Comparison of oral fluids and pooled pen fecal samples for detection of Lawsonia intracellularis by qPCR using Bayesian latent class analysis
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Updated: Jul 9, 2026

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
Published on: October 23, 2011
Guilherme A Cezar1, Fernando L Leite2, Jana Morgan2
1Department of Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, USA.
Abstract:
This study evaluated the diagnostic performance of oral fluids (OF) and pooled pen fecal (PPF) samples for detecting Lawsonia intracellularis (L. intracellularis) DNA in pigs using quantitative polymerase chain reaction (qPCR) results applied in a Bayesian latent class analysis (BCLA) model. A controlled trial and a field study were conducted. In the laboratory trial, pigs were experimentally inoculated with L. intracellularis, and both OF and fecal samples were collected over time. OF detected the pathogen as early as 7 days post-inoculation, while fecal samples became uniformly positive by day 14, regardless of the number of positive pigs within the pen. In the field study, 161 pens across three commercial sites were sampled. OF and PPF samples were tested by qPCR, and individual fecal samples were collected from 21 pens to estimate within-pen prevalence. BCLA models, assuming conditional independence, estimated OF sensitivity at 98% and PPF at 88%, with non-overlapping 95% posterior probability intervals. Logistic regression showed that detection probability increased with pen prevalence; however, PPF outperformed OF in low-prevalence pens (<10%). A weak correlation (R² = 2.7%) was found between individual fecal and OF genomic copies, which improved to 40.6% when accounting for farm and pen effects. The findings support OF as a highly sensitive, non-invasive diagnostic tool for herd-level surveillance of L. intracellularis, especially in high-prevalence settings. However, PPF sampling may be more effective in low-prevalence scenarios. The study highlights the importance of selecting sample types based on prevalence and reinforces the utility of OF in swine health monitoring.
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