Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Organic molecules are deterministically assembled in variably inundated river sediments, but drivers remain unclear

Dissolved organic matter (DOM) is vital to ecosystem functions, influencing nutrient cycles and water quality. Understanding the processes driving DOM chemistry variation remains a challenge. By examining these processes through a community ecology perspective, we aim to understand the balance between stochastic forces (e.g., random mixing of DOM) and deterministic forces (e.g., systematic loss of certain types of DOM molecules) shaping DOM chemistry. Previous research on stochastic and deterministic influences over DOM chemistry applied null models to aquatic environments and subsurface pore water. Our study extends this to variably inundated riverbed sediments, which are widespread globally. We studied 38 river reaches across biomes, finding that DOM chemistry within most sites was governed by deterministic processes that were highly localized and led to spatial divergence in DOM chemistry within each reach. The degree of determinism varied substantially across reaches and we hypothesized this was related to differences in sediment moisture. Our findings partially supported this, showing that the upper limit of determinism decreased with increasing sediment moisture. We integrated our results with previous studies to develop a post-hoc conceptual model proposing that DOM assemblages become more deterministic along the continuum from river water to saturated sediment pore spaces to drier sediments or soils. This conceptual model aligns with previous work linking DOM chemistry to the Damköhler number and hydrologic connectivity, suggesting generalizable patterns and processes that can be further revealed by quantifying the stochastic-deterministic balance through space, time, and across scales.

Microbiome-metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient

Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO2 and CH4 porewater variations. Our study showcases insights gained by using feature-level data and microorganism-metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.

Tracing sources of dissolved organic matter along the terrestrial-aquatic continuum in the Ore Mountains, Germany

There is growing concern about the rising levels of dissolved organic matter (DOM) in surface waters across the Northern hemisphere. However, only limited research has been conducted to unveil its precise origin. Compositional changes along terrestrial-aquatic pathways can help determine the terrestrial sources of DOM in streams. Stream water, soil water and soil horizons were sampled at four sites representing typical settings within a forested catchment in the Ore Mountains (Erzgebirge, Germany) from winter 2020 to spring 2022. The samples were analyzed using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). The resulting data were successfully subjected to semi-automatic processing of the molecular composition of DOM, reaching a percentage of identified peaks up to 98 %. Principal component analysis (PCA) and cluster analyses were carried out to identify distinct differences between DOM from the potential sources and in the streams. According to the PCA, organic soil horizons, soil water, and stream water samples could be clearly distinguished. Cluster analysis revealed that soil water DOM at all depths of Peats and deeper horizons of the Peaty Gleysols contributed the most to DOM in the stream section dominated by organic soils. In areas dominated by mineral soils, stream DOM resembled the DOM from the deeper mineral horizons of Cambisols and Podzols. Overall, our results suggested that most of the DOM exported from the catchment was derived from deeper mineral soil horizons, with little contribution of DOM derived from organic soils. Therefore, DOM fingerprint analysis of in-situ soil water proved to be a promising approach for tracing back the main sources of stream water DOM.

Disentangling drivers of mudflat intertidal DOM chemodiversity using ecological models

Microorganisms consume and transform dissolved organic matter (DOM) into various forms. However, it remains unclear whether the ecological patterns and drivers of DOM chemodiversity are analogous to those of microbial communities. Here, a large-scale investigation is conducted along the Chinese coasts to resolve the intrinsic linkages among the complex intertidal DOM pools, microbial communities and environmental heterogeneity. The abundance of DOM molecular formulae best fits log-normal distribution and follows Taylor's Law. Distance-decay relationships are observed for labile molecular formulae, while latitudinal diversity gradients are noted for recalcitrant molecular formulae. Latitudinal patterns are also observed for DOM molecular features. Negative cohesion, bacterial diversity, and molecular traits are the main drivers of DOM chemodiversity. Stochasticity analyses demonstrate that determinism dominantly shapes the DOM compositional variations. This study unveils the intrinsic mechanisms underlying the intertidal DOM chemodiversity and microbial communities from ecological perspectives, deepening our understanding of microbially driven chemical ecology.

Chemodiversity of riverine dissolved organic matter: Effects of local environments and watershed characteristics

Riverine dissolved organic matter (DOM) is crucial to global carbon cycling and aquatic ecosystems. However, the geographical patterns and environmental drivers of DOM chemodiversity remain elusive especially in the waters and sediments of continental rivers. Here, we systematically analyzed DOM molecular diversity and composition in surface waters and sediments across 97 broadly distributed rivers using data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. We further examined the associations of molecular richness and composition with geographical, climatic, physicochemical variables, as well as the watershed characteristics. We found that molecular richness significantly decreased toward higher latitudes, but only in sediments (r = -0.24, p < 0.001). The environmental variables like precipitation and non-purgeable organic carbon showed strong associations with DOM molecular richness and composition. Interestingly, we identified that less-documented factors like watershed characteristics were also related to DOM molecular richness and composition. For instance, DOM molecular richness was positively correlated with the soil sand fraction for waters, while with the percentage of forest for sediments. Importantly, the effects of watershed characteristics on DOM molecular richness and composition were generally stronger in waters than sediments. This phenomenon was further supported by the fact that 11 out of 13 watershed characteristics (e.g., the percentages of impervious area and cropland) showed more positive than negative correlations with molecular abundance especially in waters. As the percentage of forest increased, there was a continuous accumulation of the compounds with higher molecular weight, aromaticity, and degree of unsaturation. In contrast, human activities accumulated the compounds with lower molecular weight and oxygenation, and higher bioavailability. Our findings imply that it may be possible to use a small set of broadly available data types to predict DOM molecular richness and composition across diverse river systems. Elucidation of mechanisms underlying these relationships will provide further enhancements to such predictions, especially when extrapolating to unsampled systems.

Quantifying Stochastic Processes in Shaping Dissolved Organic Matter Pool with High-Resolution Mass Spectrometry

Natural dissolved organic matter (DOM) represents a ubiquitous molecular mixture, progressively characterized by spatiotemporal resolution. However, an inadequate comprehension of DOM molecular dynamics, especially the stochastic processes involved, hinders carbon cycling predictions. This study employs ecological principles to introduce a neutral theory to elucidate the fundamental processes involving molecular generation, degradation, and migration. A neutral model is thus formulated to assess the probability distribution of DOM molecules, whose frequencies and abundances follow a β-distribution relationship. The neutral model is subsequently validated with high-resolution mass spectrometry (HRMS) data from various waterbodies, including lakes, rivers, and seas. The model fitting highlights the prevalence of molecular neutral distribution and quantifies the stochasticity within DOM molecular dynamics. Furthermore, the model identifies deviations of HRMS observations from neutral expectations in photochemical and microbial experiments, revealing nonrandom molecular transformations. The ecological null model further validates the neutral modeling results, demonstrating that photodegradation reduces molecular stochastic dynamics at the surface of an acidic pit lake, while random distribution intensifies at the river surface compared with the porewater. Taken together, the DOM molecular neutral model emphasizes the significance of stochastic processes in shaping a natural DOM pool, offering a potential theoretical framework for DOM molecular dynamics in aquatic and other ecosystems.

Rethinking Aerobic Respiration in the Hyporheic Zone under Variation in Carbon and Nitrogen Stoichiometry

Hyporheic zones (HZs)─zones of groundwater-surface water mixing─are hotspots for dissolved organic matter (DOM) and nutrient cycling that can disproportionately impact aquatic ecosystem functions. However, the mechanisms affecting DOM metabolism through space and time in HZs remain poorly understood. To resolve this gap, we investigate a recently proposed theory describing trade-offs between carbon (C) and nitrogen (N) limitations as a key regulator of HZ metabolism. We propose that throughout the extent of the HZ, a single process like aerobic respiration (AR) can be limited by both DOM thermodynamics and N content due to highly variable C/N ratios over short distances (centimeter scale). To investigate this theory, we used a large flume, continuous optode measurements of dissolved oxygen (DO), and spatially and temporally resolved molecular analysis of DOM. Carbon and N limitations were inferred from changes in the elemental stoichiometric ratio. We show sequential, depth-stratified relationships of DO with DOM thermodynamics and organic N that change across centimeter scales. In the shallow HZ with low C/N, DO was associated with the thermodynamics of DOM, while deeper in the HZ with higher C/N, DO was associated with inferred biochemical reactions involving organic N. Collectively, our results suggest that there are multiple competing processes that limit AR in the HZ. Resolving this spatiotemporal variation could improve predictions from mechanistic models, either via more highly resolved grid cells or by representing AR colimitation by DOM thermodynamics and organic N.

Mechanisms shaping dissolved organic matter and microbial community in lake ecosystems

Lakes are active components of the global carbon cycle and host a range of processes that degrade and modify dissolved organic matter (DOM). Through the degradation of DOM molecules and the synthesis of new compounds, microbes in aquatic environments strongly and continuously influence chemodiversity, which can feedback to influence microbial diversity. Developing a better understanding of the biodiversity patterns that emerge along spatial and environmental gradients is one of the key objectives of community ecology. A changing climate may affect ecological feedback, including those that affect microbial communities. To maintain the function of a lake ecosystem and predict carbon cycling in the environment, it is increasingly important to understand the coupling between microbial and DOM diversity. To unravel the biotic and abiotic mechanisms that control the structure and patterns of DOM and microbial communities in lakes, we combined high-throughput sequencing and ultra-high resolution mass spectrometry together with a null modeling approach. The advantage of null models is their ability to evaluate the relative influences of stochastic and deterministic assembly processes in both DOM and microbial community assemblages. The present study includes spatiotemporal signatures of DOM and the microbial community in six temperate lakes contrasting continental and Mediterranean climates during the productive season. Different environmental conditions and nutrient sources characterized the studied lakes. Our results have shown high covariance between molecular-level DOM diversity and the diversity of individual microbial communities especially with diversity of microeukaryotes and free-living bacteria indicating their dynamic feedback. We found that the differences between lakes and climatic regions were mainly reflected in the diversity of DOM at the molecular formula-level and the microeukaryota community. Furthermore, using null models the DOM assembly was governed by deterministic variable selection operating consistently and strongly within and among lakes. In contrast, microbial community assembly processes were highly variable across lakes with different trophic status and climatic regions. Difference in the processes governing DOM and microbial composition does not indicate weak coupling between these components, rather it suggests that distinct factors may be influencing microbial communities and DOM assemblages separately. Further understanding of the DOM-microbe coupling (or lack thereof) is key to formulating predictive models of future lake ecology and function.

Integration of LC-MS-Based and GC-MS-Based Metabolic Profiling to Reveal the Effects of Domestication and Boiling on the Composition of Duck Egg Yolks

Egg yolks contain abundant lipids, proteins, and minerals that provide not only essential nutrients for embryonic development but also cheap sources of nutrients for consumers worldwide. Previous composition analyses of egg yolks primarily focused on nutrients such as lipids and minerals. However, few studies have reported the effects of domestication and heating on yolk composition and characteristics. The objective of this study was to investigate the impact of domestication and boiling on the metabolite contents of egg yolks via untargeted metabolomics using GC-MS and LC-MS. In this study, eggs were collected from Fenghua teals, captive mallards, and Shaoxing ducks. Twelve duck eggs (half raw and half cooked) were randomly selected from each variety, and the egg yolks were separated for metabolic profiling. The analysis identified 1205 compounds in the egg yolks. Domestication generated more differential metabolites than boiling, which indicated that the changes in the metabolome of duck egg yolk caused by domestication were greater than those caused by boiling. In a comparative analysis of domestic and mallard ducks, 48 overlapping differential metabolites were discovered. Among them, nine metabolites were upregulated in domesticated ducks, including monoolein, emodin, daidzein, genistein, and glycitein, which may be involved in lipid metabolism; some of them may also act as phytoestrogens (flavonoids). Another 39 metabolites, including imethylethanolamine, harmalan, mannitol, nornicotine, linoleic acid, diphenylamine, proline betaine, alloxanthin, and resolvin d1, were downregulated by domestication and were linked to immunity, anti-inflammatory, antibacterial, and antioxidant properties. Furthermore, four overlapping differential metabolites that included amino acids and dipeptides were discovered in paired comparisons of the raw and boiled samples. Our findings provided new insights into the molecular response of duck domestication and supported the use of metabolomics to examine the impact of boiling on the composition of egg yolks.

Bacterioplankton dispersal and biogeochemical function across Alaskan Arctic catchments

In Arctic catchments, bacterioplankton are dispersed through soils and streams, both of which freeze and thaw/flow in phase, seasonally. To characterize this dispersal and its potential impact on biogeochemistry, we collected bacterioplankton and measured stream physicochemistry during snowmelt and after vegetation senescence across multiple stream orders in alpine, tundra, and tundra-dominated-by-lakes catchments. In all catchments, differences in community composition were associated with seasonal thaw, then attachment status (i.e. free floating or sediment associated), and then stream order. Bacterioplankton taxonomic diversity and richness were elevated in sediment-associated fractions and in higher-order reaches during snowmelt. Families Chthonomonadaceae, Pyrinomonadaceae, and Xiphinematobacteraceae were abundantly different across seasons, while Flavobacteriaceae and Microscillaceae were abundantly different between free-floating and sediment-associated fractions. Physicochemical data suggested there was high iron (Fe⁺ ) production (alpine catchment); Fe⁺ production and chloride (Cl^- ) removal (tundra catchment); and phosphorus (SRP) removal and ammonium (NH₄ ⁺ ) production (lake catchment). In tundra landscapes, these 'hot spots' of Fe⁺ production and Cl^- removal accompanied shifts in species richness, while SRP promoted the antecedent community. Our findings suggest that freshet increases bacterial dispersal from headwater catchments to receiving catchments, where bacterioplankton-mineral relations stabilized communities in free-flowing reaches, but bacterioplankton-nutrient relations stabilized those punctuated by lakes.

Bulk and Spatially Resolved Extracellular Metabolome of Free-Living Nitrogen Fixation

Soil nitrogen (N) transformations constrain terrestrial net primary productivity and are driven by the activity of soil microorganisms. Free-living N fixation (FLNF) is an important soil N transformation and key N input to terrestrial systems, but the forms of N contributed to soil by FLNF are poorly understood. To address this knowledge gap, a focus on microorganisms and microbial scale processes is needed that links N-fixing bacteria and their contributed N sources to FLNF process rates. However, studying the activity of soil microorganisms in situ poses inherent challenges, including differences in sampling scale between microorganism and process rates, which can be addressed with culture-based studies and an emphasis on microbial-scale measurements. Culture conditions can differ significantly from soil conditions, so it also important that such studies include multiple culture conditions like liquid and solid media as proxies for soil environments like soil pore water and soil aggregate surfaces. Here we characterized extracellular N-containing metabolites produced by two common, diazotrophic soil bacteria in liquid and solid media, with or without N, across two sampling scales (bulk via GC-MS and spatially resolved via MALDI mass spec imaging). We found extracellular production of inorganic and organic N during FLNF, indicating terrestrial N contributions from FLNF occur in multiple forms not only as ammonium as previously thought. Extracellular metabolite profiles differed between liquid and solid media supporting previous work indicating environmental structure influences microbial function. Metabolite profiles also differed between sampling scales underscoring the need to quantify microbial scale conditions to accurately interpret microbial function.

IMPORTANCE Free-living nitrogen-fixing bacteria contribute significantly to terrestrial nitrogen availability; however, the forms of nitrogen contributed by this process are poorly understood. This is in part because of inherent challenges to studying soil microorganisms in situ, such as vast differences in scale between microorganism and ecosystem and complexities of the soil system (e.g., opacity, chemical complexity). Thus, upscaling important ecosystem processes driven by soil microorganisms, like free-living nitrogen fixation, requires microbial-scale measurements in controlled systems. Our work generated bulk and spatially resolved measurements of nitrogen released during free-living nitrogen fixation under two contrasting growth conditions analogous to soil pores and aggregates. This work allowed us to determine that diverse forms of nitrogen are likely contributed to terrestrial systems by free-living nitrogen bacteria. We also demonstrated that microbial habitat (e.g., liquid versus solid media) alters microbial activity and that measurement of microbial activity is altered by sampling scale (e.g., bulk versus spatially resolved) highlighting the critical importance of quantifying microbial-scale processes to upscaling of ecosystem function.

Implications of sample treatment on characterization of riverine dissolved organic matter

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (-), non-SPE (-), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (-) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for heterotrophic microbial respiration. Thus, we infer that the SPE (-) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (-) and SPE (+) to adequately characterize these molecules.

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI_feat), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI_feat, we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI_feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI_feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI_feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.