Fingerprinting and profiling in metabolomics of biosamples

Ghini, Veronica; Meoni, Gaia; Vignoli, Alessia; Di Cesare, Francesca; Tenori, Leonardo; Turano, Paola; Luchinat, Claudio

doi:10.1016/j.pnmrs.2023.10.002

Cited by 9 publications

(12 citation statements)

References 259 publications

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“…Intact tissues (10 samples per group, Table S1) were analyzed through High Resolution (HR) Magic Angle Spinning (MAS) NMR analysis. ,, To this end, frozen colon samples were trimmed (15–20 mg) to fit HR-MAS ZrO 2 rotor insert capacity (50 μL). Each insert was filled with 2 H 2 O containing 5.8 mM sodium trimethylsilyl [2,2,3,3- 2 H 4 ] propionate (TMSP).…”

Section: Methodsmentioning

confidence: 99%

“…We examine both types of disease states (acute and chronic), and most importantly, we examine two early states, from each model, in which there are no detectable symptoms and therefore can be regarded as “presymptomatic”. Nuclear magnetic resonance (NMR) metabolomics − data on tissues and fecal extracts and liquid chromatography–tandem mass spectrometry (LC-MS/MS)-based proteomics data on tissues were combined to derive the molecular signature of disease onset and progression.…”

Section: Introductionmentioning

confidence: 99%

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Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis

Shimshoni,

Solomonov,

Sagi

et al. 2024

J. Proteome Res.

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Colitis has a multifactorial pathogenesis with a strong cross-talk among microbiota, hypoxia, and tissue metabolism. Here, we aimed to characterize the molecular signature of the disease in symptomatic and presymptomatic stages of the inflammatory process at the tissue and fecal level. The study is based on two different murine models for colitis, and HR-MAS NMR on "intact" colon tissues and LC-MS/MS on colon tissue extracts were used to derive untargeted metabolomics and proteomics information, respectively. Solution NMR was used to derive metabolomic profiles of the fecal extracts. By combining metabolomic and proteomic analyses of the tissues, we found increased anaerobic glycolysis, accompanied by an altered citric acid cycle and oxidative phosphorylation in inflamed colons; these changes associate with inflammation-induced hypoxia taking place in colon tissues. Different colitis states were also characterized by significantly different metabolomic profiles of fecal extracts, attributable to both the dysbiosis characteristic of colitis as well as the dysregulated tissue metabolism. Strong and distinctive tissue and fecal metabolomic signatures can be detected before the onset of symptoms. Therefore, untargeted metabolomics of tissues and fecal extracts provides a comprehensive picture of the changes accompanying the disease onset already at preclinical stages, highlighting the diagnostic potential of global metabolomics for inflammatory diseases.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis

Shimshoni,

Solomonov,

Sagi

et al. 2024

J. Proteome Res.

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“…Cell lysates and the respective growth media were analyzed using an untargeted 1 H NMR-based metabolomics [26]. For A2780 and A2780cis cells, the NMR experiments were performed on biological triplicates (i.e., from different culture batches).…”

Section: Nmr Sample Preparation and Nmr Analysismentioning

confidence: 99%

NMR Metabolomics of Primary Ovarian Cancer Cells in Comparison to Established Cisplatin-Resistant and -Sensitive Cell Lines

Ghini,

Sorbi,

Fambrini

et al. 2024

Cells

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Cancer cell lines are frequently used in metabolomics, such as in vitro tumor models. In particular, A2780 cells are commonly used as a model for ovarian cancer to evaluate the effects of drug treatment. Here, we compare the NMR metabolomics profiles of A2780 and cisplatin-resistant A2780 cells with those of cells derived from 10 patients with high-grade serous ovarian carcinoma (collected during primary cytoreduction before any chemotherapeutic treatment). Our analysis reveals a substantial similarity among all primary cells but significant differences between them and both A2780 and cisplatin-resistant A2780 cells. Notably, the patient-derived cells are closer to the resistant A2780 cells when considering the exo-metabolome, whereas they are essentially equidistant from A2780 and A2780-resistant cells in terms of the endo-metabolome. This behavior results from dissimilarities in the levels of several metabolites attributable to the differential modulation of underlying biochemical pathways. The patient-derived cells are those with the most pronounced glycolytic phenotype, whereas A2780-resistant cells mainly diverge from the others due to alterations in a few specific metabolites already known as markers of resistance.

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“…As natural experts in organic synthesis, plants are able to generate large numbers of specific metabolites with widely varying structures, such as lipids, nucleic acids, amino acids, peptides, carbohydrates, organic acids, ketones, aldehydes, amines, steroids, vitamins, signaling molecules, hormones, polyphenols, and some other small-molecule metabolic intermediates, which play an important role in the growth and development of plants [ 1 ]. Metabolomic profiling can provide botanists with the chemical fingerprint that represents the biochemical state of an organism or sample at a specific point in time, thus revealing biochemical and molecular mechanisms more effectively [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

In-Situ Metabolic Profiling of Different Kinds of Rheum palmatum L. by Laser Desorption–Dielectric Barrier Discharge Ionization Mass Spectrometry Imaging

Xiao,

Guan,

et al. 2024

Metabolites

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With its high resolving power and sensitivity, mass spectrometry is considered the most informative technique for metabolite qualitation and quantification in the plant sciences. However, the spatial location information, which is crucial for the exploration of plant physiological mechanisms, is lost. Mass spectrometry imaging (MSI) is able to visualize the spatial distribution of a large number of metabolites from the complex sample surface in a single experiment. In this paper, a flexible and low-cost laser desorption–dielectric barrier discharge ionization-MSI (LD-DBDI-MSI) platform was constructed by combining an LD system with an in-line DBDI source, a high-precision sample translation stage, and an ambient mass spectrometer. It can be operated at a spatial resolution of 20 μm in an atmospheric environment and requires minimal sample preparation. This study presents images of in-situ metabolic profiling of two kinds of plants from different origins, a wild and a farmed Rheum palmatum L. From the screen of these two root sections, the wild one presented five more endogenous molecules than the farmed one, which provides information about the differences in metabolomics.

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Fingerprinting and profiling in metabolomics of biosamples

Cited by 9 publications

References 259 publications

Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis

Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis

NMR Metabolomics of Primary Ovarian Cancer Cells in Comparison to Established Cisplatin-Resistant and -Sensitive Cell Lines

In-Situ Metabolic Profiling of Different Kinds of Rheum palmatum L. by Laser Desorption–Dielectric Barrier Discharge Ionization Mass Spectrometry Imaging

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