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Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics.

Biswapriya B Misra1,2

  • 1Center for Precision Medicine, Section of Molecular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA. bbmisraccb@gmail.com.

Methods in Molecular Biology (Clifton, N.J.)
|October 1, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a workflow for single-cell metabolomics, enabling detailed analysis of cellular metabolism. It addresses challenges in handling and interpreting complex -omics data for biomedical insights.

Keywords:
AnalysisAnimalCellComputationalDataDatabaseMass spectrometryMetabolomicsMicrobialNetworkPathwayPlantSingle cellSingle-cell typeSoftwareStatisticalToolWeb server–Omics

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Area of Science:

  • Biochemistry
  • Cell Biology
  • Analytical Chemistry

Background:

  • Metabolomics offers phenotype insights, crucial for understanding cellular processes.
  • Cell-specific resolution is vital for biomedical applications, yet challenging to achieve.
  • Mass spectrometry (MS) is a powerful tool for analyzing diverse metabolites with high performance.

Purpose of the Study:

  • To present a comprehensive workflow for single-cell and single-cell-type metabolomics.
  • To facilitate the analysis, visualization, and interpretation of complex metabolomic data.
  • To enable granular understanding of cellular metabolism for biomedical research.

Main Methods:

  • Utilizing advanced mass spectrometry (MS) and spectroscopy platforms.
  • Generating high-throughput data sets from single cells.
  • Developing a workflow for data handling, processing, analysis, and interpretation.

Main Results:

  • A practical workflow for single-cell metabolomics data generation is established.
  • The workflow enables detailed analysis from data acquisition to biological insight.
  • Challenges in routine handling and interpretation of single-cell metabolomics data are addressed.

Conclusions:

  • Single-cell metabolomics provides critical resolution for understanding cellular metabolism.
  • The presented workflow streamlines the process of generating and interpreting single-cell metabolomic data.
  • This approach holds significant promise for advancing biomedical applications through detailed cellular insights.