Reconstructing gene regulatory networks from high-throughput data is a long-standing problem. Through the DREAM project (Dialogue on Reverse Engineering Assessment and Methods), we performed a comprehensive blind assessment of over thirty network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae, and in silico microarray data. We characterize performance, data requirements, and inherent biases of different inference approaches offering guidelines for both algorithm application and development. We observe that no single inference method performs optimally across all datasets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse datasets. Thereby, we construct high-confidence networks for E. coli and S. aureus, each comprising ~1700 transcriptional interactions at an estimated precision of 50%. We experimentally test 53 novel interactions in E. coli, of which 23 were supported (43%). Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.
Bacterial persistence is a state in which a sub-population of dormant cells (persisters) tolerates antibiotic treatment1-4. Bacterial persisters have been implicated in biofilms and chronic and recurrent infections5-7. Despite this clinical relevance, there are currently no viable means for eradicating persisters. Here we show that specific metabolic stimuli enable aminoglycoside killing of both Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) persisters. This potentiation is aminoglycoside-specific, does not rely on growth resumption, is effective in both aerobic and anaerobic conditions, and proceeds by generation of proton-motive force (PMF) which facilitates aminoglycoside uptake. Our results demonstrate that persisters, though dormant, are primed for metabolite uptake, central metabolism, and respiration. We show that aminoglycosides in combination with specific metabolites can be used to treat E. coli and S. aureus biofilms. Further, we demonstrate that this approach can improve treatment of chronic infection in a mouse urinary tract infection model. This work establishes a metabolic-based strategy for eradicating bacterial persisters and highlights the critical importance of metabolic environment to antibiotic treatment.
Deeper understanding of antibiotic-induced physiological responses is critical to identifying means for enhancing our current antibiotic arsenal. Bactericidal antibiotics with diverse targets have been hypothesized to kill bacteria, in part by inducing production of damaging reactive species. This notion has been supported by many groups but has been challenged recently. Here we robustly test the hypothesis using biochemical, enzymatic, and biophysical assays along with genetic and phenotypic experiments. We first used a novel intracellular H 2 O 2 sensor, together with a chemically diverse panel of fluorescent dyes sensitive to an array of reactive species to demonstrate that antibiotics broadly induce redox stress. Subsequent gene-expression analyses reveal that complex antibiotic-induced oxidative stress responses are distinct from canonical responses generated by supraphysiological levels of H 2 O 2 . We next developed a method to quantify cellular respiration dynamically and found that bactericidal antibiotics elevate oxygen consumption, indicating significant alterations to bacterial redox physiology. We further show that overexpression of catalase or DNA mismatch repair enzyme, MutS, and antioxidant pretreatment limit antibiotic lethality, indicating that reactive oxygen species causatively contribute to antibiotic killing. Critically, the killing efficacy of antibiotics was diminished under strict anaerobic conditions but could be enhanced by exposure to molecular oxygen or by the addition of alternative electron acceptors, indicating that environmental factors play a role in killing cells physiologically primed for death. 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.reactive oxygen species | DNA repair | mutagenesis T he increasing incidence of antibiotic-resistant infections coupled with a declining antibiotic pipeline has created a global public health threat (1-6). Therefore there is a pressing need to expand our conceptual understanding of how antibiotics act and to use insights gained from such efforts to enhance our antibiotic arsenal. It has been proposed that different classes of bactericidal antibiotics, regardless of their drug-target interactions, generate varying levels of deleterious reactive oxygen species (ROS) that contribute to cell killing (7,8). This unanticipated notion, built upon important prior work (9-11), has been extended and supported by multiple laboratories investigating wide-ranging drug classes (e.g., β-lactams, aminoglycosides, and fluoroquinolones) and bacterial species (e.g., Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Mycobacterium tuberculosis, Bacillus subtilis, Staphylococcus aureus, Acinetobacter baumannii, Burkholderia cepecia, Streptococcus pneumonia, Enterococcus faecalis) using independent lines of evidence (12-39). Importantly,...
Here we show that bacterial communication through indole signaling induces persistence, a phenomenon in which a subset of an isogenic bacterial population tolerates antibiotic treatment. We monitor indole-induced persister formation using microfluidics, and identify the role of oxidative stress and phage-shock pathways in this phenomenon. We propose a model in which indole signaling “inoculates” a bacterial sub-population against antibiotics by activating stress responses, leading to persister formation.
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