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Soil microbiome characterization and its future directions with biosensing.

Lexi DeFord1, Jeong-Yeol Yoon2,3

  • 1Department of Biosystems Engineering, The University of Arizona, Tucson, AZ, 85721, USA.

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|September 10, 2024
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Summary

Biosensing offers a faster, field-deployable alternative to traditional next-generation sequencing (NGS) for soil microbiome characterization. This approach overcomes NGS limitations, enabling real-time environmental monitoring and in-situ analysis of soil microbial communities.

Keywords:
AptamerBiosensorMachine learningSoil healthSoil microbiome

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Area of Science:

  • Microbiology
  • Biosensing Technology
  • Environmental Science

Background:

  • Next-generation sequencing (NGS) methods like metabarcoding and meta-omics are standard for soil microbiome characterization but are time-consuming, costly, and lab-bound.
  • Current NGS techniques lack the speed and field applicability required for real-time environmental monitoring or in-situ soil analysis.
  • This necessitates alternative or complementary approaches for efficient and accessible soil microbiome studies.

Discussion:

  • Biosensing technology, proven in biomedical fields, presents a viable solution to overcome NGS limitations in soil microbiome characterization.
  • Aptamer-based biosensors are particularly promising due to their stability and suitability for field deployment.
  • Multiplexed sensors combined with machine learning can handle the complexity of soil microbiomes and large datasets.

Key Insights:

  • Biosensing offers a portable, rapid, and cost-effective method for soil microbiome analysis, complementing traditional NGS techniques.
  • Aptamers provide a stable biorecognition element for robust field-use biosensors.
  • Smartphone integration can facilitate portable optical detection and data analysis for on-site microbiome assessments.

Outlook:

  • The integration of biosensing into soil microbiome research can significantly advance environmental monitoring and in-situ diagnostics.
  • Further development in multiplexed aptasensors and machine learning algorithms will enhance the precision and scope of biosensing applications.
  • This interdisciplinary approach, merging engineering and biology, holds great potential for broader microbiological advancements.