Matrix Assisted Laser Desorption Ionization (MALDI) coupled to mass spectrometry (MS) is routinely used in clinical settings to identify (‘biotype’) harmful microorganisms. Biotyping is rapid (minutes) and considerably simpler and cheaper than nucleotide sequencing techniques. However, commercial biotyping platforms are task-restrictive and sold with proprietary software. Our existing MALDI-MS hardware is capable of acquiring biotyping data and recently open-source software was published that enables biotyping and broader taxonomic classification using generic MALDI-MS platforms. In this project, well-characterized model microbial systems will be provided by Prof James Chong, Dr Sean Meaden, and Prof Gavin Thomas, where interests lie in classifying methanogens, soil microbiome, and skin microbiome, respectively. These will be used to test and validate the identification and classification capabilities of our MALDI-MS hardware with the open source software toolkit. The student will download the open-source informatic pipeline and test it on our high-performance computers, receive training on MALDI-MS sample preparation and data acquisition, and process data through the informatic toolkit to evaluate identification and classification performance. Students will work with other members of the technical team to share data and findings and be expected to present their findings orally at a research day in York in September 2024.