A bottom-up approach for data mining in bioaromatization of beers using flow-modulated comprehensive two-dimensional gas chromatography/mass spectrometry

In this study, we report the combination of comprehensive two-dimensional gas chromatography (GCxGC) with multivariate pattern recognition through template matching for the assignment of the contribution of Brazilian Ale 02 yeast strain to the aroma profile of beer compared with the traditional Nottingham yeast. Volatile organic compounds (VOC) from two beer samples, which were fermented with these yeast strains were sampled using headspace solid-phase microextraction (HS-SPME). The aroma profiles from both beer samples were obtained using GCxGC coupled to a fast scanning quadrupole mass spectrometer. Data processing performed through multiway principal components analysis succeeded in separating both beer samples based on yeast strain. The execution of a simple and reliable procedure succeeded and identified 46 compounds as relevant for sample classification. Furthermore, the bottom-up approach spotted compounds found exclusively in the beer sample fermented with the Brazilian yeast, highlighting the bioaromatization properties introduced to the aroma profile by this yeast strain64CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP400182/2016-588882.329162/2019-0117/25490-1This research was funded by National Council for Scientific and Technological Development (CNPq 400182/2016-5), São Paulo Research Foundation (17/25490-1), and Unicamp (FAEPEX 519.292). Andre Cunha Paiva thanks the Coordination for the Improvement of Higher Education Personnel (CAPES 88882.329162/2019-01) for research fellowship

Solid phase microextraction and comprehensive two-dimensional gas chromatography : applications in lipidomics

Orientador: Fabio AugustoDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de QuímicaResumo: Neste trabalho foram desenvolvidas metodologias para a análise de lipídios na forma de seus ésteres metílicos de ácido graxo (FAME) em diversas matrizes. Para isso foram empregadas e otimizadas de forma multivariada técnicas de derivatização dos lipídios por transesterificação por catálise básica, seu isolamento e concentração por Microextração em Fase Sólida (SPME) e análise por Cromatografia Gasosa Bidimensional Abrangente (GCxGC). A partir do perfil de extração foi escolhida a fibra comercial com revestimento de poli(dimetilsiloxano) (PDMS) com espessura de filme de 7 mm. O tempo de extração escolhido foi de 10 min pois atingiu a condição de sistema estacionário. Os parâmetros cromatográficos, tais como a programação de temperatura do forno, período de modulação e tipo de fase estacionária das colunas utilizadas no protótipo GCxGC, foram também otimizados. Além disso, durante o progresso deste trabalho, foi desenvolvido o primeiro protótipo brasileiro de GCxGC acoplado a um Espectrômetro de Massas com Analizador Quadrupolar rápido (GCxGCxqMS). Dentre os parâmetros operacionais do qMS, foram otimizados o intervalo de varredura do analizador quadrupolar e sua frequencia de aquisição. O sistema GCxGCxqMS foi empregado para a identificação dos FAME presentes nas amostras empregadas neste estudo, através do uso das informações obtidas pelos espectros de massas obtidos das amostras, com padrões analíticos e combinando o uso de índices de retenção (LTPRI) e da estrutura cromatográfica. Neste trabalho, devido ao incremento em detectabilidade e sensibilidade, foi possível observar diversos FAME comumente não detectados por Cromatografia Gasosa Convencional (GC), como FAME de comprimento ímpar de cadeia e a presença de agrupamento metila no carbono 2 (-br2). Além disso, em virtude da baixa abrangência do banco de dados disponíveis, foi possível, e necessário, criar um banco de dados com índices de retenção para análise de lipídios. Espera-se que estas metodologias desenvolvidas e os resultados apresentados possam ser empregados como ferramenta em estudos de lipidômica e aplicações correlatasAbstract: The aim of this project was to develop alternative methodologies for lipidomic studies and related applications. A method for the analysis of lipids in different samples such as waxes, edible oils and cheek cells was developed. The isolation and concentration of the analytes was performed by Solid Phase Microextraction (SPME) combined with Comprehensive Two-dimensional Gas Chromatography (GCxGC). Firstly, the base-catalysed transesterification of the lipids into their respective fatty acid methyl esters (FAME) was optimized according to a multivariate model. Thus, the sample prepation was optimized considering the thickness of the coating and their respective extraction profiles. The choosen commercial coating was a poly(dimethylsiloxane) (PDMS) with 7 mm film thickness, the extraction time was 10 min where stationary state conditions were achieved. Secondly, chromatographic parameters were also optimized, such as the temperature programming, modulation period, the identity of the first and second dimensional columns used in GCxGC prototype. During the current study, the first brazillian prototype of a GCxGC coupled to a mass spectrometer with a rapid quadrupolar analyzer was developed (GCxGCxqMS). Also, the scan interval and acquisition frequency of the qMS were optimized. For the identification of the analytes similarity searches for mass spectra, analytical standards and the combination retention indexes with chromatographic structuration were used. Additionally it was possible to detected and identify FAME which couldn't be detected by conventional GC such as odd numbered chain length and branched FAME. Moreover, elution pattern of a branched FAME was reported, specifically the FAME with a methyl group in the carbon 2 (-br2). Because of the restricted content of the retention indexes and mass spectra database, the construction of a database with retention indexes for lipid analysis was built. Hence the ultimate goal of the current study is to present the potencial and applicability of SPME for lipidomic studies and related applicationsMestradoQuimica AnaliticaMestre em Químic

Application of chemometric methods to the investigation of the metabolome of eucalyptus by conventional and multidimensional chromatography coupled to mass spectrometry

Orientador: Fabio AugustoTese (doutorado) - Universidade Estadual de Campinas, Instituto de QuímicaResumo: O presente trabalho é dedicado à aplicação de técnicas cromatográficas multidimensionais à problemas complexos de separação. No primeiro conjunto de estudos foram desenvolvidos métodos analíticos para investigação do metaboloma de plantas de interesse comercial. Para isso, foram utilizadas a cromatografia gasosa bidimensional abrangente (GC×GC-MS) e a cromatografia líquida de ultra eficiência (UHPLC-MS) acopladas à espectrometria de massas para aquisição do perfil metabólico de folhas de eucalipto. Logo, foram desenvolvidos modelos quimiométricos para interpretação dos dados e determinação de marcadores biológicos associados ao estresse biótico e ao fenômeno de resistência. Estes estudos permitiram aprimorar o entendimento do mecanismo de defesa de eucaliptos contra fitopatógenos. Em segundo plano, foram desenvolvidas fases estacionárias derivadas de líquidos iônicos (IL) para separação de compostos apolares por GC×GC. Para isso, foram sintetizados diversos IL derivados de fosfônio e imidazólio. A partir destes materiais foram preparadas colunas capilares pelo método estático de revestimento. Estas colunas de GC foram utilizadas na separação de analitos modelo (i.e., hidrocarbonetos alifáticos) por GC×GC. Estes ensaios visaram aprimorar o entendimento da relação entre as características estruturais dos IL e os mecanismos que governam a retenção de compostos apolares pelas fases derivadas de ILAbstract: In the present dissertation, we discuss the application of multidimensional chromatographic techniques to solve complex problems. In the first chapter it is presented the development of chemometric strategies for data processing of metabolic data ¿ the current bottleneck of a metabolomics workflow. The case studies examined investigate the metabolome of eucalyptus leaves to address several growing concern in plant pathology, namely, prospection of orthogonal methods for early diagnosis diseases and selection of hybrids with specific phenotypes in genetic enhancement programs. To accomplish these goals, comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) were examined to generate unbiased and reliable metabolic profiles. From these experiments, it was possible to improve our understanding of the defense mechanism of plants. The second chapter addresses the limited availability of stationary phases for multidimensional gas chromatography. In this work, we evaluated ionic liquids as stationary phases for gas-liquid chromatography. The model analytes were nonpolar aliphatic hydrocarbons due to the aggravated lack of highly selective and thermally stable GC columns for their separation. From these experiments, we ascertained the structure-selectivity relationship of ILs and were able to improve our understanding on the retention of nonpolar analytes by IL-based GC columnsDoutoradoQuimica AnaliticaDoutor em Ciência

Detection Of Extraction Artifacts In The Analysis Of Honey Volatiles Using Comprehensive Two-dimensional Gas Chromatography.

Extraction using headspace solid phase microextraction (HS-SPME) coupled to comprehensive two-dimensional gas chromatography with flame ionisation detection (GC×GC-FID) was employed to evaluate the effect of SPME fractionation conditions (heating time and temperature) on the generation of artifacts. The occurrence of artifacts was more pronounced at higher fractionation temperatures and times which caused significant changes in the chromatographic profiles. The identification of the volatile fraction of the honey blend was performed through a two-dimensional gas chromatograph coupled to a mass spectrometer with time of flight analyser (GC×GC-ToFMS) by comparing the first dimension linear temperature programmed retention index ((1)D-LTPRI) with the peak's identities provided by the mass spectral similarity search. Several artifacts were found and identified - such as hydroxymethylfurfural, methyl-furone and furfural - and some of them were not previously detected as such in honey samples. These compounds were either the result of hydrolysis or thermal decomposition of components already present in the honey samples. This occurrence was attributed to the increased detectability provided by GC×GC compared to conventional GC. The possible emergence of previously unknown extraction artifacts as a general tendency related use of GC×GC instead of conventional GC is discussed as a result of these observations.1411828-3

Acrylamide mitigation in french fries using native l-asparaginase from aspergillus oryzae CCT 3940

The Maillard reaction is responsible for color and flavor formation in fried, roasted and baked foods. However, this reaction can also promote the formation of acrylamide, a potential human carcinogen. The application of l-asparaginase represents a promising method for acrylamide mitigation in heated products by the direct conversion of the precursor l-asparagine to l-aspartic acid and ammonia, which does not lead to additional acrylamide formation. Our research group produced and purified an l-asparaginase from native Aspergillus oryzae CCT 3940 with highly potential for acrylamide mitigation. To verify the enzymatic effectiveness, we compared the native l-asparaginase with the commercial recombinant enzyme. For this purpose, a GC-MS/MS method was developed, optimized and validated for the assessment of acrylamide in French fries. Our results indicate a relationship between the l-asparagine content and acrylamide formation in French fries. The acrylamide concentration of the fried potato treated with the l-asparaginase from A. oryzae CCT 3940 and treated with commercial enzyme reduced 72% and 92%, respectively compared to control sample. Moreover, the l-asparaginase from A. oryzae CCT 3940 showed no l-glutaminase activity, while commercial enzyme promoted a decrease in the l-glutamine content (25%). Our results suggest that l-asparaginase from A. oryzae CCT 3940 may be of great value for acrylamide mitigation76B222229FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2012/24046-711th Latin American Symposium on Food Science (SLACA)2015-11-08São Paulo, Brasi

Quantitative Analysis By Comprehensive Two-dimensional Gas Chromatography Using Interval Multi-way Partial Least Squares Calibration.

A new approach for target quantitative analysis for comprehensive two-dimensional gas chromatography (GC × GC), interval Multi-way Partial Least Square (iNPLS) is presented and evaluated in this paper. In iNPLS, the two-dimensional chromatogram is split in small sections; each of these pieces is treated as an independent new chromatogram. Separated conventional NPLS calibration models for the concentration of the target analyte are built for each of the pieces of the whole chromatogram, and the best model is selected for quantitative analysis. An algorithm for iNPLS running on MatLab platform was written, preliminarily evaluated with using solutions of model compounds with different chemical properties and subsequently applied to quantify some allergens in perfume samples. The results were found to be adequate, and good precision and accuracy was obtained even for poorly resolved peaks.831302-

Quantitative Analysis Of Essential Oils In Perfume Using Multivariate Curve Resolution Combined With Comprehensive Two-dimensional Gas Chromatography.

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC×GC-FID data.699120-

Multivariate Curve Resolution Combined With Gas Chromatography To Enhance Analytical Separation In Complex Samples: A Review.

This review describes the major advantages and pitfalls of iterative and non-iterative multivariate curve resolution (MCR) methods combined with gas chromatography (GC) data using literature published since 2000 and highlighting the most important combinations of GC coupled to mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) and coupled to mass spectrometry (GC×GC-MS). In addition, a brief summary of some pre-processing strategies will be discussed to correct common issues in GC, such as retention time shifts and baseline/background contributions. Additionally, algorithms such as evolving factor analysis (EFA), heuristic evolving latent projection (HELP), subwindow factor analysis (SFA), multivariate curve resolution-alternating least squares (MCR-ALS), positive matrix factorization (PMF), iterative target transformation factor analysis (ITTFA) and orthogonal projection resolution (OPR) will be described in this paper. Even more, examples of applications to food chemistry, lipidomics and medicinal chemistry, as well as in essential oil research, will be shown. Lastly, a brief illustration of the MCR method hierarchy will also be presented.73111-2

Essential Oils of New Lippia alba Genotypes Analyzed by Flow-Modulated Comprehensive Two-Dimensional Gas Chromatography (GC×GC) and Chemometric Analysis

Lippia alba (Mill.) N. E. Br. (Verbenaceae) is an aromatic shrub whose essential oils have stood out as a promising source for application in several industrial fields. In this study, the essential oils chemical characterization of eight new L. alba genotypes was performed. The selected materials were collected from the Active Germplasm Bank of the Agronomic Institute and the essential oils were extracted by hydrodistillation. Flow-modulated comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) was employed for chemical characterization and evaluation of possible co-eluted compounds. In addition, the chemical analyses were submitted to multivariate statistical analyses. From this investigation, 73 metabolites were identified in the essential oils of the genotypes, from which α-pinene, β-myrcene, 1,8-cineole, linalool, neral, geranial, and caryophyllene oxide were the most abundant compounds among the accessions. This is the first report disclosing α-pinene in higher amounts in L. alba (19.69%). In addition, sabinene, trans-verbenol, myrtenol, (E)-caryophyllene, α-guaiene, germacrene D, and α-bulnesene were also found in relevant quantities in some of the genotypes, and myrtenal and myrtenol could be well separated through the second dimension. Such results contributed to the understanding of the chemical composition of those new genotypes, being important to drive a future industrial applicability and studies in genetic breeding