Abstract: Binding of the SARS-CoV-2 S-glycoprotein to cell receptors is vital for the entry of the virus into cells and subsequent infection. ACE2 is the main cell receptor for SARS-CoV-2, which can attach to the C-terminal receptor-binding domain (RBD) of the SARS-CoV-2 S-glycoprotein. The GRP78 receptor plays an anchoring role, which attaches to the RBD and increases the chance of other RBDs binding to ACE2. Although high levels of reactive oxygen and nitrogen species (RONS) are produced during viral infections, it is not clear how they affect the RBD structure and its binding to ACE2 and GRP78. In this research, we apply molecular dynamics simulations to study the effect of oxidation of the highly reactive cysteine (Cys) amino acids of the RBD on its binding to ACE2 and GRP78. The interaction energy of both ACE2 and GRP78 with the whole RBD, as well as with the RBD main regions, is compared in both the native and oxidized RBDs. Our results show that the interaction energy between the oxidized RBD and ACE2 is strengthened by 155 kJ/mol, increasing the binding of the RBD to ACE2 after oxidation. In addition, the interaction energy between the RBD and GRP78 is slightly increased by 8 kJ/mol after oxidation, but this difference is not significant. Overall, these findings highlight the role of RONS in the binding of the SARS-CoV-2 S-glycoprotein to host cell receptors and suggest an alternative mechanism by which RONS could modulate the entrance of viral particles into the cells.

Abstract: A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

Abstract: A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass of the diffraction pattern at one probe position at a time, it is able to update the resulting image each time a new probe position is visited without storing any intermediate diffraction patterns. The results show clear features at high spatial frequency, such as atomic column positions. It is also demonstrated that some common post-processing methods, such as band-pass filtering, can be directly integrated in the real-time processing flow. Compared with other reconstruction methods, the proposed method produces high-quality reconstructions with good noise robustness at extremely low memory and computational requirements. An efficient, interactive open source implementation of the concept is further presented, which is compatible with frame-based, as well as event-based camera/file types. This method provides the attractive feature of immediate feedback that microscope operators have become used to, for example, conventional high-angle annular dark field STEM imaging, allowing for rapid decision-making and fine-tuning to obtain the best possible images for beam-sensitive samples at the lowest possible dose.

Abstract: Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 x 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision <= 6 x 10(-4) (0.06%).

Abstract: High-energy-density nickel (Ni)-rich cathode materials are used in commercial lithium (Li)-ion batteries for electric vehicles, but they suffer from severe structural degradation upon cycling. Planar gliding and microcracking are seeds for fatal mechanical fracture, but their origin remains unclear. Herein, we show that “layer-by -layer delithiation”is activated at high voltages during the charge process when the “lattice collapse”(a characteristic high-voltage lattice evolution in Ni-rich cathodes) occurs. Layer-by-layer deli-thiation is evidenced by direct observation of the consecutive lattice collapse using in situ scanning transmission electron micro-scopy (STEM). The collapsing of the lattice initiates in the expanded planes and consecutively extends to the whole crystal. Localized strain will be induced at lattice-collapsing interface where planar gliding and intragranular microcracks are generated to release this strain. Our study reveals that layer-by-layer delithia-tion during lattice collapse is the fundamental origin of the mechanical instability in single-crystalline Ni-rich cathodes.

Abstract: The oxygen release of layered cathodes causes many battery failures, but the underlying mechanism in an actual working cathode is still elusive as it involves secondary agglomerates that introduce complicated boundary structures. Here, we report a general structure instability on the mismatch boundaries driven by interfacial gliding-it introduces a shear stress causing a distortion of the metal-oxygen octahedra framework that reduces its kinetic stability. The migration of cations and diffusion of oxygen vacancies continue to degrade the whole particle from the boundary to the interior, followed by the formation of nano-sized cracks on the fast-degrading interfaces. This work reveals a robust chemical and mechanical interplay on the oxygen release inherent to the intergranular boundaries of layered cathodes. It also suggests that radially patterned columnar grains with low-angle planar boundaries would be an efficient approach to mitigate the boundary oxygen release.

Abstract: Quantitative PCR (qPCR) is broadly used as the gold standard to quantify microbial community fractions in environmental microbiology and biotechnology. Benchmarking efforts to ensure the comparability of qPCR data for environmental bioprocesses are still scarce. Also, for partial nitritation/anammox (PN/A) systems systematic investigations are still missing, rendering meta-analysis of reported trends and generic insights potentially precarious. We report a baseline investigation of the variability of qPCR-based analyses for microbial communities applied to PN/A systems. Round-robin testing was performed for three PN/A biomass samples in six laboratories, using the respective in-house DNA extraction and qPCR protocols. The concentration of extracted DNA was significantly different between labs, ranged between 2.7 and 328 ng mg−1 wet biomass. The variability among the qPCR abundance data of different labs was very high (1−7 log fold) but differed for different target microbial guilds. DNA extraction caused maximum variation (3–7 log fold), followed by the primers (1–3 log fold). These insights will guide environmental scientists and engineers as well as treatment plant operators in the interpretation of qPCR data.

Abstract: Anammox, the oxidation of ammonium with nitrite, is a key microbial process in the nitrogen cycle. Under mesophilic conditions (below 40 °C), it is widely implemented to remove nitrogen from wastewaters lacking organic carbon. Despite evidence of the presence of anammox bacteria in high-temperature environments, reports on the cultivation of thermophilic anammox bacteria are limited to a short-term experiment of 2 weeks. This study showcases the adaptation of a mesophilic inoculum to thermophilic conditions, and its characterization. First, an attached growth technology was chosen to obtain the process. In an anoxic fixed-bed biofilm bioreactor (FBBR), a slow linear temperature increase from 38 to over 48 °C (0.05–0.07 °C d−1) was imposed to the community over 220 days, after which the reactor was operated at 48 °C for over 200 days. Maximum total nitrogen removal rates reached up to 0.62 g N L−1 d−1. Given this promising performance, a suspended growth system was tested. The obtained enrichment culture served as inoculum for membrane bioreactors (MBR) operated at 50 °C, reaching a maximum total nitrogen removal rate of 1.7 g N L−1 d−1 after 35 days. The biomass in the MBR had a maximum specific anammox activity of 1.1 ± 0.1 g NH4+-N g−1 VSS d−1, and the growth rate was estimated at 0.075–0.19 d−1. The thermophilic cultures displayed nitrogen stoichiometry ratios typical for mesophilic anammox: 0.93–1.42 g NO2--Nremoved g−1 NH4+-Nremoved and 0.16–0.35 g NO3--Nproduced g−1 NH4+-Nremoved. Amplicon and Sanger sequencing of the 16S rRNA genes revealed a disappearance of the original “Ca. Brocadia” and “Ca. Jettenia” taxa, yielding Planctomycetes members with only 94–95% similarity to “Ca. Brocadia anammoxidans” and “Ca. B. caroliniensis”, accounting for 45% of the bacterial FBBR community. The long-term operation of thermophilic anammox reactors and snapshot views on the nitrogen stoichiometry, kinetics and microbial community open up the development path of thermophilic partial nitritation/anammox. A first economic assessment highlighted that treatment of sludge reject water from thermophilic anaerobic digestion of sewage sludge may become attractive.

Abstract: Nitrification and denitrification, the key biological processes for thermophilic nitrogen removal, have separately been established in bioreactors at 50 °C. A well-characterized set of kinetic parameters is essential to integrate these processes while safeguarding the autotrophs performing nitrification. Knowledge on thermophilic nitrifying kinetics is restricted to isolated or highly enriched batch cultures, which do not represent bioreactor conditions. This study characterized the stoichiometry and kinetics of two thermophilic (50 °C) nitrifying communities. The most abundant ammonia oxidizing archaea (AOA) were related to the Nitrososphaera genus, clustering relatively far from known species Nitrososphaera gargensis (95.5% 16S rRNA gene sequence identity). The most abundant nitrite oxidizing bacteria (NOB) were related to Nitrospira calida (97% 16S rRNA gene sequence identity). The nitrification biomass yield was 0.200.24 g VSS g−1 N, resulting mainly from a high AOA yield (0.160.20 g VSS g−1 N), which was reflected in a high AOA abundance in the community (5776%) compared to NOB (511%). Batch-wise determination of decay rates (AOA: 0.230.29 d−1; NOB: 0.320.43 d−1) rendered an overestimation compared to in situ estimations of overall decay rate (0.0260.078 d−1). Possibly, the inactivation rate rather than the actual decay rate was determined in batch experiments. Maximum growth rates of AOA and NOB were 0.120.15 d−1 and 0.130.33 d−1 respectively. NOB were susceptible to nitrite, opening up opportunities for shortcut nitrogen removal. However, NOB had a similar growth rate and oxygen affinity (0.150.55 mg O2 L−1) as AOA and were resilient towards free ammonia (IC50 > 16 mg NH3-N L−1). This might complicate NOB outselection using common practices to establish shortcut nitrogen removal (SRT control; aeration control; free ammonia shocks). Overall, the obtained insights can assist in integrating thermophilic conversions and facilitate single-sludge nitrification/denitrification.

Abstract: Oxygen inhibits anammox, a bioconversion executed by anoxic ammonium oxidizing bacteria (AnAOB). Nonetheless, oxygen is mostly found in the proximity of AnAOB in nitrogen removal applications, being a substrate for nitritation. The experiments performed to date were mostly limited to batch activity tests where AnAOB activity is estimated during oxygen exposure. However, little attention has been paid to the recovery and reversibility of activity following aerobic conditions, of direct relevance for bioreactor operation. In this work, anoxic and autotrophic reactor cultivation at 20 degrees C yielded an enriched microbial community in AnAOB, consisting for 75% of a member of the genus Brocadia. High-resolution kinetic data were obtained with online ammonium measurements and further processed with a newly developed Python data pipeline. The experimentally obtained AnAOB response showed complete inhibition until micro-aerobic conditions were reached again (<0.02 mg O-2 L-1). After oxygen inhibition, AnAOB recovered gradually, with recovery times of 5-37 h to reach a steady-state activity, dependent on the perceived inhibition. The recovery immediately after inhibition was lowest when exposed to higher oxygen concentrations (range: 0.5-8 mg O-2 L-1) with long contact times (range: 9-24 h). The experimental data did not fit well with a conventional 'instant recovery' Monod-type inhibition model. Yet, the fit greatly improved by incorporating a dynamic growth rate formula accurately describing gradual activity recovery. With the upgraded model, long-term kinetic simulations for partial nitritation/anammox (PN/A) with intermittent aeration showed a decrease in growth rate compared to the instant recovery mode. These results indicate that recovery of AnAOB after oxygen exposure was previously overlooked. It is recommended to account for this effect in the intensification of partial nitritation/anammox. (C) 2018 Elsevier Ltd. All rights reserved.