Detection of Protein Toxin Simulants from Contaminated Surfaces by Paper Spray Mass Spectrometry.
William R A WichertElizabeth S DhummakuptChengsen ZhangPhillip M MachRobert C BernhardsTrevor GlarosNicholas E ManickePublished in: Journal of the American Society for Mass Spectrometry (2019)
Proteinaceous toxins are harmful proteins derived from plants, bacteria, and other natural sources. They pose a risk to human health due to infection and also as possible biological warfare agents. Paper spray mass spectrometry (PS-MS) with wipe sampling was used to detect proteins from surfaces as a potential tool for identifying the presence of these toxins. Proteins ranging in mass between 12.4 and 66.5 kDa were tested, including a biological toxin simulant/vaccine for Staphylococcal enterotoxin B (SEBv). Various substrates were tested for these representative proteins, including a laboratory bench, a notebook cover, steel, glass, plant leaf and vinyl flooring. Carbon sputtered porous polyethylene (CSPP) was found to outperform typical chromatography paper used for paper spray, as well as carbon nanotube (CNT)-coated paper and polyethylene (PE), which have been previously shown to be well-suited for protein analysis. Low microgram quantities of the protein toxin simulant and other test proteins were successfully detected with good signal-to-noise from surfaces using a porous wipe. These applications demonstrate that PS-MS can potentially be used for rapid, sample preparation-free detection of proteins and biological warfare agents, which would be beneficial to first responders and warfighters.
Keyphrases
- mass spectrometry
- human health
- escherichia coli
- liquid chromatography
- risk assessment
- multiple sclerosis
- gas chromatography
- protein protein
- high performance liquid chromatography
- carbon nanotubes
- biofilm formation
- binding protein
- small molecule
- drinking water
- staphylococcus aureus
- tandem mass spectrometry
- air pollution
- cystic fibrosis
- label free
- candida albicans
- cell wall
- molecularly imprinted
- data analysis