Summary Toxin‐antitoxin systems are mediators of diverse activities in bacterial physiology. For the ParE‐type toxins, their reported role of gyrase inhibition utilized during plasmid‐segregation killing indicates they are toxic. However, their location throughout chromosomes leads to questions about function, including potential non‐toxic outcomes. The current study has characterized a ParDE system from the opportunistic human pathogen Pseudomonas aeruginosa (Pa). We identified a protective function for this ParE toxin, PaParE, against effects of quinolone and other antibiotics. However, higher concentrations of PaParE are themselves toxic to cells, indicating the phenotypic outcome can vary based on its concentration. Our assays confirmed PaParE inhibition of gyrase‐mediated supercoiling of DNA with an IC50 value in the low micromolar range, a species‐specificity that resulted in more efficacious inhibition of Escherichia coli derived gyrase versus Pa gyrase, and overexpression in the absence of antitoxin yielded an expected filamentous morphology with multi‐foci nucleic acid material. Additional data revealed that the PaParE toxin is monomeric and interacts with dimeric PaParD antitoxin with a KD in the lower picomolar range, yielding a heterotetramer. This work provides novel insights into chromosome‐encoded ParE function, whereby its expression can impart partial protection to cultures from selected antibiotics.

The American Society for Pharmacology and Experimental Therapeutics has revised the Instructions to Authors for Drug Metabolism and Disposition, Journal of Pharmacology and Experimental Therapeutics, and Molecular Pharmacology. These revisions relate to data analysis (including statistical analysis) and reporting but do not tell investigators how to design and perform their experiments. Their overall focus is on greater granularity in the description of what has been done and found. Key recommendations include the need to differentiate between preplanned, hypothesis-testing, and exploratory experiments or studies; explanations of whether key elements of study design, such as sample size and choice of specific statistical tests, had been specified before any data were obtained or adapted thereafter; and explanations of whether any outliers (data points or entire experiments) were eliminated and when the rules for doing so had been defined. Variability should be described by S.D. or interquartile range, and precision should be described by confidence intervals; S.E. should not be used. P values should be used sparingly; in most cases, reporting differences or ratios (effect sizes) with their confidence intervals will be preferred. Depiction of data in figures should provide as much granularity as possible, e.g., by replacing bar graphs with scatter plots wherever feasible and violin or box-and-whisker plots when not. This editorial explains the revisions and the underlying scientific rationale. We believe that these revised guidelines will lead to a less biased and more transparent reporting of research findings.

The American Society for Pharmacology and Experimental Therapeutics has revised the Instructions to Authors for Drug Metabolism and Disposition, Journal of Pharmacology and Experimental Therapeutics, and Molecular Pharmacology. These revisions relate to data analysis (including statistical analysis) and reporting but do not tell investigators how to design and perform their experiments. Their overall focus is on greater granularity in the description of what has been done and found. Key recommendations include the need to differentiate between preplanned, hypothesis-testing, and exploratory experiments or studies; explanations of whether key elements of study design, such as sample size and choice of specific statistical tests, had been specified before any data were obtained or adapted thereafter; and explanation of whether any outliers (data points or entire experiments) were eliminated and when the rules for doing so had been defined. Variability should be described by S.D. or interquartile range, and precision should be described by confidence intervals; S.E. should not be used. P values should be used sparingly; in most cases, reporting differences or ratios (effect sizes) with their confidence intervals will be preferred. Depiction of data in figures should provide as much granularity as possible, e.g., by replacing bar graphs with scatter plots wherever feasible and violin or box-and-whisker plots when not. This editorial explains the revisions and the underlying scientific rationale. We believe that these revised guidelines will lead to a less biased and more transparent reporting of research findings.

The American Society for Pharmacology and Experimental Therapeutics has revised the Instructions to Authors for Drug Metabolism and Disposition, Journal of Pharmacology and Experimental Therapeutics, and Molecular Pharmacology. These revisions relate to data analysis (including statistical analysis) and reporting but do not tell investigators how to design and perform their experiments. Their overall focus is on greater granularity in the description of what has been done and found. Key recommendations include the need to differentiate between preplanned, hypothesis-testing, and exploratory experiments or studies; explanations of whether key elements of study design, such as sample size and choice of specific statistical tests, had been specified before any data were obtained or adapted thereafter; and explanations of whether any outliers (data points or entire experiments) were eliminated and when the rules for doing so had been defined. Variability should be described by S.D. or interquartile range, and precision should be described by confidence intervals; S.E. should not be used. P values should be used sparingly; in most cases, reporting differences or ratios (effect sizes) with their confidence intervals will be preferred. Depiction of data in figures should provide as much granularity as possible, e.g., by replacing bar graphs with scatter plots wherever feasible and violin or box-and-whisker plots when not. This editorial explains the revisions and the underlying scientific rationale. We believe that these revised guidelines will lead to a less biased and more transparent reporting of research findings.