76 research outputs found
Trichlorobacter ammonificans, a dedicated acetate-dependent ammonifier with a novel module for dissimilatory nitrate reduction to ammonia
No full textDissimilatory nitrate reduction to ammonia (DNRA) is a common biochemical process in the nitrogen cycle in natural and man-made habitats, but its significance in wastewater treatment plants is not well understood. Several ammonifying Trichlorobacter strains (former Geobacter) were previously enriched from activated sludge in nitrate-limited chemostats with acetate as electron (e) donor, demonstrating their presence in these systems. Here, we isolated and characterized the new species Trichlorobacter ammonificans strain G1 using a combination of low redox potential and copper-depleted conditions. This allowed purification of this DNRA organism from competing denitrifiers. T. ammonificans is an extremely specialized ammonifier, actively growing only with acetate as e-donor and carbon source and nitrate as e-acceptor, but H2 can be used as an additional e-donor. The genome of G1 does not encode the classical ammonifying modules NrfAH/NrfABCD. Instead, we identified a locus encoding a periplasmic nitrate reductase immediately followed by an octaheme cytochrome c that is conserved in many Geobacteraceae species. We purified this octaheme cytochrome c protein (TaNiR), which is a highly active dissimilatory ammonifying nitrite reductase loosely associated with the cytoplasmic membrane. It presumably interacts with two ferredoxin subunits (NapGH) that donate electrons from the menaquinol pool to the periplasmic nitrate reductase (NapAB) and TaNiR. Thus, the Nap-TaNiR complex represents a novel type of highly functional DNRA module. Our results indicate that DNRA catalyzed by octaheme nitrite reductases is a metabolic feature of many Geobacteraceae, representing important community members in various anaerobic systems, such as rice paddy soil and wastewater treatment facilities.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.BT/Environmental BiotechnologyBT/Industriele Microbiologi
Response to "Miliary tuberculosis disease complicated by Pott's abscess in an infant: Seven-year follow-up"
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COVID-19 Induced Hemophagocytic Lymphohistiocytosis in a Patient with Novel Homozygous UNC13D Gene Variant.
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Clinical Evaluations of 49 Cases with Kawasaki Disease: A Retrospective Cohort Study
No full textObjective: Kawasaki disease is the most common cause of an acute febrile vasculitis with unknown etiology after Henoch-Schnlein purpura ( HSP). The aim of our study is to contribute data on Kawasaki disease, which may lead to severe cardiac complications and death when it is misdiagnosed or not treated appropriately
On selecting the initial cluster centers in the K-means algorithm
No full textK-means clustering algorithm which is a process of separating n number of points into K clusters according to the predefined value of K is one of the clustering analysis algorithms. This algorithm has many applications in analysis of clustering. There are many factors that affect performance of the K-means clustering algorithm to better cluster. One of these is selecting initial cluster centers. In this study, two methods have been proposed for selecting the initial cluster centers. The proposed methods have been tested on data sets taken from UCI database and compared with the method proposed by Erisoglu etc and K-means algorithm which generates initial centers randomly. The comparison results show that the K-means algorithm which uses the proposed methods converges to better clustering results. © 2017 IEEE.The first author gratefully acknowledges the support of TUBITAK (The Scientific and Technological Research Council of Turkey) 2228 program. -
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