Background
Progressive and irreversible airflow obstruction are characteristics of chronic obstructive pulmonary disease (COPD), which are caused by chronic inflammation of airways [
1]. COPD is a major cause of morbidity and mortality worldwide and is projected to become the third leading cause of death by 2030 [
2]. The major therapeutic goal of COPD treatment is to prevent acute exacerbations. However, available treatments for acute exacerbations of COPD (AECOPD) are currently not very effective [
3]. Bacterial infections of the lower respiratory tract are believed to play a major role in the pathogenesis of AECOPD. Generally, nontypeable
Haemophilus influenzae,
Streptococcus pneumoniae, and to a lesser extent,
Moraxella catarrhalis are the most frequent species isolated by microbiological culture during COPD exacerbations [
4]. These organisms can often be found colonizing the airways of COPD patients between exacerbations [
5]. Since many of these bacteria persist in the airways of COPD patients, their presence may promote chronic inflammatory states that drives COPD pathogenesis. However, information on the quantitative analysis of bacterial burden in the lower respiratory tract in stable COPD and AECOPD patients are quite limited. Previous studies frequently analyzed bacteria in the respiratory tract of patients by traditional microbiological culture techniques. However, the current microbiological gold standard has a number of limitations, particularly the lack of sensitivity and time-consuming culture; which significantly impacts the treatment and management of patients, and limits our understanding of the development and progression of COPD [
4]. Furthermore, bacterial cultures can lead to false-negative results, especially during concurrent antibiotic treatment. A challenge in COPD diagnostics is to distinguish disease-causing strains from colonizing strains. It has been shown that for
Streptococcus pneumoniae [
6], the load of many types of bacteria in the respiratory tract is probably greater during infection than during carriage; and therefore, quantitative methods would most likely improve diagnostic quality.
In recent years, real-time quantitative PCR (RT-qPCR) has emerged as a valuable tool for the quantitative and rapid detection of various biological specimens in body fluids [
7,
8]. Guma
et al. developed a RT-qPCR method using primers and a TaqMan probe complementary to sequences in the omp P6 gene for rapid detection of
Haemophilus influenzeae, and their study concluded that P6 RT-qPCR is both sensitive and specific for identifying
Haemophilus influenzeae in respiratory secretions [
9]. In another study, the prevelance of
Moraxella catarrhalis was detected by RT-qPCR using primers and probes targeting the copB gene, which provided a sensitive and reliable means of rapidly detecting and quantifying
Moraxella catarrhalis during lower respiratory tract infections; and this may be applied to other clinical samples [
10]. In addition, some other common pathogenic bacteria in respiratory tract infections such as
Klebsiella pneumoniae [
11],
Staphylococcus aureus [
12],
Streptococcus pneumoniae [
13], and
Pseudomonos aeruginosa [
14] were detected by RT-qPCR, targeting bacteria-specific genes. These methods present sensitive and reliable means of rapidly detecting and quantifying microorganisms. The load of common bacteria in the respiratory tract of patients with COPD or lower respiratory tract infection was analyzed by RT-qPCR or multiplex PCR in sputum samples [
4,
15]
. In another study, the spectrum of potentially pathogenic microorganisms in sputum of COPD patients was determined by PCR-denaturing gradient gel electrophoresis (DGGE) [
16]. However, most of these previous studies focused on the respiratory tract microbiome of COPD patients in the stable stage [
17], and only few studies compared common bacteria between the stable stage and acute exacerbations of COPD. Furthermore, most of the studied samples were sputum or bronchoalveolar lavage fluid (BALF) samples, in which contamination by pathogens colonizing the upper respiratory tract are difficult to avoid. Therefore, proper collection of samples from the lower respiratory tract is a key for the precise quantitative analysis of pathogens. The usefulness of a protected specimen brush (PSB) for diagnosing respiratory infections has been reported earlier [
18‐
20]. The tip of the sampling brush or PSB is covered by a sheath to avoid contamination by organisms in the upper tract while the brush is being inserted or pulled out [
21]. Thus, PSB or protected BALF from bronchoscopy appears as the best choice for sample collection from the lower respiratory tract in COPD patients.
In this present study, we describe the application of RT-qPCR in tageting specific bacterial pathogen genes for the simultaneous and direct detection and quantification of a range of the most common pathogens in the lower respiratory tract including Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonos aeruginosa, Haemophilus influenzeae, and Moraxella catarrhalis in PSB and BALF samples obtained from stable COPD and AECOPD patients. Moreover, we explored the relationship among bacterial burden, inflammtory response such as neurotophil count and cytokine levels of IL-1β, IL-6 and IL-8 in BALF, and the forced expiratory volume in one second (FEV1) % predicted, forced vital capacity (FVC) % predicted, and FEV1/FVC lung function values in COPD patients. Our study is the first to describe common bacteria in the lower respiratory tract by RT-qPCR analysis using PSB and protected BALF samples, and compare the change of bacterial load between the stable stage and acute exacerbations of COPD. These results may provide guidance for the effective and timely antibiotic treatment of AECOPD patients.
Materials and Methods
Study subjects
Sixty-six COPD patients (GOLD stage II-III, COPD group) and 33 healthy subjects (HS group) with normal pulmonary function (non-smokers) were enrolled in this case–control study, which was carried out at the Department of Respiratory Diseases, Affiliated Yinzhou Hospital, College of Medicine, Ningbo University, China. COPD was diagnosed according to the patient’s history of tobacco smoking, symptoms, and post-bronchodilator pulmonary function tests with FEV1/FVC lower than 70 %, according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines [
22]. All patients were clinically assessed including chest radiography, temperature recording and blood gas analysis (as needed) to exclude other causes of breathlessness. Moreover, patients in the COPD group were further divided into two subgroups according to disease stage: stable COPD group and AECOPD group. The stable COPD group consisted of 34 patients who were evaluated as clinically stable and underwent an exacerbation-free period of six weeks. Patients in the stable COPD and HS groups were examined by bronchoscopy to exclude other lung lesions. The AECOPD group consisted of 32 patients who were identified according to the Anthonisen criteria [
23] and the consensus definition for COPD exacerbations [
24]. Patients in the AECOPD group were diagnosed according to pulmonary function and underwent mechanical ventilation via tracheal tubing to treat type-II respiratory failure. Bronchoscope examinations were guided by a tracheal tube. All subjects enrolled in this study underwent routine blood examination. Patients that presented with pneumonia, neuromuscular diseases, thoracic deformities, restrictive lung diseases, pulmonary vascular disease, as well as patients who underwent lung resection, were excluded from this study. Two hours after tracheal tube intubation and before antibiotic treatment, lower respiratory tract samples were collected by a protected specimen brush (PSB) and protected bronchoalveolar lavage (BAL) during bronchoscopy. This study protocol was authorized by the ethics and research committee of the Affiliated Yinzhou Hospital, College of Medicine, Ningbo University, China. Signed informed consent was obtained from all subjects.
Collection of PSB and BALF samples from patients
PSB samples were collected with a sheath brush (Olympus BC-5 CE, Olympus Imaging, Center Valley, PA, USA) with a distal occlusion composed of polyethylene glycerol through a flexible bronchoscope (Olympus, BF-260). The brush was pushed out of the sheath, cut with ethanol-disinfected scissors, and placed in an Eppendorf tube containing 1.5 ml of saline solution. A part of the PSB samples (0.5 ml) were used for standard bacterial cultures and remaining samples were prepared for total DNA extraction. Simultaneously with PSB sample collection, BAL specimens were obtained by lavaging the airway with approximately 50 ml of 0.9 % NaCl solution through the bronchoscope; and approximately 60 % lavage return volume was collected. Total BALF cells were counted from a 0.05 ml aliquot, 0.5 ml of BALF samples were used for bacterial cultures, and 1 ml of BALF samples were taken for total DNA extraction. Remaining fluid samples were centrifuged (1,000 g for 10 min) at 4 °C, and the supernatant was stored at −80 °C for subsequent cytokine analysis by ELISA. The remaining cell pellets were resuspended with 0.9 % NaCl solution, and a differential cell count was performed using cytospin and Wright-Giemsa staining.
Bacterial cultures
PSB and BALF samples were inoculated into Eosin methylene blue agar, Brucella agar, blood agar, and chocolate agar media (Biomérieux, Marcy l'Etoile. France); and incubated for 24–48 h at 37 °C. Colony identification was performed using the Vitek 2 Compact full automatic identification system (Biomérieux, France). For PSB and BALF cultures, after 24 h of incubation, bacterial colonies with growth of ≥103 and ≥105, respectively, were considered as pathogenic.
Cytokine ELISA
IL-1β, IL-6, IL-8, IL-10 and TNF-α cytokine concentrations in BALF supernatants were measured by standardized sandwich ELISA (eBioscience, San Diego, CA, USA) according to manufacturer’s protocols.
Preparation of bacterial DNA from PSB and BALF samples
PSB or BALF samples (1 ml) were centrifuged at 11,000 g for five minutes. Aliquots of 0.2 ml of the pellet were used in order to obtain a 5-fold concentration of the samples. DNA was prepared using a Qiagen DNA Mini Kit (Qiagen, Hilden, Germany) according to manufacturer’s instructions. DNA was stored at −20 °C before amplification by RT-qPCR. In each experiment, a negative control that contained all reagents except the PSB sample was included.
RT- qPCR of PSB and BALF samples
Primers and TaqMan probes for the specific amplification of
Staphylococcus aureus,
Klebsiella pneumoniae,
Streptococcus pneumoniae,
Pseudomonos aeruginosa,
Haemophilus influenzeae and
Moraxella catarrhalis were synthesized by Sangon Biotech Co., Ltd. (Shanghai, P.R. China). Primer sequences and assay performance are summarized in Table
1. DNA amplification and detection were performed with a TaqMan 7500 Fast system (Applied Biosystems, Foster City, CA, USA). The reaction mixture (20 μl) used in the PCR assay was as follows: 10 μl of TaqMan Universal PCR Mastermix (Applied Biosystems), 2 μl of extracted DNA, 0.5 μl of specific primers (final concentration was 0.6 μmol/l), and probes (final concentration was 0.3 μmol/l). PCR cycling conditions applied for khe, cps, omp P6, and copB gene assays were as follows: heating at 94 °C for four minutes, followed by 40 cycles of 94 °C for 30 s and 60 °C for one minute. PCR cycling conditions applied for egc and gyrB gene assays were as follows: heating at 95 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for one minute. Optimized conditions of the RT-qPCR assay are summarized in Table
2. Fluorescence was measured after each cycle, and each assay was carried out in duplicate. Two negative RT-qPCR controls were run on each sample plate, and the median cycle of quantification (Cq) value from each duplicate was used for analysis.
Table 1
RT-qPCR primers and assay performance summary
Staphylococcus aureus
|
egc
| F:5′-CTTCATATGTGTTAAGTCTTGCAGCTT-3′ | R2 = 0.995 | |
R:5′-TTCACTCGCTTTATTCAATTGTTCTG-3′ | Slope = −3.91 |
P: 5′-6-FAM -ATGTTAAATGGCAATCCT-TAMRA -3′ | Efficiency = 1.04 |
Klebsiella pneumoniae
|
khe
| F: 5′-GATGAAACGACCTGATTGCATTC-3′ | R2 = 0.997 | |
R: 5′-CCGGGCTGTCGGGATAAG-3′ | Slope = −3.60 |
P:5′-6-FAM-CGCGAACTGGAAGGGCCCG-TAMRA-3′ | Efficiency = 1.07 |
Streptococcus pneumoniae
|
cps
| F: 5′-GCTGTTTTAGCAGATAGTGAGATCGA-3′ | R2 = 0.995 | |
R: 5′-TCCCAGTCGGTGCTGTCA-3′ | Slope = −3.11 |
P: 5′-6-FAM-AATGTTACGCAACTGACGAG-TAMRA -3′ | Efficiency = 1.12 |
Pseudomonos aeruginosa
|
gyrB
| F: 5′-GGCGTGGGTGTGGAAGTC-3′ | R2 = 0.995 | |
R: 5′-TGGTGGCGATCTTGAACTTCTT-3′ | Slope = −3.55 |
P: 5′-6-FAM-TGCAGTGGAACGACA-TAMRA-3′ | Efficiency = 0.96 |
Haemophilus influenzeae
|
omp P6
| F:5′-CCAGCTGCTAAAGTATTAGTAGAAG-3′ | R2 = 0.997 | |
R: 5′-TTCACCGTAAGATACTGTGCC-3′ | Slope = −4.22 |
P: 5′-6-FAM -CAGATGCAGTTGAAGGTTATTTAG- | Efficiency = 0.95 |
TAMRA-3′ | |
Moraxella catarrhalis
|
copB
| F: 5′-GTGAGTGCCGCTTTACAACC-3′ | R2 = 0.998 | |
R: 5′-TGTATCGCCTGCCAAGACAA-3′ | Slope = −3.66 |
P:5′-6-FAM-TGCTTTTGCAGCTGTTAGCCAGCCTAA- | Efficiency = 0.91 |
TAMRA-3′ | |
Table 2
Optimized conditions for egc, khe, cps, gyrB, omp P6 and copB RT-qPCR assay
Primer | 0.6 μmol/L | 0.6 μmol/L | 0.6 μmol/L | 0.6 μmol/L | 0.6 μmol/L | 0.6 μmol/L |
Probe | 0.3 μmol/L | 0.3 μmol/L | 0.3 μmol/L | 0.3 μmol/L | 0.3 μmol/L | 0.3 μmol/L |
Total volume | 20 μl | 20 μl | 20 μl | 20 μl | 20 μl | 20 μl |
Melt | 95 °C, 10 min | 94 °C, 4 min | 94 °C, 4 min | 95 °C, 10 min | 94 °C, 4 min | 94 °C, 4 min |
Denaturation | 95 °C, 15 s | 94 °C, 30 s | 94 °C, 30 s | 95 °C, 15 s | 94 °C, 30 s | 94 °C, 30 s |
Annealing/Extension | 60 °C, 60 s | 60 °C, 60 s | 60 °C, 60 s | 60 °C, 60 s | 60 °C, 60 s | 60 °C, 60 s |
Cycles | 45 | 40 | 40 | 45 | 40 | 40 |
PCR Product Size | 82 base pairs | 77 base pairs | 67 base pairs | 190 base pairs | 156 base pairs | 71base pairs |
Table 3
Demographic and clinical characteristics of patients in the HS, stable COPD and AECOPD groups
Age (years) | 65 ± 8 | 67 ± 7 | 69 ± 6 |
Gender (M/F) | 20/13 | 28/6 | 27/5 |
BMI (kg/m2) | 23.1 ± 5.1 | 24.2 ± 4.9 | 23.8 ± 3.9 |
Tobacco (pack/year) | - | 44.2 ± 25.6 | 43.7 ± 27.8 |
FEV1 (L) | 3.3 ± 0.3 | 1.3 ± 0.1** | 1.2 ± 0.2** |
FEV1 % predicted | 103.6 ± 7.3 | 53.4 ± 8.8** | 51.4 ± 9.0** |
FVC (L) | 4.0 ± 0.2 | 2.9 ± 0.2* | 2.7 ± 0.2* |
FVC % predicted | 102.7 ± 6.7 | 81.4 ± 9.3** | 79.9 ± 7.4** |
FEV1/FVC (%) | 82.3 ± 6.1 | 43.8 ± 4.4** | 44.1 ± 7.1** |
WBC (x109/L) | 5.6 ± 1.2 | 6.1 ± 1.7 | 11.4 ± 5.1**## |
Neutrophils (%) | 64.6 ± 6.7 | 68.7 ± 7.6* | 85.4 ± 6.1**## |
CRP (mg/L) | 6.7 ± 2.4 | 16.1 ± 6.7** | 85.2 ± 30.4**## |
Table 4
Microbiological culture results of PSB and BALF samples obtained from patients in the HS, stable COPD and AECOPD groups
No isolated or Normal flora
| 29 (87.9) | 29 (87.9) | 20 (58.8) | 15 (44.1) | 9 (28.1) | 8 (25.0) |
Staphylococcus aureus
| 1 (3.0) | 1 (3.0) | 2 (5.9) | 4 (11.8) | 3 (9.4) | 3 (9.4) |
Klebsiella pneumoniae
| 1 (3.0) | 1 (3.0) | 1 (2.9) | 3 (8.8) | 4 (12.5) | 4 (12.5) |
Streptococcus pneumoniae
| 2 (6.0) | 2 (6.0) | 4 (11.8) | 5 (14.7) | 3 (9.4) | 4 (12.5) |
Pseudomonos aeruginosa
| 0 | 0 | 2 (5.9) | 2 (2.9) | 4 (12.5) | 5 (15.6) |
Haemophilus influenzeae
| 0 | 0 | 2 (5.9) | 3 (8.8) | 6 (18.8) | 5 (15.6) |
Moraxella catarrhalis
| 0 | 0 | 1 (2.9) | 2 (2.9) | 2 (6.3) | 2 (6.3) |
Others
a
| 0 | 0 | 1 (2.9) | 2 (2.9) | 1 (3.1) | 1 (3.1) |
Quantification of microorganism load in PSB and BALF samples
To quantify the number of bacterial cells in PSB and protected BALF samples, six ATCC standard strains were used as positive controls. Staphylococcus aureus (ATCC 25923) and Pseudomonos aeruginosa (ATCC 27853) were provided by the Clinical Laboratory, First Hospital, Ningbo City, China. Klebsiella pneumoniae (ATCC 700603), Streptococcus pneumoniae (ATCC 49619), Haemophilus influenzeae (ATCC 49247), and Moraxella catarrhalis (ATCC 25238) were purchased from Bioplus Biotech Co., Ltd. (Shanghai, China). A dense suspension of bacteria grown on agar plates was inoculated in phosphate-buffered saline, representing a bacterial concentration of approximately 108 CFU/ml. A 10-fold serial dilution scheme ranging between 108 and 103 CFU/ml was prepared. To correlate cycle threshold (CT) values measured by RT-qPCR with the number of bacterial cells present in each sample, aliquots (100 ml) of each dilution of bacterial suspension were plated out in triplicate onto agar plates. Agar plates were incubated overnight at 37 °C, and colonies were counted in order to calculate the number of CFU per dilution tube. DNA extraction was performed from a sample (5 ml) of each dilution tube and was analyzed concomitantly by RT-qPCR. Each positive control was carried out in triplicate, mean CT values were calculated and plotted against the base 10 logarithm of CFU per ml, and a standard curve was generated. The load of microorganisms in PSB and BALF samples was determined using a standard equation.
Statistical analysis
All data were expressed as means ± SEM. Differences between groups were examined for statistical significance by one-way analysis of variance (ANOVA) using SPSS 11.0 software (SPSS Inc., Chicago, USA). The correlation among bacterial burden, inflammatory mediators such as neutrophil cell count and cytokine levels, and pulmonary function such as FEV1 % predicted, FVC % predicted, and FEV1/FVC were calculated using Pearson’s correlation coefficient. P values <0.05 denoted that the difference was statistically significant.
Discussion
Several innate immune mechanisms are involved in maintaining the sterility of a healthy human airway. However, immune mechanisms are disrupted by smoking or other hazardous substances; resulting in the persistence of microbial pathogens in the lower airway of COPD patients [
25], which is called “colonization” by some researchers. Previous studies have proven that bacterial colonization is associated with greater levels of airway inflammation measured in sputum [
26‐
28] and has been implicated as the cause of most exacerbations in COPD [
29‐
31]
. Acute exacerbations are associated with a more rapid decline in lung function and an impaired quality of life, which are both major causes of morbidity and mortality in COPD [
22]. However, the pathogens involved, the number of pathogens that change, and the mechanism on how these infections alter lower airway inflammation remains unclear.
Bacterial colonization and airway inflammation in COPD patients have been previously demonstrated in studies. However, these studies have been limited to sampling the central tracheobronchial tree and/or detecting the pathogen by traditional cultures [
26‐
28]. In this present study, the load of pathogenic bacteria strain
Staphylococcus aureus,
Klebsiella pneumoniae,
Streptococcus pneumoniae,
Pseudomonos aeruginosa,
Haemophilus influenzeae and
Moraxella catarrhali were detected in PSB and BALF samples obtained from COPD patients and HS by RT-q-PCR assays, targeting specific pathogen genes. Moreover, cell count in BALF and pro-inflammatory cytokine concentrations in BALF supernatants were analyzed. Significantly higher levels of
Klebsiella pneumoniae,
Pseudomonos aeruginosa,
Haemophilus influenzeae, and
Moraxella catarrhalis were identified in both PSB and BALF samples obtained from stable COPD and AECOPD patients. Additionally, a significantly higher number of total cells and percentage of neutrophils in BALF, together with higher levels of IL-1 β, IL-6, IL-8, IL-10 and TNF-α in BALF supernatants, were detected in stable COPD and AECOPD patients. More importantly, pathogen loads in BALF samples were positively correlated with the percentage of neutrophils and levels of pro-inflammatory cytokines in BALF. Pathogen loads in PSB samples were negatively correlated with FEV1 % predicted, FVC % predicted, and FEV1/FVC values. Thus, the increase of pathogens in the lower respiratory tract likely contributed to the inflammatory response in the airways, leading to recurrent AECOPD and pulmonary function decline.
Obtaining samples from the lower respiratory tract without being contaminated by the upper airway flora is a crucial factor in accurately determining the prevalence of bacteria in the lower respiratory tract. Previous studies have found higher rates of bacterial isolates in sputum than in samples collected by bronchoscopy in stable COPD patients [
32‐
34]. This is likely due to the high contamination rate of sputum with the upper respiratory tract flora. Therefore, bronchoscopy with PSB appears as the best method to avoid upper airway contamination. For the same reason, protected BALF samples are appropriate for contamination-free pathogen analysis. Our results did not reveal significant differences in rates of the six analyzed pathogens between PSB and BALF samples among the three study groups. However, significantly higher rates of these six pathogens were found in PSB and BALF samples obtained from COPD patients compared with samples obtained from HS, and no significant differences between stable COPD and AECOPD patients were detected. These data confirms bacterial colonization in the lower respiratory tract of COPD patients, regardless of the patient’s status (stable or acute exacerbation of COPD). Nevertheless, persistent symptoms and recurrent exacerbations were seen in ex-smokers with moderate to severe COPD, suggesting that persistent inflammation resulting from bacterial infections has clinical consequences. Thus, the number of bacteria in the airway is a key factor for the development of AECOPD in stable COPD pateints.
Previous studies have demonstrated bacterial load changes in airways of COPD patients using conventional methods [
26‐
29]. However, conventional methods such as microbiological cultures are time-consuming and may give false-negative results, especially during ongoing antibiotic treatments. Non-culture based methods such as RT-qPCR are sensitive, specific and provide fast results; and are valuable tools for the early diagnosis and effective therapy of COPD. Erb-Downward
et al. identified a core pulmonary bacterial microbiome that includes
Pseudomonas,
Streptococcus,
Prevotella,
Fusobacterium,
Haemophilus,
Veillonella, and
Porphyromonas by massively parallel pyrosequencing of bacterial 16S amplicons [
35]
. In another study, the composition of the lung microbiome was determined using 454 pyrosequencing of 16S rDNA in BALF; and found that the main phyla in all samples were
Actinobacteria,
Firmicutes, and
Proteobacteria [
17]. However, analysis of microbiomes by 16S rDNA or 16 s rRNA focuses in building a picture of the complete microbial community in an environment, making a cluster analysis and studying the evolution history of microbiomes. Nevertheless, it is important to identify common bacterial species in the lower respiratory tract of COPD patients for guidance in clinical antibiotic therapy and analysis of inflammatory response. In this present study, RT-qPCR analysis revealed significantly higher detection rates for
Staphylococcus aureus,
Klebsiella pneumoniae,
Streptococcus pneumoniae,
Pseudomonos aeruginosa,
Haemophilus influenzeae, and
Moraxella catarrhalis, compared to conventional microbiological culture in all subjects. These results reflect the higher sensitivity and specificity of RT-qPCR, as a fast pathogen detection method.
Pathogens such as
Streptococcus pneumoniae,
Haemophilus influenzae, and
Moraxella catarrhalis are associated with approximately 50 % of COPD exacerbations, as demonstrated by traditional microbiological culture. These organisms can often be found colonizing the respiratory airways of COPD patients between exacerbations [
5], and are consistent with our culture results. However, bacteria in COPD varies with disease severity, as
Pseudomonas aeruginosa is more commonly detected in patients with severe COPD in both stable [
36,
37] and acute exacerbations [
38‐
40]. Microbiome analysis by 16S rDNA or 16 s rRNA also revealed that
Haemophilus species were strongly associated with the presence of COPD [
41], while
Pseudomonas species were more commonly observed in subjects with moderate or severe COPD [
35]. Patients in our present study presented with moderate and severe COPD (GOLD stage II-III), and the load of
Klebsiella pneumoniae,
Haemophilus influenzeae,
Moraxella catarrhalis and
Pseudomonos aeruginosa in PSB and BALF samples obtained from COPD patients significantly increased compared with samples obtained from HS, as detected by RT-qPCR; suggesting that bacterial species quantitatively analyzed by RT-qPCR are consistent with bacterial species cultured in previous studies. Moreover, the load of
Klebsiella pneumoniae,
Haemophilus influenzeae,
Moraxella catarrhalis and
Pseudomonos aeruginosa in AECOPD patients also significantly increased compared with stable COPD patients; which suggest that this increase of bacterial load in the lower respiratory tract may contribute to acute exacerbation in COPD. A previous study has indicated the colonization of
Streptococcus pneumoniae in AECOPD patients [
42]. In this present study, there was no significant increase of
Streptococcus pneumoniae in PSB and BALF samples from AECOPD patients, compared with stable COPD patients and HS. However, our study results had no discrepancy with previous studies, because high loads of
Streptococcus pneumoniae were found in both stable COPD patients and HS; which is consistent with a previous study [
35]. Our results by RT-qPCR indicated that
Streptococcus pneumoniae was present in all study subjects, although previous studies did not detect a high load of
Streptococcus pneumoniae in these subjects by using conventional culture methods.
In the contrary, diagnosing lower respiratory tract infections caused by
Streptococcus peumoniae,
Haemophilus influenzae, and
Moraxella catarrhalis by PCR has been limited to distinguishing colonization from infections. This may depend on the analysis that combined the load of the above pathogens with symptoms and inflammatory mediators such as C-reactive protein, the number of neutrophils, and some pro-inflammatory cytokines. Exacerbations are typically associated with increased neutrophilic airway inflammation [
43,
44]. Pro-inflammatory cytokines such as TNF-α, IL-1 β and IL-6 are increased in COPD and appear to amplify inflammation [
45]. In this present study, there was a significant increase in the number of neutrophils in BALF, and in the levels of pro-inflammatory cytokines IL-1 β, IL-6, IL-8, IL-10 and TNF-α in BALF supernatants obtained from AECOPD patients, compared with stable COPD patients and HS; and there was a positive correlation between the load of
Klebsiella pneumoniae,
Haemophilus influenzeae,
Moraxella catarrhalis and
Pseudomonos aeruginosa, and most inflammatory mediators. These data indicate that the increase in the load of common pathogens in the lower respiratory tract of COPD patients may contribute to the increase in pro-inflammatory response as acute exacerbations occur, resulting in disease progression and gradual decline in lung function. Indeed, there was a negative correlation between the load of the six pathogens and the FEV1 % predicted, FVC % predicted and FEV1/FVC values, which revealed that increased loads of common pathogens led to the decline of lung functions in COPD patients. However, in this present study, there was no quantitative data regarding changes in the above bacteria in the lower respiratory tract of mild COPD patients (GOLD stage I). Thus, the association between the load of these six bacteria and the degree of airflow obstruction in COPD patients was limited, requiring a more in-depth study in the future.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
Wang HY carried out the clinical study, participated in the RT-qPCR analysis and drafted the manuscript. Gu X carried out the ELISA measurement. YW participated in the conventional culture and RT-qPCR analysis. Xu T and Fu ZM participated in the clinical samples collection. Peng WD participated in the design of the study and performed the statistical analysis. WY conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.