Browsing by Subject "Mass spectrometry"

Now showing 1 - 8 of 8
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    A volatilomic approach using ion mobility and mass spectrometry combined with multivariate chemometrics for the assessment of lemon juice quality
    (Elsevier, 2024-11-09) Giménez Campillo, Claudia; Arroyo Manzanares, Natalia; Campillo Seva, Natalia; Díaz García, Miriam Cristina; Viñas López-Pelegrin, Pilar; Química Analítica
    Lemon (Citrus limon (L.) Burm.) is a citrus fruit known for its high nutritional value and potent antioxidant activity. Lemon juice, obtained by squeezing the fruit, is widely used in the kitchen for its acidic taste to flavour dishes and drinks. It has also been attributed with various medicinal properties to treat conditions such as sore throat, fever, rheumatism and hypertension. Ensuring the quality and safety of lemon juice, as well as its geographical origin, is not easy due to the scarcity of analytical methods available for this purpose, which makes it difficult to detect adulterations. To meet this challenge of testing the authenticity and safety of lemon juice, multiple physicochemical parameters need to be evaluated, which is expensive and time-consuming, so it is of great interest to develop an alternative simple method. In this research, two alternative analytical methods were developed and optimized for the analysis of lemon juice samples based on headspace gas chromatography coupled to both mass spectrometry (HS-GC-MS) or ion mobility spectrometry (HS-GC-IMS). These new methods were compared with the method currently used in the food industry for quality control of juices, which is Fourier transform near infrared spectroscopy (FT-NIR). A total of 159 samples belonging to different lemon varieties were analysed by measuring the physicochemical parameters, FT-NIR spectra and fingerprinting of the juice samples based on the total volatile compounds profile by GC-MS and GC-IMS. Partial least squares (PLS) regression models were then constructed and all models were validated by paired tests with the values measured by the reference chemical methods. The models developed confirm that both HS-GC-MS and HS-GC-IMS methods are viable alternatives for predicting physicochemical parameters and ensuring lemon juice quality. Finally, the data were used to build chemometric models using orthogonal partial least squares discriminant analysis (OPLSDA) to distinguish lemon juices according to the lemon variety used in their manufacture. Very promising models were obtained with the HS-GC-MS and HS-GC-IMS data, suggesting the potential use of the volatile profile for lemon variety confirmation. Consequently, fingerprinting represents an alternative proposal to the conventional method applied in the food industry based on the use of chemical reference parameters or the use of the NIR technique.
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    Discrimination of the geographical origin of peaches by the monitoring of volatile organic compounds by gas chromatography with mass spectrometry and chemometric tools
    (Elsevier, 2024-02-24) Giménez Campillo, Claudia; Arroyo Manzanares, Natalia; Pastor Belda, Marta; Campillo Seva, Natalia; Viñas López-Pelegrin, Pilar; Química Analítica
    The peach is one of the most popular and widely consumed fruits in Europe. Spain is the largest peach-producing country in the world with several growing areas recognised by consumers. This work focuses on the development, optimisation and validation of a non-targeted metabolomics strategy for the determination of peach volatile organic compounds from different origins by headspace gas chromatography coupled to mass spectrometry (HS–GC–MS). The volatil profile found in each sample is used to classify peaches according to their origin. The results obtained were processed using MS-DIAL software and 279 features were detected, of which 102 volatile compounds were tentatively identified and 30 of them could also be quantified. In addition, the areas of all the features were used to build models based on orthogonal partial least squares discriminant analysis (OPLS-DA) to differentiate peaches according to their geographical origin. A very promising model was obtained, with a validation rate of 90.32%, which means that it could be used to guarantee the Protected Designation of Origin of different peaches with a simple analysis.
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    Open Access
    Fiber type diversity in skeletal muscle explored by mass spectrometry-based single fiber proteomics
    (Universidad de Murcia, Departamento de Biologia Celular e Histiologia, 2020) Schiaffino, Stefano; Reggiani, Carlo; Murgia, Marta
    Mammalian skeletal muscles are composed of a variety of muscle fibers with specialized functional properties. Slow fibers are suited for long lasting and low intensity contractile activity, while various subtypes of fast fibers are optimized to produce high force and power even with a significant fatigue. The functional specialization of muscle fibers is based on selective gene expression regulation, which provides each fiber with a specific protein complement. The recent refinement of small-scale sample preparation, combined with the development of mass spectrometers characterized by high sensitivity, sequencing speed and mass accuracy, has allowed the characterization of the proteome of single muscle fibers with an unprecedented resolution. In the last few years, the first studies on the global proteomics of individual fibers of different types have been published. In this short review we discuss the methodological advancements which have opened the way to single fiber proteomics and the discovery power of this approach. We provide examples of how specific features of single fibers can be overlooked when whole muscle or multi- fiber samples are analyzed and can only be detected when a single fiber proteome is analyzed. Thus, novel subtype-specific metabolic features, most prominently mitochondrial specialization of fiber types, have been revealed by single fiber proteomics. In the same way, specific adaptive responses of single fibers to aging or loss of neural input have been detected when single fibers were individually analyzed. We conclude that the fiber type-resolved proteomes represent a powerful tool which can be applied to a variety of physiological and pathological conditions.
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    Open Access
    Fiber type diversity in skeletal muscle explored by mass spectrometry-based single fiber proteomics.
    (Universidad de Murcia, Departamento de Biologia Celular e Histiologia, 2020) Schiaffino, Stefano; Reggiani, Carlo; Murgia, Marta
    Mammalian skeletal muscles are composed of a variety of muscle fibers with specialized functional properties. Slow fibers are suited for long lasting and low intensity contractile activity, while various subtypes of fast fibers are optimized to produce high force and power even with a significant fatigue. The functional specialization of muscle fibers is based on selective gene expression regulation, which provides each fiber with a specific protein complement. The recent refinement of small-scale sample preparation, combined with the development of mass spectrometers characterized by high sensitivity, sequencing speed and mass accuracy, has allowed the characterization of the proteome of single muscle fibers with an unprecedented resolution. In the last few years, the first studies on the global proteomics of individual fibers of different types have been published. In this short review we discuss the methodological advancements which have opened the way to single fiber proteomics and the discovery power of this approach. We provide examples of how specific features of single fibers can be overlooked when whole muscle or multi- fiber samples are analyzed and can only be detected when a single fiber proteome is analyzed. Thus, novel subtype-specific metabolic features, most prominently mitochondrial specialization of fiber types, have been revealed by single fiber proteomics. In the same way, specific adaptive responses of single fibers to aging or loss of neural input have been detected when single fibers were individually analyzed. We conclude that the fiber type-resolved proteomes represent a powerful tool which can be applied to a variety of physiological and pathological conditions
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    Open Access
    Head-space gas chromatography coupled to mass spectrometry for the assessment of the contamination of mayonnaise by yeasts
    (Elsevier B.V., 2019-08-15) Arroyo-Manzanares, N.; Markiv, B.; Hernández, J.D.; López-García, I.; Guillén, I.; Vizcaíno, P.; Hernández Córdoba, Manuel; Viñas López-Pelegrín, Pilar; Química Analítica
    Head-space (HS) gas chromatography (GC) coupled to mass spectrometry (MS) is proposed for the assessment of the contamination of mayonnaise as an alternative to plate counting, which is the technique commonly used for evaluating microbial contamination. More specifically, this method was applied in the detection of Candida metapsilosis and Zygosaccharomyces bailii, both of great importance in term of food spoilage since they are resistant to many of the common methods of food preservation. Different chemometric models were investigated using the data obtained by GC-MS (m/z profile, area of the chromatographic peaks and entire chromatographic profile), in order to obtain the highest classification success. The best results were obtained using the chromatographic profile (success rate of 92%). Contaminated samples could also be classified according to the concentration of yeast, obtaining a success rate of 87.5%. Finally, a chemometric model was constructed in an attempt to differentiate between strains.
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    Open Access
    High-resolution proteomics and metabolomics in thyroid cancer: Deciphering novel biomarkers
    (Taylor & Francis, 2017-10-30) Navas-Carrillo, Diana; Rodríguez, José Manuel; Montoro-García, Silvia; Orenes Piñero, Esteban; Bioquímica y Biología Molecular A
    Thyroid cancer (TC) is the most common endocrine malignancy and its incidence has been increasing sharply since the mid-1990s, being the fastest-increasing cancers in both men and women. Increased medical surveillance, the effect of environmental factors and more sensitive diagnostic tests, such as ultrasound and confirmation via fine-needle aspiration biopsy, are thought to account for this increased incidence. There are several histological types of thyroid cancer, including papillary thyroid carcinoma, follicular thyroid carcinoma, medullary thyroid carcinoma, and anaplastic thyroid carcinoma. Determining the type of thyroid cancer is crucial for the assessment of prognosis and treatment selection. Unfortunately, approximately 20–30% of patients undergoing fine-needle aspiration biopsy have inconclusive or indeterminate results, leading to unnecessary surgical intervention in 80% of patients with benign nodules. To resolve this diagnosis dilemma, new biomarkers of thyroid cancer are needed. Proteomic approaches offer an unbiased platform for the comprehensive analysis of the whole proteome in a certain physiological time. Although mRNA expression is widely considered to be indicative of protein expression, protein levels are the result of protein synthesis and degradation, and RNA levels are not informative of protein degradation. Clinically, there is increasing evidence for the role of proteomic and metabolomic technologies in biomarker discovery, providing novel information on the molecular events associated with TC, and potentially lead to the identification of novel drug targets. In this review, we will thoroughly describe the importance of novel proteomic and metabolomic approaches to identify new biomarkers associated with TC.
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    Histopathology of Duchenne muscular dystrophy in correlation with changes in proteomic biomarkers
    (Universidad de Murcia, Departamento de Biologia Celular e Histiologia, 2022) Zweyer, Margit; Sabir, Hemmen; Dowling, Paul; Gargan, Stephen; Murphy, Sandra; Swandulla, Dieter; Ohlendieck, Kay
    Duchenne muscular dystrophy is an inherited disorder of early childhood that affects multiple systems in the body. Besides late-onset cardio-respiratory syndrome and various body-wide pathophysiological changes, X-linked muscular dystrophy is primarily classified as a disorder of the skeletal musculature. This is reflected by severe histopathological alterations in voluntary contractile tissues, including progressive fibre degeneration, fat substitution, reactive myofibrosis and chronic inflammation. The underlying cause for dystrophinopathy are genetic abnormalities in the DMD gene, which can result in the almost complete loss of the membrane cytoskeletal protein dystrophin, which triggers the collapse of the dystrophin-associated glycoprotein complex and disintegration of sarcolemmal integrity. This in turn results in an increased frequency of membrane micro-rupturing and abnormal calcium ion fluxes through the impaired plasmalemma, which renders muscle fibres more susceptible to enhanced proteolytic degradation and necrosis. This review focuses on the complexity of skeletal muscle changes in X-linked muscular dystrophy and outlines cell biological and histological alterations in correlation to proteomewide variations as judged by mass spectrometric analyses. This includes a general outline of sample handling, subcellular fraction protocols and modern proteomic approaches using gel electrophoretic and liquid chromatographic methods for efficient protein separation prior to mass spectrometry. The proteomic profiling of the dystrophic and highly fibrotic diaphragm muscle is described as an example to swiftly identify novel proteomic markers of complex histopathological changes during skeletal muscle degeneration. The potential usefulness of new protein markers is examined in relation to key histopathological hallmarks for establishing improved diagnostic, prognostic and therapy-monitoring approaches in the field of dystrophinopathy.
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    Ion mobility spectrometry and mass spectrometry coupled to gas chromatography for analysis of microbial contaminated cosmetic creams
    (Elsevier, 2020-07-11) García Nicolás, María; Arroyo Manzanares, Natalia; Hernández, Juan de Dios; Guillén, Isidro; Vizcaino, Pascuala; Sánchez Rubio, Marta; López García, Ignacio Francisco; Hernández Córdoba, Manuel; Viñas López-Pelegrin, Pilar; Química Analítica
    The most commonly used technique for monitoring microbial contamination in cosmetic products is plate counting. In this contribution, headspace - gas chromatography (HS-GC) coupled to mass spectrometry (MS) or ion mobility spectrometry (IMS) is proposed as a technique to evaluate rapidly and accurately the state of microbial colonies in cosmetic creams using the volatile organic compounds produced by microorganisms (MVOC). The work focuses on monitoring two of the microorganisms that most frequently occur in such creams, Candida albicans and Staphylococcus aureus. In addition, two different types of ingredient with antimicrobial properties (a chemical preservative and a natural preservative) were added to study the behaviour of these microorganisms under different conditions. The facial creams were elaborated and inoculated with the two above microorganisms, and then sampled weekly for 4 weeks, analysing the evolution of the MVOCs by HS-GC-MS and HS-GC-IMS. In addition, microbial contamination was determined by the classical plate counting method. The pH, colour, viscosity and water activity parameters were also measured. The use of chemometric tools is essential because of the large amount of data generated, and different models based on discriminant analysis with an orthogonal projection on latent structures (OPLS-DA) were constructed. The optimal models obtained by both analytical techniques allowed differentiation between contaminated and non-contaminated creams, with a validation success rate of 94.4%. In addition, MVOC monitoring also allowed assessment of the microbial concentration.