polylactic-co-glycolic acid (PLGA). The short-term adhesive behavior (2 h) of HUVEC on the various substrata was not closely-replicated by either CRL 2873 or CRL 2922. This was likely because the 2 h timeframe is too short for identification of differences in the interaction among the three cell types grown on various substrata. There was much faster proliferation of CRL 2922 on all seven substrata when compared to HUVEC and CRL 2873. Moreover, the proliferation rates of CRL 2922 on the various substrata showed little variation. In contrast, HUVEC and CRL 2873 displayed similar trends in proliferation rates, with gelatin and TCPS yielding the highest rates, and PLLA and PLGA yielding the lowest rates. Hence, CRL 2873 is better suited for modeling primary endothelial cell interaction with newly-formulated biomaterials than CRL 2922. The advantage of using CRL 2873 over HUVEC for biomaterial screening is that it is immortalized and displays much less inter-batch variability than primary culture.     

Learning Biomarkers of Pluripotent Stem Cells in Mouse

Pluripotent stem cells are able to self-renew, and to differentiate into all adult cell types. Many studies report data describing these cells, and characterize them in molecular terms. Machine learning yields classifiers that can accurately identify pluripotent stem cells, but there is a lack of studies yielding minimal sets of best biomarkers (genes/features). We assembled gene expression data of pluripotent stem cells and non-pluripotent cells from the mouse. After normalization and filtering, we applied machine learning, classifying samples into pluripotent and non-pluripotent with high cross-validated accuracy. Furthermore, to identify minimal sets of best biomarkers, we used three methods: information gain, random forests and a wrapper of genetic algorithm and support vector machine (GA/SVM). We demonstrate that the GA/SVM biomarkers work best in combination with each other; pathway and enrichment analyses show that they cover the widest variety of processes implicated in pluripotency. The GA/SVM wrapper yields best biomarkers, no matter which classification method is used. The consensus best biomarker based on the three methods is Tet1, implicated in pluripotency just recently. The best biomarker based on the GA/SVM wrapper approach alone is Fam134b, possibly a missing link between pluripotency and some standard surface markers of unknown function processed by the Golgi apparatus.     

A consensus map of QTLs controlling the root length of maize

Despite their low carbon (C) content, most subsoil horizons contribute to more than half of the total soil C stocks, and therefore need to be considered in the global C cycle. Until recently, the properties and dynamics of C in deep soils was largely ignored. The aim of this review is to synthesize literature concerning the sources, composition, mechanisms of stabilisation and destabilization of soil organic matter (SOM) stored in subsoil horizons. Organic C input into subsoils occurs in dissolved form (DOC) following preferential flow pathways, as aboveground or root litter and exudates along root channels and/or through bioturbation. The relative importance of these inputs for subsoil C distribution and dynamics still needs to be evaluated. Generally, C in deep soil horizons is characterized by high mean residence times of up to several thousand years. With few exceptions, the carbon-to-nitrogen (C/N) ratio is decreasing with soil depth, while the stable C and N isotope ratios of SOM are increasing, indicating that organic matter (OM) in deep soil horizons is highly processed. Several studies suggest that SOM in subsoils is enriched in microbial-derived C compounds and depleted in energy-rich plant material compared to topsoil SOM. However, the chemical composition of SOM in subsoils is soil-type specific and greatly influenced by pedological processes. Interaction with the mineral phase, in particular amorphous iron (Fe) and aluminum (Al) oxides was reported to be the main stabilization mechanism in acid and near neutral soils. In addition, occlusion within soil aggregates has been identified to account for a great proportion of SOM preserved in subsoils. Laboratory studies have shown that the decomposition of subsoil C with high residence times could be stimulated by addition of labile C. Other mechanisms leading to destabilisation of SOM in subsoils include disruption of the physical structure and nutrient supply to soil microorganisms. One of the most important factors leading to protection of SOM in subsoils may be the spatial separation of SOM, microorganisms and extracellular enzyme activity possibly related to the heterogeneity of C input. As a result of the different processes, stabilized SOM in subsoils is horizontally stratified. In order to better understand deep SOM dynamics and to include them into soil C models, quantitative information about C fluxes resulting from C input, stabilization and destabilization processes at the field scale are necessary.     

Biotreibstoffe aus Entwicklungsländern

Biofuels from developing countries The pressure for reducing greenhouse gas emissions, rising oil prices, but also the lobbying by the agricultural sector and the automotive industry have induced the recent boom on biofuels. Due to limited land availability, competition with food production and high overall environmental impacts, the sustainability market potential for biofuels is assumed to be significantly smaller than 10% of global fuel consumption. Nevertheless, niches for the sustainable production and use of biofuels exist especially in developing countries. It is often more sustainable to use biomass feedstock for local supply of electricity and heat than producing biofuels for export.     

Enhancement of auxin sensitivity in Ranunculus sceleratus by ethylene: A mechanism to escape from hypoxia under temporary submergence

We analyzed auxin-induced and ethylene-enhanced elongation of petiole segments in Ranunculus sceleratus L. The early time course of elongation in petiolar segments was monitored with a computer-based video digitizer system. The application of ethylene-releasing ethrel slightly increased the elongation rate in the absence of IAA. When IAA alone was applied, elongation increased after a latent period of approximately 30 min. Maximal elongation rate was attained immediately after the latent period, and then the stabilized steady rate was recorded. During this phase, addition of ethrel strongly increased the elongation rate after a period of approximately 18 min. Although ethrel could acidify the growth medium, only a small part of the enhanced elongation was due to an acid-growth effect. Most of the growth stimulation was auxin-dependent and must be ascribed to the presence of ethylene. In the presence of ethrel, the log-concentration-response curve of IAA appeared to be shifted to the left. This kinetic analysis indicates an increase, due to ethylene, in the sensitivity of the R. sceleratus petiole to auxin, which results in inducing rapid growth to escape from hypoxia under temporary submergence.     

Small RNA sequencing reveals miR-642a-3p as a novel adipocyte-specific microRNA and miR-30 as a key regulator of human adipogenesis

Background  

In severe obesity, as well as in normal development, the growth of adipose tissue is the result of an increase in adipocyte size and numbers, which is underlain by the stimulation of adipogenic differentiation of precursor cells. A better knowledge of the pathways that regulate adipogenesis is therefore essential for an improved understanding of adipose tissue expansion. As microRNAs (miRNAs) have a critical role in many differentiation processes, our study aimed to identify the role of miRNA-mediated gene silencing in the regulation of adipogenic differentiation.     

Arginine interactions with anatase TiO2 (100) surface and the perturbation of 49Ti NMR chemical shifts – a DFT investigation: relevance to Renu-Seeram bio solar cell

Density functional theoretical calculations have been utilized to investigate the interaction of the amino acid arginine with the (100) surface of anatase and the reproduction of experimentally measured ⁴⁹Ti NMR chemical shifts of anatase. Significant binding of arginine through electrostatic interaction and hydrogen bonds of the arginine guanidinium protons to the TiO₂ surface oxygen atoms is observed, allowing attachment of proteins to titania surfaces in the construction of bio-sensitized solar cells. GIAO-B3LYP/6-31G(d) NMR calculation of a three-layer model based on the experimental structure of this TiO₂ modification gives an excellent reproduction of the experimental value (-927 ppm) within +/- 7 ppm, however, the change in relative chemical shifts, EFGs and CSA suggest that the effect of the electrostatic arginine binding might be too small for experimental detection.