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Related Concept Videos

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

527
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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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Integrating Bayesian Analysis and Cumulative Probability Generates High Confidence Using a Single Microbial Source

Kyle Curtis1, Raul A Gonzalez1

  • 1Hampton Roads Sanitation District , 1434 Air Rail Blvd , Virginia Beach , Virginia 23455 , United States.

Environmental Science & Technology
|November 5, 2019
PubMed
Summary
This summary is machine-generated.

Microbial source tracking uses molecular markers to detect fecal contamination. Applying Bayes' Theorem with multiple markers and samples significantly increases confidence in identifying human waste in waterbodies.

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Area of Science:

  • Environmental microbiology
  • Molecular biology
  • Water quality assessment

Background:

  • Microbial source tracking (MST) is crucial for identifying fecal contamination in waterbodies.
  • Existing MST assays lack both perfect host specificity and sensitivity for human or animal waste.
  • Host-associated molecular markers are key tools in MST.

Purpose of the Study:

  • To apply Bayes' Theorem to assess the reliability of the HF183 human fecal-associated marker in MST.
  • To evaluate the impact of marker specificity and sensitivity on contamination detection.
  • To determine the confidence levels achievable with concurrent marker use and multiple sampling.

Main Methods:

  • Bayes' Theorem was used with literature-derived sensitivity and specificity values for the HF183 marker.
  • Type I and Type II error rates were analyzed across various prior probabilities.
  • Conditional probabilities were calculated for concurrent use of HF183 and HumM2 markers.
  • Cumulative probability analysis was performed using multiple samples to assess detection likelihood.

Main Results:

  • Marker specificity and sensitivity values directly influence the accuracy of true positive and true negative results.
  • Concurrent use of HF183 and HumM2 markers, with practical priors, achieved 99% confidence in results.
  • Cumulative probability analysis demonstrated that multiple samples (>95% confidence) can yield reliable positive and negative results.

Conclusions:

  • Bayes' Theorem provides a robust framework for improving the reliability of MST.
  • Concurrent use of multiple human fecal markers enhances confidence in identifying contamination sources.
  • Multiple sampling events at a single site can compensate for in situ variability and ensure accurate MST results, even with a single marker.