Microbial source tracking using metagenomics and other new technologies

Shahbaz Raza; Jungman Kim; Michael J. Sadowsky; Tatsuya Unno

doi:10.1007/s12275-021-0668-9

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Microbial source tracking using metagenomics and other new technologies: Shahbaz Raza ¹, Jungman Kim ², Michael J. Sadowsky ^3,4, Tatsuya Unno ¹; Journal of Microbiology 2021;59(3):259-269.
DOI: https://doi.org/10.1007/s12275-021-0668-9
Published online: February 10, 2021

¹Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University, Jeju 63243, Republic of Korea, ²Research Institute for Basic Sciences (RIBS), Jeju National University, Jeju 63243, Republic of Korea, ³BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, USA, ⁴Department of Soil, Water & Climate, and Department of Microbial and Plant Biology, University of Minnesota, St. Paul, Minnesota 55108, USA¹Faculty of Biotechnology, College of Applied Life Sciences, SARI, Jeju National University, Jeju 63243, Republic of Korea, ²Research Institute for Basic Sciences (RIBS), Jeju National University, Jeju 63243, Republic of Korea, ³BioTechnology Institute, University of Minnesota, St. Paul, Minnesota 55108, USA, ⁴Department of Soil, Water & Climate, and Department of Microbial and Plant Biology, University of Minnesota, St. Paul, Minnesota 55108, USA

Corresponding author: Tatsuya Unno , Tel: +82-64-754-3354;,

Received: 18 December 2020 • Revised: 8 January 2021 • Accepted: 8 January 2021

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Abstract

The environment is under siege from a variety of pollution sources. Fecal pollution is especially harmful as it disperses pathogenic bacteria into waterways. Unraveling origins of mixed sources of fecal bacteria is difficult and microbial source tracking (MST) in complex environments is still a daunting task. Despite the challenges, the need for answers far outweighs the difficulties experienced. Advancements in qPCR and next generation sequencing (NGS) technologies have shifted the traditional culture-based MST approaches towards culture independent technologies, where communitybased MST is becoming a method of choice. Metagenomic tools may be useful to overcome some of the limitations of community-based MST methods as they can give deep insight into identifying host specific fecal markers and their association with different environments. Adoption of machine learning (ML) algorithms, along with the metagenomic based MST approaches, will also provide a statistically robust and automated platform. To compliment that, ML-based approaches provide accurate optimization of resources. With the successful application of ML based models in disease prediction, outbreak investigation and medicine prescription, it would be possible that these methods would serve as a better surrogate of traditional MST approaches in future.

Keywords: COVID-19;Candida albicans;Coumarin;MD simulation;QSAR modelling;docking

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Microbial source tracking using metagenomics and other new technologies

J. Microbiol. 2021;59(3):259-269. Published online February 10, 2021

DOI: https://doi.org/10.1007/s12275-021-0668-9

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