TY - JOUR
T1 - Using Infrared Spectroscopy and Multivariate Analysis to Detect Antibiotics' Resistant Escherichia coli Bacteria
AU - Sharaha, Uraib
AU - Rodriguez-Diaz, Eladio
AU - Riesenberg, Klaris
AU - Bigio, Irving J.
AU - Huleihel, Mahmoud
AU - Salman, Ahmad
N1 - Publisher Copyright:
© 2017 American Chemical Society.
PY - 2017/9/5
Y1 - 2017/9/5
N2 - Bacterial pathogens are one of the primary causes of human morbidity worldwide. Historically, antibiotics have been highly effective against most bacterial pathogens; however, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Early and rapid determination of bacterial susceptibility to antibiotics has become essential in many clinical settings and, sometimes, can save lives. Currently classical procedures require at least 48 h for determining bacterial susceptibility, which can constitute a life-threatening delay for effective treatment. Infrared (IR) microscopy is a rapid and inexpensive technique, which has been used successfully for the detection and identification of various biological samples; nonetheless, its true potential in routine clinical diagnosis has not yet been established. In this study, we evaluated the potential of this technique for rapid identification of bacterial susceptibility to specific antibiotics based on the IR spectra of the bacteria. IR spectroscopy was conducted on bacterial colonies, obtained after 24 h culture from patients' samples. An IR microscope was utilized, and a computational classification method was developed to analyze the IR spectra by novel pattern-recognition and statistical tools, to determine E. coli susceptibility within a few minutes to different antibiotics, gentamicin, ceftazidime, nitrofurantoin, nalidixic acid, ofloxacin. Our results show that it was possible to classify the tested bacteria into sensitive and resistant types, with success rates as high as 85% for a number of examined antibiotics. These promising results open the potential of this technique for faster determination of bacterial susceptibility to certain antibiotics.
AB - Bacterial pathogens are one of the primary causes of human morbidity worldwide. Historically, antibiotics have been highly effective against most bacterial pathogens; however, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Early and rapid determination of bacterial susceptibility to antibiotics has become essential in many clinical settings and, sometimes, can save lives. Currently classical procedures require at least 48 h for determining bacterial susceptibility, which can constitute a life-threatening delay for effective treatment. Infrared (IR) microscopy is a rapid and inexpensive technique, which has been used successfully for the detection and identification of various biological samples; nonetheless, its true potential in routine clinical diagnosis has not yet been established. In this study, we evaluated the potential of this technique for rapid identification of bacterial susceptibility to specific antibiotics based on the IR spectra of the bacteria. IR spectroscopy was conducted on bacterial colonies, obtained after 24 h culture from patients' samples. An IR microscope was utilized, and a computational classification method was developed to analyze the IR spectra by novel pattern-recognition and statistical tools, to determine E. coli susceptibility within a few minutes to different antibiotics, gentamicin, ceftazidime, nitrofurantoin, nalidixic acid, ofloxacin. Our results show that it was possible to classify the tested bacteria into sensitive and resistant types, with success rates as high as 85% for a number of examined antibiotics. These promising results open the potential of this technique for faster determination of bacterial susceptibility to certain antibiotics.
UR - http://www.scopus.com/inward/record.url?scp=85028949900&partnerID=8YFLogxK
U2 - 10.1021/acs.analchem.7b01025
DO - 10.1021/acs.analchem.7b01025
M3 - Article
C2 - 28731324
AN - SCOPUS:85028949900
SN - 0003-2700
VL - 89
SP - 8782
EP - 8790
JO - Analytical Chemistry
JF - Analytical Chemistry
IS - 17
ER -