Identification of antibiotic resistance proteins via MiCId's augmented workflow. A mass spectrometry-based proteomics approach

Fast and accurate identification of pathogenic bacteria along with the identification of antibiotic resistance proteins is of paramount importance for the treatment of patients and public health. While mass spectrometry has become an important technique for these purposes there is a lack of mass spectrometry workflow offering this capability. To meet this need we have augmented the previously published Microorganism Classification Identification (MiCId) workflow with this capability. Evaluation results showed that MiCId's workflow has a sensitivity value around 86% and a precision greater than 95% in the identification of antibiotic resistance proteins. Futhermore, we showed that MiCId's workflow is fast. It is capable of providing microorganismal identification, protein identification, sample biomass estimation, and antibiotic resistance protein identification in about 6-17 minutes using computer resources that are available in most desktop and laptop computers making it highly portable workflow. The newly augmented MiCId is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.