Mechanism of Bacterial Inactivation by (+)-Limonene and Its Potential Use in Food Preservation Combined Processes

This work explores the bactericidal effect of (+)-limonene, the major constituent of citrus fruits' essential oils, against E. coli. The degree of E. coli BJ4 inactivation achieved by (+)-limonene was influenced by the pH of the treatment medium, being more bactericidal at pH 4.0 than at pH 7.0. Deletion of rpoS and exposure to a sub-lethal heat or an acid shock did not modify E. coli BJ4 resistance to (+)-limonene. However, exposure to a sub-lethal cold shock decreased its resistance to (+)-limonene. Although no sub-lethal injury was detected in the cell envelopes after exposure to (+)-limonene by the selective-plating technique, the uptake of propidium iodide by inactivated E. coli BJ4 cells pointed out these structures as important targets in the mechanism of action. Attenuated Total Reflectance Infrared Microspectroscopy (ATR-IRMS) allowed identification of altered E. coli BJ4 structures after (+)-limonene treatments as a function of the treatment pH: ß-sheet proteins at pH 4.0 and phosphodiester bonds at pH 7.0. The increased sensitivity to (+)-limonene observed at pH 4.0 in an E. coli MC4100 lptD4213 mutant with an increased outer membrane permeability along with the identification of altered ß-sheet proteins by ATR-IRMS indicated the importance of this structure in the mechanism of action of (+)-limonene. The study of mechanism of inactivation by (+)-limonene led to the design of a synergistic combined process with heat for the inactivation of the pathogen E. coli O157:H7 in fruit juices. These results show the potential of (+)-limonene in food preservation, either acting alone or in combination with lethal heat treatments

Rapid discrimination and classification of edible insect powders using ATR-FTIR spectroscopy combined with multivariate analysis

Insects are being proposed as an alternative way to ensure world''s food and feed security. Methods to determine edible insect powder''s origin and species will be needed for quality control purposes. Infrared spectroscopy has been extensively used in rapid chemical fingerprinting of food products. The present research explores a new approach to discriminate and classify commercial edible insect powders using attenuated total reflectance mid-infrared spectroscopy combined with multivariate analysis. Infrared spectra of seven commercial edible insect powders from different species (Tenebrio molitor, Alphitobius diaperinus, Gryllodes sigillatus, Acheta domesticus and Locusta migratoria) and origins (the Netherlands and New Zealand) were collected to build up soft independent modelling of class analogy (SIMCA) models. SIMCA models clearly discriminated insects by their species and origin linking their differences to lipids and chitin. SIMCA models performance was tested using five spectra of each class not used to build up the training set. 100% correct predictions were obtained for all the samples analysed with the exception of one sample of Alphitobius diaperinus. Infrared spectroscopy coupled to multivariate analysis provided a powerful method for the assurance of insect powder''s authenticity

Surface-Enhanced Raman Spectroscopy Combined with Multivariate Analysis for Fingerprinting Clinically Similar Fibromyalgia and Long COVID Syndromes

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC

Discrimination of heavy metal acclimated environmental strains by chemometric analysis of FTIR spectra

Heavy metal acclimated bacteria are profoundly the preferred choice for bioremediation studies. Bacteria get acclimated to toxic concentrations of heavy metals by induction of specific enzymes and genetic selection favoring new metabolic abilities leading to activation of one or several of resistance mechanisms creating bacterial populations with differences in resistance profile and/or level. Therefore, to use in bioremediation processes, it is important to discriminate acclimated bacterial populations and choose a more resistant strain. In this study, we discriminated heavy metal acclimated bacteria by using Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy and multivariate analysis methods namely Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA). Two acclimation methods, acute and gradual, were used which cause differences in molecular changes resulting in bacterial populations with different molecular and resistance profiles. Brevundimonas sp., Gordonia sp., and Microbacterium oxydans were exposed to the toxic concentrations of Cd (30 mu g/ml) or Pb (90 mu g/ml) by using broth medium as a growth media. Our results revealed that PCA and HCA clearly discriminated the acute-acclimated, gradual acclimated, and control bacteria from each other in protein, carbohydrate, and whole spectral regions. Furthermore, we classified acclimated (acute and gradual) and control bacteria more accurately by using SIMCA with 99.9% confidence. This study demonstrated that heavy metal acclimated and control group bacteria can be discriminated by using chemometric analysis of FTIR spectra in a powerful, cost-effective, and handy way. In addition to the determination of the most appropriate acclimation procedure, this approach can be used in the detection of the most resistant bacterial strains to be used in bioremediation studies