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Harvey DJ. Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022. MASS SPECTROMETRY REVIEWS 2024. [PMID: 38925550 DOI: 10.1002/mas.21873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 02/05/2024] [Accepted: 02/12/2024] [Indexed: 06/28/2024]
Abstract
The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.
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Fucito M, Spedicato M, Felletti S, Yu AC, Busin M, Pasti L, Franchina FA, Cavazzini A, De Luca C, Catani M. A Look into Ocular Diseases: The Pivotal Role of Omics Sciences in Ophthalmology Research. ACS MEASUREMENT SCIENCE AU 2024; 4:247-259. [PMID: 38910860 PMCID: PMC11191728 DOI: 10.1021/acsmeasuresciau.3c00067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 06/25/2024]
Abstract
Precision medicine is a new medical approach which considers both population characteristics and individual variability to provide customized healthcare. The transition from traditional reactive medicine to personalized medicine is based on a biomarker-driven process and a deep knowledge of biological mechanisms according to which the development of diseases occurs. In this context, the advancements in high-throughput omics technologies represent a unique opportunity to discover novel biomarkers and to provide an unbiased picture of the biological system. One of the medical fields in which omics science has started to be recently applied is that of ophthalmology. Ocular diseases are very common, and some of them could be highly disabling, thus leading to vision loss and blindness. The pathogenic mechanism of most ocular diseases may be dependent on various genetic and environmental factors, whose effect has not been yet completely understood. In this context, large-scale omics approaches are fundamental to have a comprehensive evaluation of the whole system and represent an essential tool for the development of novel therapies. This Review summarizes the recent advancements in omics science applied to ophthalmology in the last ten years, in particular by focusing on proteomics, metabolomics and lipidomics applications from an analytical perspective. The role of high-efficiency separation techniques coupled to (high-resolution) mass spectrometry ((HR)MS) is also discussed, as well as the impact of sampling, sample preparation and data analysis as integrating parts of the analytical workflow.
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Affiliation(s)
- Maurine Fucito
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
| | - Matteo Spedicato
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
| | - Simona Felletti
- Department
of Environmental and Prevention Sciences, University of Ferrara, via L. Borsari 46, Ferrara 44121, Italy
| | - Angeli Christy Yu
- Department
of Translational Medicine and for Romagna, University of Ferrara, via Aldo Moro 8, 44124 Ferrara, Italy
| | - Massimo Busin
- Department
of Translational Medicine and for Romagna, University of Ferrara, via Aldo Moro 8, 44124 Ferrara, Italy
| | - Luisa Pasti
- Department
of Environmental and Prevention Sciences, University of Ferrara, via L. Borsari 46, Ferrara 44121, Italy
| | - Flavio A. Franchina
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
| | - Alberto Cavazzini
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
- Council
for Agricultural Research and Economics, via della Navicella 2/4, Rome 00184, Italy
| | - Chiara De Luca
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
| | - Martina Catani
- Department
of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121 Ferrara, Italy
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Hachem M, Ahmmed MK, Nacir-Delord H. Phospholipidomics in Clinical Trials for Brain Disorders: Advancing our Understanding and Therapeutic Potentials. Mol Neurobiol 2024; 61:3272-3295. [PMID: 37981628 PMCID: PMC11087356 DOI: 10.1007/s12035-023-03793-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 10/31/2023] [Indexed: 11/21/2023]
Abstract
Phospholipidomics is a specialized branch of lipidomics that focuses on the characterization and quantification of phospholipids. By using sensitive analytical techniques, phospholipidomics enables researchers to better understand the metabolism and activities of phospholipids in brain disorders such as Alzheimer's and Parkinson's diseases. In the brain, identifying specific phospholipid biomarkers can offer valuable insights into the underlying molecular features and biochemistry of these diseases through a variety of sensitive analytical techniques. Phospholipidomics has emerged as a promising tool in clinical studies, with immense potential to advance our knowledge of neurological diseases and enhance diagnosis and treatment options for patients. In the present review paper, we discussed numerous applications of phospholipidomics tools in clinical studies, with a particular focus on the neurological field. By exploring phospholipids' functions in neurological diseases and the potential of phospholipidomics in clinical research, we provided valuable insights that could aid researchers and clinicians in harnessing the full prospective of this innovative practice and improve patient outcomes by providing more potent treatments for neurological diseases.
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Affiliation(s)
- Mayssa Hachem
- Department of Chemistry and Healthcare Engineering Innovation Center, Khalifa University of Sciences and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates.
| | - Mirja Kaizer Ahmmed
- Department of Fishing and Post-Harvest Technology, Chattogram Veterinary and Animal Sciences University, Chattogram, Bangladesh
- Riddet Institute, Massey University, Palmerston North, New Zealand
| | - Houda Nacir-Delord
- Department of Chemistry, Khalifa University of Sciences and Technology, P.O. Box 127788, Abu Dhabi, United Arab Emirates
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Mehrotra S, Sharma S, Pandey RK. A journey from omics to clinicomics in solid cancers: Success stories and challenges. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2024; 139:89-139. [PMID: 38448145 DOI: 10.1016/bs.apcsb.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
The word 'cancer' encompasses a heterogenous group of distinct disease types characterized by a spectrum of pathological features, genetic alterations and response to therapies. According to the World Health Organization, cancer is the second leading cause of death worldwide, responsible for one in six deaths and hence imposes a significant burden on global healthcare systems. High-throughput omics technologies combined with advanced imaging tools, have revolutionized our ability to interrogate the molecular landscape of tumors and has provided unprecedented understanding of the disease. Yet, there is a gap between basic research discoveries and their translation into clinically meaningful therapies for improving patient care. To bridge this gap, there is a need to analyse the vast amounts of high dimensional datasets from multi-omics platforms. The integration of multi-omics data with clinical information like patient history, histological examination and imaging has led to the novel concept of clinicomics and may expedite the bench-to-bedside transition in cancer. The journey from omics to clinicomics has gained momentum with development of radiomics which involves extracting quantitative features from medical imaging data with the help of deep learning and artificial intelligence (AI) tools. These features capture detailed information about the tumor's shape, texture, intensity, and spatial distribution. Together, the related fields of multiomics, translational bioinformatics, radiomics and clinicomics may provide evidence-based recommendations tailored to the individual cancer patient's molecular profile and clinical characteristics. In this chapter, we summarize multiomics studies in solid cancers with a specific focus on breast cancer. We also review machine learning and AI based algorithms and their use in cancer diagnosis, subtyping, prognosis and predicting treatment resistance and relapse.
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Mafata M, Stander M, Masike K, Buica A. Exploratory data fusion of untargeted multimodal LC-HRMS with annotation by LCMS-TOF-ion mobility: White wine case study. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2023; 29:111-122. [PMID: 36942424 PMCID: PMC10068406 DOI: 10.1177/14690667231164096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Applied sciences have increased focus on omics studies which merge data science with analytical tools. These studies often result in large amounts of data produced and the objective is to generate meaningful interpretations from them. This can sometimes mean combining and integrating different datasets through data fusion techniques. The most strategic course of action when dealing with products of unknown profile is to use exploratory approaches. For omics, this means using untargeted analytical methods and exploratory data analysis techniques. The current study aimed to perform data fusion on untargeted multimodal (negative and positive mode) liquid chromatography-high-resolution mass spectrometry data using multiple factor analysis. The data fusion results were interpreted using agglomerative hierarchical clustering on biplot projections. The study reduced the thousands of spectral signals processed to less than a hundred features (a primary parameter combination of retention time and mass-to-charge ratios, RT_m/z). The correlations between cluster members (samples and features from) were calculated and the top 10% highly correlated features were identified for each cluster. These features were then tentatively identified using secondary parameters (drift time, ion mobility constant and collision cross-section values) from the ion mobility spectra. These ion mobility (secondary) parameters can be used for future studies in wine chemical analysis and added to the growing list of annotated chemical signals in applied sciences.
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Affiliation(s)
- Mpho Mafata
- School for Data Science and Computational Thinking,
Stellenbosch
University, Stellenbosch, South
Africa
- Department of Viticulture and Oenology, South African Grape and Wine
Research Institute, Stellenbosch
University, Stellenbosch, South
Africa
| | - Maria Stander
- Central Analytical Facility, Stellenbosch
University, Stellenbosch, South Africa
| | - Keabetswe Masike
- Central Analytical Facility, Stellenbosch
University, Stellenbosch, South Africa
| | - Astrid Buica
- School for Data Science and Computational Thinking,
Stellenbosch
University, Stellenbosch, South
Africa
- Department of Viticulture and Oenology, South African Grape and Wine
Research Institute, Stellenbosch
University, Stellenbosch, South
Africa
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Ilyushenkova VV, Zimens ME, Polovkov NY, Topolyan AP, Borisov RS, Zaikin VG. Derivatization to increase the detectability of small peptides in blood serum in the analysis by ESI and MALDI high resolution mass spectrometric methods. Talanta 2023; 253:123922. [PMID: 36122435 DOI: 10.1016/j.talanta.2022.123922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/26/2022] [Accepted: 09/04/2022] [Indexed: 12/13/2022]
Abstract
This work highlights the efficient approach to highly sensitive determination of dipeptides that can present in biological liquids at very low and trace quantities. The approach involves preliminary derivatization of peptides with tris(2,4,6-trimethoxyphenyl)-methyl carbenium hexafluoroborate followed by ESI and MALDI high-resolution mass spectrometry. Using model dipeptides with various amino acid compositions and sequences, it was shown that the derivatization reaction proceeded smoothly in mild conditions and gave rise to pink-red colored salt derivatives. Ready cations of interest for the analysis are easily desorbed from the salt-derivatives providing strong signals in ESI and MALDI mass spectra and this ensures high sensitivity of the analysis. Another positive aspect is the removal of the target signal from the region of a matrix noise, since the introduced fragment possesses a large mass increment (359 Da). High resolution mass spectrometry, which provides the determination of accurate weights and elemental compositions of ions, was used to reliably detect model dipeptides added to artificial urine and blood serum. A number of these dipeptides was shown to be present in real blood serum collected from volunteers. Collision induced dissociation of precursor cations composed of derivatizing reagent and dipeptide moieties gives rise to characteristic and simple fragmentation mass spectra. A comparison of limits of detection (LOD) measured for non-modified and derivatized dipeptides showed that the latter derivatives provide the highest sensitivity when LOD is determined by using multiple reaction monitoring (MRM) transitions. The suggested derivatization approach was shown to be useful for unambiguous identification of special dipeptides in artificial media and dietary supplements.
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Affiliation(s)
- Valentina V Ilyushenkova
- N. D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, 47 Leninsky Prosp., Moscow, 119991, Russian Federation
| | - Marina E Zimens
- A.V.Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, 29 Leninsky pr., 119991, Moscow, Russia
| | - Nikolay Yu Polovkov
- A.V.Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, 29 Leninsky pr., 119991, Moscow, Russia
| | - Artyom P Topolyan
- Mendeleev University of Chemical Technology of Russia, Miusskaya sq. 9, Moscow, 125047, Russia
| | - Roman S Borisov
- A.V.Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, 29 Leninsky pr., 119991, Moscow, Russia; Mendeleev University of Chemical Technology of Russia, Miusskaya sq. 9, Moscow, 125047, Russia.
| | - Vladimir G Zaikin
- A.V.Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, 29 Leninsky pr., 119991, Moscow, Russia
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Wolfer JD, Minkoff BB, Sussman MR. Mass spectrometric based analysis of whole eggs dissolved in formic acid. Food Chem 2022; 405:134846. [DOI: 10.1016/j.foodchem.2022.134846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/13/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
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Extraction of High-Value Chemicals from Plants for Technical and Medical Applications. Int J Mol Sci 2022; 23:ijms231810334. [PMID: 36142238 PMCID: PMC9499410 DOI: 10.3390/ijms231810334] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 09/03/2022] [Accepted: 09/05/2022] [Indexed: 11/24/2022] Open
Abstract
Plants produce a variety of high-value chemicals (e.g., secondary metabolites) which have a plethora of biological activities, which may be utilised in many facets of industry (e.g., agrisciences, cosmetics, drugs, neutraceuticals, household products, etc.). Exposure to various different environments, as well as their treatment (e.g., exposure to chemicals), can influence the chemical makeup of these plants and, in turn, which chemicals will be prevalent within them. Essential oils (EOs) usually have complex compositions (>300 organic compounds, e.g., alkaloids, flavonoids, phenolic acids, saponins and terpenes) and are obtained from botanically defined plant raw materials by dry/steam distillation or a suitable mechanical process (without heating). In certain cases, an antioxidant may be added to the EO (EOs are produced by more than 17,500 species of plants, but only ca. 250 EOs are commercially available). The interesting bioactivity of the chemicals produced by plants renders them high in value, motivating investment in their production, extraction and analysis. Traditional methods for effectively extracting plant-derived biomolecules include cold pressing and hydro/steam distillation; newer methods include solvent/Soxhlet extractions and sustainable processes that reduce waste, decrease processing times and deliver competitive yields, examples of which include microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), subcritical water extraction (SWE) and supercritical CO2 extraction (scCO2). Once extracted, analytical techniques such as chromatography and mass spectrometry may be used to analyse the contents of the high-value extracts within a given feedstock. The bioactive components, which can be used in a variety of formulations and products (e.g., displaying anti-aging, antibacterial, anticancer, anti-depressive, antifungal, anti-inflammatory, antioxidant, antiparasitic, antiviral and anti-stress properties), are biorenewable high-value chemicals.
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