Bioenergetic mapping of ‘healthy microbiomes’ via compound processing potential imprinted in gut and soil metagenomes
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Abstract
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Functional potential profiles were derived from good quality read 1 sequences using SUPER-FOCUS570(33) software, linked to the Diamond sequence aligner (v0.9.19; 90) and version 2 100% identity-571clustered reference database (100_v2; https://github.com/metageni/SUPER-FOCUS/issues/66).572Where subjects/samples were represented by multiple sequence files, the combined SUPER-FOCUS573outputs were normalized so that the total functional relative abundances summed to 100% in each574subject/sample
I'm really excited by the approach profiled in this paper. I think it's a very clever use of chemical reactions and stoichiometry. However, I'm concerned about the pre-processing step mentioned here. Do you have a sense of how lossy SUPER-FOCUS is, especially for soil microbiomes? Typically, metagenome analysis of soils can lose up to 80% of …
Functional potential profiles were derived from good quality read 1 sequences using SUPER-FOCUS570(33) software, linked to the Diamond sequence aligner (v0.9.19; 90) and version 2 100% identity-571clustered reference database (100_v2; https://github.com/metageni/SUPER-FOCUS/issues/66).572Where subjects/samples were represented by multiple sequence files, the combined SUPER-FOCUS573outputs were normalized so that the total functional relative abundances summed to 100% in each574subject/sample
I'm really excited by the approach profiled in this paper. I think it's a very clever use of chemical reactions and stoichiometry. However, I'm concerned about the pre-processing step mentioned here. Do you have a sense of how lossy SUPER-FOCUS is, especially for soil microbiomes? Typically, metagenome analysis of soils can lose up to 80% of information due to the system complexity and the amount we have yet to observe. Depending on the fraction of loss of functional information, how do you expect that to impact that results presented in this study?
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