Spatially resolved sampling for untargeted metabolomics: A new tool for salivomics

Spatially and temporally resolved metabolome of the human oral cavity

Saliva is a complex bodily fluid composed of secretions by major and minor salivary glands. Salivary glands and their secretions are known to be unevenly distributed in the human oral cavity. Moreover, saliva flow rate and composition vary across locations and time of the day. This remarkable heterogeneity of salivary secretions suggests that different subtypes of saliva fulfill different functions. By coupling a non-invasive and facile collection method with comprehensive metabolomic profiling, we investigated the spatial and temporal distributions of salivary components. We identified location-specific metabolite profiles, novel oscillating metabolites, and location-specific diurnal patterns. In summary, our study paves the way for a deeper and more comprehensive understanding of the complex dynamics and functionalities of the salivary metabolome and its integration in multi-omics studies related to oral and systemic (patho-)physiology.

Reducing Mass Confusion over the Microbiome

As genetic tools continue to emerge and mature, more information is revealed about the identity and diversity of microbial community members. Genetic tools can also be used to make predictions about the chemistry that bacteria and fungi produce to function and communicate with one another and the host. Ongoing efforts to identify these products and link genetic information to microbiome chemistry rely on analytical tools. This tutorial highlights recent advancements in microbiome studies driven by techniques in mass spectrometry.

Standard operating procedures for the collection, processing, and storage of oral biospecimens at the Korea Oral Biobank Network

PURPOSE

The Korea Oral Biobank Network (KOBN) was established in 2021 as a branch of the Korea Biobank Network under the Korea Centers for Disease Control and Prevention to provide infrastructure for the collection, management, storage, and utilization of human bioresources from the oral cavity and associated clinical data for basic research and clinical studies.

METHODS

To address the need for the unification of the biobanking process, the KOBN organized the concept review for all the processes.

RESULTS

The KOBN established standard operating procedures for the collection, processing, and storage of oral samples.

CONCLUSIONS

The importance of collecting high-quality bioresources to generate accurate and reproducible research results has always been emphasized. A standardized procedure is a basic prerequisite for implementing comprehensive quality management of biological resources and accurate data production.

Obtaining a Reliable Diagnostic Biomarker for Diabetes Mellitus by Standardizing Salivary Glucose Measurements

Salivary glucose is frequently utilized in diabetes mellitus (DM), and it might be proposed as a potential biomarker candidate for DM, as it is non-invasive and cost-effective and achieves adequate diagnostic performance for DM patients. However, salivary glucose levels may change under specific conditions. It is consequently essential to maintain a consistent strategy for measuring saliva, taking into account the possibility of external factors influencing salivary glucose levels. In this study, we analyzed salivary glucose levels under different handling conditions and donor-dependent factors, including age, interdiurnal variations, and collection and processing methods. A structured questionnaire was used to determine the symptoms and predisposing factors of DM. The glucose oxidase peroxidase method was used to estimate glucose levels in the blood and saliva of people in a fasting state. The aim of this study is to investigate the effect of such conditions on salivary glucose levels. We found that these extraneous variables should be taken into account in the future when salivary glucose is used as a predictive biomarker for DM.

Spatially resolved sampling of the human oral cavity for metabolic profiling

Here, we present a spatially resolved sampling protocol for the oral human cavity aimed at untargeted metabolomics. We describe the spatial collection of salivary biospecimens, their preparation, and subsequent mass-spectrometry-based untargeted metabolomics analysis. Our protocol avoids complex procedures generally required for gland-specific saliva collection. For the human oral cavity, we provide an easy, flexible, and reproducible solution to comprehensively map the highly heterogeneous environment and elucidate the functionality of salivary components. For complete details on the use and execution of this protocol, please refer to Ciurli et al. (2021).

ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the advantages of existing packages, such as venn, RVenn, VennDiagram, and sf. Satisfactory results can be obtained with minimal configurations. Furthermore, we designed comprehensive objects to store the entire data of the Venn diagram, which allowed free access to both intersection values and Venn plot sub-elements, such as set label/edge and region label/filling. Therefore, high customization of every Venn plot sub-element can be fulfilled without increasing the cost of learning when the user is familiar with ggplot2 methods. To date, ggVennDiagram has been cited in more than 10 publications, and its source code repository has been starred by more than 140 GitHub users, suggesting a great potential in applications. The package is an open-source software released under the GPL-3 license, and it is freely available through CRAN (https://cran.r-project.org/package=ggVennDiagram).