Computational protocol: Discovery of a Novel Seminal Fluid Microbiome and Influence of Estrogen Receptor Alpha Genetic Status

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Protocol publication

[…] Paired-end Illumina MiSeq DNA reads were joined using FLASH. Usearch7 was used to clean contigs and remove those with E >0.5, as explained here: http://drive5.com/usearch/manual/exp_errs.html. Contigs were clustered to 97% identity against DNA sequences in the Greengenes database, version 13_5, using the QIIME, version 1.8, script pick_closed_reference_otus.py, which obviates chimera and PCR error detection. For alpha-diversity, Chao1 (species richness) and Shannon (species diversity) values were calculated and plotted using the phlyoSeq R package. Rarefaction metrics were calculated using the alpha_rarefaction.py script in the Qiime package and plotted using Microsoft Excel ().Measurements of beta-diversity were facilitated by the QIIME script beta_diversity_through_plots.py and visualized using Principal Coordinate Analysis, PCoA, as implemented in QIIME. LEfSe was used to identify genera most consistently different between sample types. LEfSe results were visualized using taxonomy bar-chart and cladogram plots, as implemented on the LEfSe website, http://huttenhower.sph.harvard.edu/galaxy/. PCoA was used to determine whether age of WT and ESR1 KO mice affected the seminal fluid and fecal microbiome samples, where two age-ranges where compared: <220 and >220 days of age. For the fecal microbiome, metagenomeSeq, version 1.10.0 was used to identify the OTUs in WT and ESR1 KO that varied based on these two age groups. To identify genera associated with the WT and ESR1 KO genotypes within fecal and seminal sample types, we used metagenomeSeq, version 1.10.0. Bacterial metabolic characterization of sample types was facilitated with PICRUSt, version 1.0.0. To correlate the genera changes with metabolic characteristics of sample types, we used a custom R script provided as a gift from Dr. Jun Ma and Kjersti Aagaard-Tillery, Baylor College of Medicine, Houston, TX. […]

Pipeline specifications

Software tools USEARCH, QIIME, LEfSe, metagenomeSeq, PICRUSt
Databases Greengenes
Applications Metagenomic sequencing analysis, 16S rRNA-seq analysis
Organisms Mus musculus, Cutibacterium acnes
Diseases Genital Diseases, Male, Prostatic Neoplasms, Machado-Joseph Disease
Chemicals Carbohydrates, Estrogens