Proteomic profiling of mature leaves from oil palm (Elaeis guineensis Jacq.)

Oil palm is one of the most productive oil bearing crops grown in Southeast Asia. Due to the dwindling availability of agricultural land and increasing demand for high yielding oil palm seedlings, clonal propagation is vital to the oil palm industry. Most commonly, leaf explants are used for in vitro micropropagation of oil palm and to optimize this process it is important to unravel the physiological and molecular mechanisms underlying somatic embryo production from leaves. In this study, a proteomic approach was used to determine protein abundance of mature oil palm leaves. To do this, leaf proteins were extracted using TCA/acetone precipitation protocol and separated by 2DE. A total of 191 protein spots were observed on the 2D gels and 67 of the most abundant protein spots that were consistently observed were selected for further analysis with 35 successfully identified using MALDI TOF/TOF MS. The majority of proteins were classified as being involved in photosynthesis, metabolism, cellular biogenesis, stress response, and transport. This study provides the first proteomic assessment of oil palm leaves in this important oil crop and demonstrates the successful identification of selected proteins spots using the Malaysian Palm Oil Board (MPOB) Elaeis guineensis EST and NCBI‐protein databases. The MS data have been deposited in the ProteomeXchange Consortium database with the data set identifier PXD001307.     

Size and stability modulation of ionic liquid functionalized gold nanoparticles synthesized using Elaeis guineensis (oil palm) kernel extract

Bio-synthesis approach for gold nanoparticles (AuNPs) has received tremendous attention as an efficient and eco-friendly process. However, kinetic growth and colloidal stability of AuNPs synthesized by this process remained challenging. In this study, Elaeis guineensis (oil palm) kernel (OPK) extract prepared in an ionic liquid (IL)[EMIM][OAc] (1-ethyl-3-methylimidazolium acetate) was employed to control and tune the size and morphology of AuNPs. Synthesized AuNPs were characterized using UV-vis spectrophotometer, dynamic light scattering (DLS) and transmission electron microscopy (TEM) to observe any changes in absorbance, surface charge and particle size, respectively. IL mediated AuNPs were examined for 120 days and found well dispersed and stable at room temperature. UV-vis analysis demonstrated that volume of extract played an important role to control the stability of AuNPs. After 120 days, only 8.86% reduction from maximum absorbance was observed using 2 mL of volume of extract, which was elevated to 47.64% in case of 0.3 mL. TEM analysis was performed periodically after day 1, day 30, day 60, day 90 and day 120 and minor increase in the size was observed. Insignificant change in zeta potential value after 120 days supported enhanced stability of IL mediated AuNPs. Crystalline nature of AuNPs was confirmed by X-ray diffraction (XRD) pattern. The particles size and zeta potential of AuNPs was measured as 8.72 nm and −18.7 mV, respectively. However, the absence of [EMIM][OAc] from OPK extract resulted into larger particles size (9.64 nm), low zeta potential value (−13.9 mV) and enhanced aggregation of particles. Finally, experimental data were used to predict the theoretical and the experimental settling time for AuNPs to evaluate colloidal stability.     

Metabolite Characterization and Correlations with Antioxidant and Wound Healing Properties of Oil Palm (Elaeis guineensis Jacq.) Leaflets via 1H-NMR-Based Metabolomics Approach

Oil palm (Elaeis guineensis Jacq.) leaflets (OPLs) are one of the major agricultural by-products generated from the massive cultivation of Malaysian palm oil. This biomass is also reported to be of potential value based on its health-improving effects. By employing proton nuclear magnetic resonance (¹H-NMR) spectroscopy combined with multivariate data analysis (MVDA), the metabolite profile of OPLs was characterized and correlated with their antioxidant and wound healing properties. Principal component analysis (PCA) classified four varieties of extracts, prepared using solvents ranging from polar to medium polarity, into three distinct clusters. Cumulatively, six flavonoids, eight organic acids, four carbohydrates, and an amine were identified from the solvent extracts. The more polar extracts, such as, the ethyl acetate-methanol, absolute methanol, and methanol-water, were richer in phytochemicals. Based on partial least square (PLS) analysis, the constituents in these extracts, such as (+)-catechin, (−)-epicatechin, orientin, isoorientin, vitexin, and isovitexin, were strongly correlated with the measured antioxidant activities, comprising ferric reducing antioxidant power (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and nitric oxide (NO) free radical scavenging activities, as well as with cell proliferation and migration activities. This study has provided crucial evidence on the importance of these natural antioxidant compounds on the wound healing properties of OPL.     

Quality assessment of traditional Chinese medicine herb couple by high‐performance liquid chromatography and mass spectrometry combined with chemometrics

This study was designed to develop a simple, specific and reliable method to overall analyze the chemical constituents in clematidis radix et rhizome/notopterygii rhizome et radix herb couple using high‐performance liquid chromatography coupled with tandem mass spectrometry and multiple chemometric analysis. First, the separation and qualitative analysis of herb couple was achieved on an Agilent Zorbax Eclipse Plus C₁₈ column (250 mm × 4.6 mm, 5 μm), and 69 compounds were unambiguously or tentatively identified. Moreover, in quantitative analysis, eight ingredients including six coumarins and two triterpenoid sapogenins were quantified by high‐performance liquid chromatography coupled with tandem mass spectrometry. In terms of good linearity (r² ≥ 0.9995) with a relatively wide concentration range, recovery (85.40–102.50%) and repeatability (0.99–4.45%), the validation results suggested the proposed method was reliable, and successfully used to analyze ten batches of herb couple samples. Then, hierarchical cluster analysis and principal component analysis were used to classify samples and search significant ingredients. The results showed that ten batches of herb couple samples were classified into three groups, and six compounds were found for its better quality control.     

Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

Summary A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.     

QuEChERS-液相色谱-串联质谱法测定棕榈原油中敌草快等6种农药残留

建立了QuEChERS-液相色谱-串联质谱同时测定棕榈原油中敌草快、乐果、倍硫磷、倍硫磷亚砜、倍硫磷砜、氟吡甲禾灵残留量的方法。以回收率及基质效应为考察指标,评估了乙二胺-N-丙基硅烷(PSA)/C18混合物、C18键合锆胶(Z-Sep+)/C18混合物、Z-Sep+、C18 4种分散吸附剂的净化效果,结果表明Z-Sep+/C18的净化效果最佳。样品采用含1%(v/v)乙酸的甲醇溶液提取,Z-Sep+/C18分散固相萃取净化;液相色谱以Atlantis T3色谱柱梯度洗脱分离,质谱分析采用电喷雾正离子电离、多反应监测模式,以基质匹配校准曲线外标法进行定量。6种农药在3个添加水平(10、20、250 μg/kg)下的回收率范围为70.0%~97.9%,相对标准偏差范围为2.6%~10.2%; 6种农药的定量限(S/N≥10)为0.1~2.5 μg/kg。该方法简便、灵敏、准确、环保,适用于棕榈原油中上述6种农药残留的定性、定量分析。     

Analysis of lignin from archaeological waterlogged wood by direct exposure mass spectrometry (DE-MS) and PCA evaluation of mass spectral data

The chemical characterisation of waterlogged archaeological wood is of fundamental importance to understand the degradation processes undergone by wooden objects and consequently to develop suitable consolidation and conservation procedures. Lignin extracted from archaeological waterlogged wood samples was characterized using direct exposure electron ionisation mass spectrometry (DE-MS). DE-MS achieves a mass spectral fingerprint of the sample in a few minutes, avoiding any chemical pre-treatment and requiring only few micrograms of material.Mass spectral data were put in relation to the chemical composition of lignin and evaluated by means of principal component analysis (PCA). The preliminary results, presented in this study, demonstrate the feasibility and the potential of DE-MS as a reproducible and rapid screening method for archaeological waterlogged wood samples.     

Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods

In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from coco flavor and some little difference sample prepared with coffee flavor and coco flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.     

顶空固相微萃取-气相色谱/质谱联用法结合化学计量学分析白肋烟烘焙前后挥发性、半挥发性成分

采用顶空固相微萃取-气相色谱/质谱法（HS-SPME-GC/MS）分析了白肋烟烟叶中挥发性、半挥发性成分。20 mg烟粉在60℃条件下孵化8 min,采用聚二甲基硅氧烷/二乙烯基苯（PDMS/DVB）65 μm纤维头萃取40 min,然后在250℃解吸3 min,通过与标准品和质谱数据库进行比对,初步定性了白肋烟烟叶中122种挥发性、半挥发性成分,并采用内标法进行半定量分析。通过主成分分析（PCA）和偏最小二乘-判别分析（PLS-DA）等化学计量学方法,直观反映了白肋烟烘焙前后挥发性、半挥发性成分的变化。该方法具有样品用量小、前处理简单、灵敏度高等特点,结合化学计量学方法可用于白肋烟烘焙前后化学成分变化分析,为白肋烟烘焙条件的优化提供了科学的检测方法。     

Application of near infrared spectroscopy (NIR), X-ray fluorescence (XRF) and chemometrics to the differentiation of marmora samples from the Mediterranean basin

Abstract

Near-infrared (NIR) and X-ray fluorescence spectra were recorded for 15 different samples of marmora, from the Mediterranean Basin and of different colours. After appropriate pretreatment (SNV transform + second derivative), the results were subjected to principal component analysis (PCA) treatment with a view to differentiating them. The observed differences among the samples were chemically interpreted by highlighting the NIR wavelengths and minerals, respectively, contributing the most to the PCA models. Moreover, a mid-level data fusion protocol allowed integrating the information from the different techniques and, in particular, to correctly identify (based on the distance in the score space) three test samples of known type. Moreover, it should be stressed that positive results on the differentiation and identification of marmora were obtained using two completely non-invasive, non-destructive and relatively inexpensive techniques, which can also be used in situ.     

Determination of the carbon-13 content of sugars and pulp from fruit juices by isotope-ratio mass spectrometry (internal reference method). A European interlaboratory comparison

An interlaboratory comparison by ¹³C-isotope ratio mass spectrometry was organised by working group No. 1 of the European Commission of Standardisation (CEN/TC 174) in order to define the repeatability (r) and the reproducibility (R) of the ¹³C determination in sugars and pulp, isolated from the same fruit juice. Six unlabelled juices were analysed in 19 laboratories in the European Union, Australia and the USA. Three samples were authentic juices (orange, grapefruit, pineapple) and the remaining samples were the same juices with an addition of sugar at 15 g l⁻¹ (orange, pineapple) or 11.8 g l⁻¹ (grapefruit). The sugar was prepared by mixing equal amounts of beet and cane sucroses. The different laboratories used the same experimental protocol under different conditions (operator, conversion system for CO₂ preparation, mass spectrometer). The results for the sugars (r = 0.27%., R = 0.82%.) were comparable to those from an earlier ring test (r = 0.30%., R = 0.70%.), while the results for the pulp presented higher interlaboratory variability (r = 0.38%., R = 1.89%.) possibly due to experimental difficulties. Nevertheless, the RSD_R for free sugars ranged 0.9–3.2% and for pulp, 0.9–9.3%. On the basis of the Horwitz equation and taking account of the concentration of the isotopes measured, an RSD_R of 7–8% might have been expected. The experimentally determined RSD_R values were less than twice the theoretically expected values, which is a criterion of an acceptable method. The results were therefore considered to be acceptable by specialists in the field of isotopic analysis, and the method applied was found to improve the sensitivity of the ¹³C determination for the detection of sugar addition in fruit juices.     

Characterization of Automobile Plastics by Principal Component Analysis and Near-Infrared Spectroscopy

Based on near-infrared diffuse reflection spectroscopy, multivariate calibration models for discarded automobile plastic were constructed using principal component analysis and clustering analysis to rapidly characterize four widely employed materials: polypropylene, polyethylene, acrylonitrile butadiene styrene, and polymethylmethacrylate with an accuracy rate of 97%. The method was shown to rapidly discriminate waste automobile plastic.     

Geographical Discrimination of Honeysuckle (Lonicera japonica Thunb.) from China by Characterization of the Stable Isotope Ratio and Multielemental Analysis

A total of 117 honeysuckle (Lonicera japonica Thunb.) samples from four major regions of production in China, including Fengqiu in Henan, Pingyi in Shandong, Julu in Hebei, and Xiushan in Chongqing, were analyzed to determine their geographical origin. δ¹³C, δ¹⁵N, and δ¹⁸O values were determined by isotope ratio mass spectrometry (IRMS), and the contents of 18 elements (Fe, Mn, Cu, Zn, K, Ca, Mg, Pb, Cd, Cr, As, Hg, Se, Sr, Ni, Co, B, and Mo) were measured by inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). Multivariate statistical analysis by analysis of variance (ANOVA), principal component analysis (PCA), and linear discriminant analysis (LDA) were performed. The results showed that there were very significant differences in the stable isotope ratios and elemental concentrations in honeysuckle based on geographical origin, with plants from each region having a unique fingerprint. Discriminant functions were established to distinguish the origin of honeysuckle using suitable indicators including Cd, Cr, As, Hg, Se, Co, Ni, Sr, Fe, δ¹³C, δ¹⁵N, and δ¹⁸O. Cross-validated cases of 95.7% were correctly classified.     

Discrimination of Scrophulariae Radix according to geographical origin and determination of active constituents by near infrared spectroscopy (NIRS)

The potential of near infrared reflectance spectroscopy (NIR) was investigated for its ability to non-destructively discriminate the geographic origins of Scrophularia spp., Andong, Uisung and China. Application of principal component analysis to NIR spectra leads to a clear separation of Andong sample from the others. Moreover, the contents of two neuroprotective constituents of Scrophularia spp., 8-O-(E-p-methoxycinnamoyl)-harpagide (HG), and E-p-methoxycinnamic acid (MCA), were determined by HPLC-DAD. Partial least squares (PLS) regression of NIR spectra combined with these analytical reference data yield the development of calibration models for the contents of the two constituents. The correlation coefficients of prediction models for HG and MCA were > 0.87. These outcomes indicated that the NIRS could be useful for the discrimination of Scrophularia spp.     

Adulteration of diesel/biodiesel blends by vegetable oil as determined by Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy

In this work it has been shown that the routine ASTM methods (ASTM 4052, ASTM D 445, ASTM D 4737, ASTM D 93, and ASTM D 86) recommended by the ANP (the Brazilian National Agency for Petroleum, Natural Gas and Biofuels) to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils. Considering the previous and actual problems with fuel adulterations in Brazil, we have investigated the application of vibrational spectroscopy (Fourier transform (FT) near infrared spectrometry and FT-Raman) to identify adulterations of B2 and B5 blends with vegetable oils. Partial least square regression (PLS), principal component regression (PCR), and artificial neural network (ANN) calibration models were designed and their relative performances were evaluated by external validation using the F-test. The PCR, PLS, and ANN calibration models based on the Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples. Other 62 samples were used in the validation and external validation, for a total of 182 samples. The results have shown that among the designed calibration models, the ANN/FT-Raman presented the best accuracy (0.028%, w/w) for samples used in the external validation.     

Thermogravimetry/mass spectrometry study of woody residues and an herbaceous biomass crop using PCA techniques

The devolatilization behaviour of pine and beech wood from carpentry residuals and an herbaceous product from an energy plantation (artichoke thistle) was investigated by thermogravimetry/mass spectrometry (TG/MS). The effect of three pre-treatments, hot-water washing, ethanol extraction and their combination, was also studied. Principal component analysis (PCA) was employed to help in the evaluation of the large data set of results. The characteristics of the thermal decomposition of the herbaceous crop are considerably different from that of the woody biomass samples. The evolution profiles of some characteristic pyrolysis products revealed that the thermal behaviour of wood and thistle is still considerably different after the elimination of some of the inorganic ions and extractive compounds, although the macromolecular components of the samples decompose at similar temperatures. With the help of the PCA calculations, the effect of the different pre-treatments on the production of the main pyrolysis products was evidenced.     

Mass spectrometry‐based proteomics of oxidative stress: Identification of 4‐hydroxy‐2‐nonenal (HNE) adducts of amino acids using lysozyme and bovine serum albumin as model proteins

Modification of proteins by 4‐hydroxy‐2‐nonenal (HNE), a reactive by‐product of ω6 polyunsaturated fatty acid oxidation, on specific amino acid residues is considered a biomarker for oxidative stress, as occurs in many metabolic, hereditary, and age‐related diseases. HNE modification of amino acids can occur either via Michael addition or by formation of Schiff‐base adducts. These modifications typically occur on cysteine (Cys), histidine (His), and/or lysine (Lys) residues, resulting in an increase of 156 Da (Michael addition) or 138 Da (Schiff‐base adducts), respectively, in the mass of the residue. Here, we employed biochemical and mass spectrometry (MS) approaches to determine the MS “signatures” of HNE‐modified amino acids, using lysozyme and BSA as model proteins. Using direct infusion of unmodified and HNE‐modified lysozyme into an electrospray quadrupole time‐of‐flight mass spectrometer, we were able to detect up to seven HNE modifications per molecule of lysozyme. Using nanoLC‐MS/MS, we found that, in addition to N‐terminal amino acids, Cys, His, and Lys residues, HNE modification of arginine (Arg), threonine (Thr), tryptophan (Trp), and histidine (His) residues can also occur. These sensitive and specific methods can be applied to the study of oxidative stress to evaluate HNE modification of proteins in complex mixtures from cells and tissues under diseased versus normal conditions.     

气相色谱-质谱技术分析姜油树脂中的挥发性及非挥发性成分

用超临界CO2萃取生姜根茎中的姜油树脂,并用气相色谱-质谱联用技术对其进行了成分分析。从姜油树脂中分析出77种化合物,其中挥发油成分50种,主要是α-姜烯(22.29%)、 β-倍半水芹烯(8.58%)、α-法尼烯(3.93%)、 β-没药烯(3.87%)和α-姜黄烯(2.63%)等倍半萜类化合物;姜辣素成分27种,主要成分为6-姜酚(9.38%)、6-姜烯酚(7.59%)和分析过程中由姜酚类或姜烯酚类化合物受热分解而形成的姜油酮(9.24%)。在姜辣素成分中,6-异姜酚、(Z)-10-异姜烯酚和(E)-10-异姜烯酚3种化合物是新发现的未见报道的化合物。实验中对这3种新化合物进行了质谱裂解分析。     

Real-Time Distinguishing of the Xylene Isomers Using Photoionization and Dissociation Mass Spectra Obtained by Femtosecond Laser Mass Spectrometry (FLMS)

Abstract

Distinguishing chemicals and improvement on analytical methods has a direct impact on modern chemical analysis. In this work, the dissociative ionization of xylene isomers was investigated using a femtosecond laser mass spectrometry (FLMS) method with a custom-built linear time-of-flight (TOF) instrument. Laser beams at 800?nm and 400?nm were used and intensity-dependent analysis of the obtained mass spectra was performed using principal component analysis (PCA) to distinguish the xylene isomers, which give identical mass spectra in appearance that cannot be distinguished using normal mass spectrometry methods. The results show that there is a statistically highly significant difference between the xylene isomers for two principal components (1 ? α?>?99.99%) and minimal information loss (<5%) took place during the PCA procedure. Also, the use of the k-medoid clustering method showed that the isomers may be distinguished in real-time for a wide range of ionization laser pulse powers with approximately 99% accuracy. The results suggest that real-time isomer analysis by the FLMS method is suitable for mass spectral identification applications. The FLMS method has been shown to be an important alternative to other mass spectrometric methods that use different ionization mechanisms.