Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).     

Paper spray mass spectrometry and PLS-DA improved by variable selection for the forensic discrimination of beers

Paper spray mass spectrometry (PS-MS) combined with partial least squares discriminant analysis (PLS-DA) was applied for the first time in a forensic context to a fast and effective differentiation of beers. Eight different brands of American standard lager beers produced by four different breweries (141 samples from 55 batches) were studied with the aim at performing a differentiation according to their market prices. The three leader brands in the Brazilian beer market, which have been subject to fraud, were modeled as the higher-price class, while the five brands most used for counterfeiting were modeled as the lower-price class. Parameters affecting the paper spray ionization were examined and optimized. The best MS signal stability and intensity was obtained while using the positive ion mode, with PS(+) mass spectra characterized by intense pairs of signals corresponding to sodium and potassium adducts of malto-oligosaccharides. Discrimination was not apparent neither by using visual inspection nor principal component analysis (PCA). However, supervised classification models provided high rates of sensitivity and specificity. A PLS-DA model using full scan mass spectra were improved by variable selection with ordered predictors selection (OPS), providing 100% of reliability rate and reducing the number of variables from 1701 to 60. This model was interpreted by detecting fifteen variables as the most significant VIP (variable importance in projection) scores, which were therefore considered diagnostic ions for this type of beer counterfeit.     

Liquid chromatography/mass spectrometry for metabonomics investigation of the biochemical effects induced by aristolochic acid in rats: the use of information-dependent acquisition for biomarker identification

The toxic effects of oral administrations of nephrotoxic and carcinogenic aristolochic acid (AA) to male Sprague-Dawley rats were investigated by using high-performance liquid chromatography coupled with a quadrupole time-of-flight mass spectrometer. Analysis of the urine and plasma samples revealed distinct changes in the biochemical patterns in the AA-dosed rats. After peak finding and alignment, principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were used for multivariate data analysis. Potential biomarkers were studied by high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analyses. The MS/MS spectra of all endogenous metabolites satisfying the pre-defined criteria were acquired in a single information-dependent acquisition (IDA) analysis, demonstrating that IDA was an efficient approach for structural elucidation in metabonomic studies. Citric acid and a glucuronide-containing metabolite were observed as potential biomarkers in rat urine. A significant increase in plasma creatinine concentration was also observed in the AA-dosed rats, which indicated that AA induced an adverse effect on the renal clearance function.     

Studies on azaspiracid biotoxins. II. Mass spectral behavior and structural elucidation of azaspiracid analogs

In this report, the mass spectral analysis of azaspiracid biotoxins is described. Specifically, the collision-induced dissociation (CID) behavior and differences between CID spectra obtained on a triple-quadrupole, a quadrupole time-of-flight, and an ion-trap mass spectrometer are addressed here. The CID spectra obtained on the triple-quadrupole mass spectrometer allowed the classification of the major product ions of the five investigated compounds (AZA 1-5) into five distinct fragment ion groups, according to the backbone cleavage positions. Although the identification of unknown azaspiracids was difficult based on CID alone, the spectra provided sufficient structural information to allow confirmation of known azaspiracids in marine samples. Furthermore, we were able to detect two new azaspiracid analogs (AZA 1b and 6) in our samples and provide a preliminary structural analysis. The proposed dissociation pathways under tandem mass spectrometry (MS/MS) conditions were confirmed by a comparison with accurate mass data from electrospray quadrupole time-of-flight MS/MS experiments. Regular sequential MS(n) analysis on an ion-trap mass spectrometer was more restricted in comparison to the triple-quadrupole mass spectrometer, because the azaspiracids underwent multiple [M + H - nH(2)O](+) (n = 1-6) losses from the precursor ion under CID. Thus, the structural information obtained from MS(n) experiments was somewhat limited. To overcome this limitation, we developed a wide-range excitation technique using a 180-u window that provided results comparable to the triple-quadrupole instrument. To demonstrate the potential of the method, we applied it to the analysis of degraded azaspiracids from mussel tissue extracts.     

MALDI-ToF mass spectrometry coupled with multivariate pattern recognition analysis for the rapid biomarker profiling of Escherichia coli in different growth phases

Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-ToF MS) has been exploited extensively in the field of microbiology for the characterisation of bacterial species, the detection of biomarkers for early disease diagnosis and bacterial identification. Here, the multivariate data analysis technique of partial least squares-discriminant analysis (PLS-DA) was applied to ‘intact cell’ MALDI-ToF MS data obtained from Escherichia coli cell samples to determine if such an approach could be used to distinguish between, and characterise, different growth phases. PLS-DA is a technique that has the potential to extract systematic variation from large and noisy data sets by identifying a lower-dimensional subspace that contains latent information. The application of PLS-DA to the MALDI-ToF data obtained from cells at different stages of growth resulted in the successful classification of the samples according to the growth phase of the bacteria cultures. A further outcome of the analysis was that it was possible to identify the mass-to-charge (m/z) ratio peaks or ion signals that contributed to the classification of the samples. The Swiss-Prot/TrEMBL database and primary literature were then used to provisionally assign a small number of these m/z ion signals to proteins, and these tentative assignments revealed that the major contributors from the exponential phase were ribosomal proteins. Additional assignments were possible for the stationary phase and the decline phase cultures where the proteins identified were consistent with previously observed biological interpretation. In summary, the results show that MALDI-ToF MS, PLS-DA and a protein database search can be used in combination to discriminate between ‘intact cell’ E. coli cell samples in different growth phases and thus could potentially be used as a tool in process development in the bioprocessing industry to enhance cell growth and cell engineering strategies.     

Identification of volatiles from pineapple (Ananas comosus L.) pulp by comprehensive two-dimensional gas chromatography and gas chromatography/mass spectrometry

Combining qualitative data from the chromatographic structure of 2-D gas chromatography with flame ionization detection (GC×GC-FID) and that from gas chromatography-mass spectrometry (GC/MS) should result in a more accurate assignment of the peak identities than the simple analysis by GC/MS, where coelution of analytes is unavoidable in highly complex samples (rendering spectra unsuitable for qualitative purposes) or for compounds in very low concentrations. Using data from GC×GC-FID combined with GC/MS can reveal coelutions that were not detected by mass spectra deconvolution software. In addition, some compounds can be identified according to the structure of the GC×GC-FID chromatogram. In this article, the volatile fractions of fresh and dehydrated pineapple pulp were evaluated. The extraction of the volatiles was performed by dynamic headspace extraction coupled to solid-phase microextraction (DHS-SPME), a technique appropriate for slurries or solid matrices. Extracted analytes were then analyzed by GC×GC-FID and GC/MS. The results obtained using both techniques were combined to improve compound identifications.     

Tandem mass spectrometric accurate mass performance of time-of-flight and Fourier transform ion cyclotron resonance mass spectrometry: a case study with pyridine derivatives

The interpretation of mass spectra is a key process during compound identification, and the combination of tandem mass spectrometry (MS/MS) with high-accuracy mass measurements may deliver crucial information on the identity of a compound. Obtaining accurate mass data of fragment ions in MS/MS reveals the particular problem of mass calibration when a lockmass, which is frequently used to obtain accurate masses in MS, is absent. An alternative technique is to recalibrate the MS/MS spectrum using a reference MS/MS spectrum acquired under the same conditions. We have tested and validated this approach using a hybrid quadrupole/orthogonal acceleration reflectron-type time-of-flight (TOF) mass spectrometer. The results were compared with those obtained under similar conditions on a Fourier transform ion cyclotron resonance (FT-ICR) instrument. We found that the mass accuracy observed with such an "external" recalibration on the TOF instrument in MS/MS is identical to what can be obtained on a similar instrument operating in one-dimensional MS mode using the lockmass technique. However, mass accuracy in both cases is one order of magnitude inferior to that obtained using FTMS, and also inferior to that observed using sector field MS when operated at comparable resolution. Nevertheless, for small (<200 Da) molecules, this mass accuracy was still sufficient to have the "true" elemental composition identified as the first hit in about 70% of all cases. It was possible to elucidate the fragmentation mechanism of eight azaheterocycles containing a pyridine moiety, where the accurate mass data from the TOF instrument allowed distinction between two alternative fragmentation pathways.     

FT-MIR and UV–vis data fusion strategy for origins discrimination of wild Paris Polyphylla Smith var. yunnanensis

Paris Polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz has multiple therapeutic properties and the origins may affect clinical efficacy. Tracing the geographical origin is important to the authentication and quality assessment of this species. 177 wild samples collected from central, southeast and northwest Yunnan Province, China, were analyzed by single analytical method and data fusion strategies (low- and mid-levels) using Fourier transform mid-infrared (FT-MIR) and ultraviolet-visible (UV–vis) spectroscopies combined with chemometrics (partial least squares discrimination analysis (PLS-DA) and support vector machines grid search (SVM-GS)), for categorizing samples from different geographic origins. According to the results, mid-level data fusion strategy presented a better generalization performance and accuracy rates based on latent variables selected by PLS-DA than single analytical method and low-level data fusion strategy. Accuracy rates were almost 100% when both of the PLS-DA and SVM-GS were employed for classifying samples picked from southeast and northwest districts based on mid-level dataset. For samples collected from central of Yunnan where was divided into seven categories in this paper, the accuracy rates of training set and test set of PLS-DA and SVM-GS were preferable (>87%). Based on the mid-level data set, both of the classification results of PLS-DA and SVM-GS presented satisfying accuracy for 177 samples. Additionally, as small as possible parameters showed in mid-level data set, it suggested that this method was robust and generalized. Therefore, the comprehensive method was established for the origin traceability of wild P. Polyphylla Smith var. yunnanensis, which is meaningful for the quality control of herbal medicines.     

Application of a linear ion trap/orbitrap mass spectrometer in metabolite characterization studies: Examination of the human liver microsomal metabolism of the non-tricyclic anti-depressant nefazodone using data-dependent accurate mass measurements

We report herein, facile metabolite identification workflow on the anti-depressant nefazodone, which is derived from accurate mass measurements based on a single run/experimental analysis. A hybrid LTQ/orbitrap mass spectrometer was used to obtain accurate mass full scan MS and MS/MS in a data-dependent fashion to eliminate the reliance on a parent mass list. Initial screening utilized a high mass tolerance ( approximately 10 ppm) to filter the full scan MS data for previously reported nefazodone metabolites. The tight mass tolerance reduces or eliminates background chemical noise, dramatically increasing sensitivity for confirming or eliminating the presence of metabolites as well as isobaric forms. The full scan accurate mass analysis of suspected metabolites can be confirmed or refuted using three primary tools: (1) predictive chemical formula and corresponding mass error analysis, (2) rings-plus-double bonds, and (3) accurate mass product ion spectra of parent and suspected metabolites. Accurate mass characterization of the parent ion structure provided the basis for assessing structural assignment for metabolites. Metabolites were also characterized using parent product ion m/z values to filter all tandem mass spectra for identification of precursor ions yielding similar product ions. Identified metabolite parent masses were subjected to chemical formula calculator based on accurate mass as well as bond saturation. Further analysis of potential nefazodone metabolites was executed using accurate mass product ion spectra. Reported mass measurement errors for all full scan MS and MS/MS spectra was <3 ppm, regardless of relative ion abundance, which enabled the use of predictive software in determining product ion structure. The ability to conduct biotransformation profiling via tandem mass spectrometry coupled with accurate mass measurements, all in a single experimental run, is clearly one of the most attractive features of this methodology.     

Multivariate statistical differentiation of renal cell carcinomas based on lipidomic analysis by ambient ionization imaging mass spectrometry

Desorption electrospray ionization (DESI) mass spectrometry (MS) was used in an imaging mode to interrogate the lipid profiles of thin tissue sections of 11 sample pairs of human papillary renal cell carcinoma (RCC) and adjacent normal tissue and nine sample pairs of clear cell RCC and adjacent normal tissue. DESI-MS images showing the spatial distributions of particular glycerophospholipids (GPs) and free fatty acids in the negative ion mode were compared to serial tissue sections stained with hematoxylin and eosin (H&E). Increased absolute intensities as well as changes in relative abundance were seen for particular compounds in the tumor regions of the samples. Multivariate statistical analysis using orthogonal projection to latent structures treated partial least square discriminate analysis (PLS-DA) was used for visualization and classification of the tissue pairs using the full mass spectra as predictors. PLS-DA successfully distinguished tumor from normal tissue for both papillary and clear cell RCC with misclassification rates obtained from the validation set of 14.3% and 7.8%, respectively. It was also used to distinguish papillary and clear cell RCC from each other and from the combined normal tissues with a reasonable misclassification rate of 23%, as determined from the validation set. Overall DESI-MS imaging combined with multivariate statistical analysis shows promise as a molecular pathology technique for diagnosing cancerous and normal tissue on the basis of GP profiles.