Kyle R. Allison

TL;DR: In this paper, the authors performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data.

TL;DR: A comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data defines the performance, data requirements and inherent biases of different inference approaches, and provides guidelines for algorithm application and development.

TL;DR: It is shown that specific metabolic stimuli enable the killing of both Gram-negative and Gram-positive bacterial persisters with aminoglycosides, and this approach can improve the treatment of chronic infections in a mouse urinary tract infection model.

TL;DR: This work provides direct evidence that, downstream of their target-specific interactions, bactericidal antibiotics induce complex redox alterations that contribute to cellular damage and death, thus supporting an evolving, expanded model of antibiotic lethality.

TL;DR: It is shown that bacterial communication through indole signaling induces persistence, a phenomenon in which a subset of an isogenic bacterial population tolerates antibiotic treatment, and a model in which indoles signaling “inoculates” a bacterial sub-population against antibiotics by activating stress responses, leading to persister formation is proposed.