ArticleDiagnostic microbiology and infectious disease2010
Development of a microarray for identification of pathogenic Clostridium spp.
Article in Diagnostic microbiology and infectious disease, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic Accuracy of Nucleic Acid Amplification-Based Assays for Clostridium perfringens-Associated Diseases: a Systematic Review and Meta-analysis.Journal of clinical microbiology · 2020Pooled it
- Prevalence and antimicrobial resistance patterns ofOne health (Amsterdam, Netherlands) · 2025Article
- The human gut resistome.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Review
- Transcriptional profiling of Clostridium difficile and Caco-2 cells during infection.The Journal of infectious diseases · 2010Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In recent years, Clostridium spp. have rapidly reemerged as human and animal pathogens. The detection and identification of pathogenic Clostridium spp. is therefore critical for clinical diagnosis and antimicrobial therapy. Traditional diagnostic techniques for clostridia are laborious, are time consuming, and may adversely affect the therapeutic outcome. In this study, we developed an oligonucleotide diagnostic microarray for pathogenic Clostridium spp. The microarray specificity was tested against 65 Clostridium isolates. The applicability of this microarray in a clinical setting was assessed with the use of mock stool samples. The microarray was successful in discriminating at least 4 species with the limit of detection as low as 10(4) CFU/mL. In addition, the pattern of virulence and antibiotic resistance genes of tested strains were determined through the microarrays. This approach demonstrates the high-throughput detection and identification of Clostridium spp. and provides advantages over traditional methods. Microarray-based techniques are promising applications for clinical diagnosis and epidemiologic investigations.
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