Swiss bioinformatics company SmartGene said this week that the Institute of Medical Microbiology at the University of Zurich will use its web-based platform and associated reference databases to validate mass spectrometry analyses used to identify infections pathogens in clinical diagnostics settings.
Erik Boettger, a professor of medicine and microbiology and the director and chairman of IMM, said in a statement that researchers will "evaluate how mass spec technologies and sequence-based identifications can work together in our laboratory, for best accuracy and efficiency in supporting patient care."
The agreement expands on an existing relationship between SmartGene and IMM under which IMM researchers have been using SmartGene's web-based services to identify and analyze bacterial, fungal, and mycobacterial pathogens by sequence analysis.
Additionally, IMM researchers curate a sequence reference database that’s used to identify yeasts and molds, which is available to other institutions via SmartGene's platform.
SmartGene said that mass spec platforms are partially replacing conventional culture-based methods for identifying bacterial pathogens in the field of clinical microbiology because they offer a shorter turnaround time as well as reduced labor and cost per test. However, some studies indicate that mass spec-derived answers may "partly not be sufficiently discriminatory" and as a result, "it is critical for the quality of our work to be able to back up and complement these results with our DNA sequencing routine and with our database cumulated from clinical isolates over the years," Boettger said.
As part of the arrangement with SmartGene, IMM plans to design an optimized workflow for routine clinical laboratory testing that will use sequence-based identification to validate mass spec-derived results.
In June, IMM was one of three groups that signed a research and distribution deal with Bruker to use the company's MALDI Biotyper as its next-generation, rapid microbial identification system. The mass spectrometer, which can be used to identify gram-positive and gram-negative bacteria, yeast, and multicellular fungi, has applications in clinical microbiology as well as food and feed safety and analysis among other uses.