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Background The advent of culture-independent, next-generation DNA sequencing has led to the discovery of distinct lung bacterial communities. Studies of lung microbiome taxonomy often reveal only subtle differences between health and disease, but host recognition and response may distinguish the members of similar bacterial communities in different populations. Magnetic-activated cell sorting has been applied to the gut microbiome to identify the numbers and types of bacteria eliciting a humoral response. We adapted this technique to examine the populations of immunoglobulin-bound bacteria in the lung. Methods Sixty-four individuals underwent bronchoalveolar lavage (BAL). We separated immunoglobulin G-bound bacteria using magnetic-activated cell sorting and sequenced the 16S rRNA gene on the Illumina MiSeq platform. We compared microbial sequencing data in IgG-bound bacterial communities compared to raw BAL then examined the differences in individuals with and without HIV as a representative disease state. Results Immunoglobulin G-bound bacteria were identified in all individuals. The community structure differed when compared to raw BAL, and there was a greater abundance of Pseudomonas and fewer oral bacteria in IgG-bound BAL. Examination of IgG-bound communities in individuals with HIV demonstrated the differences in Ig-bound bacteria by HIV status that were not seen in a comparison of raw BAL, and greater numbers of immunoglobulin-bound bacteria were associated with higher pulmonary cytokine levels. Conclusions We report a novel application of magnetic-activated cell sorting to identify immunoglobulin G-bound bacteria in the lung. This technique identified distinct bacterial communities which differed in composition from raw bronchoalveolar lavage, revealing the differences not detected by traditional analyses. Cytokine response was also associated with differential immunoglobulin binding of lung bacteria, suggesting the functional importance of these communities.

Background Viral infections such as influenza have been shown to predispose hosts to increased colonization of the respiratory tract by pathogenic bacteria and secondary bacterial pneumonia. To examine how viral infections and host antiviral immune responses alter the upper respiratory microbiota, we analyzed nasal bacterial composition by 16S ribosomal RNA (rRNA) gene sequencing in healthy adults at baseline and at 1 to 2 weeks and 4 to 6 weeks following instillation of live attenuated influenza vaccine or intranasal sterile saline. A subset of these samples was submitted for microarray host gene expression profiling. Results We found that live attenuated influenza vaccination led to significant changes in microbial community structure, diversity, and core taxonomic membership as well as increases in the relative abundances of Staphylococcus and Bacteroides genera (both p

Background Psoriasis is a common chronic inflammatory disease of the skin. We sought to characterize and compare the cutaneous microbiota of psoriatic lesions (lesion group), unaffected contralateral skin from psoriatic patients (unaffected group), and similar skin loci in matched healthy controls (control group) in order to discern patterns that govern skin colonization and their relationship to clinical diagnosis. Results Using high-throughput 16S rRNA gene sequencing, we assayed the cutaneous bacterial communities of 51 matched triplets and characterized these samples using community data analysis techniques. Intragroup Unifrac β diversity revealed increasing diversity from control to unaffected to lesion specimens. Likewise, principal coordinates analysis (PCoA) revealed separation of the lesion samples from unaffected and control along the first axis, suggesting that psoriasis is a major contributor to the observed diversity. The taxonomic richness and evenness decreased in both lesion and unaffected communities compared to control. These differences are explained by the combined increased abundance of the four major skin-associated genera (Corynebacterium, Propionibacterium, Staphylococcus, and Streptococcus), which present a potentially useful predictor for clinical skin type. Psoriasis samples also showed significant univariate decreases in relative abundances and strong classification performance of Cupriavidus, Flavisolibacter, Methylobacterium, and Schlegelella genera versus controls. The cutaneous microbiota separated into two distinct clusters, which we call cutaneotypes: (1) Proteobacteria-associated microbiota, and (2) Firmicutes-associated and Actinobacteria-associated microbiota. Cutaneotype 2 is enriched in lesion specimens compared to control (odds ratio 3.52 (95% CI 1.44 to 8.98), P