NLM DIR Seminar Schedule

Abstract:

Fast and accurate identification of pathogenic bacteria along with the identification of antibiotic resistance proteins is of paramount importance for patient treatments and public health. Once pathogenic bacteria causing infections are identified swiftly along with their antibiotic resistance proteins (if present), proper treatment can be administered, which can increase patients’ survival rate and minimize improper use of antibiotics. Trustworthy biomass estimates, on the other hand, are critical for microbial community structure analyses that arise in almost every microbiome study. To address these important issues, we have developed MiCId, a mass-spectrometry-based proteomics workflow for rapid identification of microorganisms and antibiotic resistance proteins and estimation of biomass.

In this talk I will demonstrate that MiCId’s workflow for pathogen identification has a sensitivity between 83.2% - 93.9% when the proportion of false discoveries controlled at the 5%. For the identification of antibiotic resistance proteins, MiCId’s workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95%. In addition to having high sensitivity and precision, MiCId’s workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as for detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6−17 min per MS/MS experiment using computing resources that are available in most desktop and laptop computers.