Crystal structure of the Anabaena sensory rhodopsin transducer.

We present crystal structures of the Anabaena sensory rhodopsin transducer (ASRT), a soluble cytoplasmic protein that interacts with the first structurally characterized eubacterial retinylidene photoreceptor Anabaena sensory rhodopsin (ASR). Four crystal structures of ASRT from three different spacegroups were obtained, in all of which ASRT is present as a planar (C4) tetramer, consistent with our characterization of ASRT as a tetramer in solution. The ASRT tetramer is tightly packed, with large interfaces where the well-structured beta-sandwich portion of the monomers provides the bulk of the tetramer-forming interactions, and forms a flat, stable surface on one side of the tetramer (the beta-face). Only one of our four different ASRT crystals reveals a C-terminal alpha-helix in the otherwise all-beta protein, together with a large loop from each monomer on the opposite face of the tetramer (the alpha-face), which is flexible and largely disordered in the other three crystal forms. Gel-filtration chromatography demonstrated that ASRT forms stable tetramers in solution and isothermal microcalorimetry showed that the ASRT tetramer binds to ASR with a stoichiometry of one ASRT tetramer per one ASR photoreceptor with a K(d) of 8 microM in the highest affinity measurements. Possible mechanisms for the interaction of this transducer tetramer with the ASR photoreceptor via its flexible alpha-face to mediate transduction of the light signal are discussed

Going Global: Scaling the Artificial Intelligence Literacy Course to an International Audience

Introduction: Applications of artificial intelligence (AI) in radiology continue to increase every year, however most radiology residencies lack a dedicated AI education curriculum. Fundamental AI education resources are even more sparse for trainees in low- to middle-income countries and under-resourced healthcare systems. The AI Literacy Course assesses the effectiveness and scalability of a free, remote AI education curriculum to increase understanding of fundamental AI terms, methods, and applications in radiology among radiology trainees in the United States and internationally. Method: A week-long AI in radiology literacy course for radiology trainees was held October 3-7, 2022. Ten 30-minute lectures utilizing a remote learning format covered basic AI terms and methods, clinical applications of AI in radiology by three different subspecialties, and special topics lectures. A proctored, hands-on clinical AI session allowed participants to directly use an FDA-cleared, AI-assisted viewer and reporting system for advanced cancer. Pre- and post-course electronic surveys were distributed to assess participants’ knowledge of AI terminology and applications, as well as their interest in AI education. Results: A total of 25 residency programs throughout the US participated in the course with participants attending from 10 countries. An average of 150 participants viewed the course per day. Nearly all participants reported insufficient exposure to AI in their radiology training (95.8%). Participant knowledge of fundamental AI terms and methods increased after completion of the course, with an average pre-course evaluation of 8.3/15 and a post-course evaluation of 10.0/15 (p=0.01). Conclusion: The scalability of the AI Literacy Course demonstrates a viable model to bring accessible fundamental AI education to radiology trainees in the United States and internationally

Detection and assay of proteases using calf lens β-crystallin aggregate as substrate

The eye lens protein, βL-crystallin, aggregates and yields a turbid solution upon refolding from its denatured state. We have observed that the addition of trace amounts of protease results in clearing of this turbidity. Based on this observation, we have developed a simple and rapid method for the detection and assay of proteases. This assay can be performed in the pH range of 6.0–9.0. We could assay the activity of trypsin at a concentration as low as 5 μg/ml

Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities

Role of the Cytoplasmic Domain in Anabaena Sensory Rhodopsin Photocycling: Vectoriality of Schiff Base Deprotonation

Light-induced electric signals in intact E. coli cells generated by heterologously expressed full-length and C-terminally truncated versions of Anabaena sensory rhodopsin (ASR) demonstrate that the charge movements within the membrane-embedded part of the molecule are stringently controlled by the cytoplasmic domain. In particular, truncation inverts the direction of proton movement during Schiff base deprotonation from outward to cytoplasmic. Truncation also alters faster charge movements that occur before Schiff base deprotonation. Asp(217) as previously shown by FTIR serves as a proton acceptor in the truncated ASR but not in the full-length version, and its mutation to Asn restores the natural outward direction of proton movement. Introduction of a potential negative charge (Ser(86) to Asp) on the cytoplasmic side favors a cytoplasmic direction of proton release from the Schiff base. In contrast, mutation of the counterion Asp(75) to Glu reverses the photocurrent to the outward direction in the truncated pigment, and in both truncated and full-length versions accelerates Schiff base deprotonation more than 10-fold. The communication between the cytoplasmic domain and the membrane-embedded photoactive site of ASR demonstrated here is likely to derive from the receptor's use of a cytoplasmic protein for signal transduction, as has been suggested previously from binding studies