Rationale: Understanding the role of the airway microbiome in chronic obstructive pulmonary disease (COPD) inflammatory endotypes may help to develop microbiome-based diagnostic and therapeutic approaches. Objectives: To understand the association of the airway microbiome with neutrophilic and eosinophilic COPD at stability and during exacerbations. Methods: An integrative analysis was performed on 1,706 sputum samples collected longitudinally from 510 patients with COPD recruited at four UK sites of the BEAT-COPD (Biomarkers to Target Antibiotic and Systemic COPD), COPDMAP (Chronic Obstructive Pulmonary Disease Medical Research Council/Association of the British Pharmaceutical Industry), and AERIS (Acute Exacerbation and Respiratory Infections in COPD) cohorts. The microbiome was analyzed using COPDMAP and AERIS as a discovery data set and BEAT-COPD as a validation data set. Measurements and Main Results: The airway microbiome in neutrophilic COPD was heterogeneous, with two primary community types differentiated by the predominance of Haemophilus. The Haemophilus-predominant subgroup had elevated sputum IL-1β and TNFα (tumor necrosis factor α) and was relatively stable over time. The other neutrophilic subgroup with a balanced microbiome profile had elevated sputum and serum IL-17A and was temporally dynamic. Patients in this state at stability were susceptible to the greatest microbiome shifts during exacerbations. This subgroup can temporally switch to both neutrophilic Haemophilus-predominant and eosinophilic states that were otherwise mutually exclusive. Time-series analysis on the microbiome showed that the temporal trajectories of Campylobacter and Granulicatella were indicative of intrapatient switches from neutrophilic to eosinophilic inflammation, in track with patient sputum eosinophilia over time. Network analysis revealed distinct host–microbiome interaction patterns among neutrophilic Haemophilus-predominant, neutrophilic balanced microbiome, and eosinophilic subgroups. Conclusions: The airway microbiome can stratify neutrophilic COPD into subgroups that justify different therapies. Neutrophilic and eosinophilic COPD are interchangeable in some patients. Monitoring temporal variability of the airway microbiome may track patient inflammatory status over time.

Emerging evidence indicates an association between gut microbiome and arthritis diseases including gout. However, how and which gut bacteria affect host urate degradation and inflammation in gout remains unclear. Here we performed a metagenome analysis on 307 fecal samples from 102 gout patients and 86 healthy controls. Gout metagenomes significantly differed from those of healthy controls. The relative abundances of Prevotella, Fusobacterium, and Bacteroides were increased in gout, whereas those of Enterobacteriaceae and butyrate-producing species were decreased. Functionally, gout patients had greater abundances for genes in fructose, mannose metabolism and lipid A biosynthesis, and lower for genes in urate degradation and short chain fatty acid production. A three-pronged association between metagenomic species, functions and clinical parameters revealed that decreased abundances of species in Enterobacteriaceae were associated with reduced amino acid metabolism and environmental sensing, which together contribute to increased serum uric acid and C-reactive protein levels in gout. A random forest classifier based on three gut microbial genes showed high predictivity for gout in both discovery and validation cohorts (0.91 and 0.80 accuracy), with high specificity in the context of other chronic disorders. Longitudinal analysis showed that uric-acid-lowering and anti-inflammatory drugs partially restored gut microbiota after 24-week treatment. Comparative analysis with obesity, type 2 diabetes, ankylosing spondylitis and rheumatoid arthritis indicated that gout metagenomes were more similar to those of autoimmune than metabolic diseases. Our results suggest that gut dysbiosis was associated with dysregulated host urate degradation and systemic inflammation and may be used as non-invasive diagnostic markers for gout.

Mining is among the human activities with widest environmental impacts, and mining-impacted environments are characterized by high levels of metals that can co-select for antibiotic resistance genes (ARGs) in microorganisms. However, ARGs in mining-impacted environments are still poorly understood. Here, we conducted a comprehensive study of ARGs in such environments worldwide, taking advantage of 272 metagenomes generated from a global-scale data collection and two national sampling efforts in China. The average total abundance of the ARGs in globally distributed studied mine sites was 1572 times per gigabase, being rivaling that of urban sewage but much higher than that of freshwater sediments. Multidrug resistance genes accounted for 40% of the total ARG abundance, tended to co-occur with multimetal resistance genes, and were highly mobile (e.g. on average 16% occurring on plasmids). Among the 1848 high-quality metagenome-assembled genomes (MAGs), 85% carried at least one multidrug resistance gene plus one multimetal resistance gene. These high-quality ARG-carrying MAGs considerably expanded the phylogenetic diversity of ARG hosts, providing the first representatives of ARG-carrying MAGs for the Archaea domain and three bacterial phyla. Moreover, 54 high-quality ARG-carrying MAGs were identified as potential pathogens. Our findings suggest that mining-impacted environments worldwide are underexplored hotspots of multidrug resistance genes.