Recent trends in application of multivariate curve resolution approaches for improving gas chromatography–mass spectrometry analysis of essential oils

Voltammetric techniques for low-cost on-site routine analysis of thymol in the medicinal plant Ocimum gratissimum

The composition of essential oils varies according to culture conditions and climate, which induces a need for simple and inexpensive characterization methods close to the place of extraction. This appears particularly important for developing countries. Herein, we develop an analytical strategy to determine the thymol content in Ocimum Gratissimum, a medicinal plant from Benin. The protocol is based on electrochemical techniques (cyclic and square wave voltammetry) implemented with a low cost potentiostat. Thymol is a phenol derivative and was directly oxidized at the electrode surface. We had to resort to submillimolar concentrations (25-300 μM) in order to minimize production of phenol oligomers that passivate the electrode. We worked first on two essential oils and realized that in one of them the thymol concentration was below our detection method. These results were confirmed by gas chromatography - mass spectrometry. Furthermore, we optimized the detection protocol to analyze an infusion made directly from the leaves of the plant. Finally, we studied whether the cost of the electrochemical cell may also be minimized by using pencil lead as working and counter electrodes.

The Effect of Foliar Application of Melatonin on Changes in Secondary Metabolite Contents in Two Citrus Species Under Drought Stress Conditions

Plant secondary metabolites are compounds that play an important role in plant interactions and defense. Persian lime and Mexican lime as the two most important sour lime varieties with high levels of secondary metabolites, are widely cultivated in tropical and subtropical areas. Melatonin is a pleiotropic molecule that plays a key role in protecting plants against drought stress through regulating the secondary metabolite biosynthesis pathway. This study was performed as a factorial experiment consisting of three factors in a completely randomized design (CRD), including four concentrations of melatonin (0, 50, 100, and 150 μM), three levels of drought stress [100% (control), 75% (moderate stress), and 40% (severe stress) field capacity (FC)], and two Citrus cultivars. The experiment was conducted for 60 days in a greenhouse condition. Based on the results of this study under severe drought stress, melatonin-treated crops had higher total flavonoid and total phenolic contents than the untreated crops. The highest level of essential oils components was observed on 100 μM foliar application of melatonin under severe drought stress in both varieties. The main component of the essential oil was limonene in both Citrus species. Moreover, based on the analysis of the results, hesperidin was the main polyphenol in both varieties. Since the use of melatonin often increases the production of secondary metabolites, this study can be considered as a very effective method for controlling the adverse effects of drought stress in citrus for both industrial and horticultural aims.

Data handling and data analysis in metabolomic studies of essential oils using GC-MS

Gas chromatography electron impact ionization mass spectrometry (GC-EI-MS) has been, and remains, the most widely applied analytical technique for metabolomic studies of essential oils. GC-EI-MS analysis of complex samples, such as essential oils, creates a large volume of data. Creating predictive models for such samples and observing patterns within complex data sets presents a significant challenge and requires application of robust data handling and data analysis methods. Accordingly, a wide variety of software and algorithms has been investigated and developed for this purpose over the years. This review provides an overview and summary of that research effort, and attempts to classify and compare different data handling and data analysis procedures that have been reported to-date in the metabolomic study of essential oils using GC-EI-MS.

Identification of systematic absence of cross-peaks (SACPs) in a two-dimensional asynchronous Spectrum using an auxiliary 2D quotient Spectrum and a statistical test

Systematic Absence of Cross Peaks (SACPs) in a two-dimensional (2D) asynchronous spectrum, a sensitive indicator of the signal purity, is very important in analyzing bilinear data. However, identification of SACPs in practice remains a challenge because of noise in the corresponding 2D asynchronous spectrum. We firstly show that SACP can be identified via a statistical test using a large amount of 2D asynchronous spectra. To meet the practical demand that SACPs must be identified based on a single 2D asynchronous spectrum in many cases, we use a 2D quotient spectrum (Q (x, y)) as an effective auxiliary tool to recognize SACPs. The expectation of Q(x, y) is zero when (x, y) is within SACP or background regions in the corresponding 2D asynchronous spectrum. When (x, y) is in a cross-peak region, the expectation of the absolute value of Q(x, y) is a constant regardless of whether the cross-peak in a 2D asynchronous spectrum is strong or weak. Thus, a unified threshold can be set up to differentiate the SACP region from cross-peak region via the auxiliary 2D quotient spectrum. We have applied this approach on two real-world examples and satisfactory results have been obtained. This result demonstrates that the statistical test with a 2D quotient spectrum is applicable in real-world systems.

Deep-Learning-Assisted multivariate curve resolution

Gas chromatography-mass spectrometry (GC-MS) is one of the major platforms for analyzing volatile compounds in complex samples. However, automatic and accurate extraction of qualitative and quantitative information is still challenging when analyzing complex GC-MS data, especially for the components incompletely separated by chromatography. Deep-Learning-Assisted Multivariate Curve Resolution (DeepResolution) was proposed in this study. It essentially consists of convolutional neural networks (CNN) models to determine the number of components of each overlapped peak and the elution region of each compound. With the assistance of the predicted elution regions, the informative regions (such as selective region and zero-concentration region) of each compound can be located precisely. Then, full rank resolution (FRR), multivariate curve resolution-alternating least squares (MCR-ALS) or iterative target transformation factor analysis (ITTFA) can be chosen adaptively to resolve the overlapped components without manual intervention. The results showed that DeepResolution has superior compound identification capability and better quantitative performances when comparing with MS-DIAL, ADAP-GC and AMDIS. It was also found that baseline levels, interferents, component concentrations and peak tailing have little influences on resolution result. Besides, DeepResolution can be extended easily when encountering unknown component(s), due to the independence of each CNN model. All procedures of DeepResolution can be performed automatically, and adaptive selection of resolution methods ensures the balance between resolution power and consumed time. It is implemented in Python and available at https://github.com/XiaqiongFan/DeepResolution.

Antifungal activity of eugenol on Cryptococcus neoformans biological activity and Cxt1p gene expression

Background and Purpose

The present study was targeted toward investigating the effects of eugenol on Cryptococcus neoformans biological activity and Cxt1p gene expression.

Materials and Methods

For the purpose of the study, the growth, urease, synergism activity, and disk diffusion of C. neoformans were assessed in eugenol-treated culture. The minimum inhibitory concentration (MIC) was determined by the Clinical and Laboratory Standards Institute M27-A3 method at a concentration range of 0.062-2 mg/mL. Subsequently, the expression of Cxt1p genes was studied at the MIC₅₀ concentration of eugenol using real-time polymerase chain reaction.

Results

The obtained results showed that eugenol at the concentrations of 125 and 500 µg/mL resulted in 50% and 100% growth inhibition in C. neoformans, respectively. In terms of urease activity, the results showed that the addition of MIC₅₀ of eugenol and fluconazole to urea medium reduced urease activity in C. neoformans. In the culture treated with eugenol, the inhibition zone of antifungal drugs, namely amphotericin B, itraconazole, and fluconazole, was increased to 36±0.002, 22±0.001, and 12±0.002 mm, respectively. The expression levels of Cxt1p in the eugenol-treated, fluconazole-treated, and non-treated samples were estimated at 46%, 58%, and 100%, respectively.

Conclusion

The findings of the current study revealed that eugenol could cause C. neoformans growth inhibition and reduce Cxt1p expression in this species. As the results indicated, the susceptibility of C. neoformans to fluconazole was increased when combined with eugenol.

Tools in the Investigation of Volatile Semiochemicals on Insects: From Sampling to Statistical Analysis

The recognition of volatile organic compounds (VOCs) involved in insect interactions with plants or other organisms is essential for constructing a holistic comprehension of their role in ecology, from which the implementation of new strategies for pest and disease vector control as well as the systematic exploitation of pollinators and natural enemies can be developed. In the present paper, some of the general methods employed in this field are examined, focusing on their available technologies. An important part of the investigations conducted in this context begin with VOC collection directly from host organisms, using classical extraction methods, by the employment of adsorption materials used in solid-phase micro extraction (SPME) and direct-contact sorptive extraction (DCSE) and, subsequently, analysis through instrumental analysis techniques such as gas chromatography (GC), nuclear magnetic resonance (NMR) and mass spectrometry (MS), which provide crucial information for determining the chemical identity of volatile metabolites. Behavioral experiments, electroantennography (EAG), and biosensors are then carried out to define the semiochemicals with the best potential for performing relevant functions in ecological relationships. Chemical synthesis of biologically-active VOCs is alternatively performed to scale up the amount to be used in different purposes such as laboratory or field evaluations. Finally, the application of statistical analysis provides tools for drawing conclusions about the type of correlations existing between the diverse experimental variables and data matrices, thus generating models that simplify the interpretation of the biological roles of VOCs.

Biological and Medical Applications of Multivariate Curve Resolution Assisted Raman Spectroscopy

Biological specimens such as cells, tissues and biofluids (urine, blood) contain mixtures of many different biomolecules, all of which contribute to a Raman spectrum at any given point. The separation and identification of pure biochemical components remains one of the biggest challenges in Raman spectroscopy. Multivariate curve resolution, a matrix factorization method, is a powerful, yet flexible, method that can be used with constraints, such as non-negativity, to decompose a complex spectroscopic data matrix into a small number of physically meaningful pure spectral components along with their relative abundances. This paper reviews recent applications of multivariate curve resolution by alternating least squares analysis to Raman spectroscopic and imaging data obtained either in vivo or in vitro from biological and medical samples.

Quantitative analysis of multiple high-resolution mass spectrometry images using chemometric methods: quantitation of chlordecone in mouse liver

In this work, a chemometrics-based strategy is developed for quantitative mass spectrometry imaging (MSI).

Preparation of Essential Oil-Based Microemulsions for Improving the Solubility, pH Stability, Photostability, and Skin Permeation of Quercetin

Quercetin can bring many benefits to skin based on its various bioactivities. However, the therapeutic effect of quercetin is limited due to the poor water solubility, pH instability, light instability, and skin permeation. The aim of the present work was applying essential oil-based microemulsions to improve the solubility, pH stability, photostability, and skin permeation of quercetin for topical application. Peppermint oil (PO-ME), clove oil (CO-ME), and rosemary oil (RMO-ME) were selected as model essential oils. Microemulsions composed of Cremophor EL/1,2-propanediol/essential oils (47:23:30, w/w) were selected as model formulations, based on the pseudo-ternary phase diagram and the characterizations. In the solubility study, the solubility of quercetin was improved dozens of times by microemulsions. Quercetin was found instable under alkaline condition, with 50% degraded in the solution of pH 13. However, PO-ME, CO-ME, and RMO-ME could protect quercetin from the hydroxide ions, with 47, 9, and 12% of quercetin degraded. In the photostability study, the essential oil-based microemulsions showed the capability of protecting quercetin from degradation under UV radiation. Where more than 67% of quercetin was degraded in aqueous solution, while less than 7% of quercetin degraded in microemulsions. At last, the in vitro skin permeation study showed that the essential oil-based microemulsions could enhance the permeation capacity of quercetin by 2.5-3 times compared to the aqueous solution. Hence, the prepared essential oil microemulsions could improve the solubility, pH stability, photostability, and skin permeation of quercetin, which will be beneficial for its topical application.

Background correction in separation techniques hyphenated to high-resolution mass spectrometry - Thorough correction with mass spectrometry scans recorded as profile spectra

Separation techniques hyphenated with high-resolution mass spectrometry have been a true revolution in analytical separation techniques. Such instruments not only provide unmatched resolution, but they also allow measuring the peaks accurate masses that permit identifying monoisotopic formulae. However, data files can be large, with a major contribution from background noise and background ions. Such unnecessary contribution to the overall signal can hide important features as well as decrease the accuracy of the centroid determination, especially with minor features. Thus, noise and baseline correction can be a valuable pre-processing step. The methodology that is described here, unlike any other approach, is used to correct the original dataset with the MS scans recorded as profiles spectrum. Using urine metabolic studies as examples, we demonstrate that this thorough correction reduces the data complexity by more than 90%. Such correction not only permits an improved visualisation of secondary peaks in the chromatographic domain, but it also facilitates the complete assignment of each MS scan which is invaluable to detect possible comigration/coeluting species.

Synergism Effect of the Essential Oil from Ocimum basilicum var. Maria Bonita and Its Major Components with Fluconazole and Its Influence on Ergosterol Biosynthesis

The aim of this study was to evaluate the activity of the EO and its major components of Ocimum basilicum var. Maria Bonita, a genetically improved cultivar, against the fluconazole sensitive and resistant strains of Candida albicans and Cryptococcus neoformans. Geraniol presented better results than the EO, with a low MIC (76 μg/mL against C. neoformans and 152 μg/mL against both Candida strains). The combination of EO, linalool, or geraniol with fluconazole enhanced their antifungal activity, especially against the resistant strain (MIC reduced to 156, 197, and 38 μg/mL, resp.). The ergosterol assay showed that subinhibitory concentrations of the substances were able to reduce the amount of sterol extracted. The substances tested were able to reduce the capsule size which suggests they have an important mechanism of action. Transmission electron microscopy demonstrated cell wall destruction of C. neoformans after treatment with subinhibitory concentrations. In C. albicans ultrastructure alterations such as irregularities in the membrane, presence of vesicles, and cell wall thickening were observed. The biofilm formation was inhibited in both C. albicans strains at MIC and twice MIC. These results provide further support for the use of O. basilicum EO and its major components as a potential source of antifungal agents.

Multivariate curve resolution-assisted GC-MS analysis of the volatile chemical constituents in Iranian Citrus aurantium L. peel

Graphical representation of the MCR-ALS mathematical decomposition for the two-dimensional GC-MS data set of one cluster.

Second-order calibration for the determination of fatty acids in pomegranate seeds by vortex-assisted extraction-dispersive liquid–liquid micro-extraction and gas chromatography-mass spectrometry

Multivariate curve resolution-alternating least squares is proposed for the simultaneous analysis of 18 fatty acid methyl esters in a standard mixture and pomegranate seed sample using vortex-assisted extraction-dispersive liquid–liquid microextraction followed by GC-MS.

Unstable simple volatiles and gas chromatography-tandem mass spectrometry analysis of essential oil from the roots bark of Oplopanax horridus extracted by supercritical fluid extraction

Volatile oil from the root bark of Oplopanax horridus is regarded to be responsible for the clinical uses of the title plant as a respiratory stimulant and expectorant. Therefore, a supercritical fluid extraction method was first employed to extract the volatile oil from the roots bark of O. horridus, which was subsequently analyzed by GC/MS. Forty-eight volatile compounds were identified by GC/MS analysis, including (S,E)-nerolidol (52.5%), τ-cadinol (21.6%) and S-falcarinol (3.6%). Accordingly, the volatile oil (100 g) was subjected to chromatographic separation and purification. As a result, the three compounds, (E)-nerolidol (2 g), τ-cadinol (62 mg) and S-falcarinol (21 mg), were isolated and purified from the volatile oil, the structures of which were unambiguously elucidated by detailed spectroscopic analysis including 1D- and 2D-NMR techniques.

Electrostatic-spray ionization mass spectrometry sniffing for perfume fingerprinting

RATIONALE

The perfume market is growing significantly, and it is easy to find imitative fragrances of probably all types of perfume. Such imitative fragrances are usually of lower quality than the authentic ones, creating a possible threat for perfume companies. Therefore, it is important to develop efficient chemical analysis techniques to screen rapidly perfume samples.

METHODS

Electrostatic-spray ionization (ESTASI) was used to analyze directly samples sprayed or deposited on different types of paper. A linear ion trap mass spectrometer was used to detect the ions produced by ESTASI with a modified extended transfer capillary for 'sniffing' ions from the paper.

RESULTS

Several commercial perfumes and a model perfume were analyzed by ESTASI-sniffing. The results obtained by paper ESTASI-MS of commercial fragrances were compared with those obtained from ESI-MS. In addition, a commercial fragrance was first nebulized on the hand and then soaked up by blotting paper, which was afterwards placed on an insulating plate for ESTASI-MS analysis. Analysis of peptides and proteins was also performed to show that the paper ESTASI-MS could be used for samples with very different molecular masses.

CONCLUSIONS

Paper ESTASI-MS yields a rapid fingerprinting characterization of perfume fragrances, avoiding time-consuming sample-preparation steps, and thereby performing a rapid screening in a few seconds.

Multivariate curve resolution: a review of advanced and tailored applications and challenges

Multivariate curve resolution (MCR) is a widespread methodology for the analysis of process data in many different application fields. This article intends to propose a critical review of the recently published works. Particular attention will be paid to situations requiring advanced and tailored applications of multivariate curve resolution, dealing with improvements in preprocessing methods, multi-set data arrangements, tailored constraints, issues related to non-ideal noise structure and deviation to linearity. These analytical issues are tackling the limits of applicability of MCR methods and, therefore, they can be considered as the most challenging ones.

Food Analysis: Present, Future, and Foodomics

This paper presents a revision on the instrumental analytical techniques and methods used in food analysis together with their main applications in food science research. The present paper includes a brief historical perspective on food analysis, together with a deep revision on the current state of the art of modern analytical instruments, methodologies, and applications in food analysis with a special emphasis on the works published on this topic in the last three years (2009–2011). The article also discusses the present and future challenges in food analysis, the application of “omics” in food analysis (including epigenomics, genomics, transcriptomics, proteomics, and metabolomics), and provides an overview on the new discipline of Foodomics.

Bifunctional ultrasound assisted extraction and determination of Elettaria cardamomum Maton essential oil

A new hyphenated extraction method composed of ultrasound assisted extraction (UAE)-optimized ultrasound assisted emulsification microextraction (USAEME) was developed for the extraction and preconcentration of the essential oil of Elettaria cardamomum Maton. The essential oil was analyzed by gas chromatography-mass spectrometry (GC-MS) and optimization was performed using gas chromatography-flame ionization detection (GC-FID). Ultrasound played two different roles in the extraction of the essential oil. First, as a source of sufficient energy to break the oil-containing glands in order to release the oil, and second as an emulsifier to disperse the organic phase within water. The effective parameters (factors) of USAEME including volume of extraction solvent (C(2)H(4)Cl(2)), extraction temperature and ultrasonic time were optimized by using a central composite design (CCD). The optimal conditions were 120 μL for extraction solvent volume, 32.5 °C for temperature and 10.5 min for ultrasonic time. The linear dynamic ranges (LDRs) were 0.01-50 mg L(-1) with the determination coefficients in the range of 0.9990-0.9999. The limits of detection (LODs) and the relative standard deviations (RSDs) were 0.001-0.007 mg L(-1) and 3.6-6.3%, respectively. The enrichment factors were 93-98. The main components of the extracted essential oil were α-terpenyl acetate (46.0%), 1,8-cineole (27.7%), linalool (5.3%), α-terpineol (4.0%), linalyl acetate (3.5%).