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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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Related Experiment Video

Updated: Jun 9, 2026

Cost-effective Method for Microbial Source Tracking Using Specific Human and Animal Viruses
11:29

Cost-effective Method for Microbial Source Tracking Using Specific Human and Animal Viruses

Published on: December 3, 2011

Estimating true human and animal host source contribution in quantitative microbial source tracking using the Monte

Dan Wang1, Sarah S Silkie, Kara L Nelson

  • 1Department of Civil & Environmental Engineering, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA.

Water Research
|September 9, 2010
PubMed
Summary

This study introduces a statistical model to correct false positives and negatives in quantitative PCR (qPCR) assays for microbial source tracking. The model improves the accuracy of host-specific genetic marker concentration estimates in environmental monitoring.

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Last Updated: Jun 9, 2026

Cost-effective Method for Microbial Source Tracking Using Specific Human and Animal Viruses
11:29

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Published on: December 3, 2011

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
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Published on: August 25, 2018

Area of Science:

  • Environmental microbiology
  • Molecular biology
  • Statistical modeling

Background:

  • Quantitative PCR (qPCR) is crucial for microbial source tracking but suffers from false positives/negatives.
  • Accurate estimation of host-specific genetic markers is vital for environmental studies.

Purpose of the Study:

  • To develop a statistical model correcting qPCR inaccuracies for precise microbial source tracking.
  • To estimate the true concentration of host-specific genetic markers.

Main Methods:

  • A statistical model based on the Law of Total Probability was developed.
  • Probabilities of false information were estimated from fecal samples.
  • Monte Carlo methods were used with qPCR precision error data.

Main Results:

  • The model successfully corrected false information in qPCR assays.
  • It provided accurate distributions of true Bacteroidales concentrations for different animal hosts.
  • Model performance was highly dependent on the precision error of the assay.

Conclusions:

  • The proposed statistical model enhances the reliability of microbial source tracking using qPCR.
  • Improving assay precision is key to maximizing the model's effectiveness.
  • This methodology is adaptable to other microbial indicators.