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We report our initial experience with the management of a mixed group of patients with COVID-19 infection, admitted and treated in a designated COVID-19 centre in the Athens Metropolitan area over a 4-week period. The SARS-CoV-2 pandemic presented a huge challenge to the Greek National Healthcare System and healthcare workers. Their response so far has been miraculously effective. Since there are essentially no therapeutic guidelines yet for this disease, we relied mainly on our medical intuition, our empathy for our patients and team work to do the best possible for 49 people with this infection. We present the therapeutic algorithm we gradually developed (on the job) and applied in our patients, based on continuous creative brainstorming and monitoring of the literature.

2 Figuras, 1 Tabla, Microbiota have emerged as key modulators of both the carcinogenic process and the immune response against cancer cells, and, thus, it seems to influence the efficacy of immunotherapy. While most studies have focused on analyzing the influence of gut microbiota, its composition substantially differs from that in the lung. Here, we describe how microbial life in the lungs is associated with host immune status in the lungs and, thus, how the identification of the microbial populations in the lower respiratory tract rather than in the gut might be key to understanding the lung carcinogenic process and to predict the efficacy of different treatments. Understanding the influence of lung microbiota on host immunity may identify new therapeutic targets and help to design new immunotherapy approaches to treat lung cancer.

Objective:Lung microbiota is increasingly implicated in multiple types of respiratory diseases. However, no study has drawn a consistent conclusion regarding the relationship between changes in the microbial community and lung diseases. This study verifies the association between microbiota level and lung diseases by performing a meta-analysis.Methods:Literature databases, including PubMed, ISI Web of Science, Embase, Google Scholar, PMC, and CNKI, were used to collect related articles published before March 20, 2021. The standard mean deviation (SMD) and related 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup, sensitivity, and publication bias analyses were also conducted.Results:Six studies, comprising 695 patients with lung diseases and 176 healthy individuals, were included in this meta-analysis. The results indicated that the microbiota level was higher in patients with lung diseases than in healthy individuals (SMD = 0.39, 95% CI = 0.22–0.55, I2 = 91.5%, P < 0.01). Subgroup analysis based on country demonstrated that the microbiota level was significantly higher in Chinese (SMD = 1.90, 95% CI = 0.87–2.93, I2 = 62.3%, P < 0.01) and Korean (SMD = 0.24, 95% CI = 0.13–0.35, I2 = 78.7%, P < 0.01) patients with lung diseases. The microbiota level of patients with idiopathic pulmonary fibrosis (IPF) (SMD = 1.40, 95% CI = 0.42–2.38, I2 = 97.3%, P = 0.005), chronic obstructive pulmonary disease (COPD) (SMD = 0.30, 95% CI = 0.09–0.50, I2 = 83.9%, P = 0.004), and asthma (SMD = 0.19, 95% CI = 0.06–0.32, I2 = 69.4%, P = 0.004) were significantly higher than those of the healthy group, whereas a lower microbiota level was found in patients with chronic hypersensitivity pneumonitis (CHP). The microbiota level significantly increased when the disease sample size was >50. Subgroup analysis based on different microbiota genera, indicated that Acinetobacter baumannii and Pseudomonas aeruginosa were significantly increased in COPD and asthma diseases.Conclusion:We observed that patients with IPF, COPD, and asthma had a higher microbiota level, whereas patients with CHP had a lower microbiota level compared to the healthy individuals. The level of A. baumannii and P. aeruginosa were significantly higher in patients with COPD and asthma, and thus represented as potential microbiota markers in the diagnosis and treatment of lung diseases.

Esta revisión bibliográfica se ha centrado en la evaluación de la posibilidad de la influencia de la microbiota como estimulante de la inmunología local y la influencia sobre el desarrollo de afecciones respiratorias, como la bronquiolitis, bronquitis, asma y alergia. La tos es uno de los motivos de consulta más frecuentes en atención primaria de pediatría hasta los siete u ocho años de edad. Se realizó una revisión de estudios científicos y revisiones sistemáticas en español e inglés, sobre la incidencia, epidemiología y fisiopatología de los cuadros respiratorios que cursan con hiperreactividad bronquial y síndromes asmáticos en niños, y se relacionó con la composición de la microbiota intestinal y respiratoria, así como la influencia de la variación de ésta sobre la incidencia y la fisiopatología de estos procesos. Buscado también evidencias sobre la eficacia de la administración de determinadas cepas de probióticos y el consumo de alimentos fermentados, para conseguir la variación de la microbiota deseada. La microbiota intestinal, la microbiota respiratoria, el sistema inmune, los patógenos y alérgenos se encuentran en constante interacción, constituyendo un ecosistema que va a determinar en gran medida la patogenia e incidencia de procesos respiratorios mediados por virus y alérgenos. Tanto los probióticos como ciertos alimentos fermentados serían fuente de microorganismos seguros y de identidad conocida, con amplios beneficios locales (a nivel intestinal) y sistémicos, con capacidad para influir en la composición de la microbiota intestinal, y esta a su vez en la respiratoria. Ejerciendo una modulación de la respuesta exagerada de las mucosas. Aquesta revisió bibliogràfica s'ha centrat en l'avaluació de la possibilitat de la influència de la microbiota com a estimulant de la immunologia local i la influència sobre el desenvolupament d'afeccions respiratòries, com la bronquiolitis, bronquitis, asma i al·lèrgia. La tos és un dels motius de consulta més freqüents en atenció primària de pediatria fins als set o vuit anys d'edat. Es va realitzar una revisió d'estudis científics i revisions sistemàtiques en espanyol i anglès, sobre la incidència, epidemiologia i fisiopatologia dels quadres respiratoris que cursen amb hiperreactividad bronquial i síndromes asmàtiques en nens, i es va relacionar amb la composició de la microbiota intestinal i respiratòria, així com la influència de la variació d'aquesta sobre la incidència i la fisiopatologia d'aquests processos. Buscat també evidències sobre l'eficàcia de l'administració de determinats ceps de probiòtics i el consum d'aliments fermentats, per a aconseguir la variació de la microbiota desitjada. La microbiota intestinal, la microbiota respiratòria, el sistema immune, els patògens i al·lergògens es troben en constant interacció, constituint un ecosistema que determinarà en gran manera la patogènia i incidència de processos respiratoris mediats per virus i al·lergògens. Tant els probiòtics com uns certs aliments fermentats serien font de microorganismes segurs i d'identitat coneguda, amb amplis beneficis locals (a nivell intestinal) i sistèmics, amb capacitat per a influir en la composició de la microbiota intestinal, i aquesta al seu torn en la respiratòria. Exercint una modulació de la resposta exagerada de les mucoses. This bibliographic study focuses on assessing the possibility of the influence of microbiota as an stimulant of local immunity and the influence on the development of respiratory diseases, such as bronchiolitis, bronchitis, asthma and allergy. Cough is one of the most frequent causes for consultation in family practice and primary care for children up to eight years old. We carried out a review of scientific studies and sistematic reviews on English and Spanish, about the impact, epidemiology and pathophysiology of respiratory cases which course includes bronchial hyperreactivity and asthmatic syndromes in children, and we related it with the composition of the gut and respiratory tract microbiótica, as well as with the impact of its variation on the influence and the pathophysiology of these processes. Searching also for the administration of certain probiotics and the consumption of fermented foods, in order to obtain the variation of the desired microbiota. The gut and respiratory microbiome, the sistema inmune, the pathogenic agents and allergens interact constantly, constituting an ecosystem that will determine mostly the pathogenesis and the impact of respiratory processes mediated by viruses and allergens. Both the probiotics and certain fermented foods would be a source of safe microorganisms of known identity, with local large benefits (at intestinal level) y systemic, with the ability of influencing on the gut microbiome, and this, in turn, on the lung microbiome. Exerciting a modulation of the excesive answer of the mucous.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Although dysbiosis of the lung and gut microbiota have been associated with NSCLC, their relative contributions are unclear; in addition, their roles in distant metastasis (DM) are still illusive. We recruited in total 121 participants, including 87 newly diagnosed treatment-naive NSCLC patients of various stages and 34 healthy volunteers, and surveyed their fecal and sputum microbiota. We compared the microbial profiles between groups, identified microbial biomarkers, and generated machine learning models for distinguishing healthy individuals from patients with NSCLC and patients of various stages. We found significant perturbations of gut and sputum microbiota in patients with NSCLC and DM. A machine learning model combining both microbiota (combined model) performed better than an individual data set in patient stratification, with the highest area under the curve (AUC) value of 0.896. Sputum and gut microbiota both contributed to the combined model; in most cases, sputum-only models performed similar to the combined models. Several microbial biomarkers were shared by both microbiotas, indicating their similar roles at distinct body sites. Microbial biomarkers of distinct disease stages were mostly shared, suggesting biomarkers for DM could be acquired early. Furthermore, Pseudomonas aeruginosa, a species previously associated with wound infections, was significantly more abundant in brain metastasis, indicating that distinct types of DMs could have different microbes. Our results indicate that alterations of the sputum microbiota have stronger relationships with NSCLC and DM than the gut and strongly support the feasibility of metagenome-based noninvasive disease diagnosis and risk evaluation. (This study has been registered at ClinicalTrials.gov under registration no. NCT03454685). IMPORTANCE Our survey on gut and sputum microbiota revealed that both were significantly disturbed in non-small cell lung cancer (NSCLC) and associated with distant metastasis (DM) while only the sputum microbiota was associated with non-DM NSCLC. The lung microbiota could therefore have a stronger association with (and thus may contribute more to) disease development than the gut microbiota. Mathematic models using both microbiotas performed better in patient stratification than using individual microbiota. Sputum models, however, performed similar to the combined models, suggesting a convenient, noninvasive diagnostic for NSCLC. Microbial biomarkers of distinct disease stages were mostly shared, suggesting that the same set of microbes were underlying disease progression, and the signals for distant metastasis could be acquired at early stages of the disease. Our results strongly support the feasibility of noninvasive diagnosis of NSCLC, including distant metastasis, are of clinical importance, and should warrant further research on the underlying molecular mechanisms.

Lung microbiota plays an important role in many diseases including lower respiratory tract infections (LRTI) and pneumonia. This study aimed to explore the effects of community-acquired pneumonia (CAP) on microbial diversity and identify potential biomarkers of respiratory tract in CAP LRTI patients. In the current study, a comprehensive bioinformatics analysis was performed based on metagenomic next-generation sequencing technology, followed by alpha and beta diversity, LEfSe, and co-occurrence network analysis, and random forest model construction. Our results showed that CAP dramatically influenced taxon abundance, and the significant differences in microbiota including Proteobacteria, Bacteroidetes, Euryarchaeota, Firmicutes and Spirochetes were observed at the phylum level. Co-occurrence network selected out novel modules involved in microbial proliferation-associated pathways. A random forest model screened Klebsiella pneumoniae and Bacillus cereus as potential diagnostic biomarkers with high AUC values. The microbial composition was different between CAP LRTI patients and non-CAP LRTI patients. Klebsiella pneumoniae and Bacillus cereus were strongly associated with increased severity of LRTI with a pneumonia history. Our findings provided an insight for a better understanding of community and structure of lung microbiota for future diagnosis and treatment in LRTI patients with a history of pneumonia. Moreover, these microbes were considered as potential biomarkers for predicting the risks for the treatment strategies of LRTI.

Rationale: Chronic hypersensitivity pneumonitis (CHP) is a condition that arises after repeated exposure and sensitization to inhaled antigens. The lung microbiome is increasingly implicated in respiratory disease, but, to date, no study has investigated the composition of microbial communities in the lower airways in CHP. Objectives: To characterize and compare the airway microbiome in subjects with CHP, subjects with idiopathic pulmonary fibrosis (IPF), and control subjects. Methods: We prospectively recruited individuals with a CHP diagnosis (n = 110), individuals with an IPF diagnosis (n = 45), and control subjects (n = 28). Subjects underwent BAL and bacterial DNA was isolated, quantified by quantitative PCR and the 16S ribosomal RNA gene was sequenced to characterize the bacterial communities in the lower airways. Measurements and Main Results: Distinct differences in the microbial profiles were evident in the lower airways of subjects with CHP and IPF. At the phylum level, the prevailing microbiota of both subjects with IPF and subjects with CHP included Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. However, in IPF, Firmicutes dominated, whereas the percentage of reads assigned to Proteobacteria in the same group was significantly lower than the percentage found in subjects with CHP. At the genus level, the Staphylococcus burden was increased in CHP, and Actinomyces and Veillonella burdens were increased in IPF. The lower airway bacterial burden in subjects with CHP was higher than that in control subjects but lower than that of those with IPF. In contrast to IPF, there was no association between bacterial burden and survival in CHP. Conclusions: The microbial profile of the lower airways in subjects with CHP is distinct from that of IPF, and, notably, the bacterial burden in individuals with CHP fails to predict survival.

Although many studies have reported that microbiota emergencies are deeply involved in the occurrence and subsequent progression of lung diseases, the present diagnosis of lung disease depends on microbiota markers, which is still poorly understood. Therefore, a meta-analysis was performed to confirm lung microbiota markers for the diagnosis of lung diseases. Literature databases were searched following the inclusion and exclusion criteria. There are 6 studies including 1347 patients and 26 comparisons to be enrolled, and then the diagnostic effect was evaluated using Stata 14.0 and Meta-disc 1.4 software. The pooled sensitivity (SEN), specificity (SPE), diagnostic likelihood ratio positive (DLR+), diagnostic likelihood ratio negative (DLR−), and diagnostic OR (DOR), as well as area under the curve (AUC) of microbiota markers in the diagnosis of lung diseases were 0.90 (95% CI: 0.83-0.94), 0.89 (95% CI: 0.76-0.95), 7.86 (95% CI: 3.39-18.21), 0.12 (95% CI: 0.06-0.21), 22.254 (95% CI: 12.83-39.59.14), and 0.95 (95% CI: 0.93-0.97), respectively. Subgroup analysis revealed that research based on Caucasian, adult, BAL fluid, PCR, pneumonia obtained higher AUC values. The microbiota markers have shown potential diagnosis value for lung diseases. But further large-scale clinical studies are still needed to verify and replicate the diagnostic value of lung microbiota markers.

Comprehensive microbial analysis has revealed that the lung harbors a complex variety of microbiota, and although the dynamic distribution of the lung microbiota in mice and laying hens of different ages is well established, this distribution has not been clarified in broilers of different ages. Here, we performed 16S rRNA gene sequencing of lung lavage fluid from broilers at 3 (3D), 7 (7D), 14 (14D), 21 (21D), and 35 (35D) days of age to evaluate changes in the composition of their lung microbiota. Upon examination of the composition and function of the broiler lung microbiota, we found that their maturation increased significantly with age. Specifically, the microbiota composition was similar between 7 and 14D and between 21 and 35D. The relative abundance of aerobic bacteria in the broiler lungs gradually increased as the broilers developed, whereas the relative abundance of potentially pathogenic bacteria reached its highest level at 3D. The relative abundance of predicted functions in microbiota was very similar among 3, 7, and 14D, whereas the Glycan Biosynthesis and Metabolism pathway in microbiota was enriched at 21D. These findings suggest that these metabolic pathways play critical roles in shaping broiler microbiota at these age stages. In addition, short-term external ammonia stimulation significantly increased lung inflammation but did not significantly affect the lung microbiota. Taken together, these data reveal the dynamics of age-related changes in the microbiota of broiler lungs and the stability (the significant variation in the microbial composition) of these microbial communities in response to short-term ammonia stress. These findings provide new insights into the development of broiler lung microbiota and serve as a reference for subsequent studies to evaluate disease prevention in broilers subjected to large-scale breeding.

The implications of the microbiome on Coronavirus disease 2019 (COVID-19) prognosis has not been thoroughly studied. In this study we aimed to characterize the lung and blood microbiome and their implication on COVID-19 prognosis through analysis of peripheral blood mononuclear cell (PBMC) samples, lung biopsy samples, and bronchoalveolar lavage fluid (BALF) samples. In all three tissue types, we found panels of microbes differentially abundant between COVID-19 and normal samples correlated to immune dysregulation and upregulation of inflammatory pathways, including key cytokine pathways such as interleukin (IL)-2, 3, 5-10 and 23 signaling pathways and downregulation of anti-inflammatory pathways including IL-4 signaling. In the PBMC samples, six microbes were correlated with worse COVID-19 severity, and one microbe was correlated with improved COVID-19 severity. Collectively, our findings contribute to the understanding of the human microbiome and suggest interplay between our identified microbes and key inflammatory pathways which may be leveraged in the development of immune therapies for treating COVID-19 patients.

BackgroundIt is now possible to comprehensively characterize the microbiota of the lungs using culture-independent, sequencing-based assays. Several sample types have been used to investigate the lung microbiota, each presenting specific challenges for preparation and analysis of microbial communities. Bronchoalveolar lavage fluid (BALF) enables the identification of microbiota specific to the lower lung but commonly has low bacterial density, increasing the risk of false-positive signal from contaminating DNA. The objectives of this study were to investigate the extent of contamination across a range of sample densities representative of BALF and identify features of contaminants that facilitate their removal from sequence data and aid in the interpretation of BALF sample 16S sequencing data.ResultsUsing three mock communities across a range of densities ranging from 8E+ 02 to 8E+ 09 16S copies/ml, we assessed taxonomic accuracy and precision by 16S rRNA gene sequencing and the proportion of reads arising from contaminants. Sequencing accuracy, precision, and the relative abundance of mock community members decreased with sample input density, with a significant drop-off below 8E+ 05 16S copies/ml. Contaminant OTUs were commonly inversely correlated with sample input density or not reproduced between technical replicates. Removal of taxa with these features or physical concentration of samples prior to sequencing improved both sequencing accuracy and precision for samples between 8E+ 04 and 8E+ 06 16S copies/ml. For the lowest densities, below 8E+ 03 16S copies/ml BALF, accuracy and precision could not be significantly improved using these approaches. Using clinical BALF samples across a large density range, we observed that OTUs with features of contaminants identified in mock communities were also evident in low-density BALF samples.ConclusionRelative abundance data and community composition generated by 16S sequencing of BALF samples across the range of density commonly observed in this sample type should be interpreted in the context of input sample density and may be improved by simple pre- and post-sequencing steps for densities above 8E+ 04 16S copies/ml.

Background Hospitalized patients with COVID-19 admitted to the intensive care unit (ICU) and requiring mechanical ventilation are at risk of ventilator-associated bacterial infections secondary to SARS-CoV-2 infection. Our study aimed to investigate clinical features of Staphylococcus aureus ventilator-associated pneumonia (SA-VAP) and, if bronchoalveolar lavage samples were available, lung bacterial community features in ICU patients with or without COVID-19. Methods We prospectively included hospitalized patients with COVID-19 across two medical ICUs of the Fondazione Policlinico Universitario A. Gemelli IRCCS (Rome, Italy), who developed SA-VAP between 20 March 2020 and 30 October 2020 (thereafter referred to as cases). After 1:2 matching based on the simplified acute physiology score II (SAPS II) and the sequential organ failure assessment (SOFA) score, cases were compared with SA-VAP patients without COVID-19 (controls). Clinical, microbiological, and lung microbiota data were analyzed. Results We studied two groups of patients (40 COVID-19 and 80 non-COVID-19). COVID-19 patients had a higher rate of late-onset (87.5% versus 63.8%; p = 0.01), methicillin-resistant (65.0% vs 27.5%; p p p = 0.12), clinical cure (p = 0.20) and microbiological eradication (p = 0.31). On multivariable logistic regression analysis, SAPS II and initial inappropriate antimicrobial therapy were independently associated with ICU mortality. Then, lung microbiota characterization in 10 COVID-19 and 16 non-COVID-19 patients revealed that the overall microbial community composition was significantly different between the patient groups (unweighted UniFrac distance, R2 0.15349; p p S. aureus (log2 fold change, 29.5), Streptococcus anginosus subspecies anginosus (log2 fold change, 24.9), and Olsenella (log2 fold change, 25.7) were significantly enriched in the COVID-19 group compared to the non–COVID-19 group of SA-VAP patients. Conclusions In our study population, COVID-19 seemed to significantly affect microbiological and clinical features of SA-VAP as well as to be associated with a peculiar lung microbiota composition.

Lung microbiota (LM) is an interesting new way to consider and redesign pathogenesis and possible therapeutic approach to many lung diseases, such as idiopathic pulmonary fibrosis (IPF), which is an interstitial pneumonia with bad prognosis. Chronic inflammation is the basis but probably not the only cause of lung fibrosis and although the risk factors are not completely clear, endogenous factors (e.g. gastroesophageal reflux) and environmental factors like cigarette smoking, industrial dusts, and precisely microbial agents could contribute to the IPF development. It is well demonstrated that many bacteria can cause epithelial cell injuries in the airways through induction of a host immune response or by activating flogosis mediators following a chronic, low-level antigenic stimulus. This persistent host response could influence fibroblast responsiveness suggesting that LM may play a role in repetitive alveolar injury in IPF. We reviewed literature regarding not only bacteria but also the role of virome and mycobiome in IPF. In fact, some viruses such as hepatitis C virus or certain fungi could be etiological agents or co-factors in the IPF progress. We aim to illustrate how the cross-talk between different local microbiotas throughout specific axis and immune modulation governed by microorganisms could be at the basis of lung dysfunctions and IPF development. Finally, since the future direction of medicine will be personalized, we suggest that the analysis of LM could be a goal to research new therapies also in IPF.

Giving the potential contribute in cancer initiation and progression, lung microbiota represents a promising topic in cancer research, although still unexplored. We performed a systematic literature search to identify clinical studies evaluating lung microbiota composition, its correlation with lung cancer patients' clinico-pathological features and prognosis. Of the identified 370 studies, 21 were eligible and included. Although studies were heterogeneous, lung cancer resulted to be enriched in peculiar microbial communities, with differences in composition and diversity according to clinico-pathological parameters. Few studies explored how lung microbiota influences cancer outcome. In light of these findings and borrowing the suggestions coming from gut microbiota, we speculate that respiratory microbiome may influence pathogenesis, progression and outcome of lung cancer. Taking advantage of the experience of chronical lung diseases, prospective studies should be designed to evaluate lung microbiota changes throughout any phase of lung cancer course, particularly with the advent of immunotherapy as pivotal treatment.

BackgroundChronic infection and concomitant airway inflammation is the leading cause of morbidity and mortality for people living with cystic fibrosis (CF). Although chronic infection in CF is undeniably polymicrobial, involving a lung microbiota, infection surveillance and control approaches remain underpinned by classical aerobic culture-based microbiology. How to use microbiomics to direct clinical management of CF airway infections remains a crucial challenge. A pivotal step towards leveraging microbiome approaches in CF clinical care is to understand the ecology of the CF lung microbiome and identify ecological patterns of CF microbiota across a wide spectrum of lung disease. Assessing sputum samples from 299 patients attending 13 CF centres in Europe and the USA, we determined whether the emerging relationship of decreasing microbiota diversity with worsening lung function could be considered a generalised pattern of CF lung microbiota and explored its potential as an informative indicator of lung disease state in CF.ResultsWe tested and found decreasing microbiota diversity with a reduction in lung function to be a significant ecological pattern. Moreover, the loss of diversity was accompanied by an increase in microbiota dominance. Subsequently, we stratified patients into lung disease categories of increasing disease severity to further investigate relationships between microbiota characteristics and lung function, and the factors contributing to microbiota variance. Core taxa group composition became highly conserved within the severe disease category, while the rarer satellite taxa underpinned the high variability observed in the microbiota diversity. Further, the lung microbiota of individual patient were increasingly dominated by recognised CF pathogens as lung function decreased. Conversely, other bacteria, especially obligate anaerobes, increasingly dominated in those with better lung function. Ordination analyses revealed lung function and antibiotics to be main explanators of compositional variance in the microbiota and the core and satellite taxa. Biogeography was found to influence acquisition of the rarer satellite taxa.ConclusionsOur findings demonstrate that microbiota diversity and dominance, as well as the identity of the dominant bacterial species, in combination with measures of lung function, can be used as informative indicators of disease state in CF.

The study was to explore the rational use of danofloxacin against Mycoplasma gallisepticum (MG) based on its clinical breakpoint (CBP) and the effect on lung microbiota. The CBP was established according to epidemiological cutoff value (ECV/COWT), pharmacokinetic–pharmacodynamic (PK–PD) cutoff value (COPD) and clinical cutoff value (COCL). The ECV was determined by the micro-broth dilution method and analyzed by ECOFFinder software. The COPD was determined according to PK–PD modeling of danofloxacin in infected lung tissue with Monte Carlo analysis. The COCL was performed based on the relationship between the minimum inhibitory concentration (MIC) and the possibility of cure (POC) from clinical trials. The CBP in infected lung tissue was 1 μg/mL according to CLSI M37-A3 decision tree. The 16S ribosomal RNA (rRNA) sequencing results showed that the lung microbiota, especially the phyla Firmicutes and Proteobacteria had changed significantly along with the process of cure regimen (the 24 h dosing interval of 16.60 mg/kg b.w for three consecutive days). Our study suggested that the rational use of danofloxacin for the treatment of MG infections should consider the MIC and effect of antibiotics on the respiratory microbiota.

Few studies have described the key features and prognostic roles of lung microbiota in patients with severe community-acquired pneumonia (SCAP). We prospectively enrolled consecutive SCAP patients admitted to ICU. Bronchoscopy was performed at bedside within 48 h of ICU admission, and 16S rRNA gene sequencing was applied to the collected bronchoalveolar lavage fluid. The primary outcome was clinical improvements defined as a decrease of 2 categories and above on a 7-category ordinal scale within 14 days following bronchoscopy. Sixty-seven patients were included. Multivariable permutational multivariate analysis of variance found that positive bacteria lab test results had the strongest independent association with lung microbiota (R2 = 0.033; P = 0.018), followed by acute kidney injury (AKI; R2 = 0.032; P = 0.011) and plasma MIP-1β level (R2 = 0.027; P = 0.044). Random forest identified that the families Prevotellaceae, Moraxellaceae, and Staphylococcaceae were the biomarkers related to the positive bacteria lab test results. Multivariable Cox regression showed that the increase in α-diversity and the abundance of the families Prevotellaceae and Actinomycetaceae were associated with clinical improvements. The positive bacteria lab test results, AKI, and plasma MIP-1β level were associated with patients’ lung microbiota composition on ICU admission. The families Prevotellaceae and Actinomycetaceae on admission predicted clinical improvements. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s11684-021-0856-3 and is accessible for authorized users.

RATIONALE: Chronic hypersensitivity pneumonitis (CHP) is a condition that arises following repeated exposure and sensitisation to inhaled antigens. The lung microbiome is increasingly implicated in respiratory disease but to date, no study has investigated the composition of microbial communities in the lower airways in CHP. OBJECTIVE: To characterise and compare the airway microbiome in subjects with CHP, idiopathic pulmonary fibrosis (IPF) and controls. METHODS: We prospectively recruited individuals diagnosed with CHP (n=110), IPF (n=45) and controls (n=28). Subjects underwent bronchoalveolar lavage and bacterial DNA was isolated, quantified by qPCR and the 16S rRNA gene was sequenced to characterise the bacterial communities in the lower airways. MAIN MEASUREMENTS AND RESULTS: Distinct differences in the microbial profiles were evident in the lower airways of subjects with CHP and IPF. At the phylum level, the prevailing microbiota of both IPF and CHP subjects included Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria. However, in IPF, Firmicutes dominated while the percentage of reads assigned to Proteobacteria in the same group was significantly lower compared to CHP subjects. At the genus level, Staphylococcus was increased in CHP and Actinomyces and Veillonella in IPF. The lower airway bacterial burden in CHP subjects was higher than controls but lower than those with IPF. In contrast to IPF, there was no association between bacterial burden and survival in CHP. CONCLUSIONS: The microbial profile of the lower airways in subjects with CHP is distinct from that of IPF and, notably, bacterial burden in individuals with CHP fails to predict survival.

Background While well-characterised on its molecular base, non-small cell lung cancer (NSCLC) and its interaction with local microbiota remains scarcely explored. Moreover, current studies vary in source of lung microbiota, from bronchoalveolar lavage fluid (BAL) to tissue, introducing potentially differing results. Therefore, the objective of this study was to provide detailed characterisation of the oral and multi-source lung microbiota of direct interest in lung cancer research. Since lung tumours in lower lobes (LL) have been associated with decreased survival, characteristics of the microbiota in upper (UL) and lower tumour lobes have also been examined. Methods Using 16S rRNA gene sequencing technology, we analysed microbiota in saliva, BAL (obtained directly on excised lobe), non-malignant, peritumoural and tumour tissue from 18 NSCLC patients eligible for surgical treatment. Detailed taxonomy, diversity and core members were provided for each microbiota, with analysis of differential abundance on all taxonomical levels (zero-inflated binomial general linear model with Benjamini-Hochberg correction), between samples and lobe locations. Results Diversity and differential abundance analysis showed clear separation of oral and lung microbiota, but more importantly, of BAL and lung tissue microbiota. Phylum Proteobacteria dominated tissue samples, while Firmicutes was more abundant in BAL and saliva (with class Clostridia and Bacilli, respectively). However, all samples showed increased abundance of phylum Firmicutes in LL, with decrease in Proteobacteria. Also, clades Actinobacteria and Flavobacteriia showed inverse abundance between BAL and extratumoural tissues depending on the lobe location. While tumour microbiota seemed the least affected by location, peritumoural tissue showed the highest susceptibility with markedly increased similarity to BAL microbiota in UL. Differences between the three lung tissues were however very limited. Conclusions Our results confirm that BAL harbours unique lung microbiota and emphasise the importance of the sample choice for lung microbiota analysis. Further, limited differences between the tissues indicate that different local tumour-related factors, such as tumour type, stage or associated immunity, might be the ones responsible for microbiota-shaping effect. Finally, the “shift” towards Firmicutes in LL might be a sign of increased pathogenicity, as suggested in similar malignancies, and connected to worse prognosis of the LL tumours. Trial registration ClinicalTrials.gov ID: NCT03068663. Registered February 27, 2017.

Highlights • Covid-19 disease show gastrointestinal symptoms in some patients hinting at a role of gut-lung axis. • Gut microbiota diversity and its role in immunity highlighted. • Possible role of gut microbiota in Covid-19 discussed. • Implications of gut dysbiosis in Covid-19 analysed. • Role of diet in strengthening the gut microbiota and in the context of Covid-19 discussed. • Suggestions on therapy and prophylaxis based on gut microbiota in Covid-19., Covid-19 is a major pandemic facing the world today caused by SARS-CoV-2 which has implications on our understanding of infectious diseases. Although, SARS-Cov-2 primarily causes lung infection through binding of ACE2 receptors present on the alveolar epithelial cells, yet it was recently reported that SARS-CoV-2 RNA was found in the faeces of infected patients. Interestingly, the intestinal epithelial cells particularly the enterocytes of the small intestine also express ACE2 receptors. Role of the gut microbiota in influencing lung diseases has been well articulated. It is also known that respiratory virus infection causes perturbations in the gut microbiota. Diet, environmental factors and genetics play an important role in shaping gut microbiota which can influence immunity. Gut microbiota diversity is decreased in old age and Covid-19 has been mainly fatal in elderly patients which again points to the role the gut microbiota may play in this disease. Improving gut microbiota profile by personalized nutrition and supplementation known to improve immunity can be one of the prophylactic ways by which the impact of this disease can be minimized in old people and immune-compromised patients. More trials may be initiated to see the effect of co-supplementation of personalized functional food including prebiotics/probiotics along with current therapies.

International audience; AbstractInfection with Bordetella bronchiseptica (Bb), a pathogen involved in canine infectious respiratory disease complex, can be confirmed using culture or qPCR. Studies about the canine lung microbiota (LM) are recent, sparse, and only one paper has been published in canine lung infection. In this study, we aimed to compare the LM between Bb infected and healthy dogs, and to correlate sequencing with culture and qPCR results. Twenty Bb infected dogs diagnosed either by qPCR and/or culture and 4 healthy dogs were included. qPCR for Mycoplasma cynos (Mc) were also available in 18 diseased and all healthy dogs. Sequencing results, obtained from bronchoalveolar lavage fluid after DNA extraction, PCR targeting the V1–V3 region of the 16S rDNA and sequencing, showed the presence of Bb in all diseased dogs, about half being co-infected with Mc. In diseased compared with healthy dogs, the β-diversity changed (P = 0.0024); bacterial richness and α-diversity were lower (P = 0.012 and 0.0061), and bacterial load higher (P = 0.004). Bb qPCR classes and culture results correlated with the abundance of Bb (r = 0.71, P

The advances in molecular biology and the emergence of Next Generation Sequencing (NGS) have revealed that microbiome composition is closely related with health and disease, including cancer. This relationship affects different levels of cancer such as development, progression, and response to treatment including immunotherapy. The efficacy of immune checkpoint inhibitors (ICIs) may be influenced by the concomitant use of antibiotics before, during or shortly after treatment with ICIs. Nevertheless, the linking mechanism between microbiote, host immunity and cancer is not clear and the role of microbiota manipulation and analyses in cancer management has not been clinically validated yet. Regarding the use of microbiome as biomarker to predict ICI efficacy it has been recently shown that the use of biochemical serum markers to monitor intestinal permeability and loss of barrier integrity, like citrulline, could be useful to monitor microbiota changes and predict ICI efficacy. There are still many unknowns about the role of these components, their relationship with the microbiota, with the use of antibiotics and the response to immunotherapy. The next challenge in microbiome research will be to identify individual microbial species that causally affect lung cancer phenotypes and response to ICI and disentangle the underlying mechanisms. Thus, further analyses in patients with lung cancer receiving treatment with ICIs and its correlation with the composition of the microbiota in different organs including the respiratory tract, peripheral blood and intestinal tract could be useful to predict the efficacy of ICIs and its modulation with antibiotic use. JP reported research funding from BMS and Gilead and speaker honoraria from Gilead and Pfizer. EG reported research funding from BMS and Gilead. JP and EG were funded by FEDER (Fondo Europeo de Desarrollo Regional, Gobierno de Aragón (Group B29_17R), Ministerio de Ciencia, Innovación e Universidades (MCNU), Agencia Estatal de Investigación (SAF2017-83120-C2- 1-R), Fundacion Inocente Inocente, ASPANOA and Carrera de la Mujer de Monzón. JP was supported by ARAID Foundation. DI reported consultation honoraria from AbbVie, Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Eli Lilly Oncology, F. Hoffmann-La Roche, Merck, MSD, Novartis, Pierre Fabre, Pfizer, and Takeda. DI reported speaker honoraria from Amgen, AstraZeneca, BMS, Boehringer Ingelheim, Eli Lilly Oncology, F. Hoffmann-La Roche, MSD, Novartis, Pierre Fabre, and Pfizer. DI reported research grant from AstraZeneca, BMS, F. Hoffmann-La Roche, MSD, and Pierre Fabre.

Microbial communities infiltrate the respiratory tract of cystic fibrosis patients, where chronic colonization and infection lead to clinical decline. This report aims to provide an overview of the diversity of bacterial and fungal species from the airway secretion of three young CF patients with severe pulmonary disease. The bacterial and fungal microbiomes were investigated by culture isolation, metataxonomics, and metagenomics shotgun. Virulence factors and antibiotic resistance genes were also explored. A. fumigatus was isolated from cultures and identified in high incidence from patient sputum samples. Candida albicans, Penicillium sp., Hanseniaspora sp., Torulaspora delbrueckii, and Talaromyces amestolkiae were isolated sporadically. Metataxonomics and metagenomics detected fungal reads (Saccharomyces cerevisiae, A. fumigatus, and Schizophyllum sp.) in one sputum sample. The main pathogenic bacteria identified were Staphylococcus aureus, Pseudomonas aeruginosa, Burkholderia cepacia complex, and Achromobacter xylosoxidans. The canonical core CF microbiome is composed of species from the genera Streptococcus, Neisseria, Rothia, Prevotella, and Haemophilus. Thus, the airways of the three young CF patients presented dominant bacterial genera and interindividual variability in microbial community composition and diversity. Additionally, a wide diversity of virulence factors and antibiotic resistance genes were identified in the CF lung microbiomes, which may be linked to the clinical condition of the CF patients. Understanding the microbial community is crucial to improve therapy because it may have the opposite effect, restructuring the pathogenic microbiota. Future studies focusing on the influence of fungi on bacterial diversity and microbial interactions in CF microbiomes will be welcome to fulfill this huge gap of fungal influence on CF physiopathology.

Lung cancer is the main cause of death by cancer worldwide. Despite the variety of available treatments, including surgery, chemotherapy, radiotherapy, and immune therapy, the average 5-year survival is 60%. One of the underlying reasons is a very high variability in patients’ susceptibility to treatment, explained by genetic background and since recently – our microbiota. The term microbiota includes bacteria, archaea, fungi, viruses and protists that inhabit our organism. The studies in animal models show that the gut microbiota (focused on bacteria) has a crucial role in host’s responsiveness to therapy through the stimulation of immune system. In this light, several “communication axes” between the gut and distal tumour sites have started to develop, including the “gut-lung” axis. However, the resident microbiota in the lungs that could directly influence the tumour response and interact with the gut microbiota has been scarcely characterised. To enable further development of the idea of the “gut-lung-lung cancer” axis, we included 18 non-small cell lung cancer (NSCLC) patients eligible for surgery and analysed the microbiota from four different lung samples (non-malignant, peritumoural and tumour tissue and bronchoalveolar lavage fluid; BAL), saliva and faeces by high-throughput sequencing. We also analysed several immune markers, as lymphocytic tumour infiltrate, Th and neutrophil profiles and cytokines in BAL and blood, and inflammatory markers in faeces along with short-chain fatty acids. Focusing first on the lungs, we show that BAL microbiota represents a significantly distinct community compared to lung tissue microbiota by providing detailed characterisation of the four different lung samples. Since tumours in lower lobes are reported as the ones with the worse prognosis, we investigated how the lobe location affected the microbiota composition. Peritumoural tissue and BAL microbiota were identified as the most affected in both abundance and diversity, and tumour as the least affected. However, phylum Firmicutes, previously reported as elevated in chronic obstructive pulmonary disease compared to controls, was found more abundant in microbiota from lower lung lobes. Therefore, we propose that both increase in Firmicutes and extensive changes in peritumoural tissue could be associated to increased aggressiveness of the lower lobe tumours. Next, we show that the presence of metastatic lymph nodes (LN), negative prognostic marker in NSCLC, significantly influence the local tissue microbiota in relation to its respiratory profile. We reported that anaerobic bacteria were more abundant within the tumour in the presence of metastatic LN, and aerobic bacteria within the one without it. Moreover, exactly inverse was observed for the same bacteria in extratumoural tissues. Along with migratory hypothesis depending on the bacterial preference for growth conditions shaped by tumour’s features, we propose several biomarkers for detection of metastatic LN that might facilitate their detection without imposing LN biopsy. Finally, we showed that BAL microbiota is the most associated to the local immune response and independent of the presence of metastatic LN. Future research will focus on the exploration of the interaction between the lung microbiota, systemic immunity and the gut microbiota.; Le cancer du poumon est la principale cause de décès par cancer dans le monde. En dépit de la variété de traitements disponibles, tels que la chirurgie, la chimiothérapie, la radiothérapie et l’immunothérapie, la survie moyenne à 5 ans est de 60 %. L’une des raisons sous-jacente est une très grande variabilité de réponse au traitement, expliquée par les antécédents génétiques du patient et depuis peu par son microbiote. Le terme « microbiote » regroupe les bactéries, les archées, les champignons, les virus et les protistes qui colonisent notre organisme. Des études utilisant des modèles animaux montrent que le microbiote intestinal joue un rôle crucial dans la réponse de l’hôte au traitement, via la stimulation du système immunitaire. Dans ce contexte, plusieurs « axes de communication » entre le site intestinal et les sites tumoraux distaux commencent à émerger, y compris l’axe « intestin-poumon ». Cependant, le microbiote pulmonaire, qui pourrait directement influencer la réponse tumorale et interagir avec le microbiote intestinal, est pour l’heure peu caractérisé. Afin de développer cette idée d’un axe « intestin, poumon et cancer du poumon », nous avons inclus dans notre étude 18 patients atteints d’un cancer du poumon non à petites cellules (CBNPC) admissibles à la chirurgie. Nous avons analysé leurs microbiotes par séquençage à haut débit à partir de quatre échantillons différents de poumon (tissu sain, tissus péritumoral et tumoral et fluide de lavage broncho-alvéolaire LBA) mais également à partir d’échantillons de salive et de fèces. Nous avons également analysé plusieurs marqueurs immunitaires (infiltration lymphocytaire des tumeurs, profils Th et neutrophiles, cytokines dans le LBA et le sang), des marqueurs inflammatoires et enfin les acides gras à chaînes courtes dans les fèces. Une caractérisation détaillée de ces quatre types d’échantillons de poumons nous a permis de montrer que le microbiote du LBA présente une communauté nettement distincte de celle du tissu pulmonaire. Les tumeurs des lobes inférieurs prédisant le plus mauvais pronostic, nous avons décidé d’étudier le lien entre l’emplacement des tumeurs et la composition du microbiote. Les microbiotes du tissu péritumoral et du LBA ont été identifiés comme étant les plus impactés en terme d’abondance et de diversité ; la tumeur est quant à elle moins impactée. Cependant nous avons observé que le phylum des Firmicutes, décrit comme étant élevé dans les maladies pulmonaires obstructives chroniques, est plus abondant dans le microbiote des lobes inférieurs du poumon. Par conséquent, nous pouvons émettre l’hypothèse que l’augmentation des Firmicutes et les variations importantes du microbiote dans le tissu péritumoral pourraient être associés à une agressivité accrue des tumeurs du lobe inférieur. Nous avons ensuite démontré que la présence de ganglions lymphatiques (GL) métastatiques, marqueur d’un pronostic négatif dans le NSCLC, influence considérablement le microbiote local de par le profil respiratoire du tissu. Nous avons en effet observé que les bactéries anaérobies étaient plus abondantes dans les tumeurs en présence de LN métastatiques. Les bactéries aérobies sont quant à elles plus représentées dans les tumeurs sans GL métastatiques. Nous avons cependant observé la situation inverse dans les tissus extratumoraux. L’hypothèse avancée est celle d’une migration bactérienne en fonction des préférences de conditions de croissance, directement liées aux caractéristiques de la tumeur. Ceci nous permet de proposer plusieurs biomarqueurs pour la détection de GL métastatique, facilitant ainsi leur détection sans imposer de biopsie. Enfin, nous montrons que le microbiote du LBA est d’avantage associé à la réponse immunitaire locale et est indépendant de la présence de GL métastatique. Les recherches à venir porteront sur l’exploration de l’interaction entre le microbiote pulmonaire, l’immunité systémique et le microbiote intestinal.