Identification of resistance in Escherichia coli and Klebsiella pneumoniae using excitation-emission matrix fluorescence spectroscopy and multivariate analysis

Abstract

Klebsiella pneumoniae and Escherichia coli are part of the Enterobacteriaceae family, being common sources of community and hospital infections and having high antimicrobial resistance. This resistance profile has become the main problem of public health infections. Determining whether a bacterium has resistance is critical to the correct treatment of the patient. Currently the method for determination of bacterial resistance used in laboratory routine is the antibiogram, whose time to obtain the results can vary from 1 to 3 days. An alternative method to perform this determination faster is excitation-emission matrix (EEM) fluorescence spectroscopy combined with multivariate classification methods. In this paper, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), coupled with dimensionality reduction and variable selection algorithms: Principal Component Analysis (PCA), Genetic Algorithm (GA), and the Successive Projections Algorithm (SPA) were used. The most satisfactory models achieved sensitivity and specificity rates of 100% for all classes, both for E. coli and for K. pneumoniae. This finding demonstrates that the proposed methodology has promising potential in routine analyzes, streamlining the results and increasing the chances of treatment efficiency. The Enterobacteriaceae family is one of the most clinically prominent bacteria groups. One of the main gramnegative pathogen is Klebsiella pneumoniae (K. pneumoniae), which causes opportunistic infections, such as pneumonia, sepsis and inflammation of the urinary tract 1. Another gram-negative that compose the entereobacteriaceae family is Escherichia coli, which are not typically pathogenic to humans and have the ability to cause several diseases in different sites including gastrointestinal tract, the renal system and the central nervous system 2,3. Antibiotic therapy induces the selection of resistant bacteria 4 , which generate environmental and health hazards, and economical risk. Over the last decades, several bacterial strains have become progressively resistant to antimicrobial agents 5. Bacteria may have natural or acquired resistance. Among the genetic variations that confer resistance in bacteria, the main ones are extended spectrum betalactamases 6 (ESBL), AmpC production, Carbapenemases production 7 , KPC group and MBL group 5. Currently, the standard detection method is culture-based, which is time-consuming and labor intensive, providing a slow detection 8. Other methods can be used to obtain faster results, such as low cytometry 9 , electrochemical detection 10 , and polymerase chain reaction (PCR) 11. Near infrared (NIR) 12 , Raman 13 and Fourier transform infrared (FTIR) spectroscopy 14 have been also reported for these applications.

Gold Nanoparticle-Based Resuscitation of Cefoxitin against Clinical Pathogens: A Nano-Antibiotic Strategy to Overcome Resistance

“…Subsequently, the prevalence of antibiotic resistance has increased globally with time. Two of the most common Gram-negative sources of community or hospital-acquired infections, i.e., Escherichia coli and Klebsiella pneumoniae [ 1 ], have developed extended-spectrum beta-lactamase and modified outer-membrane porins in the recent past to escape the effect of the cephalosporin class of antibiotics [ 2 , 3 , 4 , 5 , 6 , 7 ]. The present study was focused on the resistance issues of E. coli and K. pneumoniae for cefoxitin, which is a second-generation cephalosporin.…”

Influence of Varying Pre-Culture Conditions on the Level of Population Heterogeneity in Batch Cultures with an Escherichia coli Triple Reporter Strain

“…Generally, the principal component analysis successfully supported a faster comprehension of this larger dataset and revealed trends and correlations, as this tool was also used with great success in other studies [ 46 , 47 ]. The here used principal component analysis could be further improved by the implementation of clusters based on the Euclidean distance in the score plot.…”

Synergistic antibacterial activity and inhibition of TiO2 nanotube arrays and loaded antibiotics against gram-positive and gram-negative bacteria

“…Despite the extensive reliance on antibiotics to treat bacterial illnesses, their effectiveness has also been undermined by the advent of drug-resistant bacterial strains and alteration of the composition and population of existing, stable strains of bacteria (Pray, 2008;Bassetti and Righi, 2020). Specifically, antibiotic resistance is a new challenge found to be higher in deviceassociated infections and has intensified the threat to public health (Martinez and Baquero, 2000;Medina and Pieper, 2016;Costa et al, 2020). Klebsiella pneumoniae, in particular, has gained attention as increasingly relevant clinical bacterial species for its high pathogenicity and ability to develop extreme resistance to multiple antibiotics (Costa et al, 2020).…”