A fluorescent sensor array based on antibiotic-stabilized metal nanoclusters for the multiplex detection of bacteria

To address the need for facile, rapid detection of pathogens in water supplies, a fluorescent sensing array platform based on antibiotic-stabilized metal nanoclusters was developed for the multiplex detection of pathogens. Using five common antibiotics, eight different nanoclusters (NCs) were synthesized including ampicillin stabilized copper NCs, cefepime stabilized gold and copper NCs, kanamycin stabilized gold and copper NCs, lysozyme stabilized gold NCs, and vancomycin stabilized gold/silver and copper NCs. Based on the different interaction of each NC with the bacteria strains, unique patterns were generated. Various machine learning algorithms were employed for pattern discernment, among which the artificial neural networks proved to have the highest performance, with an accuracy of 100%. The developed prediction model performed well on an independent test dataset and on real samples gathered from drinking water, tap water and the Anzali Lagoon water, with prediction accuracy of 96.88% and 95.14%, respectively. This work demonstrates how generic antibiotics can be implemented for NC synthesis and used as recognition elements for pathogen detection. Furthermore, it displays how merging machine learning techniques can elevate sensitivity of analytical devices.

Multiplex Detection of Antibiotic Residues in Milk: Application of MCR-ALS on Excitation-Emission Matrix Fluorescence (EEMF) Data Sets

The presence of antibiotics and their metabolites in milk and dairy products is a serious concern because of their harmful effects on human health. In the current study, a novel synergistic bimetallic nanocluster with gold and silver as an emission fluorescence probe was investigated for the simultaneous determination of tetracycline (TC), ampicillin (AMP), and sulfacetamide (SAC) antibiotics in the milk samples using excitation-emission matrix fluorescence (EEMF) spectroscopy. The multivariate curve resolution-alternating least squares (MCR-ALS) method was implemented to analyze augmented EEMF data sets to quantify the multicomponent systems in the presence of interferences with considerable spectral overlap. A pseudo-univariate calibration curve of the resolved emission spectra intensity against the concentration of the mentioned antibiotics was linear in the range of 5-5000 ng mL^-1 for AMP and 50-5000 ng mL^-1 for TC and SAC. The calculated values of the limit of detection ranged between 1.4 and 14.6 ng mL^-1 with a relative standard deviation (RSD) of less than 4.9%. The obtained results show that the EEMF/MCR-ALS methodology using an emission fluorescence probe is a powerful tool for the simultaneous quantification of TC, AMP, and SAC in complex matrices with highly overlapped spectra.

Untargeted metabolomics changes on Gammarus pulex induced by propranolol, triclosan, and nimesulide pharmaceutical drugs

The presence of pharmaceuticals and personal care products (PPCPs) in natural water resources due to incomplete removal in Wastewater Treatment Plants (WWTPs) is a serious environmental concern at present. In this work, the effects of three pharmaceuticals (propranolol, triclosan, and nimesulide) on Gammarus pulex metabolic profiles at different doses and times of exposure have been investigated by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The complex data sets generated in the different exposure experiments were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest (ROI) data and on their analysis by the Multivariate Curve-Resolution Alternating Least Squares (MCR-ALS) chemometrics method. This approach, allowed the resolution and identification of the metabolites present in the analyzed samples, as well as the estimation of their concentration changes due to the exposure experiments. ANOVA Simultaneous Component Analysis (ASCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were then conducted to assess the changes in the concentration of the metabolites for the three pharmaceuticals at the different conditions of exposure. The three tested pharmaceuticals changed the concentrations of metabolites, which were related to different KEGG functional classes. These changes summarize the biochemical response of Gammarus pulex to the exposure by the three investigated pharmaceuticals. Possible pathway alterations related to protein synthesis and oxidative stress were observed in the concentration of identified metabolites.