Quinol Oxidase Encoded by \u3cem\u3ecyoABCD\u3c/em\u3e in \u3cem\u3eRhizobium etli\u3c/em\u3e CFN42 is Regulated by ActSR and is Crucial for Growth at Low pH or Low Iron Conditions

Rhizobium etli aerobically respires with several terminal oxidases. The quinol oxidase (Cyo) encoded by cyoABCD is needed for efficient adaptation to low oxygen conditions and cyo transcription is upregulated at low oxygen. This study sought to determine how transcription of the cyo operon is regulated. The 5′ sequence upstream of cyo was analysed in silico and revealed putative binding sites for ActR of the ActSR two-component regulatory system. The expression of cyo was decreased in an actSR mutant regardless of the oxygen condition. As ActSR is known to be important for growth under low pH in another rhizobial species, the effect of growth medium pH on cyo expression was tested. As the pH of the media was incrementally decreased, cyo expression gradually increased in the WT, eventually reaching ∼10-fold higher levels at low pH (4.8) compared with neutral pH (7.0) conditions. This upregulation of cyo under decreasing pH conditions was eliminated in the actSR mutant. Both the actSR and cyo mutants had severe growth defects at low pH (4.8). Lastly, the actSR and cyo mutants had severe growth defects when grown in media treated with an iron chelator. Under these conditions, cyo was upregulated in the WT, whereas cyo was not induced in the actSR mutant. Altogether, the results indicated cyo expression is largely dependent on the ActSR two-component system. This study also demonstrated additional physiological roles for Cyo in R. etli CFN42, in which it is the preferred oxidase for growth under acidic and low iron conditions

A Quinol Oxidase, Encoded by \u3cem\u3ecyoABCD\u3c/em\u3e, Is Utilized to Adapt to Lower O\u3csub\u3e2\u3c/sub\u3e Concentrations in \u3cem\u3eRhizobium etli\u3c/em\u3e CFN42

Bacteria have branched aerobic respiratory chains that terminate at different terminal oxidases. These terminal oxidases have varying properties such as their affinity for oxygen, transcriptional regulation and proton pumping ability. The focus of this study was a quinol oxidase encoded by cyoABCD. Although this oxidase (Cyo) is widespread among bacteria, not much is known about its role in the cell, particularly in bacteria that contain both cytochrome c oxidases and quinol oxidases. Using Rhizobium etli CFN42 as a model organism, a cyo mutant was analysed for its ability to grow in batch cultures at high (21 % O2) and low (1 and 0.1 % O2) ambient oxygen concentrations. In comparison with other oxidase mutants, the cyo mutant had a significantly longer lag phase under low-oxygen conditions. Using a cyo :: lacZ transcriptional fusion, it was shown that cyo expression in the wild type peaks between 1 and 2.5 % O2. In addition, it was shown with quantitative reverse transcriptase PCR that cyoB is upregulated approximately fivefold in 1 % O2 compared with fully aerobic (21 % O2) conditions. Analysis of the cyo mutant during symbiosis with Phaseolous vulgaris indicated that Cyo is utilized during early development of the symbiosis. Although it is commonly thought that Cyo is utilized only at higher oxygen concentrations, the results from this study indicate that Cyo is important for adaptation to and sustained growth under low oxygen

Machine learning-guided directed evolution for protein engineering

Machine learning (ML)-guided directed evolution is a new paradigm for biological design that enables optimization of complex functions. ML methods use data to predict how sequence maps to function without requiring a detailed model of the underlying physics or biological pathways. To demonstrate ML-guided directed evolution, we introduce the steps required to build ML sequence-function models and use them to guide engineering, making recommendations at each stage. This review covers basic concepts relevant to using ML for protein engineering as well as the current literature and applications of this new engineering paradigm. ML methods accelerate directed evolution by learning from information contained in all measured variants and using that information to select sequences that are likely to be improved. We then provide two case studies that demonstrate the ML-guided directed evolution process. We also look to future opportunities where ML will enable discovery of new protein functions and uncover the relationship between protein sequence and function.Comment: Made significant revisions to focus on aspects most relevant to applying machine learning to speed up directed evolutio

Copper(II)- and gold(III)-mediated cyclization of a thiourea to a substituted 2-aminobenzothiazole

Benzothiazole derivatives are a class of privileged molecules due to their biological activity and pharmaceutical applications. One route to these molecules is via intramolecular cyclization of thioureas to form substituted 2-aminobenzothiazoles, but this often requires harsh conditions or employs expensive metal catalysts. Herein, the copper(II)- and gold(III)-mediated cyclizations of thioureas to substituted 2-aminobenzothiazoles are reported. The single-crystal X-ray structures of the thiourea N-(3-methoxyphenyl)-N\u27- (pyridin-2-yl)thiourea, C13H13N3OS, and the intermediate metal complexes aquabis[5-methoxy-N-(pyridin-2-yl-κN)-1,3-benzothiazol-2-amine-κN3]copper(II) dinitrate, [Cu(C13H11N3OS)2(H2O)](NO3)2, and bis{2-[(5-methoxy-1,3-benzothiazol- 2-yl)amino]pyridin-1-ium} dichloridogold(I) chloride monohydrate, (C13H12N3OS)2[AuCl2]Cl⋅H2O, are reported. The copper complex exhibits a distorted trigonal–bipyramidal geometry, with direct metal-to-benzothiazoleligand coordination, while the gold complex is a salt containing the protonated uncoordinated benzothiazole, and offers evidence that metal reduction (in this case, AuIII to AuI) is required for the cyclization to proceed. As such, this study provides further mechanistic insight into the role of the metal cations in these transformations

The Outer Limits of Cognitive Processing: A Closer Look at What Is Desirable

Cognitive tasks are most satisfying when they include the right balance between ease and difficulty (Labroo & Kim, 2008). This balance is viewed as optimal for high quality and progressive learning in school and societal contexts (Bjork & Bjork, 1992). This idea is the basis of the concept of desirable difficulties, which are defined as certain difficulties in the learning process that can greatly improve long-term retention of learned material (Bjork & Bjork, 1992). Having received a lot of attention in recent research, they allow for one to develop questions about how we, as humans, approach certain tasks and where the cognitive difficulty threshold lies for maximum personal satisfaction. This study examines participants\u27 ability to accurately recognize word and picture stimuli presented in one of five angles of rotation to determine whether a universal desirably difficult mental threshold exists or whether there are different mental thresholds based on the particular stimuli that are presented. Results show that there seem to be different mental thresholds depending on the type of stimulus that is presented. In addition, the threshold of what is considered to be desirably difficult does not act on a linear continuum; rather, it appears to fluctuate based solely on the difficulty of the task in a cubic-fashion

Snowshoe Hares (Lepus americanus) Alter Feeding Behavior in Response to Coyote (Canis latrans) and Moose (Alces alces) Cues at Diverse Vegetation Densities

Prey interpret predator cues as a warning and use them to assess the danger of a given area. Multiple prey species avoid chemical cues from predators at feeding sites because the risk of death outweighs the benefit of food. However, we lack information regarding avoidance of chemical cues from competitors as well as how foraging behavior changes alongside vegetative cover. To test if chemical cues and veget~tive cover alter prey vigilance, number of visits, and time spent at feeding sites, I observed snowshoe hares (Lepus americanus) in plots containing coyote (Canis latrans; predator) and moose (Alces alces; competitor) urine across a spectrum of vegetation densities. Snowshoe hares significantly reduced the number of visits to feeding plots when coyote or moose urine was administered. In plots containing coyote urine, number of visits decreased significantly as plots became more densely vegetated. Neither chemical cues nor vegetation density had a large effect on snowshoe hare vigilance or time spent in plots. These results suggest that competition between snowshoe hares and moose has selected for an avoidance response. This study also reinforces the idea that an increase in vegetation density could prove disadvantageous to prey, perhaps because some predators may utilize dense vegetation to their advantage while stalking