Beyond Serology: A Meta-Analysis of Advancements in Molecular Detection of Brucella spp. in Seronegative Animals and Biological Samples
Abstract
Background: Brucellosis is a zoonotic disease caused by Brucella spp., affecting various animals and humans, leading to significant economic and public health impacts. Traditional diagnostic methods, mainly serological, often fail to detect seronegative carriers, which continue to spread the infection.
Objective: This review aims to highlight advancements in molecular diagnostics that address these limitations.
Methods: A systematic search of PubMed, Web of Science and Scopus was conducted, focusing on studies using seronegative, PCR, qPCR and biosensor-based techniques. Data extraction and meta-analyses were performed, evaluating pooled detection rates and heterogeneity.
Results: Through analysis of existing studies, we review key molecular techniques, including PCR, LAMP and biosensor-based assays, which offer high sensitivity and specificity by detecting bacterial DNA directly, thus overcoming the challenges of antibody-based tests. Meta-analysis of detection rates across different studies showed significant variability, with rates ranging from 0.96% to 100%, highlighting differences in sample types, animal species and regions. The pooled detection proportion from random-effects models was 35.08%, indicating that many seronegative animals still carry Brucella spp. A forest plot analysis further confirmed heterogeneity in detection, underlining the importance of using molecular diagnostics alongside serological tests to identify hidden carriers.
Conclusion: Innovations…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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