Structural analysis of the reductase component AnfH of iron-only nitrogenase from Azotobacter vinelandii.

Biological nitrogen fixation, the conversion of atmospheric dinitrogen into bioavailable ammonium, is exclusively catalyzed by the enzyme nitrogenase that is present in nitrogen-fixing organisms, the diazotrophs. So far, three different nitrogenase variants, encoded in their corresponding, distinct gene clusters, have been found in nature. Each one of these consists of a catalytic dinitrogenase component and a unique, ATP-dependent reductase, the Fe protein. The three variant nitrogenases differ in the composition of the active site and contain either molybdenum, vanadium or only iron in the dinitrogenase component. Here we present the 2.0 Å resolution crystal structure of the ADP-bound reductase component AnfH of the iron-only nitrogenase from the model diazotroph Azotobacter vinelandii. A comparison of this structure with the ones reported for the two other Fe protein homologs NifH and VnfH in the ADP-bound state shows that all are adopting the same conformation. However, cross-reactivity assays with the three nitrogenase homologs revealed AnfH to be compatible with iron-only nitrogenase and to a lesser degree with the vanadium-containing enzyme, but not with molybdenum nitrogenase.

finDr: A web server for in silico D-peptide ligand identification.

In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ.

Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42% in the control run and by 12% with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80% for northern China, with large increments over the Liaoning Province and the North China Plain (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets and observationally constrained box model simulations of OH and HO2. Running a CAM-Chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29% for CO, 18% for ozone, 11% for HO2, and 27% for OH. Longer-lived anthropogenic VOCs whose model errors are correlated with CO are also improved, while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.

Standardization and quality management in next-generation sequencing.

DNA sequencing continues to evolve quickly even after > 30 years. Many new platforms suddenly appeared and former established systems have vanished in almost the same manner. Since establishment of next-generation sequencing devices, this progress gains momentum due to the continually growing demand for higher throughput, lower costs and better quality of data. In consequence of this rapid development, standardized procedures and data formats as well as comprehensive quality management considerations are still scarce. Here, we listed and summarized current standardization efforts and quality management initiatives from companies, organizations and societies in form of published studies and ongoing projects. These comprise on the one hand quality documentation issues like technical notes, accreditation checklists and guidelines for validation of sequencing workflows. On the other hand, general standard proposals and quality metrics are developed and applied to the sequencing workflow steps with the main focus on upstream processes. Finally, certain standard developments for downstream pipeline data handling, processing and storage are discussed in brief. These standardization approaches represent a first basis for continuing work in order to prospectively implement next-generation sequencing in important areas such as clinical diagnostics, where reliable results and fast processing is crucial. Additionally, these efforts will exert a decisive influence on traceability and reproducibility of sequence data.

Evaluation of a 32-channel versus a 12-channel head coil for high-resolution post-contrast MRI in giant cell arteritis (GCA) at 3T.

The aim of this study was to evaluate the diagnostic value of a 32-channel head coil for the characterization of mural inflammation patterns in the superficial cranial arteries in patients with giant cell arteritis (GCA) compared to a standard 12-channel coil at 3T MRI. 55 patients with suspected GCA underwent high resolution T1-weighted post-contrast MRI at 3T to detect inflammation related vessel wall enhancement using both coils. To account for different time delays between contrast agent injection and sequence acquisition, the patients were divided into two cohorts: 27 patients were examined with the 32-channel coil first and 28 patients with the 12-channel coil first. Images were evaluated by two blinded readers with regard to image quality, artifact level and arteries' inflammation according to a standardized ranking scale; furthermore signal-to-noise ratio (SNR) measurements were performed at three locations. Identification of arteries' inflammation was achieved with both coils with excellent inter-observer agreement (κ=0.89 for 12-channel and κ=0.96 for 32-channel coil). Regarding image grading, the inter-observer variability was moderate for the 12-channel (κ=0.5) and substantial for the 32-channel coil (κ=0.63). Significantly higher SNR and improved image quality (p<0.01) were obtained with the 32-channel coil in either coil order. Image quality for depiction of the superficial cranial arteries was superior for the 32-channel coil. For standardized GCA diagnosis, the 12-channel coil was sufficient.

Screening and genetic characterization of thermo-tolerant Synechocystis sp. PCC6803 strains created by adaptive evolution.

BACKGROUND: Temperature tolerance is an important aspect for commercial scale outdoor cultivation of microalgae and cyanobacteria. While various genes are known to be related to Synechocystis sp. PCC6803's heat shock response, there is very limited published data concerning the specific genes involved in long term thermal tolerance. We have previously used random mutagenesis and adaptive evolution to generate a mixture of strains of Synechocystis sp. PCC6803 with significantly increased thermal tolerance. The genetic modifications leading to the phenotypes of the newly generated strains are the focus of this work. RESULTS: We used a custom screening platform, based on 96-deepwell microplate culturing in an in house designed cultivation chamber integrated in a liquid handling robot for screening and selection; in addition we also used a more conventional system. The increased thermal tolerances of the isolated monoclonal strains were validated in larger bioreactors and their whole genomes sequenced. Comparison of the sequence information to the parental wild type identified various mutations responsible for the enhanced phenotypes. Among the affected genes identified are clpC, pnp, pyk2, sigF, nlpD, pyrR, pilJ and cya1. CONCLUSIONS: The applied methods (random mutagenesis, in vivo selection, screening, validation, whole genome sequencing) were successfully applied to identify various mutations, some of which are very unlikely to have been identified by other approaches. Several of the identified mutations are found in various strains and (due to their distribution) are likely to have occurred independently. This, coupled with the relatively low number of affected genes underscores the significance of these specific mutations to convey thermal tolerance in Synechocystis.