High-throughput sequencing of 16S rDNA amplicons characterizes bacterial composition in bronchoalveolar lavage fluid in patients with ventilator-associated pneumonia.
Ventilator-associated pneumonia (VAP) is a life-threatening disease that is associated with high rates of morbidity and likely mortality, placing a heavy burden on an individual and society. Currently available diagnostic and therapeutic approaches for VAP treatment are limited, and the prognosis of VAP is poor. The present study aimed to reveal and discriminate the identification of the full spectrum of the pathogens in patients with VAP using high-throughput sequencing approach and analyze the species richness and complexity via alpha and beta diversity analysis. The bronchoalveolar lavage fluid samples were collected from 27 patients with VAP in intensive care unit. The polymerase chain reaction products of the hypervariable regions of 16S rDNA gene in these 27 samples of VAP were sequenced using the 454 GS FLX system. A total of 103,856 pyrosequencing reads and 638 operational taxonomic units were obtained from these 27 samples. There were four dominant phyla, including Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. There were 90 different genera, of which 12 genera occurred in over ten different samples. The top five dominant genera were Streptococcus, Acinetobacter, Limnohabitans, Neisseria, and Corynebacterium, and the most widely distributed genera were Streptococcus, Limnohabitans, and Acinetobacter in these 27 samples. Of note, the mixed profile of causative pathogens was observed. Taken together, the results show that the high-throughput sequencing approach facilitates the characterization of the pathogens in bronchoalveolar lavage fluid samples and the determination of the profile for bacteria in the bronchoalveolar lavage fluid samples of the patients with VAP. This study can provide useful information of pathogens in VAP and assist clinicians to make rational and effective therapeutic decisions.
Department of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Xiao-Jun
XJ
Yang
Neurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China ; Key Laboratory of Brain Diseases of Ningxia, Yinchuan, Ningxia, People's Republic of China.
Yan-Bo
YB
Wang
Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
Zhi-Wei
ZW
Zhou
Neurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Guo-Wei
GW
Wang
Department of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Xiao-Hong
XH
Wang
Department of Intensive Care Unit, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China.
Qing-Fu
QF
Liu
Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
Shu-Feng
SF
Zhou
Neurology Center, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People's Republic of China ; Key Laboratory of Brain Diseases of Ningxia, Yinchuan, Ningxia, People's Republic of China.
Zhen-Hai
ZH
Wang
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D001992:Bronchoalveolar Lavage Fluid / Q000382:microbiology*; D019295:Computational Biology; D004269:DNA, Bacterial / Q000187:drug effects / Q000235:genetics*; D024881:Drug Resistance, Bacterial / Q000235:genetics; D005260:Female; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008297:Male; D008875:Middle Aged; D010802:Phylogeny; D053717:Pneumonia, Ventilator-Associated / Q000175:diagnosis / Q000188:drug therapy / Q000382:microbiology*; D016133:Polymerase Chain Reaction; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D021521:Ribotyping / Q000379:methods*
D000900:Anti-Bacterial Agents; D004269:DNA, Bacterial; D012336:RNA, Ribosomal, 16S
DNA sequencing; OTU; PCR; bioinformatics; drug resistance