Project Facts


In 2010, NASA called a press conference to make one of the biggest announcements in scientific history: a NASA scientist claimed to have found a new form of life - a bacterium that could thrive on arsenic. The bacterium in arsenic-rich Mono Lake was said to redefine the building blocks of life, surviving and growing by swapping phosphorus as one of the six elements necessary for life for arsenic in its DNA and cell membranes.  While arsenic is similar to phosphorus it is typically poisonous to any living organism. Mono Lake where the probes had been taken was known to reflect conditions under which early life evolved on Earth, or perhaps Mars with an unusually salty body of water and high arsenic and mineral levels. The discovery went through major media worldwide. However the original study needed to be confirmed in order to be considered a true discovery. Any institution getting involved in the tests would have to be fast and work with comprehensive tools to focus on the scientific work that could take years.  

Without the technology developed in Saarbrücken, a goal-oriented and fast analysis of the data would not have been possible.
— Dr. Patrick Kiefer | ETH Zürich


ETH Zürich's institute for molecular biology was still working with a set of different tools for a long time. Different software was used which meant measurements had to be imported and exported in various formats from one system to another. Also vendor software continuously failed to meet the researchers rapidly progressing LCMS techniques and special needs. The research team realised in early 2012 that it would need to solve this IT challenge before being able to perform a valid in-depth analysis on the NASA case. ETH Zürich reached out to KIANA:

To meet the requirements for a simple but powerful system that would meet the scientists' needs KIANA developed a customised solution based on Python. The system called emzed makes experimenting with new analysis strategies for LCMS data as simple as possible. All steps can be performed in one closed system that can be expanded flexibly by end users with new analysis methods or visualisation techniques. The Python programming language has been chosen specifically for this purpose, since the language is easily understood and used by mathematicians. Today the system is available as an open source framework.



ETH Zürich and the research team around Julia Vorholt and Patrick Kiefer could refute the NASA study in summer 2012 showing that while arsenate-resistant the bacterium was still phosphate dependent. Since then the molecular biology department could perform numerous complex studies with the help of the system. The emzed software today can also be used in chemistry and pharmaceutical settings and even applied within entirely different industries such as insurance.