Old meets new: most probable number validation of metagenomic and metatranscriptomic datasets in soil. (11th December 2017)

• Record Type: Journal Article
• Authors: Mauchline, T.H.; Hayat, R.; Clark, I.M.; Hirsch, P.R.
• Is Part Of: Letters in applied microbiology. Volume 66:Number 1(2018)
• Page Start: 14
• Page End: 18
• Publication Date: 2017-12-11
• Subjects: metagenomics -- metatranscriptomics -- most probable number -- rhizobia -- soil; Microbiology -- Periodicals; 660.62
• DOI: 10.1111/lam.12821
• Languages: English
• ISSNs: 0266-8254

Abstract

Abstract: Metagenomics and metatranscriptomics provide insights into biological processes in complex substrates such as soil, but linking the presence and expression of genes with functions can be difficult. Here, we obtain traditional most probable number estimates (MPN) of Rhizobium abundance in soil as a form of sample validation. Our work shows that in the Highfield experiment at Rothamsted, which has three contrasting conditions (>50 years continual bare fallow, wheat and grassland), MPN based on host plant nodulation assays corroborate metagenomic and metatranscriptomic estimates for Rhizobium leguminosarum sv. trifolii abundance. This validation is important to legitimize soil metagenomics and metatranscriptomics for the study of complex relationships between gene function and phylogeny. Significance and Impact of the Study: This study has demonstrated for the first time a functional assay validation of metagenomic and metatranscriptomic datasets by utilizing the clover and Rhizobium leguminosarum sv. trifolii mutualism. The results show that the Most Probable Number results corroborate the results of the 'omics approaches and gives confidence to the study of other biological systems where such a cross‐check is not available. Abstract : Significance and Impact of the Study: This study has demonstrated for the first time a functional assay validation of metagenomic and metatranscriptomic datasets by utilizing the clover and Rhizobium leguminosarum sv. trifolii mutualism. The results show that the Most Probable Number results corroborate the results of the 'omics approaches and gives confidence to the study of other biological systems where such a cross‐check is not available.