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Offer: 657

Detecting unknown metabolites

New method for trace analysis identifies unknown metabolites without reference standards using predicted mass spectra.

In environmental analysis, for example, water samples are examined for unknown metabolites using tandem mass spectrometry.
In biochemical analytics, it is standard procedure to examine material samples with tandem mass spectroscopy in order to determine even the smallest volumes of substances. Especially in the fields of medicine, pharmacy as well as environmental and food analytics, this method can be used to detect unknown metabolites of harmful substances and active agents in a sample.

In tandem mass spectrometry, every substance is characterized by a characteristic mass spectrum once it has been fragmented. To obtain this spectrum, the substance has to be available in its pure form. By comparing these reference spectra with the spectra gained from an unknown sample, the substances sought are unambiguously identified. However, this method is not applicable in the case of unknown substances to date.

Scientists of the Engler-Bunte-Institute at KIT have developed an evaluation method that can also identify unknown metabolites without a reference spectrum. First of all, a mass spectrum of the mother substance is recorded the potential metabolites of which are to be determined. For each of these measured fragments, a respective assumed mass shift of potential molecular transformations is calculated and recorded as a data set of predicted fragments. Here, the system builds on common transformation and splitting reactions. In the sample to be examined, the overall mass of the unknown metabolite is isolated by a chromatographic separation process and also undergoes mass spectrometric fragmentation. An evaluation routine then compares the predicted and the measured fragment spectra in order to determine matches.

In comparison to existing solutions, which require a substance in pure form as a reference, the new method enables the detection of unknown metabolites by systematic and rapid identification with the aid of predicted fragments. A high rate of matches means a high degree of certainty in identifying unknown metabolites.

KIT is looking for companies that are interested in the further development and use of the method in software for new devices or as an upgrade for existing equipment.

Your contact person for this offer

Frauke Helms, Karlsruhe Institute of Technology (KIT)
Innovation and Relations Management (IRM)
Phone: +49 721 608-26036

Email: frauke.helms@kit.edu

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