Experimental investigation of taxon-specific response of alkaline phosphatase activity in natural freshwater phytoplankton

It is widely accepted that alkaline phosphatase activity (APA) is an efficient indicator of phosphate limitation in freshwater phytoplankton communities. In this study, we investigated whether the response in APA to phosphate limitation differs among the taxa in a mixed phytoplankton assemblage. We used the new enzyme-labeled fluorescence (ELF) technique, which allows microscopic detection of phosphate limitation in individual cells of multiple species. The most prominent findings of this study were that alkaline phosphatase (AP) was induced in many, but not all taxa and that different taxa, as well as different cells within a single taxon, experienced different degrees of phosphate stress under the same environmental conditions. Our approach was to manipulate the limiting nutrient in a natural freshwater phytoplankton community by incubating lake water in the laboratory. We induced nitrogen (N) or phosphate limitation through additions of inorganic nutrients. Both the ELF assay and bulk APA indicated that the lake phytoplankton were not phosphate limited at the start of the experiment. During the experiment, several chlorophyte taxa (e.g., Eudorina and an unidentified solitary spiny coccoid) were driven to phosphate limitation when inorganic N was added, as evidenced by a higher percentage of ELF-labeled cells relative to controls, whereas other chlorophyte taxa such as Actinastrum and Dicryosphaerium were not phosphate stressed under these conditions. In the phosphate-limited treatments, little or no ELF labeling was observed in any cyanobacterial taxa. Furthermore, all taxa observed after the ELF labeling procedure (>10-mum fraction) were labeled with ELF at least on one occasion, demonstrating the wide applicability of the ELF method. By using ELF labeling in tandem with bulk APA, the resolution and analysis of phosphate limitation was increased, allowing the identification of specific phosphate-stressed taxa

Electrospray Ionization with High-Resolution Mass Spectrometry as a Tool for Lignomics: Lignin Mass Spectrum Deconvolution

Capability to characterize lignin, lignocellulose, and their degradation products is essential for development of new renewable feedstocks. Electrospray ionization high-resolution time-offlight mass spectrometry (ESI HR TOF MS) method was developed expanding the lignomics toolkit while targeting the simultaneous detection of low and high molecular weight (MW) lignin species. The effect of a broad range of electrolytes and various ionization conditions on ion formation and ionization effectiveness was studied using a suite of mono-, di- and triarene lignin model compounds as well as intact lignin. Contrary to the previous studies, the positive ionization mode was found to be more effective for methoxy-substituted arenes and polyphenols, i.e., species of a broadly varied MW structurally similar to the native lignin. For the first time, we report an effective formation of multiply charged species of lignin with the subsequent mass spectrum deconvolution in the presence of 100 mmol·L-1 formic acid in the positive ESI mode. The developed method enabled the detection of lignin species with an MW between 150 and 9,000 Da or higher, depending on the mass analyzer. The obtained Mn and Mw values of 1,500 and 2,500 Da, respectively, were in good agreement with those determined by gel permeation chromatography. Furthermore, the deconvoluted ESI mass spectrum was similar to that obtained with matrixassisted laser desorption/ionization (MALDI) TOF MS, yet featuring a higher signal-to-noise ratio. The formation of multiply charged species was confirmed with ESI ion mobility HR Q-TOF MS

Towards Flexibility in Future Industrial Manufacturing: A Global Framework for Self-organization of Production Cells

Conference of 7th International Conference on Ambient Systems, Networks and Technologies, ANT 2016 and the 6th International Conference on Sustainable Energy Information Technology, SEIT 2016 ; Conference Date: 23 May 2016 Through 26 May 2016; Conference Code:121607International audienceThe future of manufacturing leads to flexible industrial facilities in which production lines or systems are composed by several production cells. Production cells can be reorganized and reconfigured by introducing new devices, equipment, functionalities or even by re-configuring the communication network. In this context, machine-to-machine communication does not only provide a transport layer for monitoring and control, but also provide a high-level distributed service framework and data management system. In this contribution, the authors address the challenge to manage the self-organization of production cells by means of a global framework. This framework bases on the following technologies: RobotML for the scenario description, OPC UA for service orchestration, object memories for distributed data sharing, Frama-C/Para-C for code verification and SDN for network reconfiguration. This framework has been deployed within a use case involving the SYBOT collaborative robot and a reconfigurable Raspberry-Pi based camera to enhance human operator safety. Experiments show that from a high-level description of the scenario, it was possible to automatically orchestrate at the OPC UA level the different reconfigurations of the production cell