NleB/SseK-catalyzed arginine-glycosylation and enteropathogen virulence are finely tuned by a single variable position contiguous to the catalytic machinery

NleB/SseK effectors are arginine-GlcNAc-transferases expressed by enteric bacterial pathogens that modify host cell proteins to disrupt signaling pathways. While the conserved Citrobacter rodentium NleB and E. coli NleB1 proteins display a broad selectivity towards host proteins, Salmonella enterica SseK1, SseK2, and SseK3 have a narrowed protein substrate selectivity. Here, by combining computational and biophysical experiments, we demonstrate that the broad protein substrate selectivity of NleB relies on Tyr284^NleB/NleB1, a second-shell residue contiguous to the catalytic machinery. Tyr284^NleB/NleB1 is important in coupling protein substrate binding to catalysis. This is exemplified by S286Y^SseK1 and N302Y^SseK2 mutants, which become active towards FADD and DR3 death domains, respectively, and whose kinetic properties match those of enterohemorrhagic E. coli NleB1. The integration of these mutants into S. enterica increases S. enterica survival in macrophages, suggesting that better enzymatic kinetic parameters lead to enhanced virulence. Our findings provide insights into how these enzymes finely tune arginine-glycosylation and, in turn, bacterial virulence. In addition, our data show how promiscuous glycosyltransferases preferentially glycosylate specific protein substrates.

The NleB and SseK glycosyltransferases glycosylate arginine residues of mammalian proteins with different substrate specificities. We uncover that these differences rely on a particular second-shell residue contiguous to the catalytic machinery.     

Minimum cross‐entropy estimation of internally folded densities from Compton profiles

The internally folded density or reciprocal form factor B( r ) of many‐electron systems is tightly estimated from the knowledge of a small discrete set of values of the Compton profile J( q ). In doing so, the minimum cross‐entropy technique is employed. A numerical analysis of the approximations is carried out for the Helium atom. © 2002 John Wiley & Sons, Inc. Int J Quantum Chem, 2002     

Nonlinear and nonsmooth dynamics in a DC-DC Buck converter: Two experimental set-ups

It is well known that many nonlinear phenomena such as bifurcations and chaotic behavior occur in DC–DC converters mainly due to the switching action among all the different topologies of the circuit. Such behavior has been described with detail numerically, and also mathematical reasoning has been provided. In this paper we focuss on the experimental side of a DC–DC Buck converter controlled with two different strategies: classical Pulse Width Modulation (PWM) with a ramp and a more recently described Zero Average Dynamics (ZAD). We show some nonsmooth events and we explain with detail the experimental set-ups. In one of them, we use a FPGA card to obtain on-line results. In the other we use Virtual Instrumentation to generate an experimental two-dimensional bifurcation diagram, which will be compared to the numerical data. After the data acquisition of the system state variables some elaborated post-processing must be made. This is done through LabView. Although the main application of these results is centered in avoiding non-periodic or high-amplitude periodic behavior, they can also be applied to reducing the generated electro-magnetic interference and to the information transmission.Partially funded by SICONOS.     

Maximum-entropy analysis of momentum densities in diatomic molecules

The one-particle density in momentum space γ(p) is studied for diatomic molecules by using the maximum-entropy technique. The knowledge of one or more momentum expectation values <p"> provides approximations on the density γ(p) for any value of the momentum, which are convergent when increasing the number of known moments. Other unknown expectation values are estimated in terms of the constructed maximum-entropy densities. A numerical study of the quality of the approximations is carried out by means of experimental and theoretical data for the momentum expectation values involved. Experimental errors are also taken into account to have an idea of the sensibility of the results to the information from which they are obtained. © 1997 John Wiley & Sons, Inc.     

A Spatially Correlated Model with Generalized Autoregressive Conditionally Heteroskedastic Structure for Counts of Crimes

Crime is a negative phenomenon that affects the daily life of the population and its development. When modeling crime data, assumptions on either the spatial or the temporal relationship between observations are necessary if any statistical analysis is to be performed. In this paper, we structure space–time dependency for count data by considering a stochastic difference equation for the intensity of the space–time process rather than placing structure on a latent space–time process, as Cox processes would do. We introduce a class of spatially correlated self-exciting spatio-temporal models for count data that capture both dependence due to self-excitation, as well as dependence in an underlying spatial process. We follow the principles in Clark and Dixon (2021) but considering a generalized additive structure on spatio-temporal varying covariates. A Bayesian framework is proposed for inference of model parameters. We analyze three distinct crime datasets in the city of Riobamba (Ecuador). Our model fits the data well and provides better predictions than other alternatives.     

Antibacterial Screening of Isoespintanol,an Aromatic Monoterpene Isolated from Oxandra xylopioides Diels

The incidence of nosocomial infections, as well as the high mortality and drug resistance expressed by nosocomial pathogens, especially in immunocompromised patients, poses significant medical challenges. Currently, the efficacy of plant compounds with antimicrobial potential has been reported as a promising alternative therapy to traditional methods. Isoespintanol (ISO) is a monoterpene with high biological activity. Using the broth microdilution method, the antibacterial activity of ISO was examined in 90 clinical isolates, which included 14 different species: (Escherichia coli (38), Pseudomonas aeruginosa (12), Klebsiella pneumoniae (13), Acinetobacter baumannii (3), Proteus mirabilis (7), Staphylococcus epidermidis (3), Staphylococcus aureus (5), Enterococcus faecium (1), Enterococcus faecalis (1), Stenotrophomonas maltophilia (2), Citrobacter koseri (2), Serratia marcescens (1), Aeromonas hydrophila (1), and Providencia rettgeri (1). MIC₉₀ minimum inhibitory concentration values ranged from 694.3 to 916.5 µg/mL and MIC₅₀ values from 154.2 to 457.3 µg/mL. The eradication of mature biofilms in P. aeruginosa after 1 h of exposure to ISO was between 6.6 and 77.4%, being higher in all cases than the percentage of biofilm eradication in cells treated with ciprofloxacin, which was between 4.3 and 67.5%. ISO has antibacterial and antibiofilm potential against nosocomial bacteria and could serve as an adjuvant in the control of these pathogens.     

Molecular Recognition of Natural and Non-Natural Substrates by Cellodextrin Phosphorylase from Ruminiclostridium Thermocellum Investigated by NMR Spectroscopy

β-1→4-Glucan polysaccharides like cellulose, derivatives and analogues, are attracting attention due to their unique physicochemical properties, as ideal candidates for many different applications in biotechnology. Access to these polysaccharides with a high level of purity at scale is still challenging, and eco-friendly alternatives by using enzymes in vitro are highly desirable. One prominent candidate enzyme is cellodextrin phosphorylase (CDP) from Ruminiclostridium thermocellum, which is able to yield cellulose oligomers from short cellodextrins and α-d -glucose 1-phosphate (Glc-1-P) as substrates. Remarkably, its broad specificity towards donors and acceptors allows the generation of highly diverse cellulose-based structures to produce novel materials. However, to fully exploit this CDP broad specificity, a detailed understanding of the molecular recognition of substrates by this enzyme in solution is needed. Herein, we provide a detailed investigation of the molecular recognition of ligands by CDP in solution by saturation transfer difference (STD) NMR spectroscopy, tr-NOESY and protein-ligand docking. Our results, discussed in the context of previous reaction kinetics data in the literature, allow a better understanding of the structural basis of the broad binding specificity of this biotechnologically relevant enzyme.     

About negative efficiencies in Cross Evaluation BCC input oriented models

It will be shown in this paper that the input oriented DEA BCC model can generate negative efficiencies that are usually hidden in the model. The impact of these negative efficiencies becomes obvious when using input oriented Cross Evaluation models. With the help of an example with one input and one output, the conditions for the possible occurrence of negative efficiencies will be shown. Furthermore, we will show that a small intuitive change in the BCC multipliers model, previously presented in other papers, corrects this situation. We show why this change is used and compared it with an alternative formulation, which avoid negative efficiencies, namely the Non-Decreasing Returns to Scale (NDRS) model. We also show that the formulation studied in this paper is less restrictive than the NDRS model. The study of this variation in the DEA BCC model will be complemented with the formulation of the dual envelope model. This model changes the original frontier. Using the concept of non-observed DMUs, those variations can be graphically analyzed. We have also carried out some algebraic studies concerning benchmarks, multipliers and returns to scale.