Faster identification of phenotypes of mutants

Today we officially released our Growth Curves app, which supports analysis of high-throughput phenotypic microarray data from the OmniLog® instrument, made by Biolog. Among other things, this technology is used for identification of phenotypes of mutants which in turn can lead to the discovery of new targets for antibiotics.

“For identification of phenotypes of mutants, we use Biolog’s high-throughput phenotypic microarray instrument, OmniLog. However, we find the provided software is lacking key features and not very easy to work with. Much to our pleasure, grit42’s Growth Curves app, offers a nice and interactive way to analyse the data from the OmniLog instrument. For example we can now see the average of replicates and in the plate format, we can see the percentage of inhibition with the ability to switch reference in one click. On top of these – and additional – features, most importantly though, our analysis workflow is now 15 times faster!”, states Bacterial Infections Group Head at EVOTEC, Dr. Michael Mourez, PhD.

The Growth Curves app has been developed together with the bacterial infections group at a top 10 pharma, one of Europe’s leading biotechs, as well as input from US governmental institutions. An early version was shown by a scientist from Sanofi in June of 2017 at the IMI ND4BB Translocation workshop held at Helmholtz HZI, Germany, and since then the time has been spent perfecting the app. The old workflow involves more than eight hours of analysis work, after the experiment is done, compared to our redesigned workflow of around half an hour in total.

“Along with the rest of the scientific community, we’re experiencing a comeback of interest in the use of phenotypic cell-based assays, with studies indicating that they’re ideal for discovering efficacious small molecule drugs.” comments CEO and co-founder of grit42, Claus Stie Kallesøe, and continues, “That’s why we thought it would be interesting to support this technology, but rather than optimising the steps in the existing workflow, we completely redesigned it. Because of the way we structure the data, it becomes easy for our users to compare new experiments against old ones, as well as search across all the experiments. Everything is accessible with a few clicks and through a modern and user-friendly interface.”

The app works as a standalone tool, ready to run from grit42’s servers with a personal login. Other than the described workflow, the Growth Curves app also supports these types of studies: Profiling of cleanroom bacteria – identification of unknown microbes or fungi, optimization of cell lines and culture conditions in bioprocess development, characterization of cell phenotypes for taxonomic or epidemiological studies, determination of a cell’s metabolic and chemical sensitivity properties, as well as mode of action studies of antibiotics.

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