KMD-Enhanced MALDI-ToF MS for Polymer Biodegradation Analysis

A novel and tailored mass spectrometry workflow is presented for the analysis of polymer biodegradation products, integrating principles from the 'omics' sciences to address the challenges of complex mixture characterization. The workflow combines methodologies from polymer analysis and metabolomics, offering a comprehensive approach to data acquisition and processing, with practical considerations for user implementation. Central to the analytical strategy is the application of Kendrick Mass Defect (KMD) theory, which enhances spectral visualization and facilitates the identification of biodegradation products and metabolites within heterogeneous samples. By combining accessible and open software tools along with custom R scripts, the workflow supports reproducible MS data analysis, providing a platform for advancing polymer biodegradation research. Biodegraded samples, due to their complex polymer and metabolite content, typically generate noisy spectra, which require intensive filtering to distinguish polymer fragments from microbial metabolites. While pure polymer spectra are generally cleaner, they still necessitate specific peak detection methods, emphasizing the need for tailored data processing protocols.