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Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiome.

Nayfach S, Pollard KS - Genome Biol. (2015)

Bottom Line: We developed MicrobeCensus to rapidly and accurately estimate average genome size from shotgun metagenomic data and applied our tool to 1,352 human microbiome samples.We found that average genome size differs significantly within and between body sites and tracks with major functional and taxonomic differences.In the gut, average genome size is positively correlated with the abundance of Bacteroides and genes related to carbohydrate metabolism.

View Article: PubMed Central - PubMed

ABSTRACT
Average genome size is an important, yet often overlooked, property of microbial communities. We developed MicrobeCensus to rapidly and accurately estimate average genome size from shotgun metagenomic data and applied our tool to 1,352 human microbiome samples. We found that average genome size differs significantly within and between body sites and tracks with major functional and taxonomic differences. In the gut, average genome size is positively correlated with the abundance of Bacteroides and genes related to carbohydrate metabolism. Importantly, we found that average genome size variation can bias comparative analyses, and that normalization improves detection of differentially abundant genes.

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Average genome size reflects diverse modes of functional adaptation in the gut microbiome. (A) Barplot of AGS for stool metagenomes. (B) Log2 fold change of KOs across stool metagenomes. KOs were grouped according to the BRITE functional hierarchy. Only KOs that were significantly correlated with AGS (q < 1e-3) are displayed. (C) Log2 fold change of essential single-copy KOs across stool metagenomes.
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Fig7: Average genome size reflects diverse modes of functional adaptation in the gut microbiome. (A) Barplot of AGS for stool metagenomes. (B) Log2 fold change of KOs across stool metagenomes. KOs were grouped according to the BRITE functional hierarchy. Only KOs that were significantly correlated with AGS (q < 1e-3) are displayed. (C) Log2 fold change of essential single-copy KOs across stool metagenomes.

Mentions: To better understand this major axis of functional variation in the gut, we sought to identify classes of genes that were commonly associated with AGS. Towards this goal, we performed tests of enrichment using the BRITE functional hierarchy [38], which is an ontology that groups genes that perform related biological functions (Additional file 15). A striking pattern emerged when looking at the top-ranked functional categories from this analysis: genes whose abundances were positively correlated with AGS were enriched in functional categories related to metabolism, biosynthesis, and two-component systems, whereas genes negatively correlated with AGS were enriched in categories related to membrane transport (Figure 7 and Table 1). For example, 27% of genes in two-component systems were positively associated with AGS, compared with only 3% that were negatively associated (q < 1e-5, mean ρ = 0.15); in contrast, 30% of ABC transporter genes were negatively associated with AGS, compared with only 8% that were positively associated (q < 0.01, mean ρ = -0.15). Furthermore, the gene rpoE, an ECF-sigma factor involved in regulating expression of polysaccharide utilization loci [38], was strongly correlated with AGS (q = 0, ρ = 0.87) and reached extremely high levels of abundance in the gut.Figure 7


Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiome.

Nayfach S, Pollard KS - Genome Biol. (2015)

Average genome size reflects diverse modes of functional adaptation in the gut microbiome. (A) Barplot of AGS for stool metagenomes. (B) Log2 fold change of KOs across stool metagenomes. KOs were grouped according to the BRITE functional hierarchy. Only KOs that were significantly correlated with AGS (q < 1e-3) are displayed. (C) Log2 fold change of essential single-copy KOs across stool metagenomes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4389708&req=5

Fig7: Average genome size reflects diverse modes of functional adaptation in the gut microbiome. (A) Barplot of AGS for stool metagenomes. (B) Log2 fold change of KOs across stool metagenomes. KOs were grouped according to the BRITE functional hierarchy. Only KOs that were significantly correlated with AGS (q < 1e-3) are displayed. (C) Log2 fold change of essential single-copy KOs across stool metagenomes.
Mentions: To better understand this major axis of functional variation in the gut, we sought to identify classes of genes that were commonly associated with AGS. Towards this goal, we performed tests of enrichment using the BRITE functional hierarchy [38], which is an ontology that groups genes that perform related biological functions (Additional file 15). A striking pattern emerged when looking at the top-ranked functional categories from this analysis: genes whose abundances were positively correlated with AGS were enriched in functional categories related to metabolism, biosynthesis, and two-component systems, whereas genes negatively correlated with AGS were enriched in categories related to membrane transport (Figure 7 and Table 1). For example, 27% of genes in two-component systems were positively associated with AGS, compared with only 3% that were negatively associated (q < 1e-5, mean ρ = 0.15); in contrast, 30% of ABC transporter genes were negatively associated with AGS, compared with only 8% that were positively associated (q < 0.01, mean ρ = -0.15). Furthermore, the gene rpoE, an ECF-sigma factor involved in regulating expression of polysaccharide utilization loci [38], was strongly correlated with AGS (q = 0, ρ = 0.87) and reached extremely high levels of abundance in the gut.Figure 7

Bottom Line: We developed MicrobeCensus to rapidly and accurately estimate average genome size from shotgun metagenomic data and applied our tool to 1,352 human microbiome samples.We found that average genome size differs significantly within and between body sites and tracks with major functional and taxonomic differences.In the gut, average genome size is positively correlated with the abundance of Bacteroides and genes related to carbohydrate metabolism.

View Article: PubMed Central - PubMed

ABSTRACT
Average genome size is an important, yet often overlooked, property of microbial communities. We developed MicrobeCensus to rapidly and accurately estimate average genome size from shotgun metagenomic data and applied our tool to 1,352 human microbiome samples. We found that average genome size differs significantly within and between body sites and tracks with major functional and taxonomic differences. In the gut, average genome size is positively correlated with the abundance of Bacteroides and genes related to carbohydrate metabolism. Importantly, we found that average genome size variation can bias comparative analyses, and that normalization improves detection of differentially abundant genes.

Show MeSH