The Rho-Dependent Transcription Termination Is Involved in Broad-Spectrum Antibiotic Susceptibility in Escherichia coli

One of the major ways of acquiring multidrug resistance in bacteria is via drug influx and efflux pathways. Here, we show that E. coli with compromised Rho-dependent transcription termination function has enhanced broad-spectrum antibiotic susceptibility, which arises from the inefficient TolC-efflux process and increased permeability of the membrane. The Rho mutants have altered morphology, distinct cell surface, and increased levels of lipopolysaccharide in their outer membrane, which might have rendered the TolC efflux pumps inefficient. These alterations are due to the upregulations of poly-N-acetyl-glucosamine and lipopolysaccharide synthesis operons because of inefficient Rho functions. The Rho mutants are capable of growing on various dipeptides and carbohydrate sources, unlike their WT counterpart. Dipeptides uptake arises from the upregulations of the di-peptide permease operon in these mutants. The metabolomics of the Rho mutants revealed the presence of a high level of novel metabolites. Accumulation of these metabolites in these Rho mutants might titrate out the TolC-efflux pumps, which could further reduce their efficiency. We conclude that the transcription termination factor, Rho, regulates the broad-spectrum antibiotic susceptibility of E. coli through multipartite pathways in a TolC-dependent manner. The involvement of Rho-dependent termination in multiple pathways and its association with antibiotic susceptibility should make Rho-inhibitors useful in the anti-bacterial treatment regimen.

Natural Option Critic

The recently proposed option-critic architecture (Bacon, Harb, and Precup 2017) provides a stochastic policy gradient approach to hierarchical reinforcement learning. Specifically, it provides a way to estimate the gradient of the expected discounted return with respect to parameters that define a finite number of temporally extended actions, called options. In this paper we show how the option-critic architecture can be extended to estimate the natural gradient (Amari 1998) of the expected discounted return. To this end, the central questions that we consider in this paper are: 1) what is the definition of the natural gradient in this context, 2) what is the Fisher information matrix associated with an option’s parameterized policy, 3) what is the Fisher information matrix associated with an option’s parameterized termination function, and 4) how can a compatible function approximation approach be leveraged to obtain natural gradient estimates for both the parameterized policy and parameterized termination functions of an option with per-time-step time and space complexity linear in the total number of parameters. Based on answers to these questions we introduce the natural option critic algorithm. Experimental results showcase improvement over the vanilla gradient approach.

Redundancy of primary RNA-binding functions of the bacterial transcription terminator Rho

The bacterial transcription terminator, Rho, terminates transcription at half of the operons. According to the classical model derived from in vitro assays on a few terminators, Rho is recruited to the transcription elongation complex (EC) by recognizing specific sites (rut) on the nascent RNA. Here, we explored the mode of in vivo recruitment process of Rho. We show that sequence specific recognition of the rut site, in majority of the Rho-dependent terminators, can be compromised to a great extent without seriously affecting the genome-wide termination function as well as the viability of Escherichia coli. These terminators function optimally only through a NusG-assisted recruitment and activation of Rho. Our data also indicate that at these terminators, Rho-EC-bound NusG interaction facilitates the isomerization of Rho into a translocase-competent form by stabilizing the interactions of mRNA with the secondary RNA binding site, thereby overcoming the defects of the primary RNA binding functions.

New Method Based on the Optimal Decomposition Scale for Daily Load Forecasting in Power System

The decomposition scale value is usually given by experience while the wavelet analysis method is used for daily load forecasting. Directed to the influence of decomposition scale, the paper constructed a level-termination function as SNR and put forward a constraint conditions according the accuracy requirement to solve out the optimal decomposition level. Then followed the load data which was decomposed into high and low frequency component, built up different models for different level series and sum up the forecasting result. The accuracy assessment index shows the effectiveness of the whole method and prediction thought.

Molecular Population Genetics and Evolution of a Prion-like Protein in Saccharomyces cerevisiae

The prion-like behavior of Sup35p, the eRF3 homolog in the yeast Saccharomyces cerevisiae, mediates the activity of the cytoplasmic nonsense suppressor known as [PSI+]. Sup35p is divided into three regions of distinct function. The N-terminal and middle (M) regions are required for the induction and propagation of [PSI+] but are not necessary for translation termination or cell viability. The C-terminal region encompasses the termination function. The existence of the N-terminal region in SUP35 homologs of other fungi has led some to suggest that this region has an adaptive function separate from translation termination. To examine this hypothesis, we sequenced portions of SUP35 in 21 strains of S. cerevisiae, including 13 clinical isolates. We analyzed nucleotide polymorphism within this species and compared it to sequence divergence from a sister species, S. paradoxus. The N domain of Sup35p is highly conserved in amino acid sequence and is highly biased in codon usage toward preferred codons. Amino acid changes are under weak purifying selection based on a quantitative analysis of polymorphism and divergence. We also conclude that the clinical strains of S. cerevisiae are not recently derived and that outcrossing between strains in S. cerevisiae may be relatively rare in nature.