Limits...
Analysis of the bacterial community in chronic obstructive pulmonary disease sputum samples by denaturing gradient gel electrophoresis and real-time PCR.

Wu D, Hou C, Li Y, Zhao Z, Liu J, Lu X, Shang X, Xin Y - BMC Pulm Med (2014)

Bottom Line: Real-time PCR was further utilized to quantitatively analyze the subpopulation of microbiota using group-specific primers targeting Streptococcus pneumoniae, Klebsiella pneumoniae, Pseudomonas aeruginosa.Real-time PCR revealed significant increases of Streptococcus pneumoniae, Klebsiella pneumoniae and Pseudomonas aeruginosa (P < 0.05) in the COPD group compared with the healthy group.By determining the content of several types of bacteria, we can provide evidence to aid in the diagnosis and treatment of COPD.

View Article: PubMed Central - PubMed

Affiliation: Biotechnology Department, Dalian Medical University, 9 Western Section, Lvshun South Street, Dalian, P,R, China. jimxin0295@163.com.

ABSTRACT

Background: The Global Initiative defines COPD for chronic obstructive lung disease as an entirely preventable and treatable disease characterized by sputum production, bacterial colonisation, neutrophilic bronchial airway inflammation and poor health status. The World Health Organization (WHO) estimates that COPD will become the fourth-most common cause of death worldwide, just behind ischemic heart disease, cerebrovascular disease and HIV/AIDS, by 2030. The aim of this study was to determine the main structure feature of sputum potentially pathogenic microorganisms in subjects with COPD during the clinical stable state.

Methods: We employed a molecular genetics-based investigation of the bacteria community, including DNA isolation, PCR amplification and DGGE profiling. PCR-denaturing gradient gel electrophoresis (DGGE) with universal primers targeting the V3 region of the 16S rRNA gene was employed to characterize the overall COPD patient sputum microbiota composition, and some excised gel bands were cloned for sequencing. Real-time PCR was further utilized to quantitatively analyze the subpopulation of microbiota using group-specific primers targeting Streptococcus pneumoniae, Klebsiella pneumoniae, Pseudomonas aeruginosa.

Results: The DGGE profiles of two groups displayed significant differences between COPD and healthy groups (P < 0.05). Real-time PCR revealed significant increases of Streptococcus pneumoniae, Klebsiella pneumoniae and Pseudomonas aeruginosa (P < 0.05) in the COPD group compared with the healthy group.

Conclusion: This study revealed strong relationship between alterations of sputum microbiota and COPD. By determining the content of several types of bacteria, we can provide evidence to aid in the diagnosis and treatment of COPD.

No MeSH data available.


Related in: MedlinePlus

Dendrogram of DGGE profiles analyzed by UPGMA method(COPD group:lane 4–10;healthy group:lane 1–3).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4273488&req=5

Fig2: Dendrogram of DGGE profiles analyzed by UPGMA method(COPD group:lane 4–10;healthy group:lane 1–3).

Mentions: The dominant respiratory microbiota of the COPD and healthy group were show in Figure 1. Lanes 4–10 were samples from the COPD group, whereas lane 1–3 represented those from the healthy individuals. The diversity of respiratory microbiota from two groups was analyzed with the Mann–Whitney U test to compare the Shannon–Weaver indexes of diversity (H’) of the bands from DGGE profile. It was clearly demonstrated that the diversity in the COPD groups significantly increased compared with healthy groups (P < 0.05). The number of bands was richer in the COPD group with a P value of 0.002 by the Mann–Whitney U test. The dendrogram was constructed based on analysis of similarity score and cluster from DGGE profiles by Phoretix 1D software (Figure 2). Two groups formed significant clustering profiles. There were two main clusters in the dendrogram. One was lane 1–3, related to the healthy group, and the other was lane 4–10 involved in the COPD group. The average number of bands, H’ and evenness (E) between the two groups was listed in Table 2. Overall, the respiratory microbiota communities from the COPD group had their own characteristics that were different from those of the healthy group.Figure 1


Analysis of the bacterial community in chronic obstructive pulmonary disease sputum samples by denaturing gradient gel electrophoresis and real-time PCR.

Wu D, Hou C, Li Y, Zhao Z, Liu J, Lu X, Shang X, Xin Y - BMC Pulm Med (2014)

Dendrogram of DGGE profiles analyzed by UPGMA method(COPD group:lane 4–10;healthy group:lane 1–3).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4273488&req=5

Fig2: Dendrogram of DGGE profiles analyzed by UPGMA method(COPD group:lane 4–10;healthy group:lane 1–3).
Mentions: The dominant respiratory microbiota of the COPD and healthy group were show in Figure 1. Lanes 4–10 were samples from the COPD group, whereas lane 1–3 represented those from the healthy individuals. The diversity of respiratory microbiota from two groups was analyzed with the Mann–Whitney U test to compare the Shannon–Weaver indexes of diversity (H’) of the bands from DGGE profile. It was clearly demonstrated that the diversity in the COPD groups significantly increased compared with healthy groups (P < 0.05). The number of bands was richer in the COPD group with a P value of 0.002 by the Mann–Whitney U test. The dendrogram was constructed based on analysis of similarity score and cluster from DGGE profiles by Phoretix 1D software (Figure 2). Two groups formed significant clustering profiles. There were two main clusters in the dendrogram. One was lane 1–3, related to the healthy group, and the other was lane 4–10 involved in the COPD group. The average number of bands, H’ and evenness (E) between the two groups was listed in Table 2. Overall, the respiratory microbiota communities from the COPD group had their own characteristics that were different from those of the healthy group.Figure 1

Bottom Line: Real-time PCR was further utilized to quantitatively analyze the subpopulation of microbiota using group-specific primers targeting Streptococcus pneumoniae, Klebsiella pneumoniae, Pseudomonas aeruginosa.Real-time PCR revealed significant increases of Streptococcus pneumoniae, Klebsiella pneumoniae and Pseudomonas aeruginosa (P < 0.05) in the COPD group compared with the healthy group.By determining the content of several types of bacteria, we can provide evidence to aid in the diagnosis and treatment of COPD.

View Article: PubMed Central - PubMed

Affiliation: Biotechnology Department, Dalian Medical University, 9 Western Section, Lvshun South Street, Dalian, P,R, China. jimxin0295@163.com.

ABSTRACT

Background: The Global Initiative defines COPD for chronic obstructive lung disease as an entirely preventable and treatable disease characterized by sputum production, bacterial colonisation, neutrophilic bronchial airway inflammation and poor health status. The World Health Organization (WHO) estimates that COPD will become the fourth-most common cause of death worldwide, just behind ischemic heart disease, cerebrovascular disease and HIV/AIDS, by 2030. The aim of this study was to determine the main structure feature of sputum potentially pathogenic microorganisms in subjects with COPD during the clinical stable state.

Methods: We employed a molecular genetics-based investigation of the bacteria community, including DNA isolation, PCR amplification and DGGE profiling. PCR-denaturing gradient gel electrophoresis (DGGE) with universal primers targeting the V3 region of the 16S rRNA gene was employed to characterize the overall COPD patient sputum microbiota composition, and some excised gel bands were cloned for sequencing. Real-time PCR was further utilized to quantitatively analyze the subpopulation of microbiota using group-specific primers targeting Streptococcus pneumoniae, Klebsiella pneumoniae, Pseudomonas aeruginosa.

Results: The DGGE profiles of two groups displayed significant differences between COPD and healthy groups (P < 0.05). Real-time PCR revealed significant increases of Streptococcus pneumoniae, Klebsiella pneumoniae and Pseudomonas aeruginosa (P < 0.05) in the COPD group compared with the healthy group.

Conclusion: This study revealed strong relationship between alterations of sputum microbiota and COPD. By determining the content of several types of bacteria, we can provide evidence to aid in the diagnosis and treatment of COPD.

No MeSH data available.


Related in: MedlinePlus