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Lane AN, Higashi RM, Fan TWM. Challenges of Spatially Resolved Metabolism in Cancer Research. Metabolites 2024; 14:383. [PMID: 39057706 PMCID: PMC11278851 DOI: 10.3390/metabo14070383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 06/28/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.
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Affiliation(s)
- Andrew N. Lane
- Department of Toxicology and Cancer Biology and Markey Cancer Center, University of Kentucky, 789 S. Limestone St., Lexington, KY 40536, USA; (R.M.H.); (T.W.-M.F.)
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Ciurli A, Mohammed Y, Ammon C, Derks RJ, Olivier-Jimenez D, Ducarmon QR, Slingerland M, Neefjes J, Giera M. Spatially and temporally resolved metabolome of the human oral cavity. iScience 2024; 27:108884. [PMID: 38318352 PMCID: PMC10839270 DOI: 10.1016/j.isci.2024.108884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 12/03/2023] [Accepted: 01/08/2024] [Indexed: 02/07/2024] Open
Abstract
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.
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Affiliation(s)
- Alessio Ciurli
- Oncode Institute and Cell and Chemical Biology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Christine Ammon
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Rico J.E. Derks
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Damien Olivier-Jimenez
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Quinten R. Ducarmon
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Department of Medical Microbiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Marije Slingerland
- Department of Medical Oncology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Jacques Neefjes
- Oncode Institute and Cell and Chemical Biology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
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McAtamney A, Heaney C, Lizama-Chamu I, Sanchez LM. Reducing Mass Confusion over the Microbiome. Anal Chem 2023; 95:16775-16785. [PMID: 37934885 PMCID: PMC10841885 DOI: 10.1021/acs.analchem.3c02408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
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.
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Affiliation(s)
- Allyson McAtamney
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, United States
| | - Casey Heaney
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, United States
| | - Itzel Lizama-Chamu
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, United States
| | - Laura M Sanchez
- Department of Chemistry and Biochemistry, University of California, Santa Cruz, 1156 High Street, Santa Cruz, California 95064, United States
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Cho YD, Cho ES, Song JS, Kim YY, Hwang I, Kim SY. Standard operating procedures for the collection, processing, and storage of oral biospecimens at the Korea Oral Biobank Network. J Periodontal Implant Sci 2023; 53:336-346. [PMID: 36919006 PMCID: PMC10627733 DOI: 10.5051/jpis.2203680184] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 11/02/2022] [Accepted: 12/12/2022] [Indexed: 02/10/2023] Open
Abstract
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.
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Affiliation(s)
- Young-Dan Cho
- Department of Periodontology, School of Dentistry and Dental Research Institute, Seoul National University and Seoul National University Dental Hospital, Seoul, Korea
| | - Eunae Sandra Cho
- Department of Oral Pathology, Oral Cancer Research Institute, Yonsei University College of Dentistry, Seoul, Korea
| | - Je Seon Song
- Department of Pediatric Dentistry, Yonsei University College of Dentistry, Seoul, Korea
| | - Young-Youn Kim
- Department of Oral and Maxillofacial Surgery, Apple Tree Institute of Biomedical Science, Apple Tree Dental Hospital, Seoul, Korea
| | | | - Sun-Young Kim
- Department of Conservative Dentistry, School of Dentistry and Dental Research Institute, Seoul National University and Seoul National University Dental Hospital, Seoul, Korea.
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Cui Y, Zhang H, Wang S, Lu J, He J, Liu L, Liu W. Obtaining a Reliable Diagnostic Biomarker for Diabetes Mellitus by Standardizing Salivary Glucose Measurements. Biomolecules 2022; 12:biom12101335. [PMID: 36291544 PMCID: PMC9599863 DOI: 10.3390/biom12101335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 09/09/2022] [Accepted: 09/19/2022] [Indexed: 11/29/2022] Open
Abstract
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.
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Affiliation(s)
- Yangyang Cui
- Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
| | - Hankun Zhang
- Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
| | - Song Wang
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
- Correspondence: (S.W.); (W.L.); Tel.: +86-0755-26558633 (S.W.); +86-0755-26551376 (W.L.)
| | - Junzhe Lu
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
| | - Jinmei He
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
| | - Lanlan Liu
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
| | - Weiqiang Liu
- Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
- Biomechanics and Biotechnology Laboratory, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China
- Correspondence: (S.W.); (W.L.); Tel.: +86-0755-26558633 (S.W.); +86-0755-26551376 (W.L.)
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Abstract
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).
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Gao CH, Yu G, Cai P. ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram. Front Genet 2021; 12:706907. [PMID: 34557218 PMCID: PMC8452859 DOI: 10.3389/fgene.2021.706907] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Accepted: 08/06/2021] [Indexed: 12/24/2022] Open
Abstract
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).
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Affiliation(s)
- Chun-Hui Gao
- State Key Laboratory of Agricultural Microbiology, State Environmental Protection Key Laboratory of Soil Health and Green Remediation, College of Resources and Environment, Huazhong Agricultural University, Wuhan, China
| | - Guangchuang Yu
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Peng Cai
- State Key Laboratory of Agricultural Microbiology, State Environmental Protection Key Laboratory of Soil Health and Green Remediation, College of Resources and Environment, Huazhong Agricultural University, Wuhan, China
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