Computational protocol: Dairy and plant based food intakes are associated with altered faecal microbiota in 2 to 3 year old Australian children

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Protocol publication

[…] QIIME 1.9.0 was used for bioinformatics. QIIME’s pick_open_reference_otus.py workflow was used to generate OTUs using default parameters (97% sequence similarity; Greengenes reference database–version 13 8 ; uclust OTU picking method). The resulting OTU table was filtered to remove any OTU with a relative abundance of less than 0.05% across all samples. OTUs of significance that were not initially taxonomically classified were aligned with reference sequences using SINA (SILVA Incremental Aligner) to provide further identification.Microbiota composition was described using α and β diversity measures. α-diversity refers to the variety and abundance of species within a sample while β-diversity refers to the difference in α-diversity between samples. α-diversity can be described using richness, which reflects the number of species within a sample and evenness, which measures the similarity in abundance of species. Species richness was estimated using Chao1 while Shannon Index was used to estimate diversity, reflecting both richness and evenness. β-diversity was calculated using the weighted UniFrac distance metric which is a phylogenetic distance measure that quantifies the distance between communities based on the lineages they contain. The OTU table was rarefied to the minimum sample count (42629 reads) for calculation of measures of diversity to control for sequencing depth. Relative counts (read count divided by total reads for that sample) at phylum, genus, and species level were created using the summarize_taxa.py script in QIIME. Firmicutes –Bacteroidetes (F-B) ratio was calculated by dividing log abundances using the compute_taxonomy_ratio.py script in QIIME. [...] Adonis was employed in QIIME to explore associations between with food intakes and the weighted UniFrac distance metric. PICRUSt 1.0.0 was used on the online Galaxy interface (http://huttenhower.sph.harvard.edu/galaxy/) to predict KEGG functional pathways at Level 2 and 3 using a closed reference OTU table created in QIIME using the filter_otus_from_otu_table.py script and the Greengenes reference database–version 13 8. Spearman’s rank correlation was used to explore the impact of food intake on α –diversity and taxa and KEGG functional pathway abundance. P values were adjusted for multiple testing using the False Discovery Rate (FDR) Benjamini-Hochberg procedure. […]

Pipeline specifications

Software tools QIIME, UCLUST, SINA, UniFrac, PICRUSt
Databases Greengenes
Applications Phylogenetics, 16S rRNA-seq analysis
Organisms Homo sapiens, Firmicutes, Bacteroidetes, Escherichia coli, Bacteroides xylanisolvens, Malus domestica