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Modern Molecular Taxonomy01:29

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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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Developing diagnostic tools for canine periodontitis: combining molecular techniques and machine learning models.

Avika Ruparell1, Matthew Gibbs2, Alison Colyer2

  • 1Waltham Petcare Science Institute, Melton Mowbray, Leicestershire, UK. Avika.Ruparell@effem.com.

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|September 18, 2023
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Summary
This summary is machine-generated.

Quantitative polymerase chain reaction (qPCR) can detect microbial biomarkers for canine periodontal disease. This molecular technique offers a cost-effective and accurate diagnostic tool for veterinary oral health checks.

Keywords:
BiomarkersCanineDiagnosisMicrobiomeMicrobiotaPeriodontal diseasePeriodontitisQuantitative polymerase chain reactionqPCR

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Area of Science:

  • Veterinary microbiology
  • Molecular diagnostics
  • Canine health

Background:

  • Dental plaque microbes are crucial in canine periodontal disease development.
  • High-throughput sequencing has identified bacterial species linked to canine periodontal health and disease.
  • Molecular techniques offer opportunities to improve diagnosis during veterinary oral health assessments.

Purpose of the Study:

  • To develop and validate quantitative polymerase chain reaction (qPCR) assays for detecting microbial biomarkers associated with canine periodontal health and disease.
  • To assess the utility of qPCR for quantifying specific bacterial taxa in canine subgingival plaque.
  • To evaluate the correlation between qPCR data and high-throughput sequencing results.

Main Methods:

  • Developed and validated over 40 qPCR assays targeting specific microbial species.
  • Quantified bacterial taxa levels in canine subgingival plaque samples from healthy, gingivitis, and early periodontitis states (PD0, PD1, PD2).
  • Compared qPCR outputs with high-throughput sequencing data and applied machine learning models.

Main Results:

  • Strong correlations were observed between qPCR and high-throughput sequencing for key taxa, including Capnocytophaga sp. COT-339 (rs=0.805), Peptostreptococcaceae XI [G-4] sp. COT-019 (rs=0.902), and Clostridiales sp. COT-028 (rs=0.802).
  • Machine learning models demonstrated promising diagnostic capabilities, with the best models achieving up to 85.7% sensitivity and 80.0% specificity for certain taxa.
  • qPCR assays accurately quantified microbial biomarkers across different stages of periodontal health and disease.

Conclusions:

  • Quantitative polymerase chain reaction (qPCR) provides an accurate, sensitive, and cost-effective method for detecting microbial biomarkers in canine periodontal disease.
  • The strong correlation with high-throughput sequencing and initial accuracy data suggest qPCR is a viable strategy for developing diagnostic tools.
  • This approach holds prospective value for improving the diagnosis and management of periodontal disease in dogs.