Rapid discrimination of Enterococcus faecium strains using phenotypic analytical techniques

Clinical isolates of glycopeptide resistant enterococci (GRE) were used to compare three rapid phenotyping and analytical techniques.</p

Bacterial discrimination by Fourier transform infrared spectroscopy, MALDI-mass spectrometry and whole-genome sequencing

Aim: Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. Materials & methods: 104 pathogenic isolates of Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus pyogenes and Staphylococcus aureus were analyzed. Results: Overall prediction accuracy was 99.6% in FT-IR and 95.8% in MALDI-TOF-MS. Analysis of N. meningitidis serogroups was superior in FT-IR compared with MALDI-TOF-MS. Phylogenetic relationship of S. pyogenes was similar by FT-IR and WGS, but not S. aureus or S. pneumoniae. Clinical severity was associated with the zinc ABC transporter and DNA repair genes in S. pneumoniae and cell wall proteins (biofilm formation, antibiotic and complement permeability) in S. aureus via WGS. Conclusion: FT-IR warrants further clinical evaluation as a promising diagnostic tool

Charge Transfer Complexes of Ketotifen with 2,3-Dichloro-5,6-dicyano-p-benzoquinone and 7,7,8,8-Tetracyanoquodimethane: Spectroscopic Characterization Studies

The reactions of ketotifen fumarate (KT) with 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ) and 7,7,8,8-tetracyanoquinodimethane (TCNQ) as π acceptors to form charge transfer (CT) complexes were evaluated in this study. Experimental and theoretical approaches, including density function theory (DFT), were used to obtain the comprehensive, reliable, and accurate structure elucidation of the developed CT complexes. The CT complexes (KT-DDQ and KT-TCNQ) were monitored at 485 and 843 nm, respectively, and the calibration curve ranged from 10 to 100 ppm for KT-DDQ and 2.5 to 40 ppm for KT-TCNQ. The spectrophotometric methods were validated for the determination of KT, and the stability of the CT complexes was assessed by studying the corresponding spectroscopic physical parameters. The molar ratio of KT:DDQ and KT:TCNQ was estimated at 1:1 using Job’s method, which was compatible with the results obtained using the Benesi–Hildebrand equation. Using these complexes, the quantitative determination of KT in its dosage form was successful

Rapid detection and quantification of paracetamol and its major metabolites using surface enhanced Raman scattering

Paracetamol (also known as acetaminophen) is an over-the-counter (OTC) drug that is commonly used as an analgesic for mild pain, headache, cold and flu. While in the short term it is a safe and effective medicine, it is sometimes used for attempted suicides particularly in young adults. In such circumstances it is important for rapid diagnosis of overdoses as antidotes can be given to limit liver damage from one of its primary metabolites N-acetyl-p-benzoquinone imine (NAPQI). Unfortunately, the demand for rapid and sensitive analytical techniques to accurately monitor the abuse of OTC drugs has significantly risen. Ideally these techniques would be highly specific, sensitive, reproducible, portable and rapid. In addition, an ideal point of care (PoC) test would enable quantitative detection of drugs and their metabolites present in body fluids. While Raman spectroscopy meets these specifications, there is a need for enhancement of the signal because the Raman effect is weak. In this study, we developed a surface-enhanced Raman scattering (SERS) methodology in conjunction with chemometrics to quantify the amount of paracetamol and its main primary metabolites (viz., paracetamol sulfate, p-acetamidophenyl β-D-glucuronide and NAPQI) in water and artificial urine. The enhancement of the SERS signals was achieved by mixing the drug or xenometabolites with a gold nanoparticle followed by aggregation with 0.045 M NaCl. We found that the SERS data could be collected directly, due to immediate analyte association with the Au surface and colloid aggregation. Accurate and precise measurements were generated, with a limit of detection (LoD) of paracetamol in water and artificial urine at 7.18 × 10-6 M and 2.11 × 10-5 M, respectively, which is well below the limit needed for overdose and indeed normal levels of paracetamol in serum after taking 1 g orally. The predictive values obtained from the analysis of paracetamol in water and artificial urine were also excellent, with the coefficient of determination (Q2) being 0.995 and 0.996, respectively (1 suggests a perfect model). It was noteworthy that when artificial urine was spiked with paracetamol, no aggregating agent was required due to the salt rich medium, which led to spontaneous aggregation. Moreover, for the xenometabolites of paracetamol excellent LoDs were obtained and these ranged from 2.6 × 10-4 M to 5 × 10-5 M with paracetamol sulfate and NAPQI having Q2 values of 0.934 and 0.892 and for p-acetamidophenyl β-D-glucuronide this was slightly lower at 0.6437

Metabolic fingerprinting of Pseudomonas putida DOT-T1E strains: understanding the influence of divalent cations in adaptation mechanisms following exposure to toluene

Pseudomonas putida strains can adapt and overcome the activity of toxic organic solvents by the employment of several resistant mechanisms including efflux pumps and modification to lipopolysaccharides (LPS) in their membranes. Divalent cations such as magnesium and calcium play a crucial role in the development of solvent tolerance in bacterial cells. Here, we have used Fourier transform infrared (FT-IR) spectroscopy directly on cells (metabolic fingerprinting) to monitor bacterial response to the absence and presence of toluene, along with the influence of divalent cations present in the growth media. Multivariate analysis of the data using principal component-discriminant function analysis (PC-DFA) showed trends in scores plots, illustrating phenotypic alterations related to the effect of Mg2+, Ca2+ and toluene on cultures. Inspection of PC-DFA loadings plots revealed that several IR spectral regions including lipids, proteins and polysaccharides contribute to the separation in PC-DFA space, thereby indicating large phenotypic response to toluene and these cations. Finally, the saturated fatty acid ratio from the FT-IR spectra showed that upon toluene exposure, the saturated fatty acid ratio was reduced, while it increased in the presence of divalent cations. This study clearly demonstrates that the combination of metabolic fingerprinting with appropriate chemometric analysis can result in practicable knowledge on the responses of important environmental bacteria to external stress from pollutants such as highly toxic organic solvents, and indicates that these changes are manifest in the bacterial cell membrane. Finally, we demonstrate that divalent cations improve solvent tolerance in P. putida DOT‑T1E strains

Efficient nanostructured materials to reduce nutrient leaching to overcome environmental contaminants

Abstract Nutrient leaching is a major reason for fresh and ground water contamination. Menthol is the major bioactive ingredient of Mentha arvensis L. and one of the most traded products of global essential oil market. The indigenous production of menthol crystals in developing countries of the world can prove to be the backbone for local growers and poor farmers. Therefore, present research was designed to check the effects of nano-structured plant growth regulators (PGRs) (28-homobrassinolide and ethephon) with reduced leaching potentials on the essential oil and menthol (%) of Mentha arvensis L. The prepared nano-formulations were characterized by Fourier transform infrared (FTIR) spectroscopy, Laser induced breakdown spectroscopy (LIBS), Differential scanning colorimetry-thermal gravimetric analysis (DSC-TGA), Scanning electron microscopy (SEM), Atomic absorption spectrometry (AAS) and Zeta potential and Zeta size analysis. The menthol (%) was determined by modified spectrophotometric and gas chromatographic (GC) method. The highest essential oil (%) was obtained by the application of 28-homobrassinolide-Zn-NPs-L-II (0.92 ± 0.09%) and ethephon-Ca-NPs-L-III (0.91 ± 0.05%) as compared to the control (0.65 ± 0.03%) and blank (0.62 ± 0.09%). The highest menthol (%) was obtained by applying 28-homobrassinolide-Ca-NPs-L-I (80.06 ± 0.07%), 28-homobrassinolide-Ca-NPs-L-II (80.48 ± 0.09%) and 28-homobrassinolide-Ca-NPs-L-III (80.84 ± 0.11%) and ethephon-Ca-NPs-L-III (81.53 ± 0.17%) and ethephon-Zn-NPs-L-II (81.93 ± 0.26%) as compared to control (67.19 ± 0.14%) and blank (63.93 ± 0.17%)

Investigation the Effects of Green-Synthesized Copper Nanoparticles on the Performance of Activated Carbon-Chitosan-Alginate for the Removal of Cr(VI) from Aqueous Solution

In the present investigation, green nano-zerovalent copper (GnZVCu), activated carbon (AC), chitosan (CS) and alginate (ALG) nanocomposites were produced and used for the elimination of chromium (VI) from a polluted solution. The nanocomposites GnZVCu/AC-CS-alginate and AC-CS-alginate were prepared. Analysis and characterization were performed by the following techniques: X-ray diffraction, energy dispersive X-ray spectroscopy, scanning electron microscopy, transmission electron microscopy and Fourier transform infrared spectroscopy. The SEM analysis revealed that the nanocomposites are extremely mesoporous, which leads to the greatest adsorption of Cr+6 (i.e., 97.5% and 95%) for GnZVCu/AC-CS-alginate and AC-CS-alginate, respectively. The adsorption efficiency was enhanced by coupling GnZVCu with AC-CS-alginate with a contact time of 40 min. The maximum elimination of Cr+6 with the two nanocomposites was achieved at pH 2. The isotherm model, Freundlich adsorption isotherm and kinetics model and P.S.O.R kinetic models were discovered to be better suited to describe the exclusion of Cr+6 by the nanocomposites. The results suggested that the synthesized nanocomposites are promising for the segregation of Cr+6 from polluted solutions, specially the GnZVCu/AC-CS-alginate nanocomposite

Simultaneous Multiplexed Quantification of Banned Sudan Dyes Using Surface Enhanced Raman Scattering and Chemometrics

Azo compounds such as the Sudan dyes I–IV are frequently used illegally as colorants and added to a wide range of foods. These compounds have been linked to a number of food safety hazards. Several methods have been proposed to detect food contamination by azo compounds and most of these are laboratory based; however, the development of reliable and portable methods for the detection and quantification of food contaminated by these chemicals in low concentration is still needed due to their potentially carcinogenic properties. In this study, we investigated the ability of surface enhanced Raman scattering (SERS) combined with chemometrics to quantify Sudan I–IV dyes. SERS spectra were acquired using a portable Raman device and gold nanoparticles were employed as the SERS substrate. As these dyes are hydrophobic, they were first dissolved in water: acetonitrile (1:10, v/v) as single Sudan dyes (I–IV) at varying concentrations. SERS was performed at 785 nm and the spectra were analyzed by using partial least squares regression (PLS-R) with double cross-validations. The coefficient of determination (Q2) were 0.9286, 0.9206, 0.8676 and 0.9705 for Sudan I to IV, respectively; the corresponding limits of detection (LOD) for these dyes were estimated to be 6.27 × 10−6, 5.35 × 10−5, 9.40 × 10−6 and 1.84 × 10−6 M. Next, quadruplex mixtures were made containing all four Sudan dyes. As the number of possible combinations needed to cover the full concentration range at 5% intervals would have meant collecting SERS spectra from 194,481 samples (214 combinations) we used a sustainable solution based on Latin hypercubic sampling and reduced the number of mixtures to be analyzed to just 90. After collecting SERS spectra from these mixture PLS-R models with bootstrapping validations were employed. The results were slightly worse in which the Q2 for Sudan I to IV were 0.8593, 0.7255, 0.5207 and 0.5940 when PLS1 models (i.e., one model for one dye) was employed and they changed to 0.8329, 0.7288, 0.5032 and 0.5459 when PLS2 models were employed (i.e., four dyes were modelled simultaneously). These results showed the potential of SERS to be used as a high-throughput, low-cost, and reliable methods for detecting and quantifying multiple Sudan dyes in low concentration from illegally adulterated samples.</jats:p