Moss-cyanobacteria associations as biogenic sources of nitrogen in boreal forest ecosystems

Sphagnum physiology in the context of changing climate: emergent influences of genomics, modelling and host-microbiome interactions on understanding ecosystem function

Peatlands harbour more than one-third of terrestrial carbon leading to the argument that the bryophytes, as major components of peatland ecosystems, store more organic carbon in soils than any other collective plant taxa. Plants of the genus Sphagnum are important components of peatland ecosystems and are potentially vulnerable to changing climatic conditions. However, the response of Sphagnum to rising temperatures, elevated CO2 and shifts in local hydrology have yet to be fully characterized. In this review, we examine Sphagnum biology and ecology and explore the role of this group of keystone species and its associated microbiome in carbon and nitrogen cycling using literature review and model simulations. Several issues are highlighted including the consequences of a variable environment on plant-microbiome interactions, uncertainty associated with CO2 diffusion resistances and the relationship between fixed N and that partitioned to the photosynthetic apparatus. We note that the Sphagnum fallax genome is currently being sequenced and outline potential applications of population-level genomics and corresponding plant photosynthesis and microbial metabolic modelling techniques. We highlight Sphagnum as a model organism to explore ecosystem response to a changing climate and to define the role that Sphagnum can play at the intersection of physiology, genetics and functional genomics.

Microbial metabolic potential for carbon degradation and nutrient (nitrogen and phosphorus) acquisition in an ombrotrophic peatland

This study integrated metagenomic and nuclear magnetic resonance (NMR) spectroscopic approaches to investigate microbial metabolic potential for organic matter decomposition and nitrogen (N) and phosphorus (P) acquisition in soils of an ombrotrophic peatland in the Marcell Experimental Forest (MEF), Minnesota, USA. This analysis revealed vertical stratification in key enzymatic pathways and taxa containing these pathways. Metagenomic analyses revealed that genes encoding laccases and dioxygenases, involved in aromatic compound degradation, declined in relative abundance with depth, while the relative abundance of genes encoding metabolism of amino sugars and all four saccharide groups increased with depth in parallel with a 50% reduction in carbohydrate content. Most Cu-oxidases were closely related to genes from Proteobacteria and Acidobacteria, and type 4 laccase-like Cu-oxidase genes were >8 times more abundant than type 3 genes, suggesting an important and overlooked role for type 4 Cu-oxidase in phenolic compound degradation. Genes associated with sulfate reduction and methanogenesis were the most abundant anaerobic respiration genes in these systems, with low levels of detection observed for genes of denitrification and Fe(III) reduction. Fermentation genes increased in relative abundance with depth and were largely affiliated with Syntrophobacter. Methylocystaceae-like small-subunit (SSU) rRNA genes, pmoA, and mmoX genes were more abundant among methanotrophs. Genes encoding N2 fixation, P uptake, and P regulons were significantly enriched in the surface peat and in comparison to other ecosystems, indicating N and P limitation. Persistence of inorganic orthophosphate throughout the peat profile in this P-limiting environment indicates that P may be bound to recalcitrant organic compounds, thus limiting P bioavailability in the subsurface. Comparative metagenomic analysis revealed a high metabolic potential for P transport and starvation, N2 fixation, and oligosaccharide degradation at MEF relative to other wetland and soil environments, consistent with the nutrient-poor and carbohydrate-rich conditions found in this Sphagnum-dominated boreal peatland.

Ecological patterns of nifH genes in four terrestrial climatic zones explored with targeted metagenomics using FrameBot, a new informatics tool

Biological nitrogen fixation is an important component of sustainable soil fertility and a key component of the nitrogen cycle. We used targeted metagenomics to study the nitrogen fixation-capable terrestrial bacterial community by targeting the gene for nitrogenase reductase (nifH). We obtained 1.1 million nifH 454 amplicon sequences from 222 soil samples collected from 4 National Ecological Observatory Network (NEON) sites in Alaska, Hawaii, Utah, and Florida. To accurately detect and correct frameshifts caused by indel sequencing errors, we developed FrameBot, a tool for frameshift correction and nearest-neighbor classification, and compared its accuracy to that of two other rapid frameshift correction tools. We found FrameBot was, in general, more accurate as long as a reference protein sequence with 80% or greater identity to a query was available, as was the case for virtually all nifH reads for the 4 NEON sites. Frameshifts were present in 12.7% of the reads. Those nifH sequences related to the Proteobacteria phylum were most abundant, followed by those for Cyanobacteria in the Alaska and Utah sites. Predominant genera with nifH sequences similar to reads included Azospirillum, Bradyrhizobium, and Rhizobium, the latter two without obvious plant hosts at the sites. Surprisingly, 80% of the sequences had greater than 95% amino acid identity to known nifH gene sequences. These samples were grouped by site and correlated with soil environmental factors, especially drainage, light intensity, mean annual temperature, and mean annual precipitation. FrameBot was tested successfully on three ecofunctional genes but should be applicable to any.

High-throughput phylogenetic analysis of microbial communities using rRNA-targeted sequencing is now commonplace; however, such data often allow little inference with respect to either the presence or the diversity of genes involved in most important ecological processes. To study the gene pool for these processes, it is more straightforward to assess the genes directly responsible for the ecological function (ecofunctional genes). However, analyzing these genes involves technical challenges beyond those seen for rRNA. In particular, frameshift errors cause garbled downstream protein translations. Our FrameBot tool described here both corrects frameshift errors in query reads and determines their closest matching protein sequences in a set of reference sequences. We validated this new tool with sequences from defined communities and demonstrated the tool’s utility on nifH gene fragments sequenced from soils in well-characterized and major terrestrial ecosystem types.