Single-molecule long-read 16S sequencing to characterize the lung microbiome from mechanically ventilated patients with suspected pneumonia

Role of nasal microbiota in regulating host anti-influenza immunity in dogs

BACKGROUND

Numerous studies have confirmed a close relationship between the pathogenicity of influenza and respiratory microbiota, but the mechanistic basis for this is poorly defined. Also, the majority of these studies have been conducted on murine models, and it remains unclear how far these findings can be extrapolated from murine models to other animals. Considering that influenza A virus is increasingly recognized as an important canine respiratory pathogen, this study investigated the cross-talk between nasal and lung tissues mediated by microbes and its association with influenza susceptibility in a beagle dog model.

RESULTS

Using 16S rRNA gene sequencing, combined with comparative transcriptomic, anatomical, and histological examinations, we investigated viral presence, gene expression profiles, and microbiota in the nasal cavity and lung after influenza infection in the beagles with antibiotic-induced nasal dysbiosis. Our data showed that dysbiosis of the nasal microbiome exacerbates influenza-induced respiratory disease and the epithelial barrier disruption, and impairs host antiviral responses in the nasal cavity and lung. Moreover, dysregulation of nasal microbiota exacerbates the influenza-induced disturbance in lung microbiota. Further, we also identified a strain of Lactobacillus plantarum isolated from canine nasal cavity with a significant antiviral effect in vitro, and found that its antiviral activity might be associated with the activation of the interferon (IFN) pathway and modulation of the impaired autophagy flux induced by influenza infection.

CONCLUSIONS

Our investigation reveals that nasal microbiota dysbiosis exerts a prominent impact on host antiviral responses, inflammation thresholds, and mucosal barrier integrity during influenza infection. Lactobacilli, as part of the nasal microbiota, may contribute to host antiviral defenses by modulating the IFN and autophagy pathways. Collectively, this study underscores the importance of nasal microbiota homeostasis in maintaining respiratory health. Video Abstract.

Aggregatibacter is inversely associated with inflammatory mediators in sputa of patients with chronic airway diseases and reduces inflammation in vitro

BACKGROUND

Chronic airway disease (CAD) is characterized by chronic airway inflammation and colonization of the lungs by pro-inflammatory pathogens. However, while various other bacterial species are present in the lower airways, it is not fully understood how they influence inflammation. We aimed to identify novel anti-inflammatory species present in lower airway samples of patients with CAD.

METHODS

Paired sputum microbiome and inflammatory marker data of adults with CAD across three separate cohorts (Australian asthma and bronchiectasis, Scottish bronchiectasis) was analyzed using Linear discriminant analysis Effect Size (LEfSE) and Spearman correlation analysis to identify species associated with a low inflammatory profile in patients.

RESULTS

We identified the genus Aggregatibacter as more abundant in patients with lower levels of airway inflammatory markers in two CAD cohorts (Australian asthma and bronchiectasis). In addition, the relative abundance of Aggregatibacter was inversely correlated with sputum IL-8 (Australian bronchiectasis) and IL-1β levels (Australian asthma and bronchiectasis). Subsequent in vitro testing, using a physiologically relevant three-dimensional lung epithelial cell model, revealed that Aggregatibacter spp. (i.e. A. actinomycetemcomitans, A. aphrophilus) and their cell-free supernatant exerted anti-inflammatory activity without influencing host cell viability.

CONCLUSIONS

These findings suggest that Aggregatibacter spp. might act to reduce airway inflammation in CAD patients.

Microbiota-Derived Extracellular Vesicle as Emerging Actors in Host Interactions

The human microbiota is an intricate micro-ecosystem comprising a diverse range of dynamic microbial populations mainly consisting of bacteria, whose interactions with hosts strongly affect several physiological and pathological processes. The gut microbiota is being increasingly recognized as a critical player in maintaining homeostasis, contributing to the main functions of the intestine and distal organs such as the brain. However, gut dysbiosis, characterized by composition and function alterations of microbiota with intestinal barrier dysfunction has been linked to the development and progression of several pathologies, including intestinal inflammatory diseases, systemic autoimmune diseases, such as rheumatic arthritis, and neurodegenerative diseases, such as Alzheimer's disease. Moreover, oral microbiota research has gained significant interest in recent years due to its potential impact on overall health. Emerging evidence on the role of microbiota-host interactions in health and disease has triggered a marked interest on the functional role of bacterial extracellular vesicles (BEVs) as mediators of inter-kingdom communication. Accumulating evidence reveals that BEVs mediate host interactions by transporting and delivering into host cells effector molecules that modulate host signaling pathways and cell processes, influencing health and disease. This review discusses the critical role of BEVs from the gut, lung, skin and oral cavity in the epithelium, immune system, and CNS interactions.

Clinical evaluation of droplet digital pcr for suspected ascites infection in patients with liver cirrhosis

BACKGROUND

Droplet digital PCR (ddPCR) is increasingly used in diagnosing clinical pathogens, but its effectiveness in cirrhosis patients with suspected ascites infection remains uncertain.

METHODS

The diagnostic performance of ddPCR was assessed in 305 ascites samples, utilizing culture and clinical composite standards. The quantitative value and potential clinical impact of ddPCR were further analyzed in patients with spontaneous bacterial peritonitis.

RESULTS

With culture standards, ddPCR demonstrated a sensitivity of 86.5% and specificity of 83.2% for bacterial or fungal detection. After adjustment of clinical composite criteria, specificity increased to 96.4%. Better diagnostic performance for all types of targeted pathogens, particularly fungi, was observed with ddPCR compared to culture, and more polymicrobial infections were detected (30.4% versus 5.7%, p < 0.001). Pathogen loads detected by ddPCR correlated with white blood cell count in ascites and blood, as well as polymorphonuclear cell (PMN) count in ascites, reflecting infection status rapidly. A positive clinical impact of 55.8% (43/77) was observed for ddPCR, which was more significant among patients with PMN count ≤ 250/mm3 in terms of medication adjustment and new diagnosis. ddPCR results for fungal detection were confirmed by clinical symptoms and other microbiological tests, which could guide antifungal therapy and reduce the risk of short-term mortality.

CONCLUSIONS

ddPCR, with appropriate panel design, has advantages in pathogen detection and clinical management of ascites infection, especially for patients with fungal and polymicrobial infections. Patients with atypical spontaneous bacterial peritonitis benefited more from ddPCR.

Lung microbiome: new insights into the pathogenesis of respiratory diseases

The lungs were long thought to be sterile until technical advances uncovered the presence of the lung microbial community. The microbiome of healthy lungs is mainly derived from the upper respiratory tract (URT) microbiome but also has its own characteristic flora. The selection mechanisms in the lung, including clearance by coughing, pulmonary macrophages, the oscillation of respiratory cilia, and bacterial inhibition by alveolar surfactant, keep the microbiome transient and mobile, which is different from the microbiome in other organs. The pulmonary bacteriome has been intensively studied recently, but relatively little research has focused on the mycobiome and virome. This up-to-date review retrospectively summarizes the lung microbiome's history, composition, and function. We focus on the interaction of the lung microbiome with the oropharynx and gut microbiome and emphasize the role it plays in the innate and adaptive immune responses. More importantly, we focus on multiple respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), fibrosis, bronchiectasis, and pneumonia. The impact of the lung microbiome on coronavirus disease 2019 (COVID-19) and lung cancer has also been comprehensively studied. Furthermore, by summarizing the therapeutic potential of the lung microbiome in lung diseases and examining the shortcomings of the field, we propose an outlook of the direction of lung microbiome research.

The Complex Role of the Microbiome in Non-Small Cell Lung Cancer Development and Progression

In recent years, there has been a growing interest in the relationship between microorganisms in the surrounding environment and cancer cells. While the tumor microenvironment predominantly comprises cancer cells, stromal cells, and immune cells, emerging research highlights the significant contributions of microbial cells to tumor development and progression. Although the impact of the gut microbiome on treatment response in lung cancer is well established, recent investigations indicate complex roles of lung microbiota in lung cancer. This article focuses on recent findings on the human lung microbiome and its impacts in cancer development and progression. We delve into the characteristics of the lung microbiome and its influence on lung cancer development. Additionally, we explore the characteristics of the intratumoral microbiome, the metabolic interactions between lung tumor cells, and how microorganism-produced metabolites can contribute to cancer progression. Furthermore, we provide a comprehensive review of the current literature on the lung microbiome and its implications for the metastatic potential of tumor cells. Additionally, this review discusses the potential for therapeutic modulation of the microbiome to establish lung cancer prevention strategies and optimize lung cancer treatment.

Pneumocystis jirovecii with high probability detected in bronchoalveolar lavage fluid of chemotherapy-related interstitial pneumonia in patients with lymphoma using metagenomic next-generation sequencing technology

BACKGROUND

Previous studies achieved low microbial detection rates in lymphoma patients with interstitial pneumonia (IP) after chemotherapy. However, the metagenomic next-generation sequencing (mNGS) is a comprehensive approach that is expected to improve the pathogen identification rate. Thus far, reports on the use of mNGS in lymphoma patients with chemotherapy-related IP remain scarce. In this study, we summarized the microbial detection outcomes of lymphoma patients with chemotherapy-related IP through mNGS testing of bronchoalveolar lavage fluid (BALF).

METHODS

Fifteen lymphoma patients with chemotherapy-related IP were tested for traditional laboratory microbiology, along with the mNGS of BALF. Then, the results of mNGS and traditional laboratory microbiology were compared.

RESULTS

Of the 15 enrolled patients, 11 received rituximab and 8 were administered doxorubicin hydrochloride liposome. The overall microbial yield was 93.3% (14/15) for mNGS versus 13.3% (2/15) for traditional culture methods (P ≤ 0.05). The most frequently detected pathogens were Pneumocystis jirovecii (12/15, 80%), Cytomegalovirus (4/15, 26.7%), and Epstein-Barr virus (3/15, 20%). Mixed infections were detected in 10 cases. Five patients recovered after the treatment with antibiotics alone without glucocorticoids.

CONCLUSION

Our findings obtained through mNGS testing of BALF suggested a high microbial detection rate in lymphoma patients with IP after chemotherapy. Notably, there was an especially high detection rate of Pneumocystis jirovecii. The application of mNGS in patients with chemotherapy-related IP was more sensitive.

Effect of mechanical ventilation under intubation on respiratory tract change of bacterial count and alteration of bacterial flora

Background: The most common 'second strike' in mechanically ventilated patients is a pulmonary infection caused by the ease with which bacteria can invade and colonize the lungs due to mechanical ventilation. At the same time, metastasis of lower airway microbiota may have significant implications in developing intubation mechanical ventilation lung inflammation. Thus, we establish a rat model of tracheal intubation with mechanical ventilation and explore the effects of mechanical ventilation on lung injury and microbiological changes in rats. To provide a reference for preventing and treating bacterial flora imbalance and pulmonary infection injury caused by mechanical ventilation of tracheal intubation. Methods: Sprague-Dawley rats were randomly divided into Control, Mechanical ventilation under intubation (1, 3, 6 h) groups, and Spontaneously breathing under intubation (1, 3, 6 h). Lung histopathological injury scores were evaluated. 16SrDNA sequencing was performed to explore respiratory microbiota changes, especially, changes of bacterial count and alteration of bacterial flora. Results: Compared to groups C and SV, critical pathological changes in pulmonary lesions occurred in the MV group after 6 h (p < 0.05). The Alpha diversity and Beta diversity of lower respiratory tract microbiota in MV6, SV6, and C groups were statistically significant (p < 0.05). The main dominant bacterial phyla in the respiratory tract of rats were Proteobacteria, Firmicutes, Bacteroidetes, and Cyanobacteria. Acinetobacter radioresistens in group C was significant, Megaonas in group MV6 was significantly increased, and Parvibacter in group SV6 was significantly increased. Anaerobic, biofilm formation, and Gram-negative bacteria-related functional genes were altered during mechanical ventilation with endotracheal intubation. Conclusion: Mechanical ventilation under intubation may cause dysregulation of lower respiratory microbiota in rats.

Microbiological diagnostic performance of metagenomic next-generation sequencing compared with conventional culture for patients with community-acquired pneumonia

Background

Community-acquired pneumonia (CAP) is an extraordinarily heterogeneous illness, both in the range of responsible pathogens and the host response. Metagenomic next-generation sequencing (mNGS) is a promising technology for pathogen detection. However, the clinical application of mNGS for pathogen detection remains challenging.

Methods

A total of 205 patients with CAP admitted to the intensive care unit were recruited, and broncho alveolar lavage fluids (BALFs) from 83 patients, sputum samples from 33 cases, and blood from 89 cases were collected for pathogen detection by mNGS. At the same time, multiple samples of each patient were tested by culture. The diagnostic performance was compared between mNGS and culture for pathogen detection.

Results

The positive rate of pathogen detection by mNGS in BALF and sputum samples was 89.2% and 97.0%, which was significantly higher (P < 0.001) than that (67.4%) of blood samples. The positive rate of mNGS was significantly higher than that of culture (81.0% vs. 56.1%, P = 1.052e-07). A group of pathogens including Mycobacterium abscessus, Chlamydia psittaci, Pneumocystis jirovecii, Orientia tsutsugamushi, and all viruses were only detected by mNGS. Based on mNGS results, Escherichia coli was the most common pathogen (15/61, 24.59%) of non-severe patients with CAP, and Mycobacterium tuberculosis was the most common pathogen (21/144, 14.58%) leading to severe pneumonia. Pneumocystis jirovecii was the most common pathogen (26.09%) in severe CAP patients with an immunocompromised status, which was all detected by mNGS only.

Conclusion

mNGS has higher overall sensitivity for pathogen detection than culture, BALF, and sputum mNGS are more sensitive than blood mNGS. mNGS is a necessary supplement of conventional microbiological tests for the pathogen detection of pulmonary infection.

Diagnostic Value of Metagenomic Next-Generation Sequencing for Multi-Pathogenic Pneumonia in HIV-Infected Patients

Background

To evaluate the value and challenges of real-world clinical application of metagenomic next-generation sequencing (mNGS) for bronchoalveolar lavage fluid (BALF) in HIV-infected patients with suspected multi-pathogenic pneumonia.

Methods

Fifty-seven HIV-infected patients with suspected mixed pneumonia who were agreed to undergo the bronchoscopy were recruited and retrospectively reviewed the results of mNGS and conventional microbiological tests (CMTs) of BALF from July 2020 to June 2022.

Results

54 patients were diagnosed with pneumonia including 49 patients with definite pathogens and five patients with probable pathogens. mNGS exhibited a higher diagnostic accuracy for fungal detection than CMTs in HIV-infected patients with suspected pulmonary infection. The sensitivity of mNGS in diagnosis of pneumonia in HIV-infected patients was much higher than that of CMTs (79.6% vs 61.1%; P < 0.05). Patients with mixed infection had lower CD4 T-cell count and higher symptom duration before admitting to the hospital than those with single infection. The detection rate of mNGS for mixed infection was significantly higher than that of CMTs and more co-pathogens could be identified by mNGS. The most common pattern of mixed infection observed was fungi-virus (11/29, 37.9%), followed by fungi-virus-bacteria (6/29, 20.7%) coinfection in HIV-infected patients with multi-pathogenic pneumonia.

Conclusion

mNGS improved the pathogens detection rate and exhibited advantages in identifying multi-pathogenic pneumonia in HIV-infected patients. Early performance of bronchoscopy and mNGS are recommended in HIV-infected patients with low CD4 T cell counts and long duration of symptoms. The most common pattern of mixed infection observed was fungi-virus, followed by fungi-virus-bacteria coinfection in HIV infected patients with multi-pathogenic pneumonia.

The Lung Microbiome: A New Frontier for Lung and Brain Disease

Due to the limitations of culture techniques, the lung in a healthy state is traditionally considered to be a sterile organ. With the development of non-culture-dependent techniques, the presence of low-biomass microbiomes in the lungs has been identified. The species of the lung microbiome are similar to those of the oral microbiome, suggesting that the microbiome is derived passively within the lungs from the oral cavity via micro-aspiration. Elimination, immigration, and relative growth within its communities all contribute to the composition of the lung microbiome. The lung microbiome is reportedly altered in many lung diseases that have not traditionally been considered infectious or microbial, and potential pathways of microbe-host crosstalk are emerging. Recent studies have shown that the lung microbiome also plays an important role in brain autoimmunity. There is a close relationship between the lungs and the brain, which can be called the lung-brain axis. However, the problem now is that it is not well understood how the lung microbiota plays a role in the disease-specifically, whether there is a causal connection between disease and the lung microbiome. The lung microbiome includes bacteria, archaea, fungi, protozoa, and viruses. However, fungi and viruses have not been fully studied compared to bacteria in the lungs. In this review, we mainly discuss the role of the lung microbiome in chronic lung diseases and, in particular, we summarize the recent progress of the lung microbiome in multiple sclerosis, as well as the lung-brain axis.

LDMD: A database of microbes in human lung disease

Background

Lungs were initially thought to be sterile. However, with the development of sequencing technologies, various commensal microorganisms, especially bacteria, have been observed in the lungs of healthy humans. Several studies have also linked lung microbes to infectious lung diseases. However, few databases have focused on the metagenomics of lungs to provide microbial compositions and corresponding metadata information. Such a database would be handy for researching and treating lung diseases.

Methods

To provide researchers with a preliminary understanding of lung microbes and their research methods, the LDMD collated nearly 10,000 studies in the literature covering over 30 diseases, gathered basic information such as the sources of lung microbe samples, sequencing methods, and processing software, as well as analyzed the metagenomic sequencing characteristics of lung microbes. Besides, the LDMD also contained data collected in our laboratory.

Results

In this study, we established the Lung Disease Microorganisms Database (LDMD), a comprehensive database of microbes involved in lung disease. The LDMD offered sequence analysis capabilities, allowing users to upload their sequencing results, align them with the data collated in the database, and visually analyze the results.

Conclusion

In conclusion, the LDMD possesses various functionalities that provide a convenient and comprehensive resource to study the lung metagenome and treat lung diseases.

The performance of metagenomic next-generation sequencing in diagnosing pulmonary infectious diseases using authentic clinical specimens: The Illumina platform versus the Beijing Genomics Institute platform

Introduction: Metagenomic next-generation sequencing (mNGS) has been increasingly used to detect infectious organisms and is rapidly moving from research to clinical laboratories. Presently, mNGS platforms mainly include those from Illumina and the Beijing Genomics Institute (BGI). Previous studies have reported that various sequencing platforms have similar sensitivity in detecting the reference panel that mimics clinical specimens. However, whether the Illumina and BGI platforms provide the same diagnostic performance using authentic clinical samples remains unclear. Methods: In this prospective study, we compared the performance of the Illumina and BGI platforms in detecting pulmonary pathogens. Forty-six patients with suspected pulmonary infection were enrolled in the final analysis. All patients received bronchoscopy, and the specimens collected were sent for mNGS on the two different sequencing platforms. Results: The diagnostic sensitivity of the Illumina and BGI platforms was notably higher than that of conventional examination (76.9% vs. 38.5%, p < 0.001; 82.1% vs. 38.5%, p < 0.001; respectively). The sensitivity and specificity for pulmonary infection diagnosis were not significantly different between the Illumina and BGI platforms. Furthermore, the pathogenic detection rate of the two platforms were not significantly different. Conclusion: The Illumina and BGI platforms exhibited similar diagnostic performance for pulmonary infectious diseases using clinical specimens, and both are superior to conventional examinations.

Prevention and treatment of ventilator-associated pneumonia in COVID-19

Ventilator-associated pneumonia (VAP) is the most common acquired infection in the intensive care unit. Recent studies showed that the critical COVID-19 patients with invasive mechanical ventilation have a high risk of developing VAP, which result in a worse outcome and an increasing economic burden. With the development of critical care medicine, the morbidity and mortality of VAP remains high. Especially since the outbreak of COVID-19, the healthcare system is facing unprecedented challenges. Therefore, many efforts have been made in effective prevention, early diagnosis, and early treatment of VAP. This review focuses on the treatment and prevention drugs of VAP in COVID-19 patients. In general, prevention is more important than treatment for VAP. Prevention of VAP is based on minimizing exposure to mechanical ventilation and encouraging early release. There is little difference in drug prophylaxis from non-COVID-19. In term of treatment of VAP, empirical antibiotics is the main treatment, special attention should be paid to the antimicrobial spectrum and duration of antibiotics because of the existence of drug-resistant bacteria. Further studies with well-designed and large sample size were needed to demonstrate the prevention and treatment of ventilator-associated pneumonia in COVID-19 based on the specificity of COVID-19.

The human lung microbiome-A hidden link between microbes and human health and diseases

Once thought to be sterile, the human lung is now well recognized to harbor a consortium of microorganisms collectively known as the lung microbiome. The lung microbiome is altered in an array of lung diseases, including chronic lung diseases such as chronic obstructive pulmonary disease, asthma, and bronchiectasis, acute lung diseases caused by pneumonia, sepsis, and COVID-19, and other lung complications such as those related to lung transplantation, lung cancer, and human immunodeficiency virus. The effects of lung microbiome in modulating host immunity and inflammation in the lung and distal organs are being elucidated. However, the precise mechanism by which members of microbiota produce structural ligands that interact with host genes and pathways remains largely uncharacterized. Multiple unique challenges, both technically and biologically, exist in the field of lung microbiome, necessitating the development of tailored experimental and analytical approaches to overcome the bottlenecks. In this review, we first provide an overview of the principles and methodologies in studying the lung microbiome. We next review current knowledge of the roles of lung microbiome in human diseases, highlighting mechanistic insights. We finally discuss critical challenges in the field and share our thoughts on broad topics for future investigation.

Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential.

METHODS

We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses.

RESULTS

An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%.

CONCLUSIONS

A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

A Journey on the Skin Microbiome: Pitfalls and Opportunities

The human skin microbiota is essential for maintaining homeostasis and ensuring barrier functions. Over the years, the characterization of its composition and taxonomic diversity has reached outstanding goals, with more than 10 million bacterial genes collected and cataloged. Nevertheless, the study of the skin microbiota presents specific challenges that need to be addressed in study design. Benchmarking procedures and reproducible and robust analysis workflows for increasing comparability among studies are required. For various reasons and because of specific technical problems, these issues have been investigated in gut microbiota studies, but they have been largely overlooked for skin microbiota. After a short description of the skin microbiota, the review tackles methodological aspects and their pitfalls, covering NGS approaches and high throughput culture-based techniques. Recent insights into the "core" and "transient" types of skin microbiota and how the manipulation of these communities can prevent or combat skin diseases are also covered. Finally, this review includes an overview of the main dermatological diseases, the changes in the microbiota composition associated with them, and the recommended skin sampling procedures. The last section focuses on topical and oral probiotics to improve and maintain skin health, considering their possible applications for skin diseases.

The lung microbiome: progress and promise

The healthy lung was long thought of as sterile, but recent advances using molecular sequencing approaches have detected bacteria at low levels. Healthy lung bacteria largely reflect communities present in the upper respiratory tract that enter the lung via microaspiration, which is balanced by mechanical and immune clearance and likely involves limited local replication. The nature and dynamics of the lung microbiome, therefore, differ from those of ecological niches with robust self-sustaining microbial communities. Aberrant populations (dysbiosis) have been demonstrated in many pulmonary diseases not traditionally considered microbial in origin, and potential pathways of microbe-host crosstalk are emerging. The question now is whether and how dysbiotic microbiota contribute to initiation or perpetuation of injury. The fungal microbiome and virome are less well studied. This Review highlights features of the lung microbiome, unique considerations in studying it, examples of dysbiosis in selected disease, emerging concepts in lung microbiome-host interactions, and critical areas for investigation.

Exploring the Clinical Utility of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infection

INTRODUCTION

We aimed to explore the real-world clinical application value and challenges of metagenomic next-generation sequencing (mNGS) for pulmonary infection diagnosis.

METHODS

We retrospectively reviewed the results of mNGS and conventional tests from 140 hospitalized patients with suspected pulmonary infections from January 2019 to December 2020. The sample types included bronchoalveolar lavage fluid, lung tissue by transbronchial lung biopsy, pleural effusion, blood, and bronchial sputum. Apart from the mNGS reports that our patients received, an extra comprehensive and thorough literature search was conducted.

RESULTS

Significant differences were noticed in the positive detection rates of pathogens between mNGS and conventional diagnostic testing (115/140, 82.14% vs 50/140, 35.71%, P < 0.05). The percentage of mNGS-positive patients was significantly higher than that of conventional testing-positive patients with regard to bacterial detection (P < 0.01), but no significant differences were found with regard to fungal detection (P = 0.67). Significant statistical differences were found between mixed infection cases (15, 22.70%) and single infection cases (4, 7.84%) in terms of diabetes (P = 0.03). The most frequent pattern of mixed infection was bacteria and fungi mixed infection (40, 40/89 = 44.94%), followed by bacteria mixed infection (29, 29/89 = 32.58%). The sensitivity of mNGS in pulmonary infection diagnosis was much higher than that of conventional test (89.17% vs 50.00%; P < 0.01), but the specificity was the opposite (75.00% vs 81.82%; P > 0.05).

CONCLUSION

mNGS is a valuable tool for the detection of pulmonary infections, especially mixed pulmonary infections. The most common combinations we found were bacterial-fungal coinfection and bacterial-bacterial coinfection. Still, there are many challenges in the clinical application of mNGS in the diagnosis of pulmonary infections. There is still a lot of work to be done in interpreting the mNGS reports, because both clinical judgment and literature analysis strategy need to be refined.

Pulmonary Microbiome of Patients Receiving Mechanical Ventilation: Changes Over Time

BACKGROUND

Interest in the pulmonary microbiome is growing, particularly in patients undergoing mechanical ventilation.

OBJECTIVES

To explore the pulmonary microbiome over time in patients undergoing prolonged mechanical ventilation and to evaluate the effect of an oral suctioning intervention on the microbiome.

METHODS

This descriptive subanalysis from a clinical trial involved a random sample of 16 participants (7 intervention, 9 control) who received mechanical ventilation for at least 5 days. Five paired oral and tracheal specimens were evaluated for each participant over time. Bacterial DNA from the paired specimens was evaluated using 16S rRNA gene sequencing. Bacterial taxonomy composition, α-diversity (Shannon index), and β-diversity (Morisita-Horn index) were calculated and compared within and between participants.

RESULTS

Participants were predominantly male (69%) and White (63%), with a mean age of 58 years, and underwent mechanical ventilation for a mean of 9.36 days. Abundant bacterial taxa included Prevotella, Staphylococcus, Streptococcus, Stenotrophomonas, and Veillonella. Mean tracheal α-diversity decreased over time for the total group (P = .002) and the control group (P = .02). β-Diversity was lower (P = .04) in the control group (1.905) than in the intervention group (2.607).

CONCLUSIONS

Prolonged mechanical ventilation was associated with changes in the pulmonary microbiome, with the control group having less diversity. The oral suctioning intervention may have reduced oral-tracheal bacterial transmission.

Diagnostic Value of Metagenomic Next-Generation Sequencing for the Detection of Pathogens in Bronchoalveolar Lavage Fluid in Ventilator-Associated Pneumonia Patients

Objective: To evaluate the diagnostic performance of metagenomic next-generation sequencing (mNGS) using bronchoalveolar lavage fluid (BALF) in patients with ventilator-associated pneumonia (VAP).

Methods: BALF samples of 72 patients with VAP were collected from August 2018 to May 2020. The diagnostic performance of conventional testing (CT) and mNGS methods were compared based on bacterial and fungal examinations. The diagnostic value of mNGS for viral and mixed infections was also analyzed.

Results: The percentage of mNGS positive samples was significantly higher than that estimated by the CT method [odds ratio (OR), 4.33; 95% confidence interval (CI), 1.78–10.53; p < 0.001]. The sensitivity and specificity of mNGS for bacterial detection were 97.1% (95% CI, 93.2–101.0%) and 42.1% (95 CI, 30.7–53.5%), respectively, whereas the positive predictive value (PPV) and the negative predictive value (NPV) were 60.0% (95% CI, 48.7–71.3%) and 94.1% (95% CI, 88.7–99.6%), respectively. A total of 38 samples were negative for bacterial detection as determined by the CT method, while 22 samples were positive as shown by the mNGS method. Conflicting results were obtained for three samples between the two methods of bacterial detection. However, no significant differences were noted between the mNGS and CT methods (OR, 1.42; 95% CI, 0.68–2.97; p = 0.46) with regard to fungal infections. The sensitivity and specificity of mNGS were 71.9% (95% CI, 61.5–82.3%) and 77.5% (95% CI, 67.9–87.1%), respectively. mNGS exhibited a PPV of 71.9% (95% CI, 61.5–82.3%) and an NPV of 77.5% (95% CI, 67.9–87.1%). A total of 9 out of 40 samples were found positive for fungi according to mNGS, whereas the CT method failed to present positive results in these samples. The mNGS and CT methods produced conflicting results with regard to fungal detection of the two samples. A total of 30 patients were virus-positive using mNGS. Furthermore, 42 patients (58.3%) were identified as pulmonary mixed infection cases.

Conclusions: mNGS detection using BALF improved the sensitivity and specificity of bacterial identification in patients who developed VAP. In addition, mNGS exhibited apparent advantages in detecting viruses and identifying mixed infections.

Modulation of gut mucosal microbiota as a mechanism of probiotics-based adjunctive therapy for ulcerative colitis

This was a pilot study aiming to evaluate the effects of probiotics as adjunctive treatment for ulcerative colitis (UC). Twenty-five active patients with UC were assigned to the probiotic (n = 12) and placebo (n = 13) groups. The probiotic group received mesalazine (60 mg kg-1  day-1 ) and oral probiotics (containing Lactobacillus casei Zhang, Lactobacillus plantarum P-8 and Bifidobacterium animalis subsp. lactis V9) twice daily for 12 weeks, while the placebo group received the same amounts of mesalazine and placebo. The clinical outcomes were assessed. The gut mucosal microbiota was profiled by PacBio single-molecule, real-time (SMRT) sequencing of the full-length 16S rRNA of biopsy samples obtained by colonoscopy. A significantly greater magnitude of reduction was observed in the UC disease activity index (UCDAI) in the probiotic group compared with the placebo group (P = 0.043), accompanying by a higher remission rate (91.67% for probiotic-receivers versus 69.23% for placebo-receivers, P = 0.034). The probiotics could protect from diminishing of the microbiota diversity and richness. Moreover, the gut mucosal microbiota of the probiotic-receivers had significantly more beneficial bacteria like Eubacterium ramulus (P < 0.05), Pediococcus pentosaceus (P < 0.05), Bacteroides fragilis (P = 0.02) and Weissella cibaria (P = 0.04). Additionally, the relative abundances of the beneficial bacteria correlated significantly but negatively with the UCDAI score, suggesting that the probiotics might alleviate UC symptoms by modulating the gut mucosal microbiota. Our research has provided new insights into the mechanism of symptom alleviation in UC by applying probiotic-based adjunctive treatment.

PCR coupled to electrospray ionization mass spectrometry for microbiological diagnosis and surveillance of ventilator-associated pneumonia

Etiological diagnosis is essential for anti-infective therapy in patients with ventilator-associated pneumonia (VAP). The present study aimed to evaluate the capacity of sequential PCR coupled to electrospray ionization mass spectrometry (PCR/ESI-MS) tests as a rapid diagnostic technique for patients with VAP. A total of 12 patients diagnosed with VAP were enrolled at the intensive care unit in Zhongshan Hospital, Fudan University. Mini-bronchoalveolar lavage fluid specimens were prospectively collected on VAP 0, 5 and 10 days following the beginning of mechanical ventilation. Routine clinical culture and PCR/ESI-MS were compared for identification of microorganisms in the specimens. A total of 51 bacterial species were detected by either of the two methods. The positive rates of routine clinical culture and PCR/ESI-MS were 38.2 and 88.2%, respectively. Out of the 16 specimens positive in routine cultures, 15 were also positive on PCR/ESI-MS, except for one, from which a mix of three distinct bacterial isolates were reported by culture. Among the 50 bacterial species identified by PCR/ESI-MS, 15 (35.7%) of the common VAP pathogens were confirmed by paired culture. Furthermore, of the 16 bacterial isolates that were finally confirmed to be responsible for VAP, 14 were identified by a sequential PCR/ESI-MS test concurrently when the culture results were obtained. PCR/ESI-MS identified pathogens that may cause VAP in 8 subjects prior to the occurrence of associated clinical manifestations. To conclude, PCR/ESI-MS was a potential rapid technique for diagnosis of VAP within 6 h. Regular respiratory specimen monitoring using PCR/ESI-MS provides information for selecting appropriate and adequate antibiotic therapies in ventilated patients.

Human microbiome: an academic update on human body site specific surveillance and its possible role

Human body is inhabited by vast number of microorganisms which form a complex ecological community and influence the human physiology, in the aspect of both health and diseases. These microbes show a relationship with the human immune system based on coevolution and, therefore, have a tremendous potential to contribute to the metabolic function, protection against the pathogen and in providing nutrients and energy. However, of these microbes, many carry out some functions that play a crucial role in the host physiology and may even cause diseases. The introduction of new molecular technologies such as transcriptomics, metagenomics and metabolomics has contributed to the upliftment on the findings of the microbiome linked to the humans in the recent past. These rapidly developing technologies are boosting our capacity to understand about the human body-associated microbiome and its association with the human health. The highlights of this review are inclusion of how to derive microbiome data and the interaction between human and associated microbiome to provide an insight on the role played by the microbiome in biological processes of the human body as well as the development of major human diseases.

Persistent Legionnaires' Disease and Associated Antibiotic Treatment Engender a Highly Disturbed Pulmonary Microbiome Enriched in Opportunistic Microorganisms

Despite the importance of pneumonia to public health, little is known about the composition of the lung microbiome during infectious diseases, such as pneumonia, and how it evolves during antibiotic therapy. To study the possible relation of the pulmonary microbiome to the severity and outcome of this respiratory disease, we analyzed the dynamics of the pathogen and the human lung microbiome during persistent infections caused by the bacterium Legionella pneumophila and their evolution during antimicrobial treatment. We collected 10 bronchoalveolar lavage fluid samples from three patients during long-term hospitalization due to pneumonia and performed a unique longitudinal study of the interkingdom microbiome, analyzing the samples for presence of bacteria, archaea, fungi, and protozoa by high-throughput Illumina sequencing of marker genes. The lung microbiome of the patients was characterized by a strong predominance of the pathogen, a low diversity of the bacterial fraction, and an increased presence of opportunistic microorganisms. The fungal fraction was more stable than the bacterial fraction. During long-term treatment, no genomic changes or antibiotic resistance-associated mutations that could explain the persistent infection occurred, according to whole-genome sequencing analyses of the pathogen. After antibiotic treatment, the microbiome did not recover rapidly but was mainly constituted of antibiotic-resistant species and enriched in bacteria, archaea, fungi, or protozoa associated with pathogenicity. The lung microbiome seems to contribute to nonresolving Legionella pneumonia, as it is strongly disturbed during infection and enriched in opportunistic and/or antibiotic-resistant bacteria and microorganisms, including fungi, archaea, and protozoa that are often associated with infections.IMPORTANCE The composition and dynamics of the lung microbiome during pneumonia are not known, although the lung microbiome might influence the severity and outcome of this infectious disease, similar to what was shown for the microbiome at other body sites. Here we report the findings of a comprehensive analysis of the lung microbiome composition of three patients with long-term pneumonia due to L. pneumophila and its evolution during antibiotic treatment. This work adds to our understanding of how the microbiome changes during disease and antibiotic treatment and points to microorganisms and their interactions that might be beneficial. In addition to bacteria and fungi, our analyses included archaea and eukaryotes (protozoa), showing that both are present in the pulmonary microbiota and that they might also play a role in the response to the microbiome disturbance.

Diagnosis of severe respiratory infections in immunocompromised patients

An increasing number of critically ill patients are immunocompromised. Acute hypoxemic respiratory failure (ARF), chiefly due to pulmonary infection, is the leading reason for ICU admission. Identifying the cause of ARF increases the chances of survival, but may be extremely challenging, as the underlying disease, treatments, and infection combine to create complex clinical pictures. In addition, there may be more than one infectious agent, and the pulmonary manifestations may be related to both infectious and non-infectious insults. Clinically or microbiologically documented bacterial pneumonia accounts for one-third of cases of ARF in immunocompromised patients. Early antibiotic therapy is recommended but decreases the chances of identifying the causative organism(s) to about 50%. Viruses are the second most common cause of severe respiratory infections. Positive tests for a virus in respiratory samples do not necessarily indicate a role for the virus in the current acute illness. Invasive fungal infections (Aspergillus, Mucorales, and Pneumocystis jirovecii) account for about 15% of severe respiratory infections, whereas parasites rarely cause severe acute infections in immunocompromised patients. This review focuses on the diagnosis of severe respiratory infections in immunocompromised patients. Special attention is given to newly validated diagnostic tests designed to be used on non-invasive samples or bronchoalveolar lavage fluid and capable of increasing the likelihood of an early etiological diagnosis.

Molecular Diagnostics in Pulmonary Infections

Infection of the lung parenchyma, or pneumonia, accounts for over four million deaths per year worldwide (Ferkol and Schraufnagel, Ann Am Thorac Soc 11:404–406, 2014). The condition is common, but also over-diagnosed, in part due to relatively poor laboratory and radiographic diagnostics. Indeed, we continue to rely on antiquated tools such as sputum culture and chest X-ray – the former of which lacks speed and sensitivity, and the latter specificity (Albaum et al. Chest 110:343–50, 1996). The resulting presumptive diagnoses of pneumonia lead to excessive use of empiric broad spectrum antibiotics; indeed, by some estimates, 30–70% of antibiotic prescriptions for lower respiratory tract infection are inappropriate (Kraus, PLoS One 12(3): e0174584, 2017). This approach begets microbial resistance, exposes patients to medication side effects, and puts patients at risk of potentially life-threatening complications including Clostridium difficile colitis.

To improve diagnostic certainty in patients with suspected pneumonia, we must begin to consider and implement emerging technologies for efficient and accurate characterization of host responses to infection and identification of pathogens. In this chapter, we will discuss precision diagnostics already in common practice and those poised to be, and how these tools may ultimately enable personalization in the diagnosis of pneumonia.

Dynamics of microbiota during mechanical ventilation in aspiration pneumonia

BACKGROUND

The emergence of multi-drug resistant pathogens is an urgent health-related problem, and the appropriate use of antibiotics is imperative. It is often difficult to identify the causative bacteria in patients with aspiration pneumonia because tracheal aspirate contains contaminants of oral bacteria. We investigated the dynamics of microbiota in mechanically ventilated patients with aspiration pneumonia to develop a treatment strategy.

METHODS

Twenty-two intubated patients with aspiration pneumonia were recruited. Saliva and tracheal aspirate of the subjects were collected at three time points: (A) within 2 h after intubation, (B) just before administration of antibiotics, and (C) 48-72 h after administration of antibiotics. The microbiota in each specimen was analyzed by using the 16S rRNA gene clone library sequencing method. Bacterial floras of the samples were analyzed by principal component analysis.

RESULTS

Principal component analysis based on the composition of genus revealed that although the changes of microbiota in the saliva from (A) to (B) were not clear, the composition of anaerobes in the tracheal aspirate (B) was lower than (A). In fact, the reduction of anaerobes, not in the saliva but in the tracheal aspirate from (A) to (B), was confirmed by incident rate ratios estimated by a multilevel Poisson regression model (p < 0.001). The extent of decrease in anaerobes was fully dependent on the time difference between the sampling of tracheal aspirate (A) and (B)-in particular, over 3 h of mechanical ventilation. This indicates that the alterations of microbiota (involving the reduction of anaerobes in the lower respiratory tract) occurred during mechanical ventilation prior to the administration of antibiotics. After the administration of antibiotics, Enterobacter spp., Corynebacterium spp., Pseudomonas aeruginosa, Klebsiella pneumoniae, Staphylococcus aureus, and Granulicatera adiacens were predominantly detected in the tracheal aspirate (C).

CONCLUSION

The microbiota of the lower respiratory tract changes dynamically during mechanical ventilation and during the administration of antibiotics in intubated patients with aspiration pneumonia. Antibiotics should be selected on the premise that dynamic changes in microbiota (involved in the reduction of anaerobes) may occur during the mechanical ventilation in these patients.

Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

Background

Metagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce.

Methods

From July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared.

Results

The sensitivity of mNGS in mixed pulmonary infection diagnosis was much higher than that of conventional test (97.2% vs 13.9%; P < 0.01), but the specificity was the opposite (63.2% vs 94.7%; P = 0.07). The positive predictive value of mNGS was 83.3% (95% CI, 68.0–92.5%), and the negative predictive value was 92.3% (95% CI, 62.1–99.6%). A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1 (1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1 (1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected by mNGS was Human cytomegalovirus in our study, which was identified in 19 (34.5%) cases of mixed pulmonary infection. Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7 (12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection.

Conclusions

mNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.

Trial registration

(retrospectively registered): ChiCTR1900023727. Registrated 9 JUNE 2019.

The Response of Microbiota Community to Streptococcus agalactiae Infection in Zebrafish Intestine

Recently, Streptococcus agalactiae has become a major pathogen leading to Streptococcosis. To understand the physiological responses of zebrafish (Danio rerio) to S. agalactiae, the intestinal microbiota composition of the intestine (12 and 24 h post-infection, hpi, respectively) in zebrafish infected with S. agalactiae were investigated. The intestinal bacterial composition was analyzed using PacBio high-throughput full-length 16S rRNA gene sequencing. The most predominant bacteria in the zebrafish intestine were the Fusobacteria phylum and Sphingomonas genus. S. agalactiae infection affected the composition of partially intestinal microbiota. At the species level, the relative abundance of the pathogenic intestinal bacteria Aeromonas veronii, S. agalactiae, and Clostridium tarantellae significantly increased after S. agalactiae infection (p < 0.05), while that of the beneficial intestinal bacteria Bacillus licheniformis, Comamonas koreensis, and Romboutsia ilealis significantly decreased (p < 0.05), showing that S. agalactiae infection aggravates the zebrafish disease through promoting abundance of other intestinal pathogenic bacteria. This study is the first PacBio analyses of the zebrafish intestinal microbiota community under pathogenic infection. Results suggest that the S. agalactiae infection alters the intestinal flora structure in zebrafish.

Development of a reference data set for assigning Streptococcus and Enterococcus species based on next generation sequencing of the 16S-23S rRNA region

Background

Many members of Streptococcus and Enterococcus genera are clinically relevant opportunistic pathogens warranting accurate and rapid identification for targeted therapy. Currently, the developed method based on next generation sequencing (NGS) of the 16S-23S rRNA region proved to be a rapid, reliable and precise approach for species identification directly from polymicrobial and challenging clinical samples. The introduction of this new method to routine diagnostics is hindered by a lack of the reference sequences for the 16S-23S rRNA region for many bacterial species. The aim of this study was to develop a careful assignment for streptococcal and enterococcal species based on NGS of the 16S-23S rRNA region.

Methods

Thirty two strains recovered from clinical samples and 19 reference strains representing 42 streptococcal species and nine enterococcal species were subjected to bacterial identification by four Sanger-based sequencing methods targeting the genes encoding (i) 16S rRNA, (ii) sodA, (iii) tuf and (iv) rpoB; and NGS of the 16S-23S rRNA region.

Results

This study allowed obtainment and deposition of reference sequences of the 16S-23S rRNA region for 15 streptococcal and 3 enterococcal species followed by enrichment for 27 and 6 species, respectively, for which reference sequences were available in the databases. For Streptococcus, NGS of the 16S-23S rRNA region was as discriminative as Sanger sequencing of the tuf and rpoB genes allowing for an unambiguous identification of 93% of analyzed species. For Enterococcus, sodA, tuf and rpoB genes sequencing allowed for identification of all species, while the NGS-based method did not allow for identification of only one enterococcal species. For both genera, the sequence analysis of the 16S rRNA gene was endowed with a low identification potential and was inferior to that of other tested identification methods. Moreover, in case of phylogenetically related species the sequence analysis of only the intergenic spacer region was not sufficient enough to precisely identify Streptococcus strains at the species level.

Conclusions

Based on the developed reference dataset, clinically relevant streptococcal and enterococcal species can now be reliably identified by 16S-23S rRNA sequences in samples. This study will be useful for introduction of a novel diagnostic tool, NGS of the 16S-23S rRNA region, which undoubtedly is an improvement for reliable culture-independent species identification directly from polymicrobially constituted clinical samples.

Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practice

Background

Metagenomic next-generation sequencing (mNGS) was suggested to potentially replace traditional microbiological methodology because of its comprehensiveness. However, clinical experience with application of the test is relatively limited.

Methods

From April 2017 to December 2017, 511 specimens were collected, and their retrospective diagnoses were classified into infectious disease (347 [67.9%]), noninfectious disease (119 [23.3%]), and unknown cases (45 [8.8%]). The diagnostic performance of pathogens was compared between mNGS and culture. The effect of antibiotic exposure on detection rate was also assessed.

Results

The sensitivity and specificity of mNGS for diagnosing infectious disease were 50.7% and 85.7%, respectively, and these values outperformed those of culture, especially for Mycobacterium tuberculosis (odds ratio [OR], 4 [95% confidence interval {CI}, 1.7-10.8]; P < .01), viruses (mNGS only; P < .01), anaerobes (OR, ∞ [95% CI, 1.71-∞]; P < .01) and fungi (OR, 4.0 [95% CI, 1.6-10.3]; P < .01). Importantly, for mNGS-positive cases where the conventional method was inconclusive, 43 (61%) cases led to diagnosis modification, and 41 (58%) cases were not covered by empirical antibiotics. For cases where viruses were identified, broad-spectrum antibiotics were commonly administered (14/27), and 10 of 27 of these cases were suspected to be inappropriate. Interestingly, the sensitivity of mNGS was superior to that of culture (52.5% vs 34.2%; P < .01) in cases with, but not without, antibiotic exposure.

Conclusions

mNGS could yield a higher sensitivity for pathogen identification and is less affected by prior antibiotic exposure, thereby emerging as a promising technology for detecting infectious diseases.

Acinetobacter baumannii Is a Risk Factor for Lower Respiratory Tract Infections in Children and Adolescents With a Tracheostomy

BACKGROUND

Lower respiratory tract infections (LRIs) are a major cause of hospitalization for children and adolescents with a tracheostomy. The aim of this study was to identify risk factors for LRI.

METHODS

In this retrospective study, we assessed the number of LRI and hospitalizations for LRI from 2004 to 2014 at the University Hospital Muenster Pediatric Department. We analyzed associations between LRI and clinical findings, and we cultured pathogens in tracheal aspirates (TAs) during noninfection periods. Univariable and multivariable negative, binomial regression analyses were applied to identify associations between possible risk factors and LRI.

RESULTS

Seventy-eight patients had 148 LRI, of which 99 were treated in hospital. The median number of LRI per year was 0.4. Six-hundred thirteen pathogens were detected in 315 specimens; Staphylococcus aureus (22.5%), Pseudomonas aeruginosa (14.8%) and Haemophilus influenzae (6.2%) were most frequently detected. Acinetobacter baumannii is an independent risk factor for LRI (rate ratio, 1.792; P = 0.030) and hospital admissions for LRI (rate ratio, 1.917; P = 0.011).

CONCLUSIONS

Children with a tracheostomy have frequent LRI. A. baumannii but not P. aeruginosa or S. aureus in TA is a risk factor for LRI in children with a long-term tracheostomy. This supports repetitive culture of TA for microbiologic workup to identify children and adolescents with an increased risk for LRI.

Development and Validation of a Reference Data Set for Assigning Staphylococcus Species Based on Next-Generation Sequencing of the 16S-23S rRNA Region

Many members of the Staphylococcus genus are clinically relevant opportunistic pathogens that warrant accurate and rapid identification for targeted therapy. The aim of this study was to develop a careful assignment scheme for staphylococcal species based on next-generation sequencing (NGS) of the 16S-23S rRNA region. All reference staphylococcal strains were identified at the species level using Sanger sequencing of the 16S rRNA, sodA, tuf, and rpoB genes and NGS of the 16S-23S rRNA region. To broaden the database, an additional 100 staphylococcal strains, including 29 species, were identified by routine diagnostic methods, 16S rRNA Sanger sequencing and NGS of the 16S-23S rRNA region. The results enabled development of reference sequences encompassing the 16S-23S rRNA region for 50 species (including one newly proposed species) and 6 subspecies of the Staphylococcus genus. This study showed sodA and rpoB targets were the most discriminative but NGS of the 16S-23S rRNA region was more discriminative than tuf gene sequencing and much more discriminative than 16S rRNA gene sequencing. Almost all Staphylococcus species could be distinguished when the max score was 99.0% or higher and the sequence similarity between the best and second best species was equal to or >0.2% (min. 9 nucleotides). This study allowed development of reference sequences for 21 staphylococcal species and enrichment for 29 species for which sequences were publicly available. We confirmed the usefulness of NGS of the 16S-23S rRNA region by identifying the whole species content in 45 clinical samples and comparing the results to those obtained using routine diagnostic methods. Based on the developed reference database, all staphylococcal species can be reliably detected based on the 16S-23S rRNA sequences in samples composed of both single species and more complex polymicrobial communities. This study will be useful for introduction of a novel diagnostic tool, which undoubtedly is an improvement for reliable species identification in polymicrobial samples. The introduction of this new method is hindered by a lack of reference sequences for the 16S-23S rRNA region for many bacterial species. The results will allow identification of all Staphylococcus species, which are clinically relevant pathogens.

The respiratory microbiota: new insights into pulmonary tuberculosis

Background

Previous studies demonstrated that the diversity and composition of respiratory microbiota in TB patients were different from healthy individuals. Therefore, the aim of the present analysis was to estimate the relative proportion of respiratory microbiota at phylum and genus levels among TB cases and healthy controls.

Methods

The PubMed and Google Scholar online databases were searched to retrieve relevant studies for the analysis. The statistical analysis was done using STATA version 11, pooled estimates are presented using graphs. The summary of findings in included studies is also presented in Table 1.

Results

The phylum level analysis shows that the pooled proportions of Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, and Crenarchaeota were determined among tuberculosis patients and healthy controls. In brief, Firmicutes, and Proteobacteria were the most abundant bacterial phyla in both TB cases and healthy controls, composing 39.9 and 22.7% in TB cases and 39.4 and 19.5% in healthy controls, respectively. The genus level analysis noted that Streptococcus (35.01%), Neisseria (27.1%), Prevotella (9.02%) and Veillonella (7.8%) were abundant in TB patients. The Prevotella (36.9%), Gammaproteobacteria (22%), Streptococcus (19.2%) and Haemophilus (15.4%) were largely seen in healthy controls. Interestingly, Veillonella, Rothia, Leuconostoc were unique to TB cases, whereas Lactobacillus, and Gammaproteobacteria, Haemophilus, and Actinobacillus were identified only in healthy controls.

Conclusion

The composition of the respiratory microbiota in TB patients and healthy controls were quite different. More deep sequencing studies are needed to explore the microbial variation in the respiratory system in connection with TB.

Integrative Physiology of Pneumonia

Pneumonia is a type of acute lower respiratory infection that is common and severe. The outcome of lower respiratory infection is determined by the degrees to which immunity is protective and inflammation is damaging. Intercellular and interorgan signaling networks coordinate these actions to fight infection and protect the tissue. Cells residing in the lung initiate and steer these responses, with additional immunity effectors recruited from the bloodstream. Responses of extrapulmonary tissues, including the liver, bone marrow, and others, are essential to resistance and resilience. Responses in the lung and extrapulmonary organs can also be counterproductive and drive acute and chronic comorbidities after respiratory infection. This review discusses cell-specific and organ-specific roles in the integrated physiological response to acute lung infection, and the mechanisms by which intercellular and interorgan signaling contribute to host defense and healthy respiratory physiology or to acute lung injury, chronic pulmonary disease, and adverse extrapulmonary sequelae. Pneumonia should no longer be perceived as simply an acute infection of the lung. Pneumonia susceptibility reflects ongoing and poorly understood chronic conditions, and pneumonia results in diverse and often persistent deleterious consequences for multiple physiological systems.

High Throughput Manufacturing of Bacteriophages Using Continuous Stirred Tank Bioreactors Connected in Series to Ensure Optimum Host Bacteria Physiology for Phage Production

Future industrial demand for large quantities of bacteriophages e.g., for phage therapy, necessitates the development of scalable Good Manufacturing Practice compliant (cGMP) production platforms. The continuous production of high titres of E coli T3 phages (10¹¹ PFU mL⁻¹) was achieved using two continuous stirred tank bioreactors connected in series, and a third bioreactor was used as a final holding tank operated in semi-batch mode to finish the infection process. The first bioreactor allowed the steady-state propagation of host bacteria using a fully synthetic medium with glucose as the limiting substrate. Host bacterial growth was decoupled from the phage production reactor downstream of it to suppress the production of phage-resistant mutants, thereby allowing stable operation over a period of several days. The novelty of this process is that the manipulation of the host reactor dilution rates (range 0.1–0.6 hr⁻¹) allows control over the physiological state of the bacterial population. This results in bacteria with considerably higher intracellular phage production capability whilst operating at high dilution rates yielding significantly higher overall phage process productivity. Using a pilot-scale chemostat system allowed optimisation of the upstream phage amplification conditions conducive for high intracellular phage production in the host bacteria. The effect of the host reactor dilution rates on the phage burst size, lag time, and adsorption rate were evaluated. The host bacterium physiology was found to influence phage burst size, thereby affecting the productivity of the overall process. Mathematical modelling of the dynamics of the process allowed parameter sensitivity evaluation and provided valuable insights into the factors affecting the phage production process. The approach presented here may be used at an industrial scale to significantly improve process control, increase productivity via process intensification, and reduce process manufacturing costs through process footprint reduction.

Nanoencapsulation of Bacteriophages in Liposomes Prepared Using Microfluidic Hydrodynamic Flow Focusing

Increasing antibiotic resistance in pathogenic microorganisms has led to renewed interest in bacteriophage therapy in both humans and animals. A “Trojan Horse” approach utilizing liposome encapsulated phages may facilitate access to phagocytic cells infected with intracellular pathogens residing therein, e.g., to treat infections caused by Mycobacterium tuberculosis, Listeria, Salmonella, and Staphylococcus sp. Additionally, liposome encapsulated phages may adhere to and diffuse within mucosa harboring resistant bacteria which are challenges in treating respiratory and gastrointestinal infections. Orally delivered phages tend to have short residence times in the gastrointestinal tract due to clinical symptoms such as diarrhea; this may be addressed through mucoadhesion of liposomes. In the present study we have evaluated the use of a microfluidic based technique for the encapsulation of bacteriophages in liposomes having mean sizes between 100 and 300 nm. Encapsulation of two model phages was undertaken, an Escherichia coli T3 podovirus (size ~65 nm) and a myovirus Staphylococcus aureus phage K (capsid head ~80 nm and phage tail length ~200 nm). The yield of encapsulated T3 phages was 10⁹ PFU/ml and for phage K was much lower at 10⁵ PFU/ml. The encapsulation yield for E. coli T3 phages was affected by aggregation of T3 phages. S. aureus phage K was found to interact with the liposome lipid bilayer resulting in large numbers of phages bound to the outside of the formed liposomes instead of being trapped inside them. We were able to inactivate the liposome bound S. aureus K phages whilst retaining the activity of the encapsulated phages in order to estimate the yield of microfluidic encapsulation of large tailed phages. Previous published studies on phage encapsulation in liposomes may have overestimated the yield of encapsulated tailed phages. This overestimation may affect the efficacy of phage dose delivered at the site of infection. Externally bound phages would be inactivated in the stomach acid resulting in low doses of phages delivered at the site of infection further downstream in the gastrointestinal tract.

High-Glucose or -Fructose Diet Cause Changes of the Gut Microbiota and Metabolic Disorders in Mice without Body Weight Change

High fat diet-induced changes in gut microbiota have been linked to intestinal permeability and metabolic endotoxemia, which is related to metabolic disorders. However, the influence of a high-glucose (HGD) or high-fructose (HFrD) diet on gut microbiota is largely unknown. We performed changes of gut microbiota in HGD- or HFrD-fed C57BL/6J mice by 16S rRNA analysis. Gut microbiota-derived endotoxin-induced metabolic disorders were evaluated by glucose and insulin tolerance test, gut permeability, Western blot and histological analysis. We found that the HGD and HFrD groups had comparatively higher blood glucose and endotoxin levels, fat mass, dyslipidemia, and glucose intolerance without changes in bodyweight. The HGD- and HFrD-fed mice lost gut microbial diversity, characterized by a lower proportion of Bacteroidetes and a markedly increased proportion of Proteobacteria. Moreover, the HGD and HFrD groups had increased gut permeability due to alterations to the tight junction proteins caused by gut inflammation. Hepatic inflammation and lipid accumulation were also markedly increased in the HGD and HFrD groups. High levels of glucose or fructose in the diet regulate the gut microbiota and increase intestinal permeability, which precedes the development of metabolic endotoxemia, inflammation, and lipid accumulation, ultimately leading to hepatic steatosis and normal-weight obesity.

Respiratory microbiota and lower respiratory tract disease

INTRODUCTION

The respiratory airways harbor a complex succession of ecological niches with distinct but related bacterial communities. Particular challenges of respiratory microbiome research have led to limited scientific output compared to other human microbiomes. Areas covered: In this review, we summarize the current state of knowledge of the bacterial respiratory microbiome, with a particular focus on associations between the respiratory microbiome and lower respiratory tract conditions. Expert commentary: There is growing evidence that the respiratory microbiome is associated with lower respiratory infectious diseases and related conditions. Most respiratory microbiome reports are metataxonomic cross-sectional or case-control studies with relatively small sample sizes. Large, prospective projects with metatranscriptomics or metabolomics approach are needed to unravel the effect of the respiratory microbiome on health-related conditions. Moreover, standardization in sampling, library preparation, sequencing techniques and data analysis should be encouraged.

Profiling of Oral Microbiota in Early Childhood Caries Using Single-Molecule Real-Time Sequencing

Background: Alterations of oral microbiota are the main cause of the progression of caries. The goal of this study was to characterize the oral microbiota in childhood caries based on single-molecule real-time sequencing. Methods: A total of 21 preschoolers, aged 3-5 years old with severe early childhood caries, and 20 age-matched, caries-free children as controls were recruited. Saliva samples were collected, followed by DNA extraction, Pacbio sequencing, and phylogenetic analyses of the oral microbial communities. Results: Eight hundred and seventy six species derived from 13 known bacterial phyla and 110 genera were detected from 41 children using Pacbio sequencing. At the species level, 38 species, including Veillonella spp., Streptococcus spp., Prevotella spp., and Lactobacillus spp., showed higher abundance in the caries group compared to the caries-free group (p < 0.05). The core microbiota at the genus and species levels was more stable in the caries-free micro-ecological niche. At follow-up, oral examinations 6 months after sample collection, development of new dental caries was observed in 5 children (the transitional group) among the 21 caries free children. Compared with the caries-free children, in the transitional and caries groups, 6 species, which were more abundant in the caries-free group, exhibited a relatively low abundance in both the caries group and the transitional group (p < 0.05). We conclude that Abiotrophia spp., Neisseria spp., and Veillonella spp., might be associated with healthy oral microbial ecosystem. Prevotella spp., Lactobacillus spp., Dialister spp., and Filifactor spp. may be related to the pathogenesis and progression of dental caries.

The temporal dynamics of the tracheal microbiome in tracheostomised patients with and without lower respiratory infections

BACKGROUND

Airway microbiota dynamics during lower respiratory infection (LRI) are still poorly understood due, in part, to insufficient longitudinal studies and lack of uncontaminated lower airways samples. Furthermore, the similarity between upper and lower airway microbiomes is still under debate. Here we compare the diversity and temporal dynamics of microbiotas directly sampled from the trachea via tracheostomy in patients with (YLRI) and without (NLRI) lower respiratory infections.

METHODS

We prospectively collected 127 tracheal aspirates across four consecutive meteorological seasons (quarters) from 40 patients, of whom 20 developed LRIs and 20 remained healthy. All aspirates were collected when patients had no LRI. We generated 16S rRNA-based microbial profiles (~250 bp) in a MiSeq platform and analyzed them using Mothur and the SILVAv123 database. Differences in microbial diversity and taxon normalized (via negative binomial distribution) abundances were assessed using linear mixed effects models and multivariate analysis of variance.

RESULTS AND DISCUSSION

Alpha-diversity (ACE, Fisher and phylogenetic diversity) and beta-diversity (Bray-Curtis, Jaccard and Unifrac distances) indices varied significantly (P<0.05) between NLRI and YLRI microbiotas from tracheostomised patients. Additionally, Haemophilus was significantly (P = 0.009) more abundant in YLRI patients than in NLRI patients, while Acinetobacter, Corynebacterium and Pseudomonas (P<0.05) showed the inverse relationship. We did not detect significant differences in diversity and bacterial abundance among seasons. This result disagrees with previous evidence suggesting seasonal variation in airway microbiotas. Further study is needed to address the interaction between microbes and LRI during times of health and disease.

The Human Microbiome and Understanding the 16S rRNA Gene in Translational Nursing Science

BACKGROUND

As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and healthcare practitioners to analyze these microbial communities and their role in health and disease. 16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings.

OBJECTIVES

The objectives of this review are to (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung, and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science.

DISCUSSION

Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists-individuals uniquely positioned to utilize these techniques in future studies in clinical settings.

Nasopharyngeal microbiome in premature infants and stability during rhinovirus infection

RATIONALE

The nasopharyngeal (NP) microbiota of newborns and infants plays a key role in modulating airway inflammation and respiratory symptoms during viral infections. Premature (PM) birth modifies the early NP environment and is a major risk factor for severe viral respiratory infections. However, it is currently unknown if the NP microbiota of PM infants is altered relative to full-term (FT) individuals.

OBJECTIVES

To characterize the NP microbiota differences in preterm and FT infants during rhinovirus (RV) infection.

METHODS

We determined the NP microbiota of infants 6 months to ≤2 years of age born FT (n=6) or severely PM<32 weeks gestation (n=7). We compared microbiota composition in healthy NP samples and performed a longitudinal analysis during naturally occurring RV infections to contrast the microbiota dynamics in PM versus FT infants.

RESULTS

We observed significant differences in the NP bacterial community of PM versus FT. NP from PM infants had higher within-group dissimilarity (heterogeneity) relative to FT infants. Bacterial composition of NP samples from PM infants showed increased Proteobacteria and decreased in Firmicutes. There were also differences in the major taxonomic groups identified, including Streptococcus, Moraxella, and Haemophilus. Longitudinal data showed that these prematurity-related microbiota features persisted during RV infection.

CONCLUSIONS

PM is associated with NP microbiota changes beyond the neonatal stage. PM infants have an NP microbiota with high heterogeneity relative to FT infants. These prematurity-related microbiota features persisted during RV infection, suggesting that the NP microbiota of PM may play an important role in modulating airway inflammatory and immune responses in this vulnerable group.

Analysis of the Vaginal Microbiome by Next-Generation Sequencing and Evaluation of its Performance as a Clinical Diagnostic Tool in Vaginitis

Background

Next-generation sequencing (NGS) can detect many more microorganisms of a microbiome than traditional methods. This study aimed to analyze the vaginal microbiomes of Korean women by using NGS that included bacteria and other microorganisms. The NGS results were compared with the results of other assays, and NGS was evaluated for its feasibility for predicting vaginitis.

Methods

In total, 89 vaginal swab specimens were collected. Microscopic examinations of Gram staining and microbiological cultures were conducted on 67 specimens. NGS was performed with GS junior system on all of the vaginal specimens for the 16S rRNA, internal transcribed spacer (ITS), and Tvk genes to detect bacteria, fungi, and Trichomonas vaginalis. In addition, DNA probe assays of the Candida spp., Gardnerella vaginalis, and Trichomonas vaginalis were performed. Various predictors of diversity that were obtained from the NGS data were analyzed to predict vaginitis.

Results

ITS sequences were obtained in most of the specimens (56.2%). The compositions of the intermediate and vaginitis Nugent score groups were similar to each other but differed from the composition of the normal score group. The fraction of the Lactobacillus spp. showed the highest area under the curve value (0.8559) in ROC curve analysis. The NGS and DNA probe assay results showed good agreement (range, 86.2-89.7%).

Conclusions

Fungi as well as bacteria should be considered for the investigation of vaginal microbiome. The intermediate and vaginitis Nugent score groups were indistinguishable in NGS. NGS is a promising diagnostic tool of the vaginal microbiome and vaginitis, although some problems need to be resolved.

Mycoplasma pneumoniae and Streptococcus pneumoniae caused different microbial structure and correlation network in lung microbiota

Pneumonia is one of the most serious diseases for children, with which lung microbiota are proved to be associated. We performed 16S rDNA analysis on broncho-alveolar lavage fluid (BALF) for 32 children with tracheomalacia (C group), pneumonia infected with Streptococcus pneumoniae (S. pneumoniae) (D1 group) or Mycoplasma pneumoniae (M. pneumoniae) (D2 group). Children with tracheomalacia held lower microbial diversity and accumulated Lactococcus (mean ± SD, 45.21%±5.07%, P value <0.05), Porphyromonas (0.12%±0.31%, P value <0.05). D1 and D2 group were enriched by Streptococcus (7.57%±11.61%, P value <0.01 when compared with D2 group) and Mycoplasma (0.67%±1.25%, P value <0.01) respectively. Bacterial correlation in C group was mainly intermediated by Pseudomonas and Arthrobacter. Whilst, D1 group harbored simplest microbial correlation in three groups, and D2 group held the most complicated network, involving enriched Staphylococcus (0.26%±0.71%), Massilia (0.81%±2.42%). This will be of significance for understanding pneumonia incidence and progression more comprehensively, and discerning between bacterial infection and carriage.

The human microbiota: novel targets for hospital-acquired infections and antibiotic resistance

PURPOSE

Hospital-acquired infections are increasing in frequency due to multidrug resistant organisms (MDROs), and the spread of MDROs has eroded our ability to treat infections. Health care professionals cannot rely solely on traditional infection control measures and antimicrobial stewardship to prevent MDRO transmission. We review research on the microbiota as a target for infection control interventions.

METHODS

We performed a literature review of key research findings related to the microbiota as a target for infection control interventions. These data are summarized and used to outline challenges, opportunities, and unanswered questions in the field.

RESULTS

The healthy microbiota provides protective functions including colonization resistance, which refers to the microbiota's ability to prevent colonization and/or expansion of pathogens. Antibiotic use and other exposures in hospitalized patients are associated with disruptions of the microbiota that may reduce colonization resistance and select for antibiotic resistance. Novel methods to exploit protective mechanisms provided by an intact microbiota may provide the key to preventing the spread of MDROs in the health care setting.

CONCLUSIONS

Research on the microbiota as a target for infection control has been limited. Epidemiologic studies will facilitate progress toward the goal of manipulating the microbiota for control of MDROs in the health care setting.