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Gradient Internal Standard Method for Absolute Quantification of Microbial Amplicon Sequencing Data.

Shilei Wang1, Qun Wu2, Ying Han3

  • 1State Key Laboratory of Food Science and Technology, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu, China.

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High-throughput amplicon sequencing now provides absolute microbiota abundance using the new gradient internal standard absolute quantification (GIS-AQ) method. This reliable and accurate technique enhances microbiological research across diverse ecosystems.

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absolute quantificationinternal standardsmicrobiotasolid-state fermentation

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Area of Science:

  • Microbiology
  • Molecular Biology
  • Bioinformatics

Background:

  • High-throughput amplicon sequencing is crucial for microbiota studies but yields only relative abundance data.
  • Determining absolute microbiota abundance is essential for advancing microbiology research.
  • Existing methods for absolute quantification are often limited or complex.

Purpose of the Study:

  • To develop a novel method for simultaneously quantifying the absolute abundance of bacteria and fungi.
  • To overcome the limitations of relative abundance data in amplicon sequencing.
  • To establish a reliable and accurate method applicable to various ecosystems.

Main Methods:

  • Developed the gradient internal standard absolute quantification (GIS-AQ) method.
  • Implemented calibration to eliminate deviations in quantitative equations.
  • Validated the method against quantitative real-time PCR and microscopy.

Main Results:

  • The GIS-AQ method achieved high reliability (R²average = 0.998) and accuracy.
  • Demonstrated applicability across different amplicon primer sets (e.g., 336F/806R, ITS3/ITS4).
  • Showcased adaptability to diverse sample types, including food, soil, water, and fermentation samples.
  • Revealed discrepancies between relative and absolute abundance in temporal studies of fermentation microbiota.

Conclusions:

  • The GIS-AQ method accurately determines absolute microbiota abundance, complementing relative abundance data.
  • This method offers a rapid and versatile approach for microbiological research in various ecosystems.
  • Combining absolute and relative abundance provides a more comprehensive understanding of microbiota composition and dynamics.