The widespread emergence of antibiotic-resistant bacteria and a lack of new pharmaceutical development have catalyzed a need for new and innovative approaches for antibiotic drug discovery. One bottleneck in antibiotic discovery is the lack of a rapid and comprehensive method to identify compound mode of action (MOA). Since a hallmark of antibiotic action is as an inhibitor of essential cellular targets and processes, we identify a set of 308 essential genes in the clinically important pathogen Staphylococcus aureus. A total of 446 strains differentially expressing these genes were constructed in a comprehensive platform of sensitized and resistant strains. A subset of strains allows either target underexpression or target overexpression by heterologous promoter replacements with a suite of tetracycline-regulatable promoters. A further subset of 236 antisense RNA-expressing clones allows knockdown expression of cognate targets. Knockdown expression confers selective antibiotic hypersensitivity, while target overexpression confers resistance. The antisense strains were configured into a TargetArray in which pools of sensitized strains were challenged in fitness tests. A rapid detection method measures strain responses toward antibiotics. The TargetArray antibiotic fitness test results show mechanistically informative biological fingerprints that allow MOA elucidation.
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Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.