Identification of causative pathogens in eyes with bacterial conjunctivitis by bacterial cell count and microbiota analysis

Rumi Aoki, Kazumasa Fukuda, Midori Ogawa, Takako Ikeno, Hiroyuki Kondo, Akihiko Tawara, Hatsumi Taniguchi

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


Purpose: To determine the causative pathogens in eyes with bacterial conjunctivitis. Design: Evaluation of diagnostic test or technology. Participants: Thirteen eyes diagnosed clinically with bacterial conjunctivitis and 12 eyes with normal conjunctival sac were studied. Methods: The bacterial cell numbers were counted in the samples stained by ethidium bromide (EtBr). The microbiota was determined by the clone library method using polymerase chain reaction (PCR) amplification of the 16S ribosomal RNA (rRNA) gene with universal primers. In addition, examinations of smears and cultures of samples were performed. Main Outcome Measures: Bacterial cell numbers determined by the EtBr staining method and microbiota analysis based on 16S rRNA gene of samples from eyes with bacterial conjunctivitis. Results: The bacterial cell numbers in the eyes with bacterial conjunctivitis were significantly higher than those in the normal conjunctival sacs. Ten of 13 samples from the eyes with bacterial conjunctivitis had positive PCR results. The remaining 3 samples and all 12 samples from the normal conjunctiva had negative PCR results. In 5 of the 10 PCR-positive samples, the predominant species accounted for 84.5% or more of each clone library. In the remaining 5 samples, the predominant and the second dominant species accounted for 27.4% to 56.3% and 19.0% to 26.8%, respectively, of each clone library. The number of detected species in the clone libraries was between 8 and 20 (average ± standard deviation, 7.5±5.8). Bacteria were detected in 8 of the 10 bacterial conjunctivitis samples and in 5 of the 12 normal samples in the cultures. The number of species detected by cultures was 1 in the eyes with bacterial conjunctivitis and between 1 and 3 (mean ± standard deviation, 1.6±0.9) in the normal conjunctiva. Conclusions: These results showed that the bacterial cell number in a sample is a good method of determining bacterial conjunctivitis. The microbiota analysis detected a diverse group of microbiota in the eyes with bacterial conjunctivitis and showed that the causative pathogens could be determined based on percentages of bacterial species in the clone libraries. The combination of bacterial cell count and microbiota analysis is a good method for identifying the causative pathogens in cases of monomicrobial and polymicrobial conjunctivitis. Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Original languageEnglish
Pages (from-to)668-676
Number of pages9
Issue number4
Publication statusPublished - Apr 2013

All Science Journal Classification (ASJC) codes

  • Ophthalmology


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