Beyond the pan-genome: current perspectives on the functional and practical outcomes of the distributed genome hypothesis.

The principle of monoclonality with regard to bacterial infections was considered immutable prior to 30 years ago. This view, espoused by Koch for acute infections, has proven inadequate regarding chronic infections as persistence requires multiple forms of heterogeneity among the bacterial population. This understanding of bacterial plurality emerged from a synthesis of what-were-then novel technologies in molecular biology and imaging science. These technologies demonstrated that bacteria have complex life cycles, polymicrobial ecologies, and evolve in situ via the horizontal exchange of genic characters. Thus, there is an ongoing generation of diversity during infection that results in far more highly complex microbial communities than previously envisioned. This perspective is based on the fundamental tenet that the bacteria within an infecting population display genotypic diversity, including gene possession differences, which result from horizontal gene transfer mechanisms including transformation, conjugation, and transduction. This understanding is embodied in the concepts of the supragenome/pan-genome and the distributed genome hypothesis (DGH). These paradigms have fostered multiple researches in diverse areas of bacterial ecology including host-bacterial interactions covering the gamut of symbiotic relationships including mutualism, commensalism, and parasitism. With regard to the human host, within each of these symbiotic relationships all bacterial species possess attributes that contribute to colonization and persistence; those species/strains that are pathogenic also encode traits for invasion and metastases. Herein we provide an update on our understanding of bacterial plurality and discuss potential applications in diagnostics, therapeutics, and vaccinology based on perspectives provided by the DGH with regard to the evolution of pathogenicity.

Urinary fungi associated with urinary symptom severity among women with interstitial cystitis/bladder pain syndrome (IC/BPS).

PURPOSE: To correlate the presence of fungi with symptom flares, pain and urinary severity in a prospective, longitudinal study of women with IC/BPS enrolled in the MAPP Research Network. METHODS: Flare status, pelvic pain, urinary severity, and midstream urine were collected at baseline, 6 and 12 months from female IC/BPS participants with at least one flare and age-matched participants with no reported flares. Multilocus PCR coupled with electrospray ionization/mass spectrometry was used for identification of fungal species and genus. Associations between "mycobiome" (species/genus presence, relative abundance, Shannon's/Chao1 diversity indices) and current flare status, pain, urinary severity were evaluated using generalized linear mixed models, permutational multivariate analysis of variance, Wilcoxon's rank-sum test. RESULTS: The most specific analysis detected 13 fungal species from 8 genera in 504 urine samples from 202 females. A more sensitive analysis detected 43 genera. No overall differences were observed in fungal species/genus composition or diversity by flare status or pain severity. Longitudinal analyses suggested greater fungal diversity (Chao1 Mean Ratio 3.8, 95% CI 1.3-11.2, p = 0.02) and a significantly greater likelihood of detecting any fungal species (OR = 5.26, 95% CI 1.1-25.8, p = 0.04) in high vs low urinary severity participants. Individual taxa analysis showed a trend toward increased presence and relative abundance of Candida (OR = 6.63, 95% CI 0.8-58.5, p = 0.088) and Malassezia (only identified in 'high' urinary severity phenotype) for high vs low urinary symptoms. CONCLUSION: This analysis suggests the possibility that greater urinary symptom severity is associated with the urinary mycobiome urine in some females with IC/BPS.

Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.

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. 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. RESULTS: Analysis 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. 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.