Spatially and temporally resolved metabolome of the human oral cavity

Ciurli, Alessio; Mohammed, Yassene; Ammon, Christine; Derks, Rico J.E.; Olivier-Jimenez, Damien; Ducarmon, Quinten R.; Slingerland, Marije; Neefjes, Jacques; Giera, Martin

doi:10.1016/j.isci.2024.108884

Cited by 4 publications

(3 citation statements)

References 64 publications

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“…The use of saliva as a biological sample is advantageous due to its minimally invasive nature, ease of collection, and the comprehensive metabolic data it offers ( 17–20 ). The rich vascularization of salivary glands facilitates an efficient exchange of metabolites, making saliva an ideal matrix for reflecting systemic metabolic changes ( 19 , 20 ).…”

Section: Discussionmentioning

confidence: 99%

“…Our approach has not only provided a novel perspective on swine reproductive management but also laid the groundwork for future molecular diagnostic techniques. The use of saliva as a biological sample is advantageous due to its minimally invasive nature, ease of collection, and the comprehensive metabolic data it offers (17)(18)(19)(20). The rich vascularization of salivary glands facilitates an efficient exchange of metabolites, making saliva an ideal matrix for reflecting systemic metabolic changes (19,20).…”

Section: Discussionmentioning

confidence: 99%

“…The use of saliva as a biological sample is advantageous due to its minimally invasive nature, ease of collection, and the comprehensive metabolic data it offers (17)(18)(19)(20). The rich vascularization of salivary glands facilitates an efficient exchange of metabolites, making saliva an ideal matrix for reflecting systemic metabolic changes (19,20). Through our untargeted metabolomics analysis, we identified 286 differentially expressed metabolites, with Hyodeoxycholic acid and 2′-deoxyguanosine showing significant differential expression and high diagnostic accuracy as potential biomarkers for early pregnancy.…”

Section: Discussionmentioning

confidence: 99%

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Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach

Ren,

Zhang,

et al. 2024

Front. Vet. Sci.

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In an effort to enhance reproductive management and reduce non-productive periods in swine breeding, this study presents a novel, non-invasive metabolomics approach for the identification of early pregnancy biomarkers in sows. Utilizing an untargeted metabolomics approach with mass spectrometry analysis, we examined saliva samples from pregnant (n = 6) and non-pregnant control sows (n = 6, artificially inseminated with non-viable sperm). Our analysis revealed 286 differentially expressed metabolites, with 152 being up-regulated and 134 down-regulated in the pregnant group. Among these, three metabolites, namely Hyodeoxycholic acid, 2′-deoxyguanosine, and Thymidine, emerged as potential early pregnancy biomarkers. These biomarkers were further evaluated using targeted LC–MS/MS quantification and qualification, accompanied by ROC curve analysis. The study confirmed Hyodeoxycholic acid and 2′-deoxyguanosine as promising biomarkers for early pregnancy detection, offering potential for future implementation in swine production environments. This research establishes a robust theoretical foundation for the development of innovative molecular diagnostic techniques and explores new avenues for molecular genetic breeding and non-invasive diagnostics, ultimately enhancing fertility and productivity in sow herds.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach

Ren,

Zhang,

et al. 2024

Front. Vet. Sci.

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Assessing the influence of sleep and sampling time on metabolites in oral fluid: implications for metabolomics studies

Scholz,

Steuer,

Dobay

et al. 2024

Metabolomics

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Introduction The human salivary metabolome is a rich source of information for metabolomics studies. Among other influences, individual differences in sleep-wake history and time of day may affect the metabolome. Objectives We aimed to characterize the influence of a single night of sleep deprivation compared to sufficient sleep on the metabolites present in oral fluid and to assess the implications of sampling time points for the design of metabolomics studies. Methods Oral fluid specimens of 13 healthy young males were obtained in Salivette® devices at regular intervals in both a control condition (repeated 8-hour sleep) and a sleep deprivation condition (total sleep deprivation of 8 h, recovery sleep of 8 h) and their metabolic contents compared in a semi-targeted metabolomics approach. Results Analysis of variance results showed factor ‘time’ (i.e., sampling time point) representing the major influencer (median 9.24%, range 3.02–42.91%), surpassing the intervention of sleep deprivation (median 1.81%, range 0.19–12.46%). In addition, we found about 10% of all metabolic features to have significantly changed in at least one time point after a night of sleep deprivation when compared to 8 h of sleep. Conclusion The majority of significant alterations in metabolites’ abundances were found when sampled in the morning hours, which can lead to subsequent misinterpretations of experimental effects in metabolomics studies. Beyond applying a within-subject design with identical sample collection times, we highly recommend monitoring participants’ sleep-wake schedules prior to and during experiments, even if the study focus is not sleep-related (e.g., via actigraphy).

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Intra- and inter-day variations in oral metabolites from mouth-rinsed water determined using capillary electrophoresis–mass spectrometry metabolomics

Maruyama,

Fujii,

Kawamata

et al. 2025

Clinica Chimica Acta

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Spatially and temporally resolved metabolome of the human oral cavity

Cited by 4 publications

References 64 publications

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach

Assessing the influence of sleep and sampling time on metabolites in oral fluid: implications for metabolomics studies

Intra- and inter-day variations in oral metabolites from mouth-rinsed water determined using capillary electrophoresis–mass spectrometry metabolomics

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