The Lung Microbiome.

Although the lungs were once considered a sterile environment, advances in sequencing technology have revealed dynamic, low-biomass communities in the respiratory tract, even in health. Key features of these communities-composition, diversity, and burden-are consistently altered in lung disease, associate with host physiology and immunity, and can predict clinical outcomes. Although initial studies of the lung microbiome were descriptive, recent studies have leveraged advances in technology to identify metabolically active microbes and potential associations with their immunomodulatory by-products and lung disease. In this brief review, we discuss novel insights in airway disease and parenchymal lung disease, exploring host-microbiome interactions in disease pathogenesis. We also discuss complex interactions between gut and oropharyngeal microbiota and lung immunobiology. Our advancing knowledge of the lung microbiome will provide disease targets in acute and chronic lung disease and may facilitate the development of new therapeutic strategies.

The Lung Microbiome Predicts Mortality and Response to Azithromycin in Lung Transplant Recipients with Chronic Rejection.

Rationale: Chronic lung allograft dysfunction (CLAD) is the leading cause of death after lung transplant, and azithromycin has variable efficacy in CLAD. The lung microbiome is a risk factor for developing CLAD, but the relationship between lung dysbiosis, pulmonary inflammation, and allograft dysfunction remains poorly understood. Whether lung microbiota predict outcomes or modify treatment response after CLAD is unknown. Objectives: To determine whether lung microbiota predict post-CLAD outcomes and clinical response to azithromycin. Methods: Retrospective cohort study using acellular BAL fluid prospectively collected from recipients of lung transplant within 90 days of CLAD onset. Lung microbiota were characterized using 16S rRNA gene sequencing and droplet digital PCR. In two additional cohorts, causal relationships of dysbiosis and inflammation were evaluated by comparing lung microbiota with CLAD-associated cytokines and measuring ex vivo P. aeruginosa growth in sterilized BAL fluid. Measurements and Main Results: Patients with higher bacterial burden had shorter post-CLAD survival, independent of CLAD phenotype, azithromycin treatment, and relevant covariates. Azithromycin treatment improved survival in patients with high bacterial burden but had negligible impact on patients with low or moderate burden. Lung bacterial burden was positively associated with CLAD-associated cytokines, and ex vivo growth of P. aeruginosa was augmented in BAL fluid from transplant recipients with CLAD. Conclusions: In recipients of lung transplants with chronic rejection, increased lung bacterial burden is an independent risk factor for mortality and predicts clinical response to azithromycin. Lung bacterial dysbiosis is associated with alveolar inflammation and may be promoted by underlying lung allograft dysfunction.

Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells - United States, 2023.

During July 7-11, 2023, CDC received reports of two patients in different states with a tuberculosis (TB) diagnosis following spinal surgical procedures that used bone allografts containing live cells from the same deceased donor. An outbreak associated with a similar product manufactured by the same tissue establishment (i.e., manufacturer) occurred in 2021. Because of concern that these cases represented a second outbreak, CDC and the Food and Drug Administration worked with the tissue establishment to determine that this product was obtained from a donor different from the one implicated in the 2021 outbreak and learned that the bone allograft product was distributed to 13 health care facilities in seven states. Notifications to all seven states occurred on July 12. As of December 20, 2023, five of 36 surgical bone allograft recipients received laboratory-confirmed TB disease diagnoses; two patients died of TB. Whole-genome sequencing demonstrated close genetic relatedness between positive Mycobacterium tuberculosis cultures from surgical recipients and unused product. Although the bone product had tested negative by nucleic acid amplification testing before distribution, M. tuberculosis culture of unused product was not performed until after the outbreak was recognized. The public health response prevented up to 53 additional surgical procedures using allografts from that donor; additional measures to protect patients from tissue-transmitted M. tuberculosis are urgently needed.

The Gut Microbiome Modulates Body Temperature Both in Sepsis and Health.

Rationale: Among patients with sepsis, variation in temperature trajectories predicts clinical outcomes. In healthy individuals, normal body temperature is variable and has decreased consistently since the 1860s. The biologic underpinnings of this temperature variation in disease and health are unknown. Objectives: To establish and interrogate the role of the gut microbiome in calibrating body temperature. Methods: We performed a series of translational analyses and experiments to determine whether and how variation in gut microbiota explains variation in body temperature in sepsis and in health. We studied patient temperature trajectories using electronic medical record data. We characterized gut microbiota in hospitalized patients using 16S ribosomal RNA gene sequencing. We modeled sepsis using intraperitoneal LPS in mice and modulated the microbiome using antibiotics, germ-free, and gnotobiotic animals. Measurements and Main Results: Consistent with prior work, we identified four temperature trajectories in patients hospitalized with sepsis that predicted clinical outcomes. In a separate cohort of 116 hospitalized patients, we found that the composition of patients' gut microbiota at admission predicted their temperature trajectories. Compared with conventional mice, germ-free mice had reduced temperature loss during experimental sepsis. Among conventional mice, heterogeneity of temperature response in sepsis was strongly explained by variation in gut microbiota. Healthy germ-free and antibiotic-treated mice both had lower basal body temperatures compared with control animals. The Lachnospiraceae family was consistently associated with temperature trajectories in hospitalized patients, experimental sepsis, and antibiotic-treated mice. Conclusions: The gut microbiome is a key modulator of body temperature variation in both health and critical illness and is thus a major, understudied target for modulating physiologic heterogeneity in sepsis.

Commensal Oral Microbiota, Disease Severity and Mortality in Fibrotic Lung Disease.

RATIONALE: Oral microbiota associate with diseases of the mouth and serve as a source of lung microbiota. However, the role of oral microbiota in lung disease is unknown. OBJECTIVES: To determine associations between oral microbiota and disease severity and death in idiopathic pulmonary fibrosis. METHODS: We analyzed 16S rRNA gene and shotgun metagenomic sequencing data of buccal swabs from 511 patients with idiopathic pulmonary fibrosis in the multicenter CleanUP-IPF trial. Buccal swabs were collected from usual care, and antimicrobial cohorts. Microbiome data was correlated with measures of disease severity using principal component analysis and linear regression models. Associations between the buccal microbiome and mortality were determined using Cox additive models, Kaplan Meier analysis and Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS: Greater buccal microbial diversity associated with lower forced vital capacity (FVC) at baseline [mean diff -3.60: 95% CI -5.92 to -1.29 percent predicted FVC per 1 unit increment]. The buccal proportion of Streptococcus correlated positively with FVC [mean diff 0.80: 95% CI 0.16-1.43 percent predicted per 10% increase] (n=490). Greater microbial diversity was associated with an increased risk of death [HR 1.73: 95% CI 1.03-2.90] while a greater proportion of Streptococcus was associated with a reduced risk of death [HR 0.85: 95% CI 0.73 to 0.99]. The Streptococcus genus was mainly comprised of Streptococcus mitis species. CONCLUSIONS: Increasing buccal microbial diversity predicts disease severity and death in IPF. The oral commensal Streptococcus mitis spp associates with preserved lung function and improved survival.

In critically ill patients, anti-anaerobic antibiotics increase risk of adverse clinical outcomes.

BACKGROUND: Critically ill patients routinely receive antibiotics with activity against anaerobic gut bacteria. However, in other disease states and animal models, gut anaerobes are protective against pneumonia, organ failure and mortality. We therefore designed a translational series of analyses and experiments to determine the effects of anti-anaerobic antibiotics on the risk of adverse clinical outcomes among critically ill patients. METHODS: We conducted a retrospective single-centre cohort study of 3032 critically ill patients, comparing patients who did and did not receive early anti-anaerobic antibiotics. We compared intensive care unit outcomes (ventilator-associated pneumonia (VAP)-free survival, infection-free survival and overall survival) in all patients and changes in gut microbiota in a subcohort of 116 patients. In murine models, we studied the effects of anaerobe depletion in infectious (Klebsiella pneumoniae and Staphylococcus aureus pneumonia) and noninfectious (hyperoxia) injury models. RESULTS: Early administration of anti-anaerobic antibiotics was associated with decreased VAP-free survival (hazard ratio (HR) 1.24, 95% CI 1.06-1.45), infection-free survival (HR 1.22, 95% CI 1.09-1.38) and overall survival (HR 1.14, 95% CI 1.02-1.28). Patients who received anti-anaerobic antibiotics had decreased initial gut bacterial density (p=0.00038), increased microbiome expansion during hospitalisation (p=0.011) and domination by Enterobacteriaceae spp. (p=0.045). Enterobacteriaceae were also enriched among respiratory pathogens in anti-anaerobic-treated patients (p<2.2×10-16). In murine models, treatment with anti-anaerobic antibiotics increased susceptibility to Enterobacteriaceae pneumonia (p<0.05) and increased the lethality of hyperoxia (p=0.0002). CONCLUSIONS: In critically ill patients, early treatment with anti-anaerobic antibiotics is associated with increased mortality. Mechanisms may include enrichment of the gut with respiratory pathogens, but increased mortality is incompletely explained by infections alone. Given consistent clinical and experimental evidence of harm, the widespread use of anti-anaerobic antibiotics should be reconsidered.

SNIKT: sequence-independent adapter identification and removal in long-read shotgun sequencing data.

SUMMARY: Here, we introduce SNIKT, a command-line tool for sequence-independent visual confirmation and input-assisted removal of adapter contamination in whole-genome shotgun or metagenomic shotgun long-read sequencing DNA or RNA data. AVAILABILITY AND IMPLEMENTATION: SNIKT is implemented in R and is compatible with Unix-like platforms. The source code, along with documentation, is freely available under an MIT license at https://github.com/piyuranjan/SNIKT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Update on the Features and Measurements of Experimental Acute Lung Injury in Animals: An Official American Thoracic Society Workshop Report.

Advancements in methods, technology, and our understanding of the pathobiology of lung injury have created the need to update the definition of experimental acute lung injury (ALI). We queried 50 participants with expertise in ALI and acute respiratory distress syndrome using a Delphi method composed of a series of electronic surveys and a virtual workshop. We propose that ALI presents as a "multidimensional entity" characterized by four "domains" that reflect the key pathophysiologic features and underlying biology of human acute respiratory distress syndrome. These domains are 1) histological evidence of tissue injury, 2) alteration of the alveolar-capillary barrier, 3) presence of an inflammatory response, and 4) physiologic dysfunction. For each domain, we present "relevant measurements," defined as those proposed by at least 30% of respondents. We propose that experimental ALI encompasses a continuum of models ranging from those focusing on gaining specific mechanistic insights to those primarily concerned with preclinical testing of novel therapeutics or interventions. We suggest that mechanistic studies may justifiably focus on a single domain of lung injury, but models must document alterations of at least three of the four domains to qualify as "experimental ALI." Finally, we propose that a time criterion defining "acute" in ALI remains relevant, but the actual time may vary based on the specific model and the aspect of injury being modeled. The continuum concept of ALI increases the flexibility and applicability of the definition to multiple models while increasing the likelihood of translating preclinical findings to critically ill patients.

Nucleic Acid-based Testing for Noninfluenza Viral Pathogens in Adults with Suspected Community-acquired Pneumonia. An Official American Thoracic Society Clinical Practice Guideline.

Background: This document provides evidence-based clinical practice guidelines on the diagnostic utility of nucleic acid-based testing of respiratory samples for viral pathogens other than influenza in adults with suspected community-acquired pneumonia (CAP).Methods: A multidisciplinary panel developed a Population-Intervention-Comparison-Outcome question, conducted a pragmatic systematic review, and applied Grading of Recommendations, Assessment, Development, and Evaluation methodology for clinical recommendations.Results: The panel evaluated the literature to develop recommendations regarding whether routine diagnostics should include nucleic acid-based testing of respiratory samples for viral pathogens other than influenza in suspected CAP. The evidence addressing this topic was generally adjudicated to be of very low quality because of risk of bias and imprecision. Furthermore, there was little direct evidence supporting a role for routine nucleic acid-based testing of respiratory samples in improving critical outcomes such as overall survival or antibiotic use patterns. However, on the basis of direct and indirect evidence, recommendations were made for both outpatient and hospitalized patients with suspected CAP. Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was not addressed in the literature at the time of the evidence review.Conclusions: The panel formulated and provided their rationale for recommendations on nucleic acid-based diagnostics for viral pathogens other than influenza for patients with suspected CAP.

Toll-like receptors, environmental caging, and lung dysbiosis.

Recent studies have implicated lung microbiota in shaping local alveolar immune responses. Toll-like receptors are major sensors of microbiota and determinants of local epithelial homeostasis. The impact of toll-like receptor deficiency on lung microbiota is unknown. To determine whether the absence of toll-like receptors results in altered lung microbiota or dysbiosis, we compared lung microbiota in wild-type and toll-like receptor-deficient experimental mice using 16S ribosomal RNA gene quantification and sequencing. We used a randomized environmental caging strategy to determine the impact of toll-like receptors on lung microbiota. Lung microbiota are detectable in toll-like receptor-deficient experimental mice and exhibit considerable variability. The lung microbiota of toll-like receptor-deficient mice are altered in community composition (PERMANOVA P < 0.001), display reduced diversity (t test P = 0.0075), and bacterial burden (t test P = 0.016) compared with wild-type mice with intact toll-like receptors and associated signaling pathways. The lung microbiota of wild-type mice when randomized to cages with toll-like receptor-deficient mice converged with no significant difference in community composition (PERMANOVA P > 0.05) after 3 wk of cohousing. The lung microbiome of toll-like receptor-deficient mice is distinct from wild-type mice and may be less susceptible to the effects of caging as an environmental variable. Our observations support a role for toll-like receptor signaling in the shaping of lung microbiota.

Rapid identification of pathogens associated with ventilator-associated pneumonia by Nanopore sequencing.

BACKGROUND: Aetiology detection is crucial in the diagnosis and treatment of ventilator-associated pneumonia (VAP). However, the detection method needs improvement. In this study, we used Nanopore sequencing to build a quick detection protocol and compared the efficiency of different methods for detecting 7 VAP pathogens. METHODS: The endotracheal aspirate (ETA) of 83 patients with suspected VAP from Peking University Third Hospital (PUTH) was collected, saponins were used to deplete host genomes, and PCR- or non-PCR-amplified library construction methods were used and compared. Sequence was performed with MinION equipment and local data analysis methods were used for sequencing and data analysis. RESULTS: Saponin depletion effectively removed 11 of 12 human genomes, while most pathogenic bacterial genome results showed no significant difference except for S. pneumoniae. Moreover, the average sequence time decreased from 19.6 h to 3.62 h. The non-PCR amplification method and PCR amplification method for library build has a similar average sensitivity (85.8% vs. 86.35%), but the non-PCR amplification method has a better average specificity (100% VS 91.15%), and required less time. The whole method takes 5-6 h from ETA extraction to pathogen classification. After analysing the 7 pathogens enrolled in our study, the average sensitivity of metagenomic sequencing was approximately 2.4 times higher than that of clinical culture (89.15% vs. 37.77%), and the average specificity was 98.8%. CONCLUSIONS: Using saponins to remove the human genome and a non-PCR amplification method to build libraries can be used for the identification of pathogens in the ETA of VAP patients within 6 h by MinION, which provides a new approach for the rapid identification of pathogens in clinical departments.

Lung Microbiota Predict Clinical Outcomes in Critically Ill Patients.

Rationale: Recent studies have revealed that, in critically ill patients, lung microbiota are altered and correlate with alveolar inflammation. The clinical significance of altered lung bacteria in critical illness is unknown.Objectives: To determine if clinical outcomes of critically ill patients are predicted by features of the lung microbiome at the time of admission.Methods: We performed a prospective, observational cohort study in an ICU at a university hospital. Lung microbiota were quantified and characterized using droplet digital PCR and bacterial 16S ribosomal RNA gene quantification and sequencing. Primary predictors were the bacterial burden, community diversity, and community composition of lung microbiota. The primary outcome was ventilator-free days, determined at 28 days after admission.Measurements and Main Results: Lungs of 91 critically ill patients were sampled using miniature BAL within 24 hours of ICU admission. Patients with increased lung bacterial burden had fewer ventilator-free days (hazard ratio, 0.43; 95% confidence interval, 0.21-0.88), which remained significant when the analysis was controlled for pneumonia and severity of illness. The community composition of lung bacteria predicted ventilator-free days (P = 0.003), driven by the presence of gut-associated bacteria (e.g., species of the Lachnospiraceae and Enterobacteriaceae families). Detection of gut-associated bacteria was also associated with the presence of acute respiratory distress syndrome.Conclusions: Key features of the lung microbiome (bacterial burden and enrichment with gut-associated bacteria) predict outcomes in critically ill patients. The lung microbiome is an understudied source of clinical variation in critical illness and represents a novel therapeutic target for the prevention and treatment of acute respiratory failure.

Methods in Lung Microbiome Research.

The lung microbiome is associated with host immune response and health outcomes in experimental models and patient cohorts. Lung microbiome research is increasing in volume and scope; however, there are no established guidelines for study design, conduct, and reporting of lung microbiome studies. Standardized approaches to yield reliable and reproducible data that can be synthesized across studies will ultimately improve the scientific rigor and impact of published work and greatly benefit microbiome research. In this review, we identify and address several key elements of microbiome research: conceptual modeling and hypothesis framing; study design; experimental methodology and pitfalls; data analysis; and reporting considerations. Finally, we explore possible future directions and research opportunities. Our goal is to aid investigators who are interested in this burgeoning research area and hopefully provide the foundation for formulating consensus approaches in lung microbiome research.

Host-microbe cross-talk in the lung microenvironment: implications for understanding and treating chronic lung disease.

Chronic respiratory diseases are highly prevalent worldwide and will continue to rise in the foreseeable future. Despite intensive efforts over recent decades, the development of novel and effective therapeutic approaches has been slow. However, there is new and increasing evidence that communities of micro-organisms in our body, the human microbiome, are crucially involved in the development and progression of chronic respiratory diseases. Understanding the detailed mechanisms underlying this cross-talk between host and microbiota is critical for development of microbiome- or host-targeted therapeutics and prevention strategies. Here we review and discuss the most recent knowledge on the continuous reciprocal interaction between the host and microbes in health and respiratory disease. Furthermore, we highlight promising developments in microbiome-based therapies and discuss the need to employ more holistic approaches of restoring both the pulmonary niche and the microbial community.

Lung Microbiota Contribute to Pulmonary Inflammation and Disease Progression in Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes considerable global morbidity and mortality, and its mechanisms of disease progression are poorly understood. Recent observational studies have reported associations between lung dysbiosis, mortality, and altered host defense gene expression, supporting a role for lung microbiota in IPF. However, the causal significance of altered lung microbiota in disease progression is undetermined. Objectives: To examine the effect of microbiota on local alveolar inflammation and disease progression using both animal models and human subjects with IPF. Methods: For human studies, we characterized lung microbiota in BAL fluid from 68 patients with IPF. For animal modeling, we used a murine model of pulmonary fibrosis in conventional and germ-free mice. Lung bacteria were characterized using 16S rRNA gene sequencing with novel techniques optimized for low-biomass sample load. Microbiota were correlated with alveolar inflammation, measures of pulmonary fibrosis, and disease progression. Measurements and Main Results: Disruption of the lung microbiome predicts disease progression, correlates with local host inflammation, and participates in disease progression. In patients with IPF, lung bacterial burden predicts fibrosis progression, and microbiota diversity and composition correlate with increased alveolar profibrotic cytokines. In murine models of fibrosis, lung dysbiosis precedes peak lung injury and is persistent. In germ-free animals, the absence of a microbiome protects against mortality. Conclusions: Our results demonstrate that lung microbiota contribute to the progression of IPF. We provide biological plausibility for the hypothesis that lung dysbiosis promotes alveolar inflammation and aberrant repair. Manipulation of lung microbiota may represent a novel target for the treatment of IPF.

The Microbiome and the Respiratory Tract.

Although the notion that "the normal lung is free from bacteria" remains common in textbooks, it is virtually always stated without citation or argument. The lungs are constantly exposed to diverse communities of microbes from the oropharynx and other sources, and over the past decade, novel culture-independent techniques of microbial identification have revealed that the lungs, previously considered sterile in health, harbor diverse communities of microbes. In this review, we describe the topography and population dynamics of the respiratory tract, both in health and as altered by acute and chronic lung disease. We provide a survey of current techniques of sampling, sequencing, and analysis of respiratory microbiota and review technical challenges and controversies in the field. We review and synthesize what is known about lung microbiota in various diseases and identify key lessons learned across disease states.

Lung Microbiome Is Influenced by the Environment and Asthmatic Status in an Equine Model of Asthma.

There is evidence that the lung microbiome differs between patients with asthma and healthy humans, but the effect of environmental conditions and medication is unknown and difficult to study. Equine asthma is a naturally occurring chronic airway disease characterized by reversible airway inflammation and bronchoconstriction upon exposure to inhaled antigens. In the present study, we evaluated the effect that environmental conditions and disease status have on pulmonary, nasal, and oral microbiomes. Six asthmatic and six healthy horses were studied while at pasture ("low antigen exposure"), as well as when being housed indoors and fed good-quality hay ("moderate exposure") and poor-quality hay ("high exposure"). At each time point, lung function was recorded; BAL, oral, and nasal rinses were collected; and 16S rRNA gene sequencing was performed. Asthmatic horses developed airway obstruction and inflammation under moderate and high antigen exposure conditions, whereas nonasthmatic horses showed mild inflammation under high antigen exposure, without bronchoconstriction. Lung, oral, and nasal communities clustered by environmental condition, but only lung communities were different between healthy and asthmatic horses. The association between asthma and lung microbiome was strongest in horses under moderate antigen exposure. Pulmonary, oral, and nasal microbiomes are influenced by environmental conditions, but only the pulmonary microbiome differs between horses with and without asthma. This difference, seen mainly when airway inflammation was present in horses with asthma but not in control animals, suggests that the altered lung microbiome in asthma might not be inherent but coincident with inflammation.

Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable two-dimensional gas chromatography device.

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~ 30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Graphical abstract.