TY - JOUR
T1 - Robust detection of P. aeruginosa and S. aureus acute lung infections by secondary electrospray ionization-mass spectrometry (SESI-MS) breathprinting
T2 - From initial infection to clearance
AU - Zhu, Jiangjiang
AU - Jiménez-Díaz, Jaime
AU - Bean, Heather D.
AU - Daphtary, Nirav A.
AU - Aliyeva, Minara I.
AU - Lundblad, Lennart K.A.
AU - Hill, Jane E.
PY - 2013/9
Y1 - 2013/9
N2 - Before breath-based diagnostics for lung infections can be implemented in the clinic, it is necessary to understand how the breath volatiles change during the course of infection, and ideally, to identify a core set of breath markers that can be used to diagnose the pathogen at any point during the infection. In the study presented here, we use secondary electrospray ionization-mass spectrometry (SESI-MS) to characterize the breathprint of Pseudomonas aeruginosa and Staphylococcus aureus lung infections in a murine model over a period of 120 h, with a total of 86 mice in the study. Using partial least squares-discriminant analysis (PLS-DA) to evaluate the time-course data, we were able to show that SESI-MS breathprinting can be used to robustly classify acute P. aeruginosa and S. aureus mouse lung infections at any time during the 120 h infection/clearance process. The variable importance plot from PLS indicates that multiple peaks from the SESI-MS breathprints are required for discriminating the bacterial infections. Therefore, by utilizing the entire breathprint rather than single biomarkers, infectious agents can be diagnosed by SESI-MS independent of when during the infection breath is tested.
AB - Before breath-based diagnostics for lung infections can be implemented in the clinic, it is necessary to understand how the breath volatiles change during the course of infection, and ideally, to identify a core set of breath markers that can be used to diagnose the pathogen at any point during the infection. In the study presented here, we use secondary electrospray ionization-mass spectrometry (SESI-MS) to characterize the breathprint of Pseudomonas aeruginosa and Staphylococcus aureus lung infections in a murine model over a period of 120 h, with a total of 86 mice in the study. Using partial least squares-discriminant analysis (PLS-DA) to evaluate the time-course data, we were able to show that SESI-MS breathprinting can be used to robustly classify acute P. aeruginosa and S. aureus mouse lung infections at any time during the 120 h infection/clearance process. The variable importance plot from PLS indicates that multiple peaks from the SESI-MS breathprints are required for discriminating the bacterial infections. Therefore, by utilizing the entire breathprint rather than single biomarkers, infectious agents can be diagnosed by SESI-MS independent of when during the infection breath is tested.
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U2 - 10.1088/1752-7155/7/3/037106
DO - 10.1088/1752-7155/7/3/037106
M3 - Article
C2 - 23867706
AN - SCOPUS:84884161403
SN - 1752-7155
VL - 7
JO - Journal of Breath Research
JF - Journal of Breath Research
IS - 3
M1 - 037106
ER -