Soil metabolome response to whole-ecosystem warming at the Spruce and Peatland Responses under Changing Environments experiment.

In this study, a suite of complementary environmental geochemical analyses, including NMR and gas chromatography-mass spectrometry (GC-MS) analyses of central metabolites, Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) of secondary metabolites, and lipidomics, was used to investigate the influence of organic matter (OM) quality on the heterotrophic microbial mechanisms controlling peatland CO2, CH4, and CO2:CH4 porewater production ratios in response to climate warming. Our investigations leverage the Spruce and Peatland Responses under Changing Environments (SPRUCE) experiment, where air and peat warming were combined in a whole-ecosystem warming treatment. We hypothesized that warming would enhance the production of plant-derived metabolites, resulting in increased labile OM inputs to the surface peat, thereby enhancing microbial activity and greenhouse gas production. Because shallow peat is most susceptible to enhanced warming, increases in labile OM inputs to the surface, in particular, are likely to result in significant changes to CO2 and CH4 dynamics and methanogenic pathways. In support of this hypothesis, significant correlations were observed between metabolites and temperature consistent with increased availability of labile substrates, which may stimulate more rapid turnover of microbial proteins. An increase in the abundance of methanogenic genes in response to the increase in the abundance of labile substrates was accompanied by a shift toward acetoclastic and methylotrophic methanogenesis. Our results suggest that as peatland vegetation trends toward increasing vascular plant cover with warming, we can expect a concomitant shift toward increasingly methanogenic conditions and amplified climate-peatland feedbacks.

A History of Molecular Level Analysis of Natural Organic Matter by FTICR Mass Spectrometry and The Paradigm Shift in Organic Geochemistry.

Natural organic matter (NOM) is a complex mixture of biogenic molecules resulting from the deposition and transformation of plant and animal matter. It has long been recognized that NOM plays an important role in many geological, geochemical, and environmental processes. Of particular concern is the fate of NOM in response to a warming climate in environments that have historically sequestered carbon (e.g., peatlands and swamps) but may transition to net carbon emitters. In this review, we will highlight developments in the application of high-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) in identifying the individual components of complex NOM mixtures, focusing primarily on the fraction that is dissolved in natural waters (dissolved organic matter or DOM). We will first provide some historical perspective on developments in FTICR technology that made molecular-level characterizations of DOM possible. A variety of applications of the technique will then be described, followed by our view of the future of high-field FTICR MS in carbon cycling research, including a particularly exciting metabolomic approach.

Microbial sensitivity to temperature and sulfate deposition modulates greenhouse gas emissions from peat soils.

Peatlands are among the largest natural sources of atmospheric methane (CH4 ) worldwide. Microbial processes play a key role in regulating CH4 emissions from peatland ecosystems, yet the complex interplay between soil substrates and microbial communities in controlling CH4 emissions as a function of global change remains unclear. Herein, we performed an integrated analysis of multi-omics data sets to provide a comprehensive understanding of the molecular processes driving changes in greenhouse gas (GHG) emissions in peatland ecosystems with increasing temperature and sulfate deposition in a laboratory incubation study. We sought to first investigate how increasing temperatures (4, 21, and 35°C) impact soil microbiome-metabolome interactions; then explore the competition between methanogens and sulfate-reducing bacteria (SRBs) with increasing sulfate concentrations at the optimum temperature for methanogenesis. Our results revealed that peat soil organic matter degradation, mediated by biotic and potentially abiotic processes, is the main driver of the increase in CO2 production with temperature. In contrast, the decrease in CH4 production at 35°C was linked to the absence of syntrophic communities and the potential inhibitory effect of phenols on methanogens. Elevated temperatures further induced the microbial communities to develop high growth yield and stress tolerator trait-based strategies leading to a shift in their composition and function. On the other hand, SRBs were able to outcompete methanogens in the presence of non-limiting sulfate concentrations at 21°C, thereby reducing CH4 emissions. At higher sulfate concentrations, however, the prevalence of communities capable of producing sufficient low-molecular-weight carbon substrates for the coexistence of SRBs and methanogens was translated into elevated CH4 emissions. The use of omics in this study enhanced our understanding of the structure and interactions among microbes with the abiotic components of the system that can be useful for mitigating GHG emissions from peatland ecosystems in the face of global change.

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland.

Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO2 ) and methane (CH4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post-thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post-thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO2 and CH4  fluxes from decomposition. Thus, the increased C-storage expected from higher productivity was limited and the high global warming potential of CH4 contributed a net positive warming effect. Although post-thaw peatlands are currently C sinks due to high NPP offsetting high CO2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

Elucidating Drought-Tolerance Mechanisms in Plant Roots through 1H NMR Metabolomics in Parallel with MALDI-MS, and NanoSIMS Imaging Techniques.

As direct mediators between plants and soil, roots play an important role in metabolic responses to environmental stresses such as drought, yet these responses are vastly uncharacterized on a plant-specific level, especially for co-occurring species. Here, we aim to examine the effects of drought on root metabolic profiles and carbon allocation pathways of three tropical rainforest species by combining cutting-edge metabolomic and imaging technologies in an in situ position-specific 13C-pyruvate root-labeling experiment. Further, washed (rhizosphere-depleted) and unwashed roots were examined to test the impact of microbial presence on root metabolic pathways. Drought had a species-specific impact on the metabolic profiles and spatial distribution in Piper sp. and Hibiscus rosa sinensis roots, signifying different defense mechanisms; Piper sp. enhanced root structural defense via recalcitrant compounds including lignin, while H. rosa sinensis enhanced biochemical defense via secretion of antioxidants and fatty acids. In contrast, Clitoria fairchildiana, a legume tree, was not influenced as much by drought but rather by rhizosphere presence where carbohydrate storage was enhanced, indicating a close association with symbiotic microbes. This study demonstrates how multiple techniques can be combined to identify how plants cope with drought through different drought-tolerance strategies and the consequences of such changes on below-ground organic matter composition.

Simple Plant and Microbial Exudates Destabilize Mineral-Associated Organic Matter via Multiple Pathways.

Most mineral-associated organic matter (MAOM) is protected against microbial attack, thereby contributing to long-term carbon storage in soils. However, the extent to which reactive compounds released by plants and microbes may destabilize MAOM and so enhance microbial access, as well as the underlying mechanisms, remain unclear. Here, we tested the ability of functionally distinct model exudates-ligands, reductants, and simple sugars-to promote microbial utilization of monomeric MAOM, bound via outer-sphere complexes to common iron and aluminum (hydr)oxide minerals. The strong ligand oxalic acid induced rapid MAOM mineralization, coinciding with greater sorption to and dissolution of minerals, suggestive of direct MAOM mobilization mechanisms. In contrast, the simple sugar glucose caused slower MAOM mineralization, but stimulated microbial activity and metabolite production, indicating an indirect microbially-mediated mechanism. Catechol, acting as reductant, promoted both mechanisms. While MAOM on ferrihydrite showed the greatest vulnerability to both direct and indirect mechanisms, MAOM on other (hydr)oxides was more susceptible to direct mechanisms. These findings suggest that MAOM persistence, and thus long-term carbon storage within a given soil, is not just a function of mineral reactivity but also depends on the capacity of plant roots and associated microbes to produce reactive compounds capable of triggering specific destabilization mechanisms.

Soil Organic Matter Characterization by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR MS): A Critical Review of Sample Preparation, Analysis, and Data Interpretation.

The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions. Thus, many studies have been conducted to reveal how anthropogenic and climate variables affect carbon sequestration and nutrient cycling. Among the analytical techniques used to better understand the speciation and transformation of SOM, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is the only technique that has sufficient mass resolving power to separate and accurately assign elemental compositions to individual SOM molecules. The global increase in the application of FTICR MS to address SOM complexity has highlighted the many challenges and opportunities associated with SOM sample preparation, FTICR MS analysis, and mass spectral interpretation. Here, we provide a critical review of recent strategies for SOM characterization by FTICR MS with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Data processing and visualization methods are presented with suggested workflows that detail the considerations needed for the application of molecular information derived from FTICR MS. Finally, we highlight current research gaps, biases, and future directions needed to improve our understanding of organic matter chemistry and cycling within terrestrial ecosystems.

Root Carbon Interaction with Soil Minerals Is Dynamic, Leaving a Legacy of Microbially Derived Residues.

Minerals preserve the oldest, most persistent soil carbon, and mineral characteristics appear to play a critical role in the formation of soil organic matter (SOM) associations. To test the hypothesis that roots, and differences in carbon source and microbial communities, influence mineral SOM associations over short timescales, we incubated permeable mineral bags in soil microcosms with and without plants, inside a 13CO2 labeling chamber. Mineral bags contained quartz, ferrihydrite, kaolinite, or soil minerals isolated via density separation. Using 13C-nuclear magnetic resonance, Fourier transform ion cyclotron resonance mass spectrometry, and lipidomics, we traced carbon deposition onto minerals, characterizing total carbon, 13C enrichment, and SOM chemistry over three growth stages of Avena barbata. Carbon accumulation was rapid and mineral-dependent but slowed with time; the accumulated amount was not significantly affected by root presence. However, plant roots strongly shaped the chemistry of mineral-associated SOM. Minerals incubated in a plant rhizosphere were associated with a more diverse array of compounds (with different functional groups-carbonyl, aromatics, carbohydrates, and lipids) than minerals incubated in an unplanted bulk soil control. We also found that many of the lipids that sorbed to minerals were microbially derived, including many fungal lipids. Together, our data suggest that diverse rhizosphere-derived compounds may represent a transient fraction of mineral SOM, rapidly exchanging with mineral surfaces.

Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data.

SUMMARY: Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user's database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples. AVAILABILITY AND IMPLEMENTATION: Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Online supercritical fluid extraction mass spectrometry (SFE-LC-FTMS) for sensitive characterization of soil organic matter.

We report a novel technical approach for subcritical fluid extraction (SFE) for organic matter characterization in complex matrices such as soil. The custom platform combines on-line SFE with micro-solid phase extraction, nano liquid chromatography (LC), electrospray ionization and Fourier transform mass spectrometry (SFE-LC-FTMS). We demonstrated the utility of SFE-LC-FTMS, including results from both Orbitrap and FTICR MS, for analysis of complex mixtures of organic compounds in a solid matrix by characterizing soil organic matter in peat, a high-carbon soil. For example, in a single experiment, >6000 molecular formulas can be assigned based upon FTICR MS data from 1-50 µL of soil samples (roughly 1-50 mg of soil, dependent on soil density), nearly twice that typically obtained from direct infusion liquid solvent extraction (LSE) from an order of magnitude larger volume of the same soil. The detected species consisted predominately of lipid-like, lignin-like and protein-like compounds, based on their O/C and H/C ratios, with predominantly CHO and CHONP molecular compositions. These results clearly demonstrate that SFE has the potential to effectively extract a variety of molecular species and could become an important member of a suite of extraction methods for studying SOM and other natural organic matter. This is especially true when comprehensive coverage, minimal sample volumes, and high sensitivity are required, or when the presence of organic solvent residue in residual soil is problematic. The SFE based extraction protocol could potentially enable spatially resolved characterization of organic matter in soil with a resolution of ∼1 mm3 to facilitate studies probing the spatial heterogeneity of soil.

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples.

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

Atmo-ecometabolomics: a novel atmospheric particle chemical characterization methodology for ecological research.

Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biological-activity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles. We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmo-ecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry.

A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements.

To better understand disease conditions and environmental perturbations, multiomic studies combining proteomic, lipidomic, and metabolomic analyses are vastly increasing in popularity. In a multiomic study, a single sample is typically extracted in multiple ways, and various analyses are performed using different instruments, most often based upon mass spectrometry (MS). Thus, one sample becomes many measurements, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injections. While some FIA systems have been created to address these challenges, many have limitations such as costly consumables, low pressure capabilities, limited pressure monitoring, and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at a range of flow rates (∼50 nL/min to 500 µL/min) to accommodate both low- and high-flow MS ionization sources. This system also functions at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system, and results showed a highly robust and reproducible platform capable of providing consistent performance over many days without carryover, as long as washing buffers specific to each molecular analysis were utilized.

Redox Fluctuations Control the Coupled Cycling of Iron and Carbon in Tropical Forest Soils.

Oscillating redox conditions are a common feature of humid tropical forest soils, driven by an ample supply and dynamics of reductants, high moisture, microbial oxygen consumption, and finely textured clays that limit diffusion. However, the net result of variable soil redox regimes on iron (Fe) mineral dynamics and associated carbon (C) forms and fluxes is poorly understood in tropical soils. Using a 44-day redox incubation experiment with humid tropical forest soils from Puerto Rico, we examined patterns in Fe and C transformations under four redox regimes: static anoxic, "flux 4-day" (4d oxic, 4d anoxic), "flux 8-day" (8d oxic, 4d anoxic) and static oxic. Prolonged anoxia promoted reductive dissolution of Fe-oxides, and led to an increase in soluble Fe(II) and amorphous Fe oxide pools. Preferential dissolution of the less-crystalline Fe pool was evident immediately following a shift in bulk redox status (oxic to anoxic), and coincided with increased dissolved organic C, presumably due to acidification or direct release of organic matter (OM) from dissolving Fe(III) mineral phases. The average nominal oxidation state of water-soluble C was lowest under persistent anoxic conditions, suggesting that more reduced organic compounds were metabolically unavailable for microbial consumption under reducing conditions. Anoxic soil compounds had high H/C values (and were similar to lignin-like compounds) whereas oxic soil compounds had higher O/C values, akin to tannin- and cellulose-like components. Cumulative respiration derived from native soil organic C was highest in static oxic soils. These results show how Fe minerals and Fe-OM interactions in tropical soils are highly sensitive to variable redox effects. Shifting soil oxygen availability rapidly impacted exchanges between mineral-sorbed and aqueous C pools, increased the dissolved organic C pool under anoxic conditions implying that the periodicity of low-redox events may control the fate of C in wet tropical soils.

Formularity: Software for Automated Formula Assignment of Natural and Other Organic Matter from Ultrahigh-Resolution Mass Spectra.

Ultrahigh resolution mass spectrometry, such as Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), can resolve thousands of molecular ions in complex organic matrices. A Compound Identification Algorithm (CIA) was previously developed for automated elemental formula assignment for natural organic matter (NOM). In this work, we describe software Formularity with a user-friendly interface for CIA function and newly developed search function Isotopic Pattern Algorithm (IPA). While CIA assigns elemental formulas for compounds containing C, H, O, N, S, and P, IPA is capable of assigning formulas for compounds containing other elements. We used halogenated organic compounds (HOC), a chemical class that is ubiquitous in nature as well as anthropogenic systems, as an example to demonstrate the capability of Formularity with IPA. A HOC standard mix was used to evaluate the identification confidence of IPA. Tap water and HOC spike in Suwannee River NOM were used to assess HOC identification in complex environmental samples. Strategies for reconciliation of CIA and IPA assignments were discussed. Software and sample databases with documentation are freely available.

Changes in peat chemistry associated with permafrost thaw increase greenhouse gas production.

Carbon release due to permafrost thaw represents a potentially major positive climate change feedback. The magnitude of carbon loss and the proportion lost as methane (CH4) vs. carbon dioxide (CO2) depend on factors including temperature, mobilization of previously frozen carbon, hydrology, and changes in organic matter chemistry associated with environmental responses to thaw. While the first three of these effects are relatively well understood, the effect of organic matter chemistry remains largely unstudied. To address this gap, we examined the biogeochemistry of peat and dissolved organic matter (DOM) along a ∼40-y permafrost thaw progression from recently- to fully thawed sites in Stordalen Mire (68.35°N, 19.05°E), a thawing peat plateau in northern Sweden. Thaw-induced subsidence and the resulting inundation along this progression led to succession in vegetation types accompanied by an evolution in organic matter chemistry. Peat C/N ratios decreased whereas humification rates increased, and DOM shifted toward lower molecular weight compounds with lower aromaticity, lower organic oxygen content, and more abundant microbially produced compounds. Corresponding changes in decomposition along this gradient included increasing CH4 and CO2 production potentials, higher relative CH4/CO2 ratios, and a shift in CH4 production pathway from CO2 reduction to acetate cleavage. These results imply that subsidence and thermokarst-associated increases in organic matter lability cause shifts in biogeochemical processes toward faster decomposition with an increasing proportion of carbon released as CH4. This impact of permafrost thaw on organic matter chemistry could intensify the predicted climate feedbacks of increasing temperatures, permafrost carbon mobilization, and hydrologic changes.

Advanced solvent based methods for molecular characterization of soil organic matter by high-resolution mass spectrometry.

Soil organic matter (SOM), a complex, heterogeneous mixture of above and belowground plant litter and animal and microbial residues at various degrees of decomposition, is a key reservoir for carbon (C) and nutrient biogeochemical cycling in soil based ecosystems. A limited understanding of the molecular composition of SOM limits the ability to routinely decipher chemical processes within soil and accurately predict how terrestrial carbon fluxes will respond to changing climatic conditions and land use. To elucidate the molecular-level structure of SOM, we selectively extracted a broad range of intact SOM compounds by a combination of different organic solvents from soils with a wide range of C content. Our use of electrospray ionization (ESI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and a suite of solvents with varying polarity significantly expands the inventory of the types of organic molecules present in soils. Specifically, we found that hexane is selective for lipid-like compounds with very low O/C ratios (<0.1); water (H2O) was selective for carbohydrates with high O/C ratios; acetonitrile (ACN) preferentially extracts lignin, condensed structures, and tannin polyphenolic compounds with O/C > 0.5; methanol (MeOH) has higher selectivity toward compounds characterized with low O/C < 0.5; and hexane, MeOH, ACN, and H2O solvents increase the number and types of organic molecules extracted from soil for a broader range of chemically diverse soil types. Our study of SOM molecules by ESI FTICR MS revealed new insight into the molecular-level complexity of organics contained in soils. We present the first comparative study of the molecular composition of SOM from different ecosystems using ultra high-resolution mass spectrometry.

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.

Microbial community stratification linked to utilization of carbohydrates and phosphorus limitation in a boreal peatland at Marcell Experimental Forest, Minnesota, USA.

This study investigated the abundance, distribution, and composition of microbial communities at the watershed scale in a boreal peatland within the Marcell Experimental Forest (MEF), Minnesota, USA. Through a close coupling of next-generation sequencing, biogeochemistry, and advanced analytical chemistry, a biogeochemical hot spot was revealed in the mesotelm (30- to 50-cm depth) as a pronounced shift in microbial community composition in parallel with elevated peat decomposition. The relative abundance of Acidobacteria and the Syntrophobacteraceae, including known hydrocarbon-utilizing genera, was positively correlated with carbohydrate and organic acid content, showing a maximum in the mesotelm. The abundance of Archaea (primarily crenarchaeal groups 1.1c and 1.3) increased with depth, reaching up to 60% of total small-subunit (SSU) rRNA gene sequences in the deep peat below the 75-cm depth. Stable isotope geochemistry and potential rates of methane production paralleled vertical changes in methanogen community composition to indicate a predominance of acetoclastic methanogenesis mediated by the Methanosarcinales in the mesotelm, while hydrogen-utilizing methanogens predominated in the deeper catotelm. RNA-derived pyrosequence libraries corroborated DNA sequence data to indicate that the above-mentioned microbial groups are metabolically active in the mid-depth zone. Fungi showed a maximum in rRNA gene abundance above the 30-cm depth, which comprised only an average of 0.1% of total bacterial and archaeal rRNA gene abundance, indicating prokaryotic dominance. Ratios of C to P enzyme activities approached 0.5 at the acrotelm and catotelm, indicating phosphorus limitation. In contrast, P limitation pressure appeared to be relieved in the mesotelm, likely due to P solubilization by microbial production of organic acids and C-P lyases. Based on path analysis and the modeling of community spatial turnover, we hypothesize that P limitation outweighs N limitation at MEF, and microbial communities are structured by the dominant shrub, Chamaedaphne calyculata, which may act as a carbon source for major consumers in the peatland.