TY - JOUR A1 - Yarman, Aysu A1 - Scheller, Frieder W. T1 - How reliable is the electrochemical readout of MIP sensors? JF - Sensors N2 - Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin MIP films. However, this process generates an overall signal, which may include nonspecific interactions with the nonimprinted surface and adsorption at the electrode surface in addition to (specific) binding to the cavities. Redox-active low-molecular-weight targets and metalloproteins enable a more specific direct quantification of their binding to MIPs by measuring the faradaic current. The in situ characterization of enzymes, MIP-based mimics of redox enzymes or enzyme-labeled targets, is based on the indication of an electroactive product. This approach allows the determination of both the activity of the bio(mimetic) catalyst and of the substrate concentration. KW - molecularly imprinted polymers KW - electropolymerization KW - direct electron KW - transfer KW - catalysis KW - redox marker KW - gate effect Y1 - 2020 U6 - https://doi.org/10.3390/s20092677 SN - 1424-8220 VL - 20 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Leimkühler, Silke T1 - The biosynthesis of the molybdenum cofactors in Escherichia coli JF - Environmental microbiology N2 - The biosynthesis of the molybdenum cofactor (Moco) is highly conserved among all kingdoms of life. In all molybdoenzymes containing Moco, the molybdenum atom is coordinated to a dithiolene group present in the pterin-based 6-alkyl side chain of molybdopterin (MPT). In general, the biosynthesis of Moco can be divided into four steps in in bacteria: (i) the starting point is the formation of the cyclic pyranopterin monophosphate (cPMP) from 5 '-GTP, (ii) in the second step the two sulfur atoms are inserted into cPMP leading to the formation of MPT, (iii) in the third step the molybdenum atom is inserted into MPT to form Moco and (iv) in the fourth step bis-Mo-MPT is formed and an additional modification of Moco is possible with the attachment of a nucleotide (CMP or GMP) to the phosphate group of MPT, forming the dinucleotide variants of Moco. This review presents an update on the well-characterized Moco biosynthesis in the model organism Escherichia coli including novel discoveries from the recent years. KW - periplasmic nitrate reductase KW - biotin sulfoxide reductase KW - in-vitro-synthesis KW - n-oxide reductase KW - crystal-structure KW - molybdopterin synthase KW - formate dehydrogenase KW - rhodobacter-capsulatus KW - xanthine dehydrogenase KW - converting factor Y1 - 2020 U6 - https://doi.org/10.1111/1462-2920.15003 SN - 1462-2912 SN - 1462-2920 VL - 22 IS - 6 SP - 2007 EP - 2026 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - van Rees, Charles B. A1 - Waylen, Kerry A. A1 - Schmidt-Kloiber, Astrid A1 - Thackeray, Stephen J. A1 - Kalinkat, Gregor A1 - Martens, Koen A1 - Domisch, Sami A1 - Lillebo, Ana A1 - Hermoso, Virgilio A1 - Grossart, Hans-Peter A1 - Schinegger, Rafaela A1 - Decleer, Kris A1 - Adriaens, Tim A1 - Denys, Luc A1 - Jaric, Ivan A1 - Janse, Jan H. A1 - Monaghan, Michael T. A1 - De Wever, Aaike A1 - Geijzendorffer, Ilse A1 - Adamescu, Mihai C. A1 - Jähnig, Sonja C. T1 - Safeguarding freshwater life beyond 2020 BT - recommendations for the new global biodiversity framework from the European experience JF - Conservation letters N2 - Plans are currently being drafted for the next decade of action on biodiversity-both the post-2020 Global Biodiversity Framework of the Convention on Biological Diversity (CBD) and Biodiversity Strategy of the European Union (EU). Freshwater biodiversity is disproportionately threatened and underprioritized relative to the marine and terrestrial biota, despite supporting a richness of species and ecosystems with their own intrinsic value and providing multiple essential ecosystem services. Future policies and strategies must have a greater focus on the unique ecology of freshwater life and its multiple threats, and now is a critical time to reflect on how this may be achieved. We identify priority topics including environmental flows, water quality, invasive species, integrated water resources management, strategic conservation planning, and emerging technologies for freshwater ecosystem monitoring. We synthesize these topics with decades of first-hand experience and recent literature into 14 special recommendations for global freshwater biodiversity conservation based on the successes and setbacks of European policy, management, and research. Applying and following these recommendations will inform and enhance the ability of global and European post-2020 biodiversity agreements to halt and reverse the rapid global decline of freshwater biodiversity. KW - climate change KW - conservation KW - ecosystem services KW - rivers KW - sustainable KW - development goals KW - water resources KW - wetlands Y1 - 2020 U6 - https://doi.org/10.1111/conl.12771 SN - 1755-263X VL - 14 IS - 1 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Apriyanto, Ardha A1 - Compart, Julia A1 - Fettke, Jörg T1 - A review of starch, a unique biopolymer - structure, metabolism and in planta modifications JF - Plant science : an international journal of experimental plant biology N2 - Starch is a complex carbohydrate polymer produced by plants and especially by crops in huge amounts. It consists of amylose and amylopectin, which have alpha-1,4-and alpha-1,6-linked glucose units. Despite this simple chemistry, the entire starch metabolism is complex, containing various (iso)enzymes/proteins. However, whose interplay is still not yet fully understood. Starch is essential for humans and animals as a source of nutrition and energy. Nowadays, starch is also commonly used in non-food industrial sectors for a variety of purposes. However, native starches do not always satisfy the needs of a wide range of (industrial) applications. This review summarizes the structural properties of starch, analytical methods for starch characterization, and in planta starch modifications. KW - starch KW - starch structure KW - starch surface KW - starch modifications; KW - analytics Y1 - 2022 U6 - https://doi.org/10.1016/j.plantsci.2022.111223 SN - 0168-9452 SN - 1873-2259 VL - 318 PB - Elsevier Science CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Omranian, Sara A1 - Nikoloski, Zoran A1 - Grimm, Dominik G. T1 - Computational identification of protein complexes from network interactions: Present state, challenges, and the way forward BT - present state, challenges, and the way forward JF - Computational and structural biotechnology journal N2 - Physically interacting proteins form macromolecule complexes that drive diverse cellular processes. Advances in experimental techniques that capture interactions between proteins provide us with protein-protein interaction (PPI) networks from several model organisms. These datasets have enabled the prediction and other computational analyses of protein complexes. Here we provide a systematic review of the state-of-the-art algorithms for protein complex prediction from PPI networks proposed in the past two decades. The existing approaches that solve this problem are categorized into three groups, including: cluster-quality-based, node affinity-based, and network embedding-based approaches, and we compare and contrast the advantages and disadvantages. We further include a comparative analysis by computing the performance of eighteen methods based on twelve well-established performance measures on four widely used benchmark protein-protein interaction networks. Finally, the limitations and drawbacks of both, current data and approaches, along with the potential solutions in this field are discussed, with emphasis on the points that pave the way for future research efforts in this field. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/). KW - Protein Complex Prediction KW - Protein-Protein interaction network KW - Network KW - Clustering Algorithms KW - Network embedding Y1 - 2022 U6 - https://doi.org/10.1016/j.csbj.2022.05.049 SN - 2001-0370 VL - 20 SP - 2699 EP - 2712 PB - Research Network of Computational and Structural Biotechnology (RNCSB) CY - Gotenburg ER -