Understanding how adaptation to a given antibiotic increases the sensitivity to other antibiotics is of great medical importance for the understanding of evolutionary trade-offs. Here, the first experimental map of such collateral sensitivity is presented, along with insights into the underlying mechanisms.

Evidence suggests that novel enzyme functions evolved from low‐level promiscuous activities in ancestral enzymes. Yet, the evolutionary dynamics and physiological mechanisms of how such side activities contribute to systems‐level adaptations are not well characterized. Furthermore, it remains untested whether knowledge of an organism's promiscuous reaction set, or underground metabolism, can aid in forecasting the genetic basis of metabolic adaptations. Here, we employ a computational model of underground metabolism and laboratory evolution experiments to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non‐native substrates in Escherichia coli K‐12 MG 1655. After as few as approximately 20 generations, evolved populations repeatedly acquired the capacity to grow on five predicted non‐native substrates—D‐lyxose, D‐2‐deoxyribose, D‐arabinose, m‐tartrate, and monomethyl succinate. Altered promiscuous activities were shown to be directly involved in establishing high‐efficiency pathways. Structural mutations shifted enzyme substrate turnover rates toward the new substrate while retaining a preference for the primary substrate. Finally, genes underlying the phenotypic innovations were accurately predicted by genome‐scale model simulations of metabolism with enzyme promiscuity.

Antibiotics that inhibit multiple bacterial targets offer a promising therapeutic strategy against resistance evolution, but developing such antibiotics is challenging. Here we demonstrate that a rational design of balanced multitargeting antibiotics is feasible by using a medicinal chemistry workflow. The resultant lead compounds, ULD1 and ULD2, belonging to a novel chemical class, almost equipotently inhibit bacterial DNA gyrase and topoisomerase IV complexes and interact with multiple evolutionary conserved amino acids in the ATPbinding pockets of their target proteins. ULD1 and ULD2 are excellently potent against a broad range of gram-positive bacteria. Notably, the efficacy of these compounds was tested against a broad panel of multidrug-resistant Staphylococcus aureus clinical strains. Antibiotics with clinical relevance against staphylococcal infections fail to inhibit a significant fraction of these isolates, whereas both ULD1 and ULD2 inhibit all of them (minimum inhibitory concentration [MIC] �1 μg/mL). Resistance mutations against these compounds are rare, have limited impact on compound susceptibility, and substantially reduce bacterial growth. Based on their efficacy and lack of toxicity demonstrated in murine infection models, these compounds could translate into new therapies against multidrug-resistant bacterial infections.

fundamental knowledge of how nucleotide mismatch repair (MMR) operates in such non-model species. One critical bottleneck is the hierarchy of recognition of different types of base mispairings as well as the need of setting up strategies for counteracting MMR and thus enabling tolerance to all types of changes. The work presented here tackles both issues and makes P. putida amenable to sophisticated genetic manipulations that were impossible before. recent years as one of the most powerful technologies of genome editing in E. coli and other Enterobacteria. However, the efforts to expand the concept and the methods towards environment microorganisms such as Pseudomonas putida have been limited thus far by several gaps in our

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Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. Here we present a functional metagenomics pipeline called Reprogrammed Bacteriophage Particle Assisted Multi-species Functional Metagenomics (DEEPMINE). This approach combines and improves the use of T7 bacteriophage with exchanged tail fibres and targeted mutagenesis to expand phage host-specificity and efficiency for functional metagenomics. These modified phage particles were used to introduce large metagenomic plasmid libraries into clinically relevant bacterial pathogens. By screening for ARGs in soil and gut microbiomes and clinical genomes against 13 antibiotics, we demonstrate that this approach substantially expands the list of identified ARGs. Many ARGs have species-specific effects on resistance; they provide a high level of resistance in one bacterial species but yield very limited resistance in a related species. Finally, we identified mobile ARGs against antibiotics that are currently under clinical development or have recently been approved. Overall, DEEPMINE expands the functional metagenomics toolbox for studying microbial communities.