Bacterial physiological adaptations to contrasting edaphic conditions identified using landscape scale metagenomics

Abstract

Environmental factors relating to soil pH are widely known to be important in structuring soil bacterial communities, yet the relationship between taxonomic community composition and functional diversity remains to be determined. Here, we analyze geographically distributed soils spanning a wide pH gradient and assess the functional gene capacity within those communities using whole genome metagenomics. Low pH soils consistently had fewer taxa (lower alpha and gamma diversity), but only marginal reductions in functional alpha diversity and equivalent functional gamma diversity. However, coherent changes in the relative abundances of annotated genes between pH classes were identified; with functional profiles clustering according to pH independent of geography. Differences in gene abundances were found to reflect survival and nutrient acquisition strategies, with organic-rich acidic soils harboring a greater abundance of cation efflux pumps, C and N direct fixation systems and fermentation pathways indicative of anaerobiosis. Conversely, high pH soils possessed more direct transporter-mediated mechanisms for organic C and N substrate acquisition. These findings show that bacterial functional versatility may not be constrained by taxonomy, and we further identify the range of physiological adaptations required to exist in soils of varying nutrient availability and edaphic conditions.

Zones of influence for soil organic matter dynamics: A conceptual framework for data and models

“…Advances in molecular metagenomics techniques permit new understanding of how soil change will affect both biodiversity and the functional potential of microbial communities (Jansson & Hofmockel, ). While the application of these technologies to global soils has revealed that different microbial taxa and genetic pathways operate across soil physico‐chemical gradients (Fierer et al, ; Malik, Thomson, Whiteley, Bailey, & Griffiths, ), we still lack a systems‐level understanding connecting these metrics to soil process rates. While there have been a few studies examining whether altered microbial communities affect CUE (Kallenbach, Frey, & Grandy, ), the relationship of microbial community structure and the range of biochemical processes in operation to the quality and nature of the microbially derived SOM is largely unknown.…”

Physiological adaptations of leaf litter microbial communities to long-term drought

“…Drawing conclusions from shifts in upperlevel classes of functions may be misleading as this level consists of a myriad genes whose expression may decrease or increase in response to the environmental perturbation 24 . Multiple genes belonging to the same class responding in opposite directions may cancel out resulting in no net effect for that class of functions.…”

A robust, cost‐effective method for DNA, RNA and protein co‐extraction from soil, other complex microbiomes and pure cultures

“…As the novelty of our method lies in the recovery of proteins from the phenol phase, typically discarded in the protocol of Griffiths et al (), we further demonstrate that our biomolecule co‐extraction is suitable for metaproteomics analysis of other soil types with varying clay contents. Indeed, the DNA and RNA co‐extraction protocol from Griffiths et al () has been cited to date by over 1,250 papers including many reporting on downstream high‐throughput sequencing, including 16SrRNA and ITS amplicon analysis (Haas et al, ; Morawe et al, ; Sayer et al, ; Whitman et al, ), metagenomics (Malik, Thomson, Whiteley, Bailey, & Griffiths, ; Soares et al, ; Wilhelm, Hanson, Chandra, & Madsen, ) and metatranscriptomics (Alessi et al, ; de Menezes, Clipson, & Doyle, ; Hesse et al, ). Here, 16S rRNA profiling from DNA and cDNA was performed on three samples corresponding to three biological replicates from one soil type (with a clay content of 11.1%) while metaproteomics was conducted for nine samples corresponding to three biological replicates from three soil types (with clay content of 11.1%, 19.4% and 35.1%).…”