Dataset Information

Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions.

ABSTRACT: Breast microbiota compositions are not well understood, and a few recent reports have begun to explore the correlation between breast tissue dysbiosis and cancer. Given that various methods for breast microbiota detection were used, the aim of the present paper was to clarify which hypervariable region of the 16S-rRNA gene (V2, V3, V4, V6 + 7, V8, and V9) is the most informative for breast tissue microbiota. Core needle biopsies (CNBs) were compared with surgical excision biopsies (SEBs) to find a less invasive form of recovery useful for the analysis of a larger statistical population and potentially for diagnostic use of breast tissue microbiota. Finally, this study was the first to analyse the breast microbiota of tumours and paired normal tissues of a Mediterranean population. Our findings showed that the V3 region is the most informative for breast tissue microbiota, accounting for 45% of all reads. No significant differences were found between CNB and SEB specimens in terms of total reads and numbers of Operational Taxonomic Units (OTUs). Moreover, we find that more similarities than differences exist between tumours and adjacent normal tissues. Finally, the presence of the Ralstonia genus is associated with breast tissue.

SUBMITTER: Costantini L

PROVIDER: S-EPMC6237987 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions.

Costantini Lara L Costantini Lara L Magno Stefano S Albanese Davide D Donati Claudio C Molinari Romina R Filippone Alessio A Masetti Riccardo R Merendino Nicolò N

Scientific reports 20181115 1

Breast microbiota compositions are not well understood, and a few recent reports have begun to explore the correlation between breast tissue dysbiosis and cancer. Given that various methods for breast microbiota detection were used, the aim of the present paper was to clarify which hypervariable region of the 16S-rRNA gene (V2, V3, V4, V6 + 7, V8, and V9) is the most informative for breast tissue microbiota. Core needle biopsies (CNBs) were compared with surgical excision biopsies (SEBs) to find ...[more]

PMID: 30442969

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Project description:BackgroundThe 16S rRNA gene is used extensively in bacterial phylogenetics, in species delineation, and now widely in microbiome studies. However, the gene suffers from intragenomic heterogeneity, and reports of recombination and an unreliable phylogenetic signal are accumulating. Here, we compare core gene phylogenies to phylogenies constructed using core gene concatenations to estimate the strength of signal for the 16S rRNA gene, its hypervariable regions, and all core genes at the intra- and inter-genus levels. Specifically, we perform four intra-genus analyses (Clostridium, n = 65; Legionella, n = 47; Staphylococcus, n = 36; and Campylobacter, n = 17) and one inter-genus analysis [41 core genera of the human gut microbiome (31 families, 17 orders, and 12 classes), n = 82].ResultsAt both taxonomic levels, the 16S rRNA gene was recombinant and subject to horizontal gene transfer. At the intra-genus level, the gene showed one of the lowest levels of concordance with the core genome phylogeny (50.7% average). Concordance for hypervariable regions was lower still, with entropy masking providing little to no benefit. A major factor influencing concordance was SNP count, which showed a positive logarithmic association. Using this relationship, we determined that 690 ± 110 SNPs were required for 80% concordance (average 16S rRNA gene SNP count was 254). We also found a wide range in 16S-23S-5S rRNA operon copy number among genomes (1-27). At the inter-genus level, concordance for the whole 16S rRNA gene was markedly higher (73.8% - 10th out of 49 loci); however, the most concordant hypervariable regions (V4, V3-V4, and V1-V2) ranked in the third quartile (62.5 to 60.0%).ConclusionsRamifications of a poor phylogenetic performance for the 16S rRNA gene are far reaching. For example, in addition to incorrect species/strain delineation and phylogenetic inference, it has the potential to confound community diversity metrics if phylogenetic information is incorporated - for example, with popular approaches such as Faith's phylogenetic diversity and UniFrac. Our results highlight the problematic nature of these approaches and their use (along with entropy masking) is discouraged. Lastly, the wide range in 16S rRNA gene copy number among genomes also has a strong potential to confound diversity metrics. Video Abstract.

Project description:Proper preservation of stool samples to minimize microbial community shifts and inactivate infectious agents is important for self-collected specimens requiring shipment to laboratories when cold chain transport is not feasible. In this study, we evaluated the performance of six preservation solutions (Norgen, OMNI, RNAlater, CURNA, HEMA, and Shield) for these aspects. Following storage of human stool samples with these preservatives at room temperature for 7 days, three hypervariable regions of the bacterial 16S rRNA gene (V1-V2, V3-V4, and V4) were amplicon sequenced. We found that samples collected in two preservatives, Norgen and OMNI, showed the least shift in community composition relative to -80°C standards compared with other storage conditions, and both efficiently inhibited the growth of aerobic and anaerobic bacteria. RNAlater did not prevent bacterial activity and exhibited relatively larger community shift. Although the effect of preservation solution was small compared to intersubject variation, notable changes in microbiota composition were observed, which could create biases in downstream data analysis. When community profiles inferred from different 16S rRNA gene hypervariable regions were compared, we found differential sensitivity of primer sets in identifying overall microbial community and certain bacterial taxa. For example, reads generated by the V4 primer pair showed a higher alpha diversity of the gut microbial community. The degenerate 27f-YM primer failed to detect the majority of Bifidobacteriales. Our data indicate that choice of preservation solution and 16S rRNA gene primer pair are critical determinants affecting gut microbiota profiling. IMPORTANCE Large-scale human microbiota studies require specimens collected from multiple sites and/or time points to maximize detection of the small effects in microbe-host interactions. However, batch biases caused by experimental protocols, such as sample collection, massively parallel sequencing, and bioinformatics analyses, remain critical and should be minimized. This work evaluated the effects of preservation solutions and bacterial 16S rRNA gene primer pairs in revealing human gut microbiota composition. Since notable changes in detecting bacterial composition and abundance were observed among choice of preservatives and primer pairs, a consistent methodology is essential in minimizing their effects to facilitate comparisons between data sets.

Project description:ObjectivesThere is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.MethodsThis paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kit™ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.ResultsResults are presented at family and genus level. The Kullback-Leibler divergence (DKL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average DKL while the V4 gave the lowest (best) average DKL. In addition to having a high DKL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.ConclusionsThe results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.

Dataset Information

Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions.

Publications

Characterization of human breast tissue microbiota from core needle biopsies through the analysis of multi hypervariable 16S-rRNA gene regions.

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