Association between Clinical Characteristics and Microbiota in Bronchiectasis Patients Based on Metagenomic Next-Generation Sequencing Technology

Bronchiectasis is a common chronic lung disease characterized by irreversible dilation of the bronchi with a diameter greater than 2 mm caused by factors such as infection, physical and chemical factors, immune dys-function, or genetic factors (Gao et al. 2021). Patients often experience acute exacerbations, presenting with symptoms such as fever, sputum production, purulent sputum, and progressive respiratory distress (Evans and Greenstone 2003; Amati et al. 2019). A study on bronchiectasis among adults in urban areas of mainland China in 2022 showed that the prevalence had increased by 2.31 times, from 75.48 per 100,000 in 2013 to 174.45 per 100,000 in 2017 (Feng et al. 2022). Studies have shown that the incidence and prevalence of bronchiectasis in the UK are increasing annually and are significantly associated with increased mortality rates (Quint et al. 2016), while the overall prevalence of bronchiectasis in Germany increases by approximately 10% per year (Ringshausen et al. 2019). Bronchiectasis poses an increasing burden on healthcare systems worldwide. Given that bronchiectasis is characterized by complex interactions between chronic infection, inflammation, and impaired mucociliary clearance leading to structural changes in the lungs, infections often result in acute exacerbations and worsening of the disease (Flume et al. 2018; Martinez-García 2018), necessitating early identification of infective pathogens and proactive use of antibiotics to control the condition (Bilton et al. 2006; Byun et al. 2017). Conventional pathogen detection methods include microbial culture, microscopy, histopathology, and polymerase chain reaction (PCR). However, microbial culture and microscopy have limitations in terms of detection rate and available targets, thereby failing to meet the needs of clinical practitioners (Zhang et al. 2020). Additionally, histopathological analysis is timeconsuming and lacks pathogen specificity (Guarner and Brandt 2011), while PCR assays require the design of specific primers or probes for microbial pathogens, limiting the ability to detect pathogens (Maartens et al. 2020). When microorganisms cannot be promptly identified, physicians often rely on empirical antibiotic use, which is often ineffective and may exacerbate reinfection and accelerate the emergence of antibiotic resistance and multidrug-resistant pathogens (Ruppé et al. 2016). Therefore, it is necessary to establish a rapid and accurate method for detecting multiple pathogenic microorganisms in bronchiectasis patients.

Metagenomic next-generation sequencing (mNGS) technology provides a powerful solution to these clinical diagnostic challenges. The unbiased molecular technique of mNGS can simultaneously identify bacteria, viruses, fungi, parasites, and other microorganisms in clinical specimens by detecting their entire DNA and/or RNA content. It offers advantages such as high precision, high sensitivity, and short detection time (Chiu and Miller 2019; Chen et al. 2021; Li et al. 2023), making it beneficial for identifying severe infections, mixed infections, and uncommon or novel pathogen infections in immunocompromised patients (Chiu and Miller 2019). Previous studies have applied mNGS in the microbial diagnosis of infectious diseases such as sepsis and acute respiratory distress syndrome (Zhang et al. 2020; Ren et al. 2021). However, there is currently no research investigating the use of mNGS in the microbial diagnosis of bronchiectasis.

Additionally, in clinical practice, there is a lack of exploration into the correlation between clinical characteristics and microbiome. This could assist physicians in rapidly determining the cause of a patient’s condition and consequently prescribing accurate medications. Therefore, this study aimed to analyze and compare the results of patients’ microbiomes obtained through mNGS and conventional culture. The goal was to provide a more comprehensive, rapid, and accurate method for pathogen detection, thoroughly revealing the pathogen spectrum in patients with bronchiectasis. This, in turn, aided in formulating targeted therapeutic strategies, guiding improvements in patient prognosis care, and ultimately enhancing the quality of life for patients.

Numerous studies have demonstrated that worsening of bronchiectasis leads to increased airway and systemic inflammation, accompanied by progressive lung damage, decreased quality of life, accelerated decline in lung function, and increased mortality rates (Chalmers et al. 2012; Chalmers et al. 2014; Aliberti et al. 2016). This imposes a heavy burden on patients regarding medical expenses and prognosis. Acute exacerbations of bronchiectasis are often attributed to bacterial infections, and the Updated BTS Adult Bronchiectasis Guideline 2018 recommends antibiotic therapy to prevent or control acute exacerbations (Hill et al. 2019). Therefore, timely and effective identification of the microbial infection types in bronchiectasis patients and the use of targeted therapeutic drugs are crucial. This study, based on mNGS technology, investigated the association between clinical characteristics of bronchiectasis patients and the microbiome. The study results showed that the types and number of pathogens detected by mNGS were significantly higher than those detected by conventional culture methods. The diagnostic performance for various pathogens was significantly more robust with mNGS compared to conventional culture methods, particularly in viral detection, where it had unmatched advantages. The most detected bacterial pathogens among the bacterial types were P. aeruginosa and H. influenzae, while the highest-detected fungal pathogen was A. fumigatus.

This study compared the effectiveness of mNGS with traditional microbiological detection methods. The results showed that the overall positivity rate of mNGS (n = 66, 98.5%) was significantly higher than that of BALF culture (n = 19, 28.4%), sputum culture (n = 18, 17.5%), and blood culture (n = 0), indicating that only mNGS could detect viruses. This conclusion is similar to a previous study by Qi et al. (2019) on patients with related pneumonia, which found a much higher positivity rate with mNGS compared to conventional culture, and mNGS can to detect pathogens that are difficult to detect with traditional methods. Cox et al. (2017) obtained similar results by using 16S rRNA. Furthermore, a study by Ren et al. (2021) investigating the diagnostic performance of mNGS in septic patients also demonstrated that mNGS can identify various pathogens in blood, BALF, and cerebrospinal fluid samples, showing a higher positivity rate compared to culture-based diagnostic methods (Ren et al. 2021). This is because mNGS is an unbiased and culture-independent method that employs high-throughput/parallel sequencing technology capable of simultaneously sequencing thousands of nucleic acid fragments. It analyzes nucleic acids in samples to detect and identify microbial DNA and/or RNA. The application of nanopore sequencing technology has significantly reduced the time from sample reception to final results, from 48 hours to 6 hours (Gu et al. 2019; Diao et al. 2022; Li et al. 2022).

Mainly, mNGS demonstrates pronounced advantages in detecting Mycobacterium tuberculosis, viruses, anaerobic bacteria, and fungi (Mei et al. 2023). Viruses require parasitism within host cells for survival and replication, making them difficult to culture using conventional methods. mNGS exhibits higher sensitivity and specificity than microbial culture, showing superior diagnostic performance over traditional methods (Qian et al. 2020).

Furthermore, compared to culture-dependent methods, mNGS results are less likely to be influenced by previous antibiotic exposure (Miao et al. 2018; Diao et al. 2022). Additionally, the results of this study also indicated that mNGS could be used to identify local infections. In this study, BALF and sputum samples were used for mNGS testing, and the results showed a high positivity rate, indicating the broad applicability of mNGS in pathogen detection, even in samples with relatively low positivity rates based on traditional culture-based diagnostic procedures (Ren et al. 2021). These findings again confirm the excellent diagnostic performance of mNGS in infectious diseases. The diagnostic method contributes to improving the clinical identification of infections of unknown origin.

In addition, the mNGS sequencing results of this study showed that P. aeruginosa and H. influenzae were the most common pathogens in patients with bronchiectasis, ranking first and second, respectively. This result is similar to a previous study on secreted mucins and airway bacterial colonization in 50 non-cystic fibrosis bronchiectasis patients from Europe (Sibila et al. 2015). However, according to the results reported by the US Bronchiectasis Research Registry, P. aeruginosa has a higher isolation rate (33%) in bronchiectasis patients, while H. influenzae is relatively uncommon (8%) (Aksamit et al. 2017). These discrepancies may be due to differences in patient sample selection, collection methods, and geographic variations in microbial characteristics. Furthermore, P. aeruginosa infection has been included as an important risk factor for disease prognosis and severity in various scoring systems used to assess the severity of bronchiectasis, such as the E-FACED score and BSI score (Martinez-Garcia et al. 2017; Gao et al. 2021). Most microbiological studies on bronchiectasis focus on bacteria, while fungi are generally considered incidental findings (Chandrasekaran et al. 2018). Aspergillus species are the most commonly isolated fungi in the sputum of bronchiectasis patients. A. fumigatus can act as a pathogen or an allergen, but its specific role in bronchiectasis is still unclear (Kosmidis and Denning 2015; Amati et al. 2019). However, due to the high specificity and sensitivity of mNGS technology (Wang et al. 2019), it is possible to detect colonization of non-pathogenic bacteria. Respiratory colonizers (such as P. aeruginosa, H. influenzae, and A. fumigatus) maintain a balance with the host by evading the immune system’s clearance (Zhao et al. 2023). Also, bronchiectasis patients are susceptible to bacterial infections (Chalmers et al. 2018). However, the microbial composition detected by mNGS cannot determine the pathogenic state of the detected microorganisms. Therefore, even though this study observed a high detection rate of P. aeruginosa, H. influenzae, and A. fumigatus, it is difficult to determine the true pathogenic microorganism. This is one of the limitations affecting the clinical application of mNGS. The impact of colonizers on respiratory tract structure and function could be a future research direction to explore the specific etiology of bronchiectasis. Based on the results of this study, we believe that in bronchiectasis patients, it may be necessary to reduce the carriage of potential pathogens in the oropharynx, stomach, intestines, or respiratory tract by using non-absorbable antibiotics or inhaled antibiotics selectively, while enhancing the patient’s immune system to resist pathogenic microorganisms.

In this study, clinicians adjusted the anti-infection treatment based on mNGS results, which assisted clinical diagnosis. The results showed that in the group with positive A. fumigatus results, 70% of patients had their empirical anti-infection therapy adjusted according to mNGS results, and the outcomes of all patients showed improvement (100%). This indicates a positive impact of mNGS testing on clinical drug guidance and patient prognosis. The overall data results of the association between clinical characteristics of bronchiectasis patients and mNGS microbial results in this study demonstrated that the microbial composition detected in bronchiectasis patients is mainly related to common scoring systems such as Reiff, BSI, E-FACED, BACI scores, and some common clinical characteristics (Kosmidis and Denning 2015; Amati et al. 2019; Ma et al. 2021; Huang et al. 2023). These characteristics are evaluation indicators of bronchiectasis and microbial infection, but they do not guide the etiological diagnosis of bronchiectasis pathogens in clinical practice. This indirectly indicates the necessity and rationality of laboratory pathogen detection for diagnosing infectious causes. In general, testing facilities can provide mNGS reports within 24 hours, and in practical treatment, this does not significantly increase the waiting time for patients. On the contrary, it is even shorter than the time required for conventional culture. Therefore, when bronchiectasis patients are at risk of infection, NGS can supplement routine microbial detection methods to increase the detection rate, shorten the turnaround time, and assist in diagnosing the etiology of patients for targeted treatment. Certainly, we hope to establish closer collaboration between hospitals and enterprises in the future, allowing the seamless deployment of the testing platform within hospital settings to achieve realtime detection. This will help reduce patient waiting times, enabling healthcare professionals to administer personalized treatments and enhance medical efficiency promptly. Additionally, it contributes to minimizing sample wastage and reducing transportation costs, alleviating the overall burden on healthcare.

Although encouraging results were achieved, it must be acknowledged that this study had certain limitations. Firstly, there was no authoritative and unified guideline for interpreting mNGS reports, which may lead to subjective misjudgments. Secondly, the sample size in this study was relatively small, which may introduce bias in the data. For instance, in the part of the study that examined the association between clinical characteristics and mNGS microbial results in patients with bronchiectasis, there were significant differences between the samples of pathogen-positive and pathogen-negative groups. Additionally, this study did not investigate the specific subtypes of single pathogen infection/ mixed infection, nor did it consider the possibility of dominant bacterial populations within mixed infection pathogens, which may introduce bias in the results. In conclusion, the results of this study demonstrated the important significance of mNGS in the diagnosis, treatment, and prognosis of bronchiectasis patients. It is clinically recommended to use mNGS as a supplementary tool to routine microbial testing to improve the detection rate and assist in treatment decisions.