A Targeted Metagenomic Approach to Characterization of Free-Living Soil Diazotrophs Using 15N2 Stable Isotope Probing.

We have combined the techniques of metagenomics and ¹⁵N₂ stable isotope probing (SIP) to create an unbiased library of the active diazotrophic microbial community from an agricultural soil. Although many nitrogen fixation genes (nif) have been identified in soils using PCR based approaches, the frequency of horizontal transfer events makes it difficult to link these functional genes to robust markers of organism phylogeny. Thus, a majority of free-living diazotrophs remain poorly characterized both in terms of their potential activities and their evolutionary significance.

A ¹⁵N₂ SIP approach was used to label the DNA of active nitrogen fixing soil microbes by incubating soils in synthetic air containing >98 % ¹⁵N₂ for a period of 20 days. Following labeling, we collected environmental DNA using extraction techniques developed specifically for preserving high molecular weight (HMW) DNA, then confirmed these results using pulse field gel electrophoresis. Partitioning labeled from unlabeled DNA was achieved by ultracentrifugation in a CsCl density gradient. An observed shift in buoyant density of a subset of the total environmental DNA indicated a portion of the microbial community had incorporated the heavy ¹⁵N isotope into genomic DNA. Labeled DNA fractions were used to create a HMW DNA metagenomic library containing large inserts (~40 KB). The library contains 1200 clones consisting of 48 megabases of genomic DNA from microbes that were actively fixing nitrogen during the incubation.

This novel approach for analysis of organisms involved in important biogeochemical processes provides advantages over current techniques: i) it alleviates PCR bias, ii) identifies metabolically active constituents of the microbial community, iii) provides the genomic context in which targeted functional and phylogenetic marker genes reside, iv) it reduces the complexity of metagenomic libraries relative to random approaches thereby increasing the probability of detecting targeted genomic fragments by more than an order of magnitude.

 

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