title: Modeling bacteriophage amplification as a predictive tool for optimized MALDI-TOF MS-based bacterial detection.
abstract: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a valuable tool for rapid bacterial detection and identification but is limited by the need for relatively high cell count samples, which have been grown under strictly controlled conditions. These requirements can be eliminated by the natural infection of a viable bacterial species of interest with a host-specific phage. This produces a rapid increase in phage protein concentrations in comparison to bacterial concentrations, which can in turn be exploited as a method for signal amplification during MALDI-TOF MS. One drawback to this approach is the requirement for repetitive, time-consuming sample preparation and analysis applied over the course of a phage infection to monitor phage concentrations as a function of time to determine the MALDI-TOF MS detection limit. To reduce the requirement for repeated preparation and analysis, a modified phage therapy model was investigated as a means for predicting the time during a given phage infection when a detectable signal would occur. The modified model used a series of three differential equations composed of predetermined experimental parameters including phage burst size and burst time to predict progeny phage concentrations as a function of time. Using Yersinia pestis with plague diagnostic phage φA1122 and Escherichia coli with phage MS2 as two separate, well-characterized model phage-host pairs, we conducted in silico modeling of the infection process and compared it with experimental infections monitored in real time by MALDI-TOF MS. Significant agreement between mathematically calculated phage growth curves and those experimentally obtained by MALDI-TOF MS was observed, thus verifying this method's utility for significant time and labor reduction.
authors.affiliation: Colorado School of Mines, Department of Chemistry and Geochemistry, Golden, CO 80401, USA.
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Cox
authors.forename: Jon C
authors.initials: JC
authors.lastname: Rees
authors.forename: Kent J
authors.initials: KJ
authors.lastname: Voorhees
mesh_terms: D001419:Bacteria / Q000302:isolation & purification / Q000378:metabolism / Q000821:virology*; D001431:Bacteriological Techniques / Q000379:methods*; D001435:Bacteriophages / Q000235:genetics / Q000378:metabolism*; D003198:Computer Simulation; D004926:Escherichia coli / Q000302:isolation & purification / Q000378:metabolism / Q000821:virology; D008954:Models, Biological; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D015010:Yersinia pestis / Q000302:isolation & purification / Q000378:metabolism / Q000821:virology