Ecosystem-wide metagenomic binning enables prediction of ecological niches from genomes

• Alneberg et al. conduct metagenomics binning of water samples collected over major environmental gradients in the Baltic Sea. They use machine-learning to predict the placement of genome clusters along niche gradients based on the content of functional genes. The genome encodes the metabolic and functional capabilities of an organism and should be a major determinant of its ecological niche. Yet, it is unknown if the niche can be predicted directly from the genome. Here, we conduct metagenomic binning on 123 water samples spanning major environmental gradients of the Baltic Sea. The resulting 1961 metagenome-assembled genomes represent 352 species-level clusters that correspond to 1/3 of the metagenome sequences of the prokaryotic size-fraction. By using machine-learning, the placement of a genome cluster along various niche gradients (salinity level, depth, size-fraction) could be predicted based solely on its functional genes. The same approach predicted the genomes' placement in a virtual niche-space that captures the highest variation in distribution patterns. The predictions generally outperformed those inferred from phylogenetic information. Our study demonstrates a strong link between genome and ecological niche and provides a conceptual framework for predictive ecology based on genomic data.

Subject headings

NATURVETENSKAP  -- Biologi -- Ekologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Ecology (hsv//eng)

NATURVETENSKAP  -- Biologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

NATURVETENSKAP  -- Biologi -- Evolutionsbiologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Evolutionary Biology (hsv//eng)

Keyword

Ecology

Ekologi

Publication and Content Type

ref (subject category)

art (subject category)