Metabolomic analysis of soil communities can be used for pollution assessment

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.

Metabolomics reveals changes in soil metabolic profiles during vegetation succession in karst area

Soil metabolites are critical in regulating the dynamics of ecosystem structure and function, particularly in fragile karst ecosystems. Clarification of response of soil metabolism to vegetation succession in karst areas will contribute to the overall understanding and management of karst soils. Here, we investigated the metabolite characteristics of karst soils with different vegetation stages (grassland, brushwood, secondary forest and primary forest) based on untargeted metabolomics. We confirmed that the abundance and composition of soil metabolites altered with vegetation succession. Of the 403 metabolites we found, 157 had significantly varied expression levels across vegetation soils, including mainly lipids and lipid-like molecules, phenylpropanoids and polyketides, organic acids and derivatives. Certain soil metabolites, such as maltotetraose and bifurcose, were sensitive to vegetation succession, increasing significantly from grassland to brushwood and then decreasing dramatically in secondary and primary forests, making them possible indicators of karst vegetation succession. In addition, soil metabolic pathways, such as galactose metabolism and biosynthesis of unsaturated fatty acids, also changed with vegetation succession. This study characterized the soil metabolic profile in different vegetation stages during karst secondary succession, which would provide new insights for the management of karst soils.

Soil metabolomics: Deciphering underground metabolic webs in terrestrial ecosystems

Soil metabolomics is an emerging approach for profiling diverse small molecule metabolites, i.e., metabolomes, in the soil. Soil metabolites, including fatty acids, amino acids, lipids, organic acids, sugars, and volatile organic compounds, often contain essential nutrients such as nitrogen, phosphorus, and sulfur and are directly linked to soil biogeochemical cycles driven by soil microorganisms. This paper presents an overview of methods for analyzing soil metabolites and the state-of-the-art of soil metabolomics in relation to soil nutrient cycling. We describe important applications of metabolomics in studying soil carbon cycling and sequestration, and the response of soil organic pools to changing environmental conditions. This includes using metabolomics to provide new insights into the close relationships between soil microbiome and metabolome, as well as responses of soil metabolome to plant and environmental stresses such as soil contamination. We also highlight the advantage of using soil metabolomics to study the biogeochemical cycles of elements and suggest that future research needs to better understand factors driving soil function and health.

Differential effects of winter cold stress on soil bacterial communities, metabolites, and physicochemical properties in two varieties of Tetrastigma hemsleyanum Diels & Gilg in reclaimed land

Tetrastigma hemsleyanum Diels & Gilg (TDG) has been recently planted in reclaimed lands in Zhejiang Province, China, to increase reclaimed land use. Winter cold stress seriously limits the growth and development of TDG and has become the bottleneck limiting the TDG planting industry. To investigate the defense mechanisms of TDG toward winter cold stress when grown on reclaimed land, a combined analysis of soil bacterial communities, metabolites, and physicochemical properties was conducted in this study. Significant differences were observed in the composition of soil bacterial communities, metabolites, and properties in soils of a cold-tolerant variety (A201201) compared with a cold-intolerant variety (B201810). The fresh weight (75.8% of tubers) and dry weight (73.6%) of A201201 were significantly higher than those of B201810. The 16S rRNA gene amplicon sequencing of soil bacteria showed that Gp5 (25.3%), Gemmatimonas (19.6%), Subdivision3 (16.7%), Lacibacterium (11.9%), Gp4 (11.8%), Gp3 (10.4%), Gp6 (7.0%), and WPS-1 (1.2%) were less common, while Chryseolinea (10.6%) were more common in A201201 soils than B201810 soils. Furthermore, linear discriminant analysis of effect size identified 35 bacterial biomarker taxa for both treatments. Co-occurrence network analyses also showed that the structures of the bacterial communities were more complex and stable in A201201 soils compared to B201810 soils. In addition, ultra-high-performance liquid chromatography coupled to mass spectrometry analysis indicated the presence of significantly different metabolites in the two soil treatments, with 10 differentially expressed metabolites (DEMs) (8 significantly upregulated by 9.2%-391.3% and 2 significantly downregulated by 25.1%-73.4%) that belonged to lipids and lipid-like molecules, organic acids and derivatives, and benzenoids. The levels of those DEMs were significantly correlated with the relative abundances of nine bacterial genera. Also, redundancy discriminant analysis revealed that the main factors affecting changes in the bacterial community composition were available potassium (AK), microbial biomass nitrogen (MBN), microbial biomass carbon (MBC), alkaline hydrolysis nitrogen (AHN), total nitrogen (TN), available phosphorus (AP), and soil organic matter (SOM). The main factors affecting changes in the metabolite profiles were AK, MBC, MBN, AHN, pH, SOM, TN, and AP. Overall, this study provides new insights into the TDG defense mechanisms involved in winter cold stress responses when grown on reclaimed land and practical guidelines for achieving optimal TDG production.IMPORTANCEChina has been undergoing rapid urbanization, and land reclamation is regarded as a viable option to balance occupation and compensation. In general, the quality of reclaimed land cannot meet plant or even cultivation requirements due to poor soil fertility and high gravel content. However, Tetrastigma hemsleyanum Diels & Gilg (TDG), extensively used in Chinese herbal medicine, can grow well in stony soils with few nutrients. So, to increase reclaimed land use, TDG has been cultivated on reclaimed lands in Zhejiang Province, China, recently. However, the artificial cultivation of TDG is often limited by winter cold stress. The aim of this study was to find out how TDG on reclaimed land deal with winter cold stress by looking at the bacterial communities, metabolites, and physicochemical properties of the soil, thereby guiding production in practice.

Evidence of interregional similarity in crayfish metabolomes at reference sites: Progress towards the metabolome as a biomonitoring tool

It has been proposed that biomonitoring may benefit from the use of metabolomics (the study of all small molecules in an organism) to detect sub-lethal organism stress through changes in the metabolite profile (i.e., the metabolome). However, to integrate the metabolome into biomonitoring programs the amount of natural variability among and within populations of indicator taxa must be established prior to generating a reference condition. This study determined variation in the metabolome among ecoregion and stream of origin in the northern crayfish (Faxonius virilis) and if that variation inhibited detection of stressor effects at sites exposed to human activities. We collected crayfish from seven minimally disturbed streams (i.e., reference streams), distributed across three level II ecoregions in central Canada and compared their metabolomes. We found ecoregion and stream origin were poor predictors of crayfish metabolomes. This result suggests crayfish metabolomes were similar, despite differing environmental conditions. Metabolomes of crayfish collected from three stream sites exposed to agricultural activity and municipal wastewater (i.e., test sites) were then compared to the crayfish metabolomes from the seven reference streams. Findings showed that crayfish metabolomes from test sites were strongly differentiated from those at all reference sites. The consistency in the northern crayfish metabolome at the studied reference streams indicates that a single reference condition may effectively detect impacts of human activities across the sampled ecoregions.

Long-term effects of oil contamination on soil quality and metabolic function

Widespread soil contamination with oil and the toxicity of petroleum hydrocarbons to soil biota make it extremely important to study microbial responses to oil stress. Soil metabolites reflect the main metabolic pathways in the soil microbial community. The examination of changes in the soil metabolic profile and metabolic function is essential for a better understanding of the nature of the pollution and restoration of the disturbed soils. The present study aimed to assess the long-term effect of oil on the ecological state of the soil, evaluate quantitative and qualitative differences in metabolite composition between soil contaminated with oil and non-contaminated soil, and reveal biologically active metabolites that are related to oil contamination and can be used for contamination assessment. A long-term field experiment was conducted to examine the effects of various oil concentrations on the biochemical properties and metabolic profile of the soil. Podzolic soil contaminated with oil demonstrated the long-term inhibition of soil biological activity and vegetation. Oil affected the metabolic activity of soil fungi increasing the production of toxic metabolites. A metabolomic approach was employed to determine soil metabolites. The metabolite profile was found to vary greatly between oil-contaminated and non-contaminated soils. Carbohydrates had the largest number of metabolites negatively affected by oil, while the content of organic acids, phenolic compounds, and terpenoids was mainly increased in oil-contaminated soil. The evaluation of the long-term impact of oil on microbial metabolism can make a valuable contribution to the assessment of soil quality and the activity of soil microorganisms being under stress from oil pollution. The results contribute to a further understanding of the role of microorganisms in the ecological functions of contaminated soil, which can be useful in the development of rehabilitation strategies for disturbed sites.

Regulatory mechanisms of submerged macrophyte on bacterial community recovery in decabromodiphenyl ether contaminated sediment: Microbiological and metabolomic perspectives

Polybrominated diphenyl ether contamination in sediments poses serious threats to human health and ecological safety. Despite the broad application of submerged macrophytes for remediating pollutants, their regulatory influence on bacterial communities in contaminated sediments remains unclear. Herein, we analyzed the effects of decabromodiphenyl ether (BDE-209) and Hydrilla verticillata on sediment bacterial community and function using 16S rRNA gene sequencing and sediment metabolomics. Results showed that BDE-209 significantly inhibited sediment bacterial diversity and metabolic functions. It also enhanced bacterial interactions and altered both the bacterial community and metabolite composition. Uridine and inosine were critical metabolites that positively co-occurred with bacterial taxa inhibited by BDE-209. Notably, planting H. verticillata effectively alleviated the adverse impacts of BDE-209 by reducing its residuals, increasing the total organic carbon, and modifying metabolic profiles. Such mitigation was evidenced by enhancing bacterial diversity, restoring metabolic functions, and attenuating bacterial interactions. However, mitigation effectiveness depended on treatment time. Additionally, propionic acid, palmitic acid, and palmitoleic acid may facilitate the restoration of phylum Proteobacteria and class Planctomycetacia in H. verticillata planted sediment. Together, these findings improve understanding of BDE-209's impacts on aquatic ecosystems and provide valuable insights for ecological restoration using submerged macrophytes.

Integrated microbiology and metabolomics analysis reveal responses of cotton rhizosphere microbiome and metabolite spectrum to conventional seed coating agents

Fludioxonil (FL) and metalaxyl-M·fludioxonil·azoxystrobin (MFA) are conventional seed coating agents for controlling cotton seedling diseases. However, their effects on seed endophytic and rhizosphere microecology are still poorly understood. This study aimed to assess the effects of FL and MFA on cotton seed endophytes, rhizosphere soil enzymatic activities, microbiome and metabolites. Both seed coating agents significantly changed seed endophytic bacterial and fungal communities. Growing coated seeds in the soils originating from the Alar (AL) and Shihezi (SH) region inhibited soil catalase activity and decreased both bacterial and fungal biomass. Seed coating agents increased rhizosphere bacterial alpha diversity for the first 21 days but decreased fungal alpha diversity after day 21 in the AL soil. Seed coating reduced the abundance of a number of beneficial microorganisms but enriched some potential pollutant-degrading microorganisms. Seed coating agents may have affected the complexity of the co-occurrence network of the microbiome in the AL soil, reducing connectivity, opposite to what was observed in the SH soil. MFA had more pronounced effects on soil metabolic activities than FL. Furthermore, there were strong links between soil microbial communities, metabolites and enzymatic activities. These findings provide valuable information for future research and development on application of seed coatings for disease management.

Soil metabolomics: A powerful tool for predicting and specifying pesticide sorption

Sorption regulates the dispersion of pesticides from cropped areas to surrounding water bodies as well as their persistence. Assessing the risk of water contamination and evaluating the efficiency of mitigation measures, requires fine-resolution sorption data and a good knowledge of its drivers. This study aimed to assess the potential of a new approach combining chemometric and soil metabolomics to estimate the adsorption and desorption coefficients of a range of pesticides. It also aims to identify and characterise key components of soil organic matter (SOM) driving the sorption of these pesticides. We constituted a dataset of 43 soils from Tunisia, France and Guadeloupe (West Indies), covering extensive ranges of texture, organic carbon and pH. We performed untargeted soil metabolomics by liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS). We measured the adsorption and desorption coefficients of three pesticides namely glyphosate, 2,4-D and difenoconazole for these soils. We developed Partial Least Square Regression (PLSR) models for the prediction of the sorption coefficients from the RT-m/z matrix and conducted further ANOVA analyses to identify, annotate and characterise the most significant constituents of SOM in the PLSR models. The curated metabolomics matrix yielded 1213 metabolic markers. The prediction performance of the PLSR models was generally high for the adsorption coefficients Kd_ads (0.3 < R² < 0.8) and for the desorption coefficients Kf_des (0.6 < R² < 0.8) but low for n_des (0.03 < R² < 0.3). The most significant features in the predictive models were annotated with a confidence level of 2 or 3. The molecular descriptors of these putative compounds suggest that the pool of SOM compounds driving glyphosate sorption is reduced compared to 2,4-D and difenoconazole, and these compounds are generally more polar. This approach can provide estimates of the adsorption and desorption coefficients of pesticides, including polar pesticide, for contrasted pedoclimates.

Co-analysis of cucumber rhizosphere metabolites and microbial PLFAs under excessive fertilization in solar greenhouse

Fertilizer application is the most common measure in agricultural production, which can promote the productivity of crops such as cucumbers, but the problem of excessive fertilization occurs frequently in solar greenhouses. However, the effects of fertilization levels on cucumber rhizosphere soil microbes and metabolites and their relationships are still unclear. In order to determine how fertilization levels affect the rhizosphere microenvironment, we set up four treatments in the solar greenhouse: no-fertilization (N0P0K0), normal fertilization (N1P1K1), slight excessive fertilization (N2P2K2), and extreme excessive fertilization (N3P3K3). The results showed that fertilization treatments significantly increased cucumber yield compared to no-fertilization, but, the yield of N3P3K3 was significantly lower than that of N1P1K1 and N2P2K2. Fertilization levels had significant effects on rhizosphere microorganisms, and pH, NH₄ ⁺-N and AP were the main environmental factors that affected the changes in microbial communities. The total PLFAs, the percentages of fungi and arbuscular mycorrhizal fungi (AMF) were significantly reduced and bacteria percentage was significantly increased in N3P3K3 compared to other fertilization treatments. Differential metabolites under different fertilization levels were mainly organic acids, esters and sugars. Soil phenols with autotoxic effect under fertilization treatments were higher than that of N0P0K0. In addition, compared with soil organic acids and alkanes of N0P0K0, N2P2K2 was significantly increased, and N3P3K3 was not significantly different. This suggested that cucumber could maintain microbial communities by secreting beneficial metabolites under slight excessive fertilization (N2P2K2). But under extremely excessive fertilization (N3P3K3), the self-regulating ability of cucumber plants and rhizosphere soil was insufficient to cope with high salt stress. Furthermore, co-occurrence network showed that 16:1ω5c (AMF) was positively correlated with 2-palmitoylglycerol, hentriacontane, 11-octadecenoic acid, decane,4-methyl- and d-trehalose, and negatively correlated with 9-octadecenoic acid at different fertilization levels. This indicated that the beneficial microorganisms in the cucumber rhizosphere soil promoted with beneficial metabolites and antagonized with harmful metabolites. But with the deepening of overfertilization, the content of beneficial microorganisms and metabolites decreased. The study provided new insights into the interaction of plant rhizosphere soil metabolites and soil microbiomes under the different fertilization levels.

Soil bacterial community and metabolism showed a more sensitive response to PBAT biodegradable mulch residues than that of LDPE mulch residues

Biodegradable mulch film (BDM) is considered as an environmentally sustainable alternative to low density polyethylene (LDPE) mulch film. However, the low degradation rate of BDM resulted in residues in soil after service period which were similar to LDPE mulch film. Distinguishing the differential responses of crop growth, soil bacteria and metabolism to residues of BDM and LDPE mulch films is favourable for comparing the environmental toxicities of the two materials. The results indicated that emergence rate and yield of Chinese cabbage (Brassica campestris L. ssp. chinensis Makino) were significantly inhibited by two types mulch residues. BDM residues significantly decreased bacterial diversity by 1.2-2.3% through the enrichment of dominant phyla and inhibition of inferior phyla, while LDPE mulch residues not. The effects of BDM residues on soil metabolite spectrum were stronger than LDPE mulch residues with significant increase (3.9% 5.8%) in the abundance of total metabolites. Besides the pathways of metabolism, organismal systems, environmental information processing influenced by LDPE mulch resides, differential pathways including human diseases and cellular processes were also determined in soil with BDM residues. According to all the results of the present study, prior to the promotion of BDM, its influences on soil safety must be carefully investigated through critical and systematic research.

Degradation of Xenobiotic Pollutants: An Environmentally Sustainable Approach

The ability of microorganisms to detoxify xenobiotic compounds allows them to thrive in a toxic environment using carbon, phosphorus, sulfur, and nitrogen from the available sources. Biotransformation is the most effective and useful metabolic process to degrade xenobiotic compounds. Microorganisms have an exceptional ability due to particular genes, enzymes, and degradative mechanisms. Microorganisms such as bacteria and fungi have unique properties that enable them to partially or completely metabolize the xenobiotic substances in various ecosystems.There are many cutting-edge approaches available to understand the molecular mechanism of degradative processes and pathways to decontaminate or change the core structure of xenobiotics in nature. These methods examine microorganisms, their metabolic machinery, novel proteins, and catabolic genes. This article addresses recent advances and current trends to characterize the catabolic genes, enzymes and the techniques involved in combating the threat of xenobiotic compounds using an eco-friendly approach.

Omics-based ecosurveillance for the assessment of ecosystem function, health, and resilience

Current environmental monitoring efforts often focus on known, regulated contaminants ignoring the potential effects of unmeasured compounds and/or environmental factors. These specific, targeted approaches lack broader environmental information and understanding, hindering effective environmental management and policy. Switching to comprehensive, untargeted monitoring of contaminants, organism health, and environmental factors, such as nutrients, temperature, and pH, would provide more effective monitoring with a likely concomitant increase in environmental health. However, even this method would not capture subtle biochemical changes in organisms induced by chronic toxicant exposure. Ecosurveillance is the systematic collection, analysis, and interpretation of ecosystem health-related data that can address this knowledge gap and provide much-needed additional lines of evidence to environmental monitoring programs. Its use would therefore be of great benefit to environmental management and assessment. Unfortunately, the science of 'ecosurveillance', especially omics-based ecosurveillance is not well known. Here, we give an overview of this emerging area and show how it has been beneficially applied in a range of systems. We anticipate this review to be a starting point for further efforts to improve environmental monitoring via the integration of comprehensive chemical assessments and molecular biology-based approaches. Bringing multiple levels of omics technology-based assessment together into a systems-wide ecosurveillance approach will bring a greater understanding of the environment, particularly the microbial communities upon which we ultimately rely to remediate perturbed ecosystems.

Current ionising radiation doses in the Chernobyl Exclusion Zone do not directly impact on soil biological activity

Although soil organisms are essential for ecosystem function, the impacts of radiation on soil biological activity at highly contaminated sites has been relatively poorly studied. In April-May 2016, we conducted the first largescale deployment of bait lamina to estimate soil organism (largely soil invertebrate) feeding activity in situ at study plots in the Chernobyl Exclusion Zone (CEZ). Across our 53 study plots, estimated weighted absorbed dose rates to soil organisms ranged from 0.7 μGy h^-1 to 1753 μGy h^-1. There was no significant relationship between soil organism feeding activity and estimated weighted absorbed dose rate. Soil biological activity did show significant relationships with soil moisture content, bulk density (used as a proxy for soil organic matter) and pH. At plots in the Red Forest (an area of coniferous plantation where trees died because of high radiation exposure in 1986) soil biological activity was low compared to plots elsewhere in the CEZ. It is possible that the lower biological activity observed in the Red Forest is a residual consequence of what was in effect an acute high exposure to radiation in 1986.

Integrated microbiology and metabolomics analysis reveal plastic mulch film residue affects soil microorganisms and their metabolic functions

Research on microplastic pollution of terrestrial soils is catching up with the aquatic environment, especially agricultural soil systems. Plastic residues have caused various environmental problems in mulch film extensively used agricultural areas. However, studies focusing specifically on the potential influence of mulch film residues on the metabolic cycle of soil systems have yet to be conducted. Here, high-throughput sequencing combined with metabolomics were first used to study the effects of residual mulch on soil microbial communities and related metabolic functions. Plastic film treatment did not significantly affect soil physicochemical properties including pH, organic matter and nitrogen, etc in short term. However, it did significantly changed overall community structure of soil bacteria, and interfered with complexity of soil bacterial symbiosis networks; exposure time and concentration of residues were particularly important factors affecting community structure. Furthermore, metabolomics analysis showed that film residue significantly changed soil metabolite spectrum, and interfered with basic carbon and lipid metabolism, and also affected basic cellular processes such as membrane transport and, in particular, interfered with the biosynthesis of secondary metabolites, as well as, biodegradation and metabolism of xenobiotics. Additionally, through linear discriminant and collinear analysis, some new potential microplastic degrading bacteria including Nitrospira, Nocardioidaceae and Pseudonocardiaceae have been excavated.

Commonwealth of Soil Health: How Do Earthworms Modify the Soil Microbial Responses to CeO2 Nanoparticles?

Soil ecotoxicological assays on nanoparticles (NPs) have mainly investigated single components (e.g., plants, fauna, and microbes) within the ecosystem, neglecting possible effects resulting from the disturbance of the interactions between these components. Here, we investigated soil microbial responses to CeO₂ NPs in the presence and absence of earthworms from the perspectives of microbial functions (i.e., enzyme activities), the community structure, and soil metabolite profiles. Exposure to CeO₂ NPs (50, 500 mg/kg) alone decreased the activities of enzymes (i.e., acid protease and acid phosphatase) participating in soil N and P cycles, while the presence of earthworms ameliorated these inhibitory effects. After the CeO₂ NP exposure, the earthworms significantly altered the relative abundance of some microbes associated with the soil N and P cycles (Flavobacterium, Pedobacter, Streptomyces, Bacillus, Bacteroidota, Actinobacteria, and Firmicutes). This was consistent with the pattern found in the significantly changed metabolites which were also involved in the microbial N and P metabolism. Both CeO₂ NPs and earthworms changed the soil bacterial community and soil metabolite profiles. Larger alterations of soil bacteria and metabolites were found under CeO₂ NP exposure with earthworms. Overall, our study indicates that the top-down control of earthworms can drastically modify the microbial responses to CeO₂ NPs from all studied biological aspects. This clearly shows the importance of the holistic consideration of all soil ecological components to assess the environmental risks of NPs to soil health.

Metabolic regulation in soil microbial succession and niche differentiation by the polymer amendment under cadmium stress

Cadmium (Cd) contamination seriously threatens the agricultural production, so exploring the response of soil microenvironment to amendments in Cd-contaminated soils is of importance. In this study, the mechanism of remediation of Cd-contaminated soil using the polymer amendment was studied in cotton flowering stage. The results showed that the concentration of Cd in cotton root and various Cd forms in Cd-contaminated soils were obviously high. High concentration of Cd, especially exchangeable Cd, could seriously affect the soil microenvironment. The root growth of cotton could be promoted, the carbon and nitrogen concentration and storage in soil were increased by 21.72-50.00%, while the exchangeable Cd concentration in soil were decreased by 41.43%, after applying the polymer amendment. In addition, the polymer amendment affected the soil microbial niche, increased the relative abundance of soil bacteria (Flaviaesturariibacter, Rubellimicrobium, and Cnuella), fungi (Verticillium and Tricharina), actinomycetes (Blastococcus and Nocardioides), and fungivores nematodes (Aphelenchus), and improved soil microbial metabolic functions (metabolism of nucleotides and carbohydrates). Therefore, this polymer amendment could be used to remediate severe Cd-contaminated soils, and the changes in the microbial and nematode communities help us understand the detoxification mechanism of the polymer amendment in Cd-contaminated soils.

Functional analysis of pristine estuarine marine sediments

Traditional environmental monitoring techniques are well suited to resolving acute exposure effects but lack resolution in determining subtle shifts in ecosystem functions resulting from chronic exposure(s). Surveillance with sensitive omics-based technologies could bridge this gap but, to date, most omics-based environmental studies have focused on previously degraded environments, identifying key metabolic differences resulting from anthropogenic perturbations. Here, we apply omics-based approaches to pristine environments to establish blueprints of microbial functionality within healthy estuarine sediment communities. We collected surface sediments (n = 50) from four pristine estuaries along the Western Cape York Peninsula of Far North Queensland, Australia. Sediment microbiomes were analyzed for 16S rRNA amplicon sequences, central carbon metabolism metabolites and associated secondary metabolites via targeted and untargeted metabolic profiling methods. Multivariate statistical analyses indicated heterogeneity among all the sampled estuaries, however, taxa-function relationships could be established that predicted community metabolism potential. Twenty-four correlated gene-metabolite pathways were identified and used to establish sediment microbial blueprints of essential carbon metabolism and amino acid biosynthesis that were positively correlated with community metabolic function outputs (2-oxisocapraote, tryptophan, histidine citrulline and succinic acid). In addition, an increase in the 125 KEGG genes related to metal homeostasis and metal resistance was observed, although, none of the detected metabolites related to these specific genes upon integration. However, there was a correlation between metal abundance and functional genes related to Fe and Zn metabolism. Our results establish a baseline microbial blueprint for the pristine sediment microbiome, one that drives important ecosystem services and to which future ecosurveillance monitoring can be compared.

Exploring the Impacts of Conformer Selection Methods on Ion Mobility Collision Cross Section Predictions

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50 000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire data set. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property: the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good trade-off between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Recent Advanced Technologies for the Characterization of Xenobiotic-Degrading Microorganisms and Microbial Communities

Global environmental contamination with a complex mixture of xenobiotics has become a major environmental issue worldwide. Many xenobiotic compounds severely impact the environment due to their high toxicity, prolonged persistence, and limited biodegradability. Microbial-assisted degradation of xenobiotic compounds is considered to be the most effective and beneficial approach. Microorganisms have remarkable catabolic potential, with genes, enzymes, and degradation pathways implicated in the process of biodegradation. A number of microbes, including Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Sphingobium, Flavobacterium, Rhodococcus, Aspergillus, Penecillium, Trichoderma, Streptomyces, Rhodotorula, Candida, and Aureobasidium, have been isolated and characterized, and have shown exceptional biodegradation potential for a variety of xenobiotic contaminants from soil/water environments. Microorganisms potentially utilize xenobiotic contaminants as carbon or nitrogen sources to sustain their growth and metabolic activities. Diverse microbial populations survive in harsh contaminated environments, exhibiting a significant biodegradation potential to degrade and transform pollutants. However, the study of such microbial populations requires a more advanced and multifaceted approach. Currently, multiple advanced approaches, including metagenomics, proteomics, transcriptomics, and metabolomics, are successfully employed for the characterization of pollutant-degrading microorganisms, their metabolic machinery, novel proteins, and catabolic genes involved in the degradation process. These technologies are highly sophisticated, and efficient for obtaining information about the genetic diversity and community structures of microorganisms. Advanced molecular technologies used for the characterization of complex microbial communities give an in-depth understanding of their structural and functional aspects, and help to resolve issues related to the biodegradation potential of microorganisms. This review article discusses the biodegradation potential of microorganisms and provides insights into recent advances and omics approaches employed for the specific characterization of xenobiotic-degrading microorganisms from contaminated environments.

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

Indicators for assessment of soil quality: a mini-review

Soil quality is the competence of soil to perform necessary functions that are able to maintain animal and plant productivity of the soil. Soil consists of various physical, chemical, and biological parameters, and all these parameters are involved in the critical functioning of soil. There is a need for continuous assessment of soil quality as soil is a complex and dynamic constituent of Earth's biosphere that is continuously changing by natural and anthropogenic disturbances. Any perturbations in the soil cause disturbances in the physical (soil texture, bulk density, etc.), chemical (pH, salinity, organic carbon, etc.), and biological (microbes and enzymes) parameters. These physical, chemical, and biological parameters can serve as indicators for soil quality assessment. However, soil quality assessment cannot be possible by evaluating only one parameter out of physical, chemical, or biological. So, there is an emergent need to establish a minimum dataset (MDS) which shall include physical, chemical, and biological parameters to assess the quality of the given soil. This review attempts to describe various physical, chemical, and biological parameters, combinations of which can be used in the establishment of MDS.

Correlations between soil metabolomics and bacterial community structures in the pepper rhizosphere under plastic greenhouse cultivation

Microbial communities in the plant rhizosphere are critical drivers of soil organic matter conversion and thus affect plant growth, especially under plastic greenhouse vegetable cultivation (PGVC). By high-throughput sequencing and soil metabolomics, we investigated the differential structures and functions of the soil bacterial community in pepper rhizosphere and bulk soils under PGVC. It was found that the soil properties, including the total dissolved organic carbon content, did not show significant differences between the rhizosphere and bulk soil. However, the soil metabolite profiles and the soil bacterial community structures changed in pepper rhizosphere. Eleven differential metabolites were detected between rhizosphere and bulk soils, including organic acids and sugars, which were positively or negatively correlated with the relative abundances of the differential bacteria. Pathway enrichment analysis indicated that the most differentially expressed metabolic pathway was starch and sucrose metabolism, and the main functional genes participating in this pathway were predicted to be downregulated in rhizosphere soil. This study linked the differential soil microbe and soil metabolite profiles in the pepper rhizosphere under PGVC and provided new insights into plant-microbe interactions in soil.

Metabolomics Study of Subsurface Wastewater Infiltration System Under Fluctuation of Organic Load

Subsurface Wastewater Infiltration System (SWIS) is a sewage ecological treatment technology with low investment, energy consumption, and operating cost. SWIS soil contains a large variety of microorganisms. The metabolic process and production of microorganisms are an important basis for qualitatively describing the process of pollutant removal. In order to discover the microbial decontamination pathways in SWIS, the metabolic profiles of soil microorganisms in SWIS were analyzed by UPLC-MS. Partial least squares-discriminant analysis (PLS-DA)and principal component analysis (PCA) pattern recognition methods were used to classify the samples. According to the model's variable importance factor (VIP value), potential biomarkers were screened and biological information contained in the metabolites was also analyzed. The correlation between metabolites and environmental factors was explored by RDA analysis. In total, 230 differential metabolites with VIP value greater than 1.5 were screened out when the influent organic load fluctuated at 250 mg L^-1, 400 mg L^-1, and 500 mg L^-1. After identifying and screening, 35 differential metabolites were identified and used to further analyze the metabolic pathway. It turns out that microbial metabolites in SWIS were mainly glycosides, fatty acids, amino acids, pigments, diterpenoids, and some polymers under medium and high organic loading conditions. At low organic load, the microbial metabolites in SWIS were mainly ketones, alcohols, and esters.

New insights into the responses of soil microorganisms to polycyclic aromatic hydrocarbon stress by combining enzyme activity and sequencing analysis with metabolomics

Polycyclic aromatic hydrocarbons (PAHs), some of the most widespread organic contaminants, are highly toxic to soil microorganisms. Whether long-term polluted soils can still respond to the fresh input of pollutants is unknown. In this study, the soil enzyme activity, soil microbial community structure and function and microbial metabolism pathways were examined to systematically investigate the responses of soil microorganisms to fresh PAH stress. Microbial activity as determined by soil dehydrogenase and urease activity was inhibited upon microbe exposure to PAH stress. In addition, the soil microbial community and function were obviously shifted under PAH stress. Both microbial diversity and richness were decreased by PAH stress. Rhizobacter, Sphingobium, Mycobacterium, Massilia, Bacillus and Pseudarthrobacter were significantly affected by PAH stress and can be considered important indicators of PAH contamination in agricultural soils. Moreover, the majority of microbial metabolic function predicted to respond to PAH stress were affected adversely. Finally, soil metabolomics further revealed specific inhibition of soil metabolism pathways associated with fatty acids, carbohydrates and amino acids. Therefore, the soil metabolic composition distinctively changed, reflecting a change in the soil metabolism. In summary, fresh contaminant introduction into long-term polluted soils inhibited microbial activity and metabolism, which might profoundly affect the whole soil quality.

Temporal Dynamics of the Soil Metabolome and Microbiome During Simulated Anaerobic Soil Disinfestation

Significant interest exists in engineering the soil microbiome to attain suppression of soil-borne plant diseases. Anaerobic soil disinfestation (ASD) has potential as a biologically regulated disease control method; however, the role of specific metabolites and microbial community dynamics contributing to ASD mediated disease control is mostly uncharacterized. Understanding the trajectory of co-evolutionary processes leading to syntrophic generation of functional metabolites during ASD is a necessary prelude to the predictive utilization of this disease management approach. Consequently, metabolic and microbial community profiling were used to generate highly dimensional datasets and network analysis to identify sequential transformations through aerobic, facultatively anaerobic, and anaerobic soil phases of the ASD process and distinct groups of metabolites and microorganisms linked with those stages. Transient alterations in abundance of specific microbial groups, not consistently accounted for in previous studies of the ASD process, were documented in this time-course study. Such events initially were associated with increases and subsequent diminution in highly labile metabolites conferred by the carbon input. Proliferation and dynamic compositional changes in the Firmicutes community continued throughout the anaerobic phase and was linked to temporal changes in metabolite abundance including accumulation of small chain organic acids, methyl sulfide compounds, hydrocarbons, and p-cresol with antimicrobial properties. Novel potential modes of disease control during ASD were identified and the importance of the amendment and "community metabolism" for temporally supplying specific classes of labile compounds were revealed.

Metabolomics approaches for the discrimination of disease suppressive soils for Rhizoctonia solani AG8 in cereal crops using 1H NMR and LC-MS

The suppression of soilborne crop pathogens such as Rhizoctonia solani AG8 may offer a sustainable and enduring method for disease control, though soils with these properties are difficult to identify. In this study, we analysed the soil metabolic profiles of suppressive and non-suppressive soils over 2 years of cereal production. We collected bulk and rhizosphere soil at different cropping stages and subjected soil extracts to liquid chromatography-mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (¹H NMR) analyses. Community analyses of suppressive and non-suppressive soils using principal component analyses and predictive modelling of LC-MS and NMR datasets respectively, revealed distinct biochemical profiles for the two soil types with clustering based on suppressiveness and cropping stage. NMR spectra revealed the suppressive soils to be more abundant in sugar molecules than non-suppressive soils, which were more abundant in lipids and terpenes. LC-MS features that were significantly more abundant in the suppressive soil were identified and assessed as potential biomarkers for disease suppression. The structures of a potential class of LC-MS biomarkers were elucidated using accurate mass data and MS fragmentation spectrum information. The most abundant compound found in association with suppressive soils was confirmed to be a macrocarpal, which is an antimicrobial secondary metabolite. Our study has demonstrated the utility of environmental metabolomics for the study of disease suppressive soils, resulting in the discovery of a macrocarpal biomarker for R. solani AG8 suppressive soil which can be further studied functionally in association with suppression pot trials and microbial isolation studies.

Untargeted Soil Metabolomics Using Liquid Chromatography-Mass Spectrometry and Gas Chromatography-Mass Spectrometry

The molecular composition of soil organic matter (SOM) sets the foundation for terrestrial microbial community structures and carbon cycling dynamics. However, the specific chemical constituents of SOM are underexplored. In this chapter we present a protocol for the extraction of small molecule metabolites from soil followed by compound detection and identification using liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry. There are options within the protocol to assess either the extracellular pool of metabolites or the total pool (including intracellular) and either polar or nonpolar metabolites, depending on the reader's research interests. These methods can be followed individually for a more targeted analysis or all methods can be combined to obtain a more comprehensive understanding of SOM metabolite composition (such as amino acids, nucleobases, organic acids, fatty acids, carbohydrates, secondary metabolites, and antibiotics).

Illuminating the dark metabolome to advance the molecular characterisation of biological systems

BACKGROUND

The latest version of the Human Metabolome Database (v4.0) lists 114,100 individual entries. Typically, however, metabolomics studies identify only around 100 compounds and many features identified in mass spectra are listed only as 'unknown compounds'. The lack of ability to detect all metabolites present, and fully identify all metabolites detected (the dark metabolome) means that, despite the great contribution of metabolomics to a range of areas in the last decade, a significant amount of useful information from publically funded studies is being lost or unused each year. This loss of data limits our potential gain in knowledge and understanding of important research areas such as cell biology, environmental pollution, plant science, food chemistry and health and biomedical research. Metabolomics therefore needs to develop new tools and methods for metabolite identification to advance as a field.

AIM OF REVIEW

In this critical review, some potential issues with metabolite identification are identified and discussed. New and novel emerging technologies and tools which may contribute to expanding the number of compounds identified in metabolomics studies (thus illuminating the dark metabolome) are reviewed. The aim is to stimulate debate and research in the molecular characterisation of biological systems to drive forward metabolomic research.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The work specifically discusses dynamic nuclear polarisation nuclear magnetic resonance spectroscopy (DNP-NMR), non-proton NMR active nuclei, two-dimensional liquid chromatography (2DLC) and Raman spectroscopy (RS). It is suggested that developing new methods for metabolomics with these techniques could lead to advances in the field and better characterisation of biological systems.

Standard methods for the assessment of structural and functional diversity of soil organisms: A review

The lack of standardized methods to study soil organisms prevents comparisons across data sets and the development of new global and regional experiments and assessments. Moreover, standardized methods are needed to evaluate the impact of anthropogenic stressors, such as chemicals, on soil organism communities in the regulatory context. The goal of this contribution is to summarize current methodological approaches to measure structural and functional diversity of soil organisms, and to identify gaps and methodological improvements so as to cross data sets generated worldwide. This is urgently needed because several currently ongoing regional and global soil biodiversity studies are not coordinated with one another in terms of methodology, including database development. Therefore, we evaluated the standard methods to sample, identify, determine, and assess soil organisms currently applied or proposed, using well-accepted criteria such as ecological relevance; practicability of usage in terms of resources, time, and costs; and the level of standardization. Methods addressing both the structure and the functions of soil organisms (populations or communities) are included, with a special focus on new molecular methods based on nucleic acid extraction and further analyses by polymerase chain reaction (PCR)-based approaches for microorganisms and invertebrates. We particularly highlight the activities of the Technical Committee (TC) 190 of the International Organization for Standardization (ISO) because ISO guidelines are legally accredited by many national or international authorities when they put conservation laws and regulations into practice. Finally, we propose detailed recommendations regarding gaps in the available set of standards, in order to identify a list of new methods to be standardized. We propose to organize this whole process under the Global Soil Biodiversity Initiative (GSBI) in order to ensure a truly global approach for the assessment of soil biodiversity. Integr Environ Assess Manag 2018;14:463-479. © 2018 SETAC.

Structural and functional measures of marine microbial communities: An experiment to assess implications for oil spill management

Microbial communities are ecologically important in aquatic environments and impacts on microbes have the potential to affect a number of functional processes. We have amended seawater with a crude oil and assessed changes in species composition as well as a measure of functional diversity (the ability of the community to utilise different carbon sources) and the community level metabolic signature. We found that there was a degree of functional redundancy in the community we tested. Oiled assemblages became less diverse and more dominated by specialist hydrocarbon degraders, carbon source utilisation increased initially but there was no change in metabolic signature in this small scale laboratory experiment. This study supports the decision framework around management of oil spills. This package of methods has the potential to be used in the testing and selection of new dispersants for use in oil spill response.

Recent Insights on Biological and Ecological Aspects of Ectomycorrhizal Fungi and Their Interactions

The roots of most terrestrial plants are colonized by mycorrhizal fungi. They play a key role in terrestrial environments influencing soil structure and ecosystem functionality. Around them a peculiar region, the mycorrhizosphere, develops. This is a very dynamic environment where plants, soil and microorganisms interact. Interest in this fascinating environment has increased over the years. For a long period the knowledge of the microbial populations in the rhizosphere has been limited, because they have always been studied by traditional culture-based techniques. These methods, which only allow the study of cultured microorganisms, do not allow the characterization of most organisms existing in nature. The introduction in the last few years of methodologies that are independent of culture techniques has bypassed this limitation. This together with the development of high-throughput molecular tools has given new insights into the biology, evolution, and biodiversity of mycorrhizal associations, as well as, the molecular dialog between plants and fungi. The genomes of many mycorrhizal fungal species have been sequenced so far allowing to better understanding the lifestyle of these fungi, their sexual reproduction modalities and metabolic functions. The possibility to detect the mycelium and the mycorrhizae of heterothallic fungi has also allowed to follow the spatial and temporal distributional patterns of strains of different mating types. On the other hand, the availability of the genome sequencing from several mycorrhizal fungi with a different lifestyle, or belonging to different groups, allowed to verify the common feature of the mycorrhizal symbiosis as well as the differences on how different mycorrhizal species interact and dialog with the plant. Here, we will consider the aspects described before, mainly focusing on ectomycorrhizal fungi and their interactions with plants and other soil microorganisms.

A Community Multi-Omics Approach towards the Assessment of Surface Water Quality in an Urban River System

A multi-omics approach was applied to an urban river system (the Brisbane River (BR), Queensland, Australia) in order to investigate surface water quality and characterize the bacterial population with respect to water contaminants. To do this, bacterial metagenomic amplicon-sequencing using Illumina next-generation sequencing (NGS) of the V5-V6 hypervariable regions of the 16S rRNA gene and untargeted community metabolomics using gas chromatography coupled with mass spectrometry (GC-MS) were utilized. The multi-omics data, in combination with fecal indicator bacteria (FIB) counts, trace metal concentrations (by inductively coupled plasma mass spectrometry (ICP-MS)) and in-situ water quality measurements collected from various locations along the BR were then used to assess the health of the river ecosystem. Sites sampled represented the transition from less affected (upstream) to polluted (downstream) environments along the BR. Chemometric analysis of the combined datasets indicated a clear separation between the sampled environments. Burkholderiales and Cyanobacteria were common key factors for differentiation of pristine waters. Increased sugar alcohol and short-chain fatty acid production was observed by Actinomycetales and Rhodospirillaceae that are known to form biofilms in urban polluted and brackish waters. Results from this study indicate that a multi-omics approach enables a deep understanding of the health of an aquatic ecosystem, providing insight into the bacterial diversity present and the metabolic output of the population when exposed to environmental contaminants.

Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems

Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as "statistically significant" in the study. Such metabolic "dark matter" means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function.

Environmental Metabolic Footprinting: A novel application to study the impact of a natural and a synthetic β-triketone herbicide in soil

This study presents a novel approach for assessing the risk of agrochemicals in soil microcosms through the use of non-targeted metabolomics. The metabolome of treated soils was extracted and tested through LCMS profiling in order to generate an "Environmental Metabolic Footprint" (EMF). A dynamic characterization of pollution biomarkers was obtained through a multivariate statistical analysis of EMF data, where our results show the possible evolution towards a state of resilience. The EMF methodology was applied to two β-triketone herbicides in soil microcosms: one natural, leptospermone, and one synthetic, sulcotrione. In spite of a four-fold higher application dose, leptospermone exhibited a lower resilience time than did sulcotrione (ca. 30 days vs ca. 45 days respectively).

Microbiota Characterization of Compost Using Omics Approaches Opens New Perspectives for Phytophthora Root Rot Control

Phytophthora root rot caused by Phytophthora nicotianae is an economically important disease in pepper crops. The use of suppressive composts is a low environmental impact method for its control. Although attempts have been made to reveal the relationship between microbiota and compost suppressiveness, little is known about the microorganisms associated with disease suppression. Here, an Ion Torrent platform was used to assess the microbial composition of composts made of different agro-industrial waste and with different levels of suppressiveness against P. nicotianae. Both bacterial and fungal populations responded differently depending on the chemical heterogeneity of materials used during the composting process. High proportions (67–75%) of vineyard pruning waste were used in the most suppressive composts, COM-A and COM-B. This material may have promoted the presence of higher relative abundance of Ascomycota as well as higher microbial activity, which have proved to be essential for controlling the disease. Although no unique fungi or bacteria have been detected in neither suppressive nor conducive composts, relatively high abundance of Fusarium and Zopfiella were found in compost COM-B and COM-A, respectively. To the best of our knowledge, this is the first work that studies compost metabolome. Surprisingly, composts and peat clustered together in principal component analysis of the metabolic data according to their levels of suppressiveness achieved. This study demonstrated the need for combining the information provided by different techniques, including metagenomics and metametabolomics, to better understand the ability of compost to control plant diseases.

Strain-level dissection of the contribution of the gut microbiome to human metabolic disease

The gut microbiota has been linked with metabolic diseases in humans, but demonstration of causality remains a challenge. The gut microbiota, as a complex microbial ecosystem, consists of hundreds of individual bacterial species, each of which contains many strains with high genetic diversity. Recent advances in genomic and metabolomic technologies are facilitating strain-level dissection of the contribution of the gut microbiome to metabolic diseases. Interventional studies and correlation analysis between variations in the microbiome and metabolome, captured by longitudinal sampling, can lead to the identification of specific bacterial strains that may contribute to human metabolic diseases via the production of bioactive metabolites. For example, high-quality draft genomes of prevalent gut bacterial strains can be assembled directly from metagenomic datasets using a canopy-based algorithm. Specific metabolites associated with a disease phenotype can be identified by nuclear magnetic resonance-based metabolomics of urine and other samples. Such multi-omics approaches can be employed to identify specific gut bacterial genomes that are not only correlated with detected metabolites but also encode the genes required for producing the precursors of those metabolites in the gut. Here, we argue that if a causative role can be demonstrated in follow-up mechanistic studies--for example, using gnotobiotic models--such functional strains have the potential to become biomarkers for diagnostics and targets for therapeutics.

Ecotoxicological assessment of antibiotics: A call for improved consideration of microorganisms

Antibiotics play a pivotal role in the management of infectious disease in humans, companion animals, livestock, and aquaculture operations at a global scale. Antibiotics are produced, consumed, and released into the environment at an unprecedented scale causing concern that the presence of antibiotic residues may adversely impact aquatic and terrestrial ecosystems. Here we critically review the ecotoxicological assessment of antibiotics as related to environmental risk assessment (ERA). We initially discuss the need for more specific protection goals based on the ecosystem service concept, and suggest that the ERA of antibiotics, through the application of a mode of toxic action approach, should make more use of ecotoxicological endpoints targeting microorganisms (especially bacteria) and microbial communities. Key ecosystem services provided by microorganisms and associated ecosystem service-providing units (e.g. taxa or functional groups) are identified. Approaches currently available for elucidating ecotoxicological effects on microorganisms are reviewed in detail and we conclude that microbial community-based tests should be used to complement single-species tests to offer more targeted protection of key ecosystem services. Specifically, we propose that ecotoxicological tests should not only assess microbial community function, but also microbial diversity (‘species’ richness) and antibiotic susceptibility. Promising areas for future basic and applied research of relevance to ERA are highlighted throughout the text. In this regard, the most fundamental knowledge gaps probably relate to our rudimentary understanding of the ecological roles of antibiotics in nature and possible adverse effects of environmental pollution with subinhibitory levels of antibiotics.

NMR metabolomics for soil analysis provide complementary, orthogonal data to MIR and traditional soil chemistry approaches--a land use study

The present study was designed to analyse soils by different methodologies to determine the range of traits that could be investigated for the study of environmental soil samples. Proton nuclear magnetic resonance spectroscopy ((1) H NMR) was employed for metametabolomic analysis of soils from agricultural systems (managed) or from soils in a native state (remnant). The metabolomic methodologies employed (grinding and extraction with sonication) are capable of breaking up cell walls and so enabled characterisation of both extracellular and intracellular components of soil. Diffuse mid-infrared spectroscopy (MIR) data was obtained for the same sample sets, and in addition, elemental composition was determined by conventional laboratory chemical testing methods. Also investigated was the antibiotic activity of the soil extracts. Resilient or suppressive soils are valued in the agricultural setting as they convey disease resistance (against bacterial and fungal pathogens) to crop plants. In order to test if any such biological activity could be detected in the soils, the extracts were tested against the bacteria Bacillus subtilis. Several extracts showed strong growth inhibition against the bacteria with the most active clustered together in principle component analysis (PCA) of the metabolomic data. The study showed that the NMR metabolomic approach corresponds more accurately to land use and biochemical properties potentially associated with suppression, while MIR data correlated well to inorganic chemical analysis. Thus, the study demonstrates the utility in combining these spectroscopic methods for soil analysis.

Untargeted metabolic profiling of Vitis vinifera during fungal degradation

This paper illustrates the application of an untargeted metabolic profiling analysis of winery-derived biomass degraded using four filamentous fungi (Trichoderma harzianum, Aspergillus niger, Penicillium chrysogenum and P. citrinum) and a yeast (Saccharomyces cerevisiae). Analysis of the metabolome resulted in the identification of 233 significant peak features [P < 0.05; fold change (FC) > 2 and signal-to-noise ratio >50] using gas chromatography-mass spectrometry followed by statistical chemometric analysis. Furthermore, A. niger and P. chrysogenum produced higher biomass degradation due to considerable β-glucosidase and xylanase activities. The major metabolites generated during fungal degradation which differentiated the metabolic profiles of fungi included sugars, sugar acids, organic acids and fatty acids. Although, P. chrysogenum could degrade hemicelluloses due to its high β-glucosidase and xylanase activities, it could not utilize the resultant pentoses, which A. niger and P. citrinum could do efficiently, thus indicating a need of mixed fungal culture to improve the biomass degradation. Saccharomyces cerevisiae, a non-cellulose degrader, exhibited sugar accumulation during the fermentation. Penicillium chrysogenum was observed to degrade about 2% lignin, a property not observed in other fungi. This study emphasized the differential fungal metabolic behavior and demonstrated the potential of metabolomics in optimizing degradation or manipulating pathways to increase yields of products of interest.

Plant metabolite profiles and the buffering capacities of ecosystems

In spite of some inherent challenges, metabolite profiling is becoming increasingly popular under field conditions. It has been used successfully to address topics like species interactions, connections between growth and chemical stoichiometry or the plant's stress response. Stress exerts a particularly clear impact on plant metabolomes and has become a central topic in many metabolite profiling experiments in the fields. In contrast to phytochambers, however, external stress is often at least partially absorbed by the environment when measuring under field conditions. Such stress-buffering capacities of (agro)-ecosystems are of crucial interest given the ever-increasing anthropogenic impact on ecosystems and this review promotes the idea of using plant metabolite profiles for respective measurements. More specifically I propose to use parameters of the response of key plant species to a given stress treatment as proxies for measuring and comparing stress-buffering capacities of ecosystems. Stress response parameters accessible by metabolite profiling comprise for example the intensity or duration of the impact of stress or the ability of the plant organism to recover from this impact after a given time. Analyses of ecosystem stress-buffering capacities may improve our understanding of how ecosystems cope with stress and may improve our abilities to predict ecosystem changes.