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      Airway Microbiota Is Associated with Upregulation of the PI3K Pathway in Lung Cancer

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          Abstract

          <p class="first" id="d380206e418"> <b>Rationale:</b> In lung cancer, upregulation of the PI3K (phosphoinositide 3-kinase) pathway is an early event that contributes to cell proliferation, survival, and tissue invasion. Upregulation of this pathway was recently described as associated with enrichment of the lower airways with bacteria identified as oral commensals. </p><p id="d380206e423"> <b>Objectives:</b> We hypothesize that host–microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. </p><p id="d380206e428"> <b>Methods:</b> Airway brushings were collected prospectively from subjects with lung nodules at time of diagnostic bronchoscopy, including 39 subjects with final lung cancer diagnoses and 36 subjects with noncancer diagnoses. In addition, samples from 10 healthy control subjects were included. 16S ribosomal RNA gene amplicon sequencing and paired transcriptome sequencing were performed on all airway samples. In addition, an <i>in vitro</i> model with airway epithelial cells exposed to bacteria/bacterial products was performed. </p><p id="d380206e436"> <b>Measurements and Main Results:</b> The composition of the lower airway transcriptome in the patients with cancer was significantly different from the control subjects, which included up-regulation of ERK (extracellular signal–regulated kinase) and PI3K signaling pathways. The lower airways of patients with lung cancer were enriched for oral taxa ( <i>Streptococcus</i> and <i>Veillonella</i>), which was associated with up-regulation of the ERK and PI3K signaling pathways. <i>In vitro</i> exposure of airway epithelial cells to <i>Veillonella</i>, <i>Prevotella</i>, and <i>Streptococcus</i> led to upregulation of these same signaling pathways. </p><p id="d380206e460"> <b>Conclusions:</b> The data presented here show that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals. </p>

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          Most cited references24

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          Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution.

          Recent data from several organisms indicate that the transcribed portions of genomes are larger and more complex than expected, and that many functional properties of transcripts are based not on coding sequences but on regulatory sequences in untranslated regions or non-coding RNAs. Alternative start and polyadenylation sites and regulation of intron splicing add additional dimensions to the rich transcriptional output. This transcriptional complexity has been sampled mainly using hybridization-based methods under one or few experimental conditions. Here we applied direct high-throughput sequencing of complementary DNAs (RNA-Seq), supplemented with data from high-density tiling arrays, to globally sample transcripts of the fission yeast Schizosaccharomyces pombe, independently from available gene annotations. We interrogated transcriptomes under multiple conditions, including rapid proliferation, meiotic differentiation and environmental stress, as well as in RNA processing mutants to reveal the dynamic plasticity of the transcriptional landscape as a function of environmental, developmental and genetic factors. High-throughput sequencing proved to be a powerful and quantitative method to sample transcriptomes deeply at maximal resolution. In contrast to hybridization, sequencing showed little, if any, background noise and was sensitive enough to detect widespread transcription in >90% of the genome, including traces of RNAs that were not robustly transcribed or rapidly degraded. The combined sequencing and strand-specific array data provide rich condition-specific information on novel, mostly non-coding transcripts, untranslated regions and gene structures, thus improving the existing genome annotation. Sequence reads spanning exon-exon or exon-intron junctions give unique insight into a surprising variability in splicing efficiency across introns, genes and conditions. Splicing efficiency was largely coordinated with transcript levels, and increased transcription led to increased splicing in test genes. Hundreds of introns showed such regulated splicing during cellular proliferation or differentiation.
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            Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

            We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community.
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              Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype.

              Microaspiration is a common phenomenon in healthy subjects, but its frequency is increased in chronic inflammatory airway diseases, and its role in inflammatory and immune phenotypes is unclear. We have previously demonstrated that acellular bronchoalveolar lavage samples from half of the healthy people examined are enriched with oral taxa (here called pneumotypeSPT) and this finding is associated with increased numbers of lymphocytes and neutrophils in bronchoalveolar lavage. Here, we have characterized the inflammatory phenotype using a multi-omic approach. By evaluating both upper airway and acellular bronchoalveolar lavage samples from 49 subjects from three cohorts without known pulmonary disease, we observed that pneumotypeSPT was associated with a distinct metabolic profile, enhanced expression of inflammatory cytokines, a pro-inflammatory phenotype characterized by elevated Th-17 lymphocytes and, conversely, a blunted alveolar macrophage TLR4 response. The cellular immune responses observed in the lower airways of humans with pneumotypeSPT indicate a role for the aspiration-derived microbiota in regulating the basal inflammatory status at the pulmonary mucosal surface.
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                Author and article information

                Journal
                American Journal of Respiratory and Critical Care Medicine
                Am J Respir Crit Care Med
                American Thoracic Society
                1073-449X
                1535-4970
                November 2018
                November 2018
                : 198
                : 9
                : 1188-1198
                Affiliations
                [1 ]Division of Pulmonary and Critical Care Medicine
                [2 ]Flatiron Institute, Center for Computational Biology, Simons Foundation, New York, New York
                [3 ]Department of Genetics and Genomic Sciences and Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York
                [4 ]New York University Genomic Technology Center, New York, New York; and
                [5 ]Department of Cardiothoracic Surgery, and
                [6 ]New York University Center for Data Science, New York, New York
                [7 ]Department of Medicine, New York University School of Medicine, New York, New York
                Article
                10.1164/rccm.201710-2118OC
                6221574
                29864375
                97deaf8b-13ec-4c01-9ff0-b4b159493bee
                © 2018
                History

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