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The \"gut-lung axis\" is commonly invoked to explain the microbiome's influence on lung inflammation. Yet the lungs harbor their own microbiome, which is altered in respiratory disease. The relative influence of gut and lung bacteria on lung inflammation is unknown. To determine whether baseline lung immune tone reflects local (lung-lung) or remote (gut-lung) microbe-host interactions. We compared lung, tongue, and cecal bacteria in 40 healthy, genetically identical, 10-week-old mice, using 16S ribosomal RNA gene quantification and sequencing. We measured inflammatory cytokines, using a multiplex assay of homogenized lung tissue. We compared lung bacteria in healthy mice treated with varied durations of systemic antibiotics. Lung bacterial communities are highly variable among mice, cluster strongly by cage, shipment, and vendor, and are altered by antibiotics in a microbiologically predictable manner. Baseline lung concentrations of two key inflammatory cytokines (IL-1α and IL-4) are correlated with the diversity and community composition of lung bacterial communities. Lung concentrations of these inflammatory cytokines correlate more strongly with variation in lung bacterial communities than with that of the gut or mouth. In the lungs of healthy mice, baseline innate immune tone more strongly reflects local (lung-lung) microbe-host interactions than remote (gut-lung) microbe-host interactions. Our results independently confirm the existence and immunologic significance of the murine lung microbiome, even in health. Variation in lung microbiota is likely an important, underappreciated source of experimental and clinical variability. The lung microbiome is an unexplored therapeutic target for the prevention and treatment of inflammatory lung disease.

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. To examine the effect of microbiota on local alveolar inflammation and disease progression using both animal models and human subjects with IPF. 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. 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. 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.

Although culture-independent techniques have refuted lung sterility in health, controversy about contamination during bronchoscope passage through the upper respiratory tract (URT) has impeded research progress. We sought to establish whether bronchoscopic sampling accurately reflects the lung microbiome in health and to distinguish between two proposed routes of authentic microbial immigration, (i) dispersion along contiguous respiratory mucosa and (ii) subclinical microaspiration. During bronchoscopy of eight adult volunteers without lung disease, we performed seven protected specimen brushings (PSB) and bilateral bronchoalveolar lavages (BALs) per subject. We amplified, sequenced, and analyzed the bacterial 16S rRNA gene V4 regions by using the Illumina MiSeq platform. Rigorous attention was paid to eliminate potential sources of error or contamination, including a randomized processing order and the inclusion and analysis of exhaustive procedural and sequencing control specimens. Indices of mouth-lung immigration (mouth-lung community similarity, bacterial burden, and community richness) were all significantly greater in airway and alveolar specimens than in bronchoscope contamination control specimens, indicating minimal evidence of pharyngeal contamination. Ecological indices of mouth-lung immigration peaked at or near the carina, as predicted for a primary immigration route of microaspiration. Bacterial burden, diversity, and mouth-lung similarity were greater in BAL than PSB samples, reflecting differences in the sampled surface areas. (This study has been registered at ClinicalTrials.gov under registration no. NCT02392182.) IMPORTANCE This study defines the bacterial topography of the healthy human respiratory tract and provides ecological evidence that bacteria enter the lungs in health primarily by microaspiration, with potential contribution in some subjects by direct dispersal along contiguous mucosa. By demonstrating that contamination contributes negligibly to microbial communities in bronchoscopically acquired specimens, we validate the use of bronchoscopy to investigate the lung microbiome. This study defines the bacterial topography of the healthy human respiratory tract and provides ecological evidence that bacteria enter the lungs in health primarily by microaspiration, with potential contribution in some subjects by direct dispersal along contiguous mucosa. By demonstrating that contamination contributes negligibly to microbial communities in bronchoscopically acquired specimens, we validate the use of bronchoscopy to investigate the lung microbiome.

The microbiome is an important and increasingly-studied mediator of organismal metabolism, although how the microbiome affects metabolism remains incompletely understood. Many investigators use antibiotics to experimentally perturb the microbiome. However, antibiotics have poorly understood yet profound off-target effects on behavior and diet, including food and water aversion, that can confound experiments and limit their applicability. We thus sought to determine the relative influence of microbiome modulation and off-target antibiotic effects on the behavior and metabolic activity of mice. Mice treated with oral antibiotics via drinking water exhibited significant weight loss in fat, liver, and muscle tissue. These mice also exhibited a reduction in water and food consumption, with marked variability across antibiotic regimens. While administration of bitter-tasting but antimicrobially-inert compounds caused a similar reduction in water consumption, this did not cause tissue weight loss or reduced food consumption. Mice administered intraperitoneal antibiotics (bypassing the gastrointestinal tract) exhibited reduced tissue weights and oral intake, comparable to the effects of oral antibiotics. Antibiotic-treated germ-free mice did not have reduced tissue weights, providing further evidence that direct microbiome modulation (rather than behavioral effects) mediates these metabolic changes. While oral antibiotics cause profound effects on food and water consumption, antibiotic effects on organismal metabolism are primarily mediated by microbiome modulation. We demonstrate that tissue-specific weight loss following antibiotic administration is due primarily to microbiome effects rather than food and water aversion, and identify antibiotic regimens that effectively modulate gut microbiota while minimizing off-target behavioral effects.

Sepsis causes brain dysfunction and neuroinflammation. It is unknown whether neuroinflammation in sepsis is initiated by dissemination of bacteria to the brain and sustained by persistent infection, or whether neuroinflammation is a sterile process resulting solely from circulating inflammatory mediators. To determine if gut bacteria translocate to the brain during sepsis, and are associated with neuroinflammation. Murine sepsis was induced using cecal ligation and puncture, and sepsis survivor mice were compared with sham and unoperated control animals. Brain tissue of patients who died of sepsis was compared with patients who died of noninfectious causes. Bacterial taxa were characterized by 16S ribosomal RNA gene sequencing in both murine and human brain specimens; compared among sepsis and nonsepsis groups; and correlated with levels of S100A8, a marker of neuroinflammation using permutational multivariate ANOVA. Viable gut-associated bacteria were enriched in the brains of mice 5 days after surviving abdominal sepsis (P < 0.01), and undetectable by 14 days. The community structure of brain-associated bacteria correlated with severity of neuroinflammation (P < 0.001). Furthermore, bacterial taxa detected in brains of humans who die of sepsis were distinct from those who died of noninfectious causes (P < 0.001) and correlated with S100A8/A9 expression (P < 0.05). Although bacterial translocation is associated with acute neuroinflammation in murine sepsis, bacterial translocation did not result in chronic cerebral infection. Postmortem analysis of patients who die of sepsis suggests a role for bacteria in acute brain dysfunction in sepsis. Further work is needed to determine if modifying gut-associated bacterial communities modulates brain dysfunction after sepsis.

Food allergy continues to be a growing public health concern, affecting at least 1 in 10 individuals in the United States alone. However, little is known about the involvement of the gastric mucosa in food allergy. Gastrointestinal Candida albicans colonization has been reported to promote gastrointestinal inflammation in a number of chronic diseases. Using a mouse model of food allergy to egg white protein, we demonstrate regionalization of the inflammatory response to C. albicans colonization, induction of robust type 2 (allergic) inflammation in the stomach, and augmentation of innate and type 3 responses by C. albicans colonization during food allergy.

Background Low-biomass microbiome studies (such as those of the lungs, placenta, and skin) are vulnerable to contamination and sequencing stochasticity, which obscure legitimate microbial signal. While human lung microbiome studies have rigorously identified sampling strategies that reliably capture microbial signal from these low-biomass microbial communities, the optimal sampling strategy for characterizing murine lung microbiota has not been empirically determined. Performing accurate, reliable characterization of murine lung microbiota and distinguishing true microbial signal from noise in these samples will be critical for further mechanistic microbiome studies in mice. Results Using an analytic approach grounded in microbial ecology, we compared bacterial DNA from the lungs of healthy adult mice collected via two common sampling approaches: homogenized whole lung tissue and bronchoalveolar lavage (BAL) fluid. We quantified bacterial DNA using droplet digital PCR, characterized bacterial communities using 16S rRNA gene sequencing, and systematically assessed the quantity and identity of bacterial DNA in both specimen types. We compared bacteria detected in lung specimens to each other and to potential source communities: negative (background) control specimens and paired oral samples. By all measures, whole lung tissue in mice contained greater bacterial signal and less evidence of contamination than did BAL fluid. Relative to BAL fluid, whole lung tissue exhibited a greater quantity of bacterial DNA, distinct community composition, decreased sample-to-sample variation, and greater biological plausibility when compared to potential source communities. In contrast, bacteria detected in BAL fluid were minimally different from those of procedural, reagent, and sequencing controls. Conclusions An ecology-based analytical approach discriminates signal from noise in this low-biomass microbiome study and identifies whole lung tissue as the preferred specimen type for murine lung microbiome studies. Sequencing, analysis, and reporting of potential source communities, including negative control specimens and contiguous biological sites, are crucial for biological interpretation of low-biomass microbiome studies, independent of specimen type. Aaejar9WP4PeeefSRNqdyt Video abstract

Lactobacillus johnsonii is a well-known probiotic species with health-beneficial properties, including host immunomodulation and pathogen inhibition. Its growing relevance in the medical industry highlights the need to understand its biology, particularly how it adapts to different host environments. In bacteria, niche adaptation is often accompanied by the loss or gain of coding sequences along with changes in the genome size. In this study, we explored the genetic diversity of L. johnsonii strains from the gastrointestinal tracts of various vertebrates such as rodents, birds, swine, and humans. We found associations between genome content and host species of origin and could conceptually demonstrate that these genes are being differentially transcribed under varying conditions. Several functions were associated with specific host groups, suggesting that L. johnsonii strains have adapted to their hosts over time.

DNA contamination from external sources (reagents, environment, operator, etc.) has long been assumed to be the main cause of spurious signals that appear under low-bacterial-biomass conditions. Here, we demonstrate that contamination can be separated from another, random signal generated during low-biomass-sample sequencing. This stochastic noise is not reproduced between technical replicates; however, results for any one replicate taken alone could look like a microbial community different from the controls. Using this information, we investigated respiratory samples from healthy humans and determined the narrow range of bacterial biomass where samples transition from producing reproducible microbial sequences to ones dominated by noise. We present a rigorous approach to studies involving low-bacterial-biomass samples to detect this source of noise and provide a framework for deciding if a sample is likely to be dominated by noise. We anticipate that this work will facilitate increased reproducibility in the characterization of potentially important low-biomass communities. The bacterial microbiome of human body sites, previously considered sterile, remains highly controversial because it can be challenging to isolate signal from noise when low-biomass samples are being analyzed. We tested the hypothesis that stochastic sequencing noise, separable from reagent contamination, is generated during sequencing on the Illumina MiSeq platform when DNA input is below a critical threshold. We first purified DNA from serial dilutions of Pseudomonas aeruginosa and from negative controls using three DNA purification kits, quantified input using droplet digital PCR, and then sequenced the 16S rRNA gene in four technical replicates. This process identified reproducible contaminant signal that was separable from an irreproducible stochastic noise, which occurred as bacterial biomass of samples decreased. This approach was then applied to authentic respiratory samples from healthy individuals ( n  = 22) that ranged from high to ultralow bacterial biomass. Using oral rinse, bronchoalveolar lavage (BAL) fluid, and exhaled breath condensate (EBC) samples and matched controls, we were able to demonstrate (i) that stochastic noise dominates sequencing in real-world low-bacterial-biomass samples that contain fewer than 10 4 copies of the 16S rRNA gene per sample, (ii) that critical examination of the community composition of technical replicates can be used to separate signal from noise, and (iii) that EBC is an irreproducible sampling modality for sampling the microbiome of the lower airways. We anticipate that these results combined with suggested methods for identifying and dealing with noisy communities will facilitate increased reproducibility while simultaneously permitting characterization of potentially important low-biomass communities. IMPORTANCE DNA contamination from external sources (reagents, environment, operator, etc.) has long been assumed to be the main cause of spurious signals that appear under low-bacterial-biomass conditions. Here, we demonstrate that contamination can be separated from another, random signal generated during low-biomass-sample sequencing. This stochastic noise is not reproduced between technical replicates; however, results for any one replicate taken alone could look like a microbial community different from the controls. Using this information, we investigated respiratory samples from healthy humans and determined the narrow range of bacterial biomass where samples transition from producing reproducible microbial sequences to ones dominated by noise. We present a rigorous approach to studies involving low-bacterial-biomass samples to detect this source of noise and provide a framework for deciding if a sample is likely to be dominated by noise. We anticipate that this work will facilitate increased reproducibility in the characterization of potentially important low-biomass communities.

Early-life respiratory syncytial virus (EL-RSV) infection has been implicated in long-term pulmonary disease in children. In these studies, neonatal BALB/c mice were infected at day 7 of life, leading to >35% losses in critical lung function, airway mucus metaplasia, and transcriptional hallmarks of mucus hypersecretion four weeks after RSV infection. While EL-RSV minimally reshaped the resident lung microbiota, it led to significant gut dysbiosis, including a long-term reduction of Proteobacteria that can be a source of protective metabolites related to barrier and immune function. Subsequent studies assessing whether a common infant antibiotic (ampicillin) could mitigate EL-RSV-induced lung alterations revealed further severe gut microbiome alterations and, on its own, later in life, recapitulated the full spectrum of RSV-associated alterations in lung function. Metagenomic inference showed that both RSV and ampicillin administered during early life reduced biosynthetic pathways for microbiome-derived metabolites, which are known to reinforce tight junctions, regulate inflammation, and preserve extracellular matrix elasticity. The shared loss of these metabolic programs provides a mechanistic bridge linking distinct early-life exposures to the microbiome changes and airway mechanical deficits later in life. Collectively, the data suggest that RSV and/or antibiotic-triggered gut dysbiosis is the primary insult that likely promotes improper lung maturation/repair through a metabolite-mediated mechanism and may suggest metabolite restoration as a strategy to promote proper developmental lung function.