Detection of pathogenic bacterium causing bloodstream infection by 16S rDNA gene PCR with a GeXP analyzer
3rd International Congress on Bacteriology and Infectious Diseases
August 04-06, 2015 Valencia, Spain

LU Xue-dong, NIE Shu-ping, Huang Lie, Wang Qiong and W U Run-xiang

Posters-Accepted Abstracts: J Bacteriol Parasitol

Abstract:

Objective: Because bloodstream infections have a high mortality rate, rapid microbiological diagnosis is required to clinical
efficient therapy. To develop a method of fast bacteria identification for pathogens causing bloodstream infection by GeXP
analysis system based on the bacterial highly conserved region of 16S rDNA gene.
Methods: We performed culture and real-time 16S rDNA gene PCR followed by direct sequencing. Clinical amples were
cultured on Columbia blood agar plates were incubated aerobically for 48 hours at 37 °C and Brucella blood agar plates
were incubated under anaerobic conditions for 72 hours at 37 °C. The 16S rDNAgene were amplified using the common
methodology and sequenced with primer 5ʹ-GAGCGGATAACAATTTCACACAGG-3ʹ.
Results: Ten clinical frequent bacterial strains were detected correctly at the species level. Candida albicans, herpes simplex
virus I, II, HBV DNA and the blank control were all negative. The identification concordance was 100% by GeXP analysis
system and conventional culture method at the genus level and it was 87.8% at the species level(36/38. Gram-positive and
Gram-negative bacilli bacteria accounted for 48.9% and 43.8% respectively and fungi for 7.3% in 252 strains isolated from
blood specimens. The most frequent Gram-negative bacilli isolated were Escherichia coli of 66 strains accouting for 26.2%,
Salmonella of 46 strains accouting for 18.3%, Klebsilla pneumoniae of 34 strains accouting for 13.5%. The most frequent grampositive
pathogenic bacteria isolated were Staphylococcus aureus of 31 strains accouting for 12.3% and coagulase negative
Staphylococcus coagulase of 25 strains accouting for 9.9%.
Conclusion: 16S rDNA Gene PCR with a GeXP genetic analysis system could detect blood culture positive sample directly and
it was a fast, accurate method of bacteria identification for pathogens causing bloodstream infection.

Biography :

LU Xue-dong from Department of Clinical Laboratory, Futian Affiliated Hospital of Guang Dong Medical University, China