ArticleACS infectious diseases2017
Experimental Evolution of Diverse Strains as a Method for the Determination of Biochemical Mechanisms of Action for Novel Pyrrolizidinone Antibiotics.
Article in ACS infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Microfluidic platform for spatially segregated experimental evolution studies withSTAR protocols · 2022Article
- Identification of Evolutionary Trajectories Associated with Antimicrobial Resistance Using Microfluidics.ACS infectious diseases · 2022Article
- Novel Immune Modulators EnhancemSphere · 2021Article
- Repurposing bioactive compounds for treating multidrug-resistant pathogens.Journal of medical microbiology · 2020Article
- Enantioselective Total Synthesis of Antibiotic CJ-16,264, Synthesis and Biological Evaluation of Designed Analogues, and Discovery of Highly Potent and Simpler Antibacterial Agents.Journal of the American Chemical Society · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The continuing rise of multidrug resistant pathogens has made it clear that in the absence of new antibiotics we are moving toward a "postantibiotic" world, in which even routine infections will become increasingly untreatable. There is a clear need for the development of new antibiotics with truly novel mechanisms of action to combat multidrug resistant pathogens. Experimental evolution to resistance can be a useful tactic for the characterization of the biochemical mechanism of action for antibiotics of interest. Herein, we demonstrate that the use of a diverse panel of strains with well-annotated reference genomes improves the success of using experimental evolution to characterize the mechanism of action of a novel pyrrolizidinone antibiotic analog. Importantly, we used experimental evolution under conditions that favor strongly polymorphic populations to adapt a panel of three substantially different Gram-positive species (lab strain Bacillus subtilis and clinical strains methicillin-resistant Staphylococcus aureus MRSA131 and Enterococcus faecalis S613) to produce a sufficiently diverse set of evolutionary outcomes. Comparative whole genome sequencing (WGS) between the susceptible starting strain and the resistant strains was then used to identify the genetic changes within each species in response to the pyrrolizidinone. Taken together, the adaptive response across a range of organisms allowed us to develop a readily testable hypothesis for the mechanism of action of the CJ-16 264 analog. In conjunction with mitochondrial inhibition studies, we were able to elucidate that this novel pyrrolizidinone antibiotic is an electron transport chain (ETC) inhibitor. By studying evolution to resistance in a panel of different species of bacteria, we have developed an enhanced method for the characterization of new lead compounds for the discovery of new mechanisms of action.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.