Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.
Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Actinobacillus pleuropneumoniae and its ciprofloxacin resistance-inducing derivatives.This study aims to explore the mechanism of acquired ciprofloxacin resistance in Actinobacillus pleuropneumoniae.
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin). We treated Escherichia coli cells with a highly toxic level of ciprofloxacin (gyrase inhibitor) for RNA extraction and hybridization on Affymetrix microarrays. We planned to find genotype specific transcriptional responses using WT control (BW25113) and fur-knockout mutant (selected from the KEIO collection) strains during antibiotic treatments. For each treatment type we used two biological replicates.
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin).
Project description:The rapid global rise of antimicrobial resistance (AMR) that increasingly invalidates conventional antibiotics has become a huge threat to human health. Although nanosized antibacterial agents have been extensively explored, they cannot sufficiently discriminate between microbes and mammals, which necessitates the exploration of other antibiotic-like candidates for clinical uses. Herein, two-dimensional boron nitride (BN) nanosheets are reported to exhibit antibiotic-like activity to AMR bacteria. Interestingly, BN nanosheets had AMR-independent antibacterial activity without triggering secondary resistance in their long-term use and displayed excellent biocompatibility in mammals. Surface proteome analysis coupled with molecular dynamic simulations and Bio-Layer Interferometry revealed that BN nanosheets could rapidly interact with the key surface proteins of cell division including FtsP, EnvC, and TolB, resulting in a specific antibacterial mechanism by impairment of Z-ring constriction in cell division. Notably, BN nanosheets had a potent antibacterial effect in a lung infection model by P. aeruginosa (AMR), displaying a two-fold increment of survival rate. Overall, these results suggested that BN nanosheets could be a promising nano-antibiotic to combat resistant bacteria and prevent AMR evolution.
Project description:The increasing antibiotic resistance of Klebsiella pneumoniae poses a serious threat to global public health. To investigate the antibiotic resistance mechanism of Klebsiella pneumonia, we performed gene expression profiling analysis using RNA-seq data for clinical isolates of Klebsiella pneumonia, KPN16 and ATCC13883. Our results showed that mutant strain KPN16 is likely to act against the antibiotics through increased increased butanoate metabolism and lipopolysaccharide biosynthesis, and decreased transmembrane transport activity.
Project description:Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild-type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.
Project description:The rise of antibiotic resistance in many bacterial pathogens has been driven by the spread of a few successful strains, suggesting that some bacteria are genetically pre-disposed to evolving resistance. We tested this hypothesis by challenging a diverse set of 222 strains of Staphylococcus aureus with the antibiotic ciprofloxacin in a large-scale evolution experiment. Surprisingly, we found that a single efflux pump, norA, causes widespread variation in evolvability across the diversity of S. aureus. In most lineages of S. aureus, elevated norA expression potentiated evolution by increasing the fitness benefit provided by resistance mutations in DNA topoisomerase under ciprofloxacin treatment. Amplification of norA provided a further mechanism of rapid evolution, but this was restricted to strains from CC398. Crucially, chemically inhibiting NorA effectively prevented the evolution of resistance across the diversity of S. aureus. Our study shows that the underlying genetic diversity of pathogenic bacteria plays a key role in shaping resistance evolution. Understanding this link makes it possible to predict which strains are likely to evolve resistance and to optimize inhibitor use to prevent this outcome.