BackgroundLung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort.ResultsOverall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas.ConclusionsThe results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1501-6) contains supplementary material, which is available to authorized users.

BackgroundPan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.ResultsAnalysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of > 90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.ConclusionsOur microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0569-2) contains supplementary material, which is available to authorized users.

Cells in culture deposit a complex extracellular matrix that remains intact following decellularization and possesses the capacity to modulate cell phenotype. The direct application of such decellularized matrices (DMs) to 3D substrates is problematic, as transport issues influence the homogeneous deposition, decellularization, and modification of DM surface coatings. In an attempt to address this shortcoming, we hypothesized that DMs deposited by human mesenchymal stem cells (MSCs) could be transferred to the surface of polymeric scaffolds while maintaining their capacity to direct cell fate. The ability of the transferred DM (tDM)-coated scaffolds to enhance the osteogenic differentiation of undifferentiated and osteogenically induced MSCs under osteogenic conditions in vitro was confirmed. tDM-coated scaffolds increased MSC expression of osteogenic marker genes (BGLAP, IBSP) and intracellular alkaline phosphatase production. In addition, undifferentiated MSCs deposited significantly more calcium when seeded onto tDM-coated scaffolds compared with control scaffolds. MSC-seeded tDM-coated scaffolds subcutaneously implanted in nude rats displayed significantly higher blood vessel density after 2 weeks compared with cells on uncoated scaffolds, but we did not observe significant differences in mineral deposition after 8 weeks. These data demonstrate that DM-coatings produced in 2D culture can be successfully transferred to 3D substrates and retain their capacity to modulate cell phenotype.

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Background: Pan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family-or genus-level taxonomy.Moreover, sequencing errors often inflate the number of taxa present. PacificBiosciences' (PacBio's) long-read technology in particular suffers from high error rates per base. Herein we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome dataResults: Analysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity. Examination of a 250-plus species mock community demonstrated correct species-level classification of >90% of taxa and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed.Propiniobacterium acnes (recently renamed Cutibacterium acnes [1]) was the predominant species throughout, but was found at distinct relative abundances by site. Conclusions:Our microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt) overcomes deficits of standard marker gene based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution.Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.