Metabolomics and its use in ecology

Urbanisation-associated shifts in the avian metabolome within the annual cycle

While organisms have evolved to cope with predictable changes in the environment, the rapid rate of current global change presents numerous novel and unpredictable stressors to which organisms have had less time to adapt. To persist in the urban environment, organisms must modify their physiology, morphology and behaviour accordingly. Metabolomics offers great potential for characterising organismal responses to natural and anthropogenic stressors at the systems level and can be applied to any species, even without genomic knowledge. Using metabolomic profiling of blood, we investigated how two closely related species of passerine bird respond to the urban environment. Great tits Parus major and blue tits Cyanistes caeruleus residing in urban and forest habitats were sampled during the breeding (spring) and non-breeding (winter) seasons across replicated sites in southern Sweden. During breeding, differences in the plasma metabolome between urban and forest birds were characterised by higher levels of amino acids in urban-dwelling tits and higher levels of fatty acyls in forest-dwelling tits. The suggested higher rates of fatty acid oxidation in forest tits could be driven by habitat-associated differences in diet and could explain the higher reproductive investment and success of forest tits. High levels of amino acids in breeding urban tits could reflect the lack of lipid-rich caterpillars in the urban environment and a dietary switch to protein-rich spiders, which could be of benefit for tackling inflammation and oxidative stress associated with pollution. In winter, metabolomic profiles indicated lower overall levels of amino acids and fatty acyls in urban tits, which could reflect relaxed energetic demands in the urban environment. Our metabolomic profiling of two urban-adapted species suggests that their metabolism is modified by urban living, though whether these changes represent adaptative or non-adaptive mechanisms to cope with anthropogenic challenges remains to be determined.

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.

Metabolome profile variation in Azolla filiculoides exposed to Bisphenol A assists in the identification of stress-responsive metabolites

This study attempted to explore the metabolome profile of Azolla filiculoides subjected to two different concentrations of BPA (1 and 30 mg L-1) in congruence with two different durations (3 and 9 days) of treatment. Bisphenol A (BPA) is a ubiquitously occurring environmental pollutant that imparts acute toxicity in aquatic plants. Therefore, studying the variations in the fern metabolome profile and identifying stress-responsive metabolites can help develop criteria for assessing the aquatic ecosystem. In recent times, metabolomics has drawn attention for its ability to detect biochemical processes and help link plant responses with environmental stresses. However, the studies concerning the metabolome profile of A. filiculoides exposed to environmental contaminants are limited. In the present study, the untargeted metabolomics study allowed the detection of a large array of metabolites, with 767 shared metabolites representing 41 crucial pathways. Exposure to 30 mg L-1 BPA seemingly disrupted the primary metabolism of the fern and induced a shift toward defense-related pathways. Additionally, BPA stress triggered the expression of metabolites like 3,4-dihydroxyphenylglycol, perillic acid, and perillaldehyde in BPA_L3 (1 mg L-1 for 3 days) and BPA_L9 (1 mg L-1 for 9 days) samples indicating protective mechanism of the plants. Conversely, the BPA_H3 (30 mg L-1 for 3 days) and BPA_H9 (30 mg L-1 for 9 days) samples expressed a distinct set of markers like luteolin, 3-hydroxyanthranilic acid, cinnamaldehyde, and l-DOPA indicating the onset of senescence and apoptosis related pathways can help in the health assessment of freshwater ecosystems and also appraisal of ecotoxicological risks imposed by BPA.

Mission Tara Microplastics: a holistic set of protocols and data resources for the field investigation of plastic pollution along the land-sea continuum in Europe

The Tara Microplastics mission was conducted for 7 months to investigate plastic pollution along nine major rivers in Europe-Thames, Elbe, Rhine, Seine, Loire, Garonne, Ebro, Rhone, and Tiber. An extensive suite of sampling protocols was applied at four to five sites on each river along a salinity gradient from the sea and the outer estuary to downstream and upstream of the first heavily populated city. Biophysicochemical parameters including salinity, temperature, irradiance, particulate matter, large and small microplastics (MPs) concentration and composition, prokaryote and microeukaryote richness, and diversity on MPs and in the surrounding waters were routinely measured onboard the French research vessel Tara or from a semi-rigid boat in shallow waters. In addition, macroplastic and microplastic concentrations and composition were determined on river banks and beaches. Finally, cages containing either pristine pieces of plastics in the form of films or granules, and others containing mussels were immersed at each sampling site, 1 month prior to sampling in order to study the metabolic activity of the plastisphere by meta-OMICS and to run toxicity tests and pollutants analyses. Here, we fully described the holistic set of protocols designed for the Mission Tara Microplastics and promoted standard procedures to achieve its ambitious goals: (1) compare traits of plastic pollution among European rivers, (2) provide a baseline of the state of plastic pollution in the Anthropocene, (3) predict their evolution in the frame of the current European initiatives, (4) shed light on the toxicological effects of plastic on aquatic life, (5) model the transport of microplastics from land towards the sea, and (6) investigate the potential impact of pathogen or invasive species rafting on drifting plastics from the land to the sea through riverine systems.

Impact of in vitro phytohormone treatments on the metabolome of the leafy liverwort Radula complanata (L.) Dumort

INTRODUCTION

Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown.

OBJECTIVES

To investigate the metabolic stress-response of the leafy liverwort Radula complanata.

METHODS

Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts.

RESULTS

It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments.

CONCLUSION

Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.

Is substrate choice an overlooked variable in ecotoxicology experiments?

It is crucial to understand the effects caused by experimental parameters such as temperature, light, and food type on lab and field-based ecotoxicology experiments, as these variables, and combinations thereof, can affect results. The type of substrate used in exposure experiments, however, is generally assumed to have no effect. This may not always be correct. The metabolic changes in the freshwater crustacean, Austrochiltonia subtenuis exposed to copper, using three common substrates, gauze; toilet paper; and cellulose were investigated. Substrate alone did not affect survival, but each substrate elicited a different metabolic response and adult and juvenile amphipods had different substrate preferences. Several classes of metabolites were shown to change in response to different substrates and toxicant. These included disaccharides, monosaccharides, fatty acids, and tricarboxylic acid cycle intermediates. The results illustrate that metabolomic responses can differ in response to experimental factors that were previously thought not to be significant. In fact, our data indicate that substrate should be viewed as an experimental factor as important to control for as more well-known confounders such as temperature or food, thus challenging the current paradigm. Assuming substrate type has no effect on the experiment could potentially lead to errors in contaminant toxicity assessments. We propose that ideal good practise would be that all experimental factors should be evaluated for their potential influence on metabolomic profiles prior to contaminant response experiments being undertaken.

The role of microbial ecology in improving the performance of anaerobic digestion of sewage sludge

The use of next-generation diagnostic tools to optimise the anaerobic digestion of municipal sewage sludge has the potential to increase renewable natural gas recovery, improve the reuse of biosolid fertilisers and help operators expand circular economies globally. This review aims to provide perspectives on the role of microbial ecology in improving digester performance in wastewater treatment plants, highlighting that a systems biology approach is fundamental for monitoring mesophilic anaerobic sewage sludge in continuously stirred reactor tanks. We further highlight the potential applications arising from investigations into sludge ecology. The principal limitation for improvements in methane recoveries or in process stability of anaerobic digestion, especially after pre-treatment or during co-digestion, are ecological knowledge gaps related to the front-end metabolism (hydrolysis and fermentation). Operational problems such as stable biological foaming are a key problem, for which ecological markers are a suitable approach. However, no biomarkers exist yet to assist in monitoring and management of clade-specific foaming potentials along with other risks, such as pollutants and pathogens. Fundamental ecological principles apply to anaerobic digestion, which presents opportunities to predict and manipulate reactor functions. The path ahead for mapping ecological markers on process endpoints and risk factors of anaerobic digestion will involve numerical ecology, an expanding field that employs metrics derived from alpha, beta, phylogenetic, taxonomic, and functional diversity, as well as from phenotypes or life strategies derived from genetic potentials. In contrast to addressing operational issues (as noted above), which are effectively addressed by whole population or individual biomarkers, broad improvement and optimisation of function will require enhancement of hydrolysis and acidogenic processes. This will require a discovery-based approach, which will involve integrative research involving the proteome and metabolome. This will utilise, but overcome current limitations of DNA-centric approaches, and likely have broad application outside the specific field of anaerobic digestion.

Exposure to Environmentally Relevant Levels of PFAS Causes Metabolic Changes in the Freshwater Amphipod Austrochiltonia subtenuis

Per and polyfluoroalkyl substances (PFAS) are of concern to environmental regulators due to their widespread occurrence, persistence and reported toxicity. However, little data exist on the effects of PFAS at environmentally relevant concentrations. The development of molecular markers for PFAS exposure would therefore be useful to better understand the environmental risks of these compounds. In this study, we assessed if such markers could be developed using Gas Chromatography–Mass Spectrometry-based metabolomics. We exposed the freshwater amphipod Austrochiltonia subtenuis to a range of environmentally relevant concentrations of perfluoro-octane sulfonic acid (PFOS), hexafluoropropylene oxide dimer acid (GenX) and perfluorohexanesulphonic acid (PFHxS) for 7 days at five concentrations. A metabolic response was detected in all concentrations and treatments even though the survival rates only differed significantly at the highest exposure levels. The metabolic response differed between compounds but all three PFAS induced changes in the levels of amino acids, fatty acids, and cholesterol, in line with the literature. PFOS was found to bioaccumulate. Both GenX and PFHxS were eliminated from the amphipods, but PFHxS was eliminated at a slower rate than GenX. This information improves our understanding of the sublethal effects of PFAS as well as their environmental fate and behaviour.

Ecological and metabolomic responses of plants to deer exclosure in a suburban forest

Trees and shrubs in suburban forests can be subject to chronic herbivory from abundant white-tailed deer, influencing survival, growth, secondary metabolites, and ecological success in the community. We investigated how deer affect the size, cover, and metabolomes of four species in the understory of a suburban forest in central New Jersey, USA: the woody shrubs Euonymus alatus and Lindera benzoin, the tree Nyssa sylvatica, and the semi-woody shrub Rosa multiflora. For each species, we compared plants in 38 16 m2 plots with or without deer exclosure, measuring proportion cover and mean height after 6.5 years of fencing. We scored each species in all plots for deer browsing over 8 years and assessed selection by deer among the species. We did untargeted metabolomics by sampling leaves from three plants of each species in an equal number of fenced and unfenced plots, conducting chloroform-methanol extractions followed by LC-MS/MS, and conducting statistical analysis on MetaboAnalyst. The proportion of a species browsed ranged from 0.24 to 0.35. Nyssa sylvatica appeared most selected by and susceptible to deer; in unfenced plots, both its cover and mean height were significantly lower. Only cover or height was lower for E. alatus and L. benzoin in unfenced plots, while R. multiflora height was greater. The metabolomic analysis identified 2333 metabolites, which clustered by species but not fencing treatment. However, targeted analysis of the top metabolites grouped by fencing for all samples and for each species alone and was especially clear in N. sylvatica, which also grouped by fencing using all metabolites. The most significant metabolites that were upregulated in fenced plants include some involved in defense-related metabolic pathways, e.g., monoterpenoid biosynthesis. In overbrowsed suburban forests, variation of deer impact on species' ecological success, potentially mediated by metabolome-wide chemical responses to deer, may contribute to changes in community structure.

A review of omics-based PFAS exposure studies reveals common biochemical response pathways

Per and Polyfluoroalkyl Substances (PFAS) are a diverse group of man-made chemicals with a range of industrial applications and which are widespread in the environment. They are structurally diverse but comprise a common chemical feature of at least one (though usually more) perfluorocarbon moiety (-C_nF_2n-) attached to a functional group such as a carboxylic or sulphonic acid. The strength of the Carbon-Fluorine bond means the compounds do not break down easily and can thus bioaccumulate. PFAS are of high concern to regulators and the public due to their potential toxicity and high persistence. At high exposure levels, PFAS have been implicated in a range of harmful effects on human and environmental health, particularly problems in/with development, cholesterol and endocrine disruption, immune system function, and oncogenesis. However, most environmental toxicology studies use far higher levels of PFAS than are generally found in the environment. Additionally, since the type of exposure, the PFAS used, and the organisms tested all vary between studies, so do the results. Traditional ecotoxicology studies may thus not identify PFAS effects at environmentally relevant exposures. Here we conduct a review of omics-based PFAS exposure studies using laboratory ecotoxicological methodologies and environmentally relevant exposure levels and show that common biochemical response pathways are identified in multiple studies. A major pathway identified was the pentose phosphate shunt pathway. Such molecular markers of sublethal PFAS exposure will greatly benefit accurate and effective risk assessments to ensure that new PFAS regulations can consider the full effects of PFAS exposure on environmental and human health receptors.

Pollution gradient leads to local adaptation and small-scale spatial variability of communities and functions in an urban marine environment

Urbanization of coastal habitats, of which harbors and marinas are the paragon, has led to various ecological paradigms about their functioning. Harbor infrastructures offer new hard substrata that are colonized by a wide variety of organisms (biofouling) including many introduced species. These structures also modify hydrodynamism and contaminant dispersal, leading to strong disturbance gradients within them. Differences in sessile community structure have previously been correlated to these gradients at small spatial scale (<100 m). Local adaptation might be involved to explain such results, but as correlation is not causation, the present study aims to understand the causal link between the environmental gradients and community structure through a reciprocal transplant experiment among three sites of a marina (inner, middle, entrance). Our results highlighted strong small-scale spatial variations of contaminants (trace metals, PCB, pesticides, and PAH) in sediments and animal samples which have been causally linked to changes in community composition after transplant. But historical contingency and colonization succession also play an important role. Our results provided strong evidence for local adaptation since community structure, respiration, and pollutant uptake in Bugula neritina, as well as the metabolomes of B. neritina and Ciona intestinalis were impacted by the transplant with a disadvantage for individuals transplanted from the entrance to the inner location. The here observed results may thus indicate that the disturbance gradient in marinas might constitute a staple for selecting pollutant-resistant species and populations, causing local adaptation. This highlights the importance of conducting further studies into small scale local adaptation.

Fish metabolome from sub-urban lakes of the Paris area (France) and potential influence of noxious metabolites produced by cyanobacteria

The recent democratization of high-throughput molecular phenotyping allows the rapid expansion of promising untargeted multi-dimensional approaches (e.g. epigenomics, transcriptomics, proteomics, and/or metabolomics). Indeed, these emerging omics tools, processed for ecologically relevant species, may present innovative perspectives for environmental assessments, that could provide early warning of eco(toxico)logical impairments. In a previous pilot study (Sotton et al., Chemosphere 2019), we explore by ¹H NMR the bio-indicative potential of metabolomics analyses on the liver of 2 sentinel fish species (Perca fluviatilis and Lepomis gibbosus) collected in 8 water bodies of the peri-urban Paris' area (France). In the present study, we further investigate on the same samples the high potential of high-throughput UHPLC-HRMS/MS analyses. We show that the LC-MS metabolome investigation allows a clear separation of individuals according to the species, but also according to their respective sampling lakes. Interestingly, similar variations of Perca and Lepomis metabolomes occur locally indicating that site-specific environmental constraints drive the metabolome variations which seem to be influenced by the production of noxious molecules by cyanobacterial blooms in certain lakes. Thus, the development of such reliable environmental metabolomics approaches appears to constitute an innovative bio-indicative tool for the assessment of ecological stress, such as toxigenic cyanobacterial blooms, and aim at being further follow up.

Microbial community functioning during plant litter decomposition

Microbial life in soil is fueled by dissolved organic matter (DOM) that leaches from the litter layer. It is well known that decomposer communities adapt to the available litter source, but it remains unclear if they functionally compete or synergistically address different litter types. Therefore, we decomposed beech, oak, pine and grass litter from two geologically distinct sites in a lab-scale decomposition experiment. We performed a correlative network analysis on the results of direct infusion HR-MS DOM analysis and cross-validated functional predictions from 16S rRNA gene amplicon sequencing and with DOM and metaproteomic analyses. Here we show that many functions are redundantly distributed within decomposer communities and that their relative expression is rapidly optimized to address litter-specific properties. However, community changes are likely forced by antagonistic mechanisms as we identified several natural antibiotics in DOM. As a consequence, the decomposer community is specializing towards the litter source and the state of decomposition (community divergence) but showing similar litter metabolomes (metabolome convergence). Our multi-omics-based results highlight that DOM not only fuels microbial life, but it additionally holds meta-metabolomic information on the functioning of ecosystems.

Gas chromatography-mass spectrometry (GC-MS) profiling reveals substantial metabolome diversity in seabuckthorn (Hippophae rhamnoides L.) berries originating from different geographical regions in the Indian Himalayas

INTRODUCTION

Seabuckthorn (Hippophae rhamnoides L.) is a high-altitude plant with immense medicinal, nutritional, and therapeutic value. Earlier studies have documented the presence of various useful bioactive substances in this species; however, comprehensive metabolome profiling of seabuckthorn berries originating from different regions of the Indian Himalayas has not been undertaken.

OBJECTIVE

Metabolomic profiling of seabuckthorn berries originating from different geographical sites in the Himachal Pradesh and Jammu & Kashmir regions of the Indian Himalayas was performed by using gas chromatography-mass spectrometry.

MATERIALS AND METHODS

The GC-MS metabolome profiles of seabuckthorn berries collected from different sites (altitude 1,400-4,270 m; average temperature 8°C-27°C) were subjected to multivariate analysis following principal component analysis and hierarchical clustering analysis.

RESULTS

The GC-MS results showed substantial variability for berry metabolites, including fatty acids, alkyl ethers, and alkyl esters. Fatty acids and their esters were mainly responsible for the variation in the berry metabolome. The metabolite expression profile heat map revealed two distinct groups of seabuckthorn berries originating from Himachal Pradesh (Lahaul and Spiti) and Jammu & Kashmir (Leh, Nubra, and Kargil), the former showing higher expression of metabolites. Interestingly, a strong negative association existed between altitude and the amounts of metabolites such as amides, alkyl esters, alcohols, sugars, and sugar esters. In contrast, temperature showed a strong positive association with ketone and alkyl ether levels.

CONCLUSION

GC-MS profiling provides important phytochemical indicators to distinguish between seabuckthorn berries from different geographical sites. Our metabolome profiling analysis generated valuable information that will be useful in the formulation of various seabuckthorn products, benefiting farmers and industries.

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.

Crayfish tissue metabolomes effectively distinguish impacts of wastewater and agriculture in aquatic ecosystems

Environmental metabolomics has been proposed as a tool for biomonitoring because organisms regulate production or consumption of metabolites in response to environmental conditions. We evaluated the efficacy of the metabolome of three tissues (hepatopancreas, gill, and tail muscle) from the northern crayfish (Faxonius virilis) to detect and differentiate between impacts of human activities (i.e., reference, municipal wastewater, and agriculture). We conducted a reciprocal transfer study exposing crayfish for 1 or 2 weeks in three streams with different amounts and types of human activities in southern Manitoba, Canada. Tissue samples were analyzed using nuclear magnetic resonance spectroscopy to generate a metabolic profile. Findings indicated the gill tissue metabolome best detected and differentiated between human activities. In particular, the gill metabolome was able to rapidly integrate abrupt changes in environmental conditions associated with municipal wastewater activity. In contrast, the tail metabolome best differentiated between crayfish collected at the reference site from those collected at the two impacted sites. Metabolites extracted from hepatopancreas tissue showed limited and inconsistent detection of among site differences. Based on our findings, we conclude that the metabolome of the northern crayfish can be an effective biomonitoring tool, but monitoring purpose will dictate tissue selection. Indeed, we recommend the gill metabolome be used for short-term assays aimed at detecting acute effects, whereas the tail be applied for survey monitoring aimed at detecting deviations in ecological condition at test sites from reference site conditions.

Correlated metabolic and elemental variations between the leaves and seeds of oak trees at contrasting geologically derived phosphorus sites

The leaves and seeds of plants frequently function as the source and sink organs for distinct metabolites, which can interactively vary in response to adverse site conditions. Subtropical soils are typically characterized as having deficient phosphorus (P), calcium (Ca), and magnesium (Mg), with enriched aluminum (Al) and iron (Fe), while Al and manganese (Mn) are toxic at low pH. It remains largely unknown how leaf- and seed-sourced metabolites are synergistically linked to adapt to P-variable soils for trees in subtropical areas. Here we quantified the metabolic and elemental profiling in the mature leaves and immature seeds of Quercus variabilis at contrasting geologically-derived phosphorus sites in subtropical China. The results revealed that carbon (C) and nitrogen (N) based metabolites (primarily sugars and organic acids), as well as enzyme- and protein/nucleic acid-related elements (N, P, Mg, and Mn) played important roles toward characterizing the profiling of metabolites and ionomes in leaves and seeds at two site types, respectively. These metabolites (sugars, amino acids, and fatty acids) and elements (N, P, Mg, and Mn) of seeds were closely related to the sugars, organic acids, and elements (N, P, Mg, and Mn) of leaves at the two site types. For the most part, the content of N and P in the soil affected the accumulation of materials (such as, starchs and proteins) in seeds, as well as N and P assimilation in leaves, by influencing C- and N-containing metabolites in leaves. These results suggested that correlated disparities of C- and N-containing metabolites, along with enzyme- and protein/nucleic acid-related elements in both leaves and seeds played important roles in plants to facilitate their adaptation to nutrient-variable sites in subtropical zones.

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.

Using metabolomics to assess the sub-lethal effects of zinc and boscalid on an estuarine polychaete worm over time

INTRODUCTION

Zinc is a heavy metal commonly detected in urban estuaries around Australia. Boscalid is a fungicide found in estuaries, both in water and sediment, it enters the system predominantly through agricultural run-off. Zinc is persistent while boscalid breaks down, with a half-life of 108 days. Both contaminants are widely distributed and their effects on ecosystems are not well understood.

OBJECTIVES

The aim of this study was to determine the metabolite changes in Simplisetia aequisetis (an estuarine polychaete) following laboratory exposure to a sub-lethal concentration of zinc or boscalid over a 2-week period.

METHODS

Individuals were collected at six time points over a 2-week period. Whole polychaete metabolites were extracted and quantified using a multi-platform approach. Polar metabolites were detected using a semi-targeted GC-MS analysis and amine containing compounds were analysed using a targeted LC-MS analysis. Total lipid energy content was also analysed for Simplisetia aequisetis.

RESULTS

The pathways that responded to zinc and boscalid exposure were alanine, aspartate and glutamate metabolism (AAG); glycine, serine and threonine metabolism (GST) and metabolites associated with the tricarboxylic acid cycle (TCA). Results showed that changes in total abundance of some metabolites could be detected as early as 24-h exposure. Changes were detected in the metabolites before commonly used total lipid energy assays identified effects.

CONCLUSION

A multi-platform approach provided a holistic overview of the metabolomic response to contaminants in polychaetes. This approach shows promise to be used in biomonitoring programs to provide early diagnostic indicators of contamination and exposure.

The adaptation strategies of Herpetospermum pedunculosum (Ser.) Baill at altitude gradient of the Tibetan plateau by physiological and metabolomic methods

BACKGROUND

Herpetospermum pedunculosum (Ser.) Baill is annual scandent herbs. They are used in the treatment of piles, inflammation of the stomach and the intestines. It can survive the extreme environment of the Tibetan Plateau (TP). However, the underlying mechanisms of this adaptation to H. pedunculosum from TP remain unclear. Here, we combined physiological and metabolomics methods to analyze H. pedunculosum response to altitude gradient differences.

RESULTS

At high altitude, increases in the activities of Ascorbate peroxidase (APX), Glutathione reductase (GR), Dehydroascorbate reductase (DHAR), Monodehydroascorbate reductase (MDHAR), Superoxide dismutase (SOD) have been observed in leaves. Total Glutathion content, total Ascorbate content and the ASA (ascorbic acid)/docosahexaenoic acid (DHA) ration were highly elevated from low altitude to high altitude. In addition, high altitude induces decrease of the Anthocyanidin content (ANTH) and increase of abscisic acid content (ABA). The GC-MS analyses identified of 50 metabolites from leaves of H. pedunculosum. In addition, a metabolic network was constructed based on metabolomic datasets using a weighted correlation network analysis (WGCNA) approach. The network analysis uncovered 4 distinguished metabolic modules highly associated with I, II, III and IV respectively. Furthermore, the analysis successfully classified 50 samples into seven groups: carbohydrates, amino acids, organic acids, lipid components, polyamine, secondary metabolism and others.

CONCLUSIONS

In the present study, the content of parts of amino acid components increased in samples collected at higher altitudes, and most of metabolites, including carbohydrates and organic acids were assigned to the carbon metabolic pathway comprising reductive pentose phosphate pathway, glycolysis and TCA cycle, indicating the direct relationship between adaptability and the carbon metabolic pathway and amino acids in H. pedunculosum response to high altitude. The results of this study laid the foundation of the molecular mechanism on H. pedunculosum from high altitude.

Resource heterogeneity structures aquatic bacterial communities

Microorganisms are strongly influenced by the bottom-up effects of resource supply. While many species respond to fluctuations in the concentration of resources, microbial diversity may also be affected by the heterogeneity of the resource pool, which often reflects a mixture of distinct molecules. To test this hypothesis, we examined resource-diversity relationships for bacterioplankton in a set of north temperate lakes that varied in their concentration and composition of dissolved organic matter (DOM), which is an important resource for heterotrophic bacteria. Using 16S rRNA transcript sequencing and ecosystem metabolomics, we documented strong relationships between bacterial alpha-diversity (richness and evenness) and the bulk concentration and the number of molecules in the DOM pool. Similarly, bacterial community beta-diversity was related to both DOM concentration and composition. However, in some lakes the relative abundance of resource generalists, which was inversely related to the DOM concentration, may have reduced the effect of DOM heterogeneity on community composition. Together, our results demonstrate the potential metabolic interactions between bacteria and organic matter and suggest that changes in organic matter composition may alter the structure and function of bacterial communities.

Recent developments in metabolomics-based research in understanding transgenic grass metabolism

BACKGROUND

Transgenic herbicide-resistant (HR) turfgrass together with its associated, broad spectrum herbicides promise cheap, selective and efficient weed control by excluding infested weeds resulting in turf lawn with high uniformity and aesthetic value. The concept of this "weeding program" initiated from modern biotechnology has been widely implemented in several principal crops including maize, soybean, canola and cotton as early as the 1990s. Transgenic HR turfgrass classified as a genetically modified organism (GMO) has undoubtedly caused public concern with respect to its biosafety and legalities similar to well-established HR crops. Nevertheless, applying metabolomics-based approaches which focuses on the identification of the global metabolic state of a biological system in response to either internal or external stimuli can also provide a comprehensive characterization of transgenic grass metabolism and its involvement in biosecurity and public perception.

AIM OF REVIEW

This review summaries the recent applications of metabolomics applied to HR crops to predict the molecular and physiological phenotypes of HR turfgrass species, glyphosate-resistant Kentucky bluegrass (Poa pratensis L.) and glufosinate-resistant creeping bentgrass (Agrotis stonifera L.). Additionally, this review also presents background knowledge with respect to the application of metabolomics, transformation of HR crops and its biosafety concerns, turfgrass botanical knowledge and its economic and aesthetic value.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is to demonstrate the molecular and physiological phenotypes of HR turfgrass based on several lines of evidence primarily derived from metabolomics data applied to HR crops to identify alterations on HR turfgrass metabolism as a result of genetic modification that confers resistant traits.

Metabolome responses of the sea cucumber Apostichopus japonicus to multiple environmental stresses: Heat and hypoxia

Economically important marine organisms face severe environmental challenges, such as high temperature and low dissolved oxygen, from global climate change. Adverse environmental factors impact the survival and growth of economically important marine organisms, thereby negatively influencing the aquaculture industry. However, little is known about the responses of sea cucumbers to combined environmental co-stressors till now. In this study, ultra-performance liquid chromatography (UPLC) was utilized to obtain metabolic profiles of sea cucumbers. Changes in the concentrations of 84, 68, and 417 metabolites related to the responses of sea cucumbers to heat (26 °C), hypoxia (2 mg/L) and the combined stress, respectively, were observed and analyzed. Representative biomarkers were discussed in detail, including deltaline, fusarin C, halichondrin B and rapanone. The concentration of metabolites involved in the regulation of energy metabolism, including amino acid, carbohydrate and lipid metabolism were significantly changed, and the tricarboxylic acid (TCA)-cycle was significantly altered under heat plus hypoxia. We interpreted these changes partly as an adaptation mechanism in response to environmental stress. Based on the decreased accumulation of glutamine, we hypothesized that heat stress is the main factor that interferes with the process of glutamic acid-glutamine metabolism. The present study showed that combined environmental stressors have a more extensive impact on the metabolites of the respiratory tree in sea cucumbers than single stress. These results would facilitate further development of the sea cucumber as an echinoderm model to study mechanisms of response to adverse environments, as well as to help advance knowledge of the adaptation of marine organisms to global climate change.

Seasonal variation of secondary metabolites in nine different bryophytes

Bryophytes occur in almost all land ecosystems and contribute to global biogeochemical cycles, ecosystem functioning, and influence vegetation dynamics. As growth and biochemistry of bryophytes are strongly dependent on the season, we analyzed metabolic variation across seasons with regard to ecological characteristics and phylogeny. Using bioinformatics methods, we present an integrative and reproducible approach to connect ecology with biochemistry. Nine different bryophyte species were collected in three composite samples in four seasons. Untargeted liquid chromatography coupled with mass spectrometry (LC/MS) was performed to obtain metabolite profiles. Redundancy analysis, Pearson's correlation, Shannon diversity, and hierarchical clustering were used to determine relationships among species, seasons, ecological characteristics, and hierarchical clustering. Metabolite profiles of Marchantia polymorpha and Fissidens taxifolius which are species with ruderal life strategy (R-selected) showed low seasonal variability, while the profiles of the pleurocarpous mosses and Grimmia pulvinata which have characteristics of a competitive strategy (C-selected) were more variable. Polytrichum strictum and Plagiomnium undulatum had intermediary life strategies. Our study revealed strong species-specific differences in metabolite profiles between the seasons. Life strategies, growth forms, and indicator values for light and soil were among the most important ecological predictors. We demonstrate that untargeted Eco-Metabolomics provide useful biochemical insight that improves our understanding of fundamental ecological strategies.

Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes

In Eco-Metabolomics interactions are studied of non-model organisms in their natural environment and relations are made between biochemistry and ecological function. Current challenges when processing such metabolomics data involve complex experiment designs which are often carried out in large field campaigns involving multiple study factors, peak detection parameter settings, the high variation of metabolite profiles and the analysis of non-model species with scarcely characterised metabolomes. Here, we present a dataset generated from 108 samples of nine bryophyte species obtained in four seasons using an untargeted liquid chromatography coupled with mass spectrometry acquisition method (LC/MS). Using this dataset we address the current challenges when processing Eco-Metabolomics data. Here, we also present a reproducible and reusable computational workflow implemented in Galaxy focusing on standard formats, data import, technical validation, feature detection, diversity analysis and multivariate statistics. We expect that the representative dataset and the reusable processing pipeline will facilitate future studies in the research field of Eco-Metabolomics.

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.

Quality markers of animal medicinal materials: Correlative analysis of musk reveals distinct metabolic changes induced by multiple factors

BACKGROUND

Common farming environmental elements, such as longitude, latitude, and altitude, and physiological conditions, such as age and body weight, are thought to influence medicinal animal homeostasis and material quality by altering endocrine functions for primary and secondary metabolite formation. However, the currently available methods for evaluating complex components of traditional Chinese animal medicines have insufficient sensitivity and specificity.

PURPOSE

Characterizing the primary/secondary metabolomes of medicinal animals is essential for understanding their material basis, controlling product quality, and reflecting on distribution interactions. Therefore, this study aimed to screen ecological- and physiological-related metabolites in captive Moschus berezovskii throughout the collection period based on the quality marker (Q-marker) concept.

STUDY DESIGN AND METHODS

Fifty-one musk deer samples from 12 different distribution farms ranging in age from 2 to 11 years were enrolled. Differentially expressed musk metabolites were assessed via chromatography-tandem mass spectrometry technologies. A metabolome that mapped connections among these factors was established using chemometric and topological calculations.

RESULTS

Statistical analysis revealed that muscone, cis-9-hexadecenal, antioxidant 2264, prasterone-3-sulfate, androstan-17-one, and 1,2-benzenedicarboxylic acid showed significantly altered expression. Partial least squares (PLS) regression analysis of qualified data for these 6 secondary metabolites (active components) demonstrated that age is the most important factor underlying the varying levels of muscone, androstan-17-one and 1,2-benzenedicarboxylic acid. Furthermore, weight was the most important factor for cis-9-hexadecenal, longitude was important for antioxidant 2264, latitude was important for prasterone-3-sulfate, and altitude was important for antioxidant 2264, androstan-17-one and 1,2-benzenedicarboxylic. Metabolite analysis within the MetaboAnalyst (MetPA) suite showed that 18 candidate biomarker metabolites were screened, including allantoin, glycine, serine, creatine, alanine, taurine, lactate, 2-oxoglutarate (2-OG), fumarate, proline, xanthine, cytosine, carnitine, arginine, threonine, aspartate, and urea. Metabolic network analysis showed 4 important pathways that were involved: arginine and proline metabolism, the urea cycle, aspartate metabolism, and glycine, serine and threonine metabolism.

CONCLUSION

Using this combined metabolomic and chemometric approach, this study was successful in screening Q-markers for musk quality control and provided new insights into correlations among "ecological & physiological factors→Q-markers→metabolites", which potentially provides crucial information for musk breeding and material quality control.

Current Challenges in Plant Eco-Metabolomics

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant⁻organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology.

Study of Methanol Extracts from Different Parts of Peganum harmala L. Using 1H-NMR Plant Metabolomics

A nuclear magnetic resonance- (NMR-) based metabolomics method was used to identify differential metabolites of methanol extracts obtained from six parts of Peganum harmala L. (P. harmala), namely, the root, stem, leaf, flower, testa, and seed. Two multivariate statistical analysis methods, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), were combined to clearly distinguish among the P. harmala samples from the six different parts. Eleven differential components were screened by the PLS-DA loading plot, and the relative contents were calculated by univariate analysis of variance. Chemometric results showed significant differences in the metabolites of the different parts of P. harmala. The seeds contained large amounts of harmaline, harmine, and vasicine compared to other organs. The acetic acid, proline, lysine, and sucrose contents of the roots were significantly higher than those of the other parts. In the testa, the vasicine, asparagine, choline, and 4-hydroxyisoleucine contents were clearly dominant. The obtained data revealed the distribution characteristics of the metabolomes of the different P. harmala parts and provided fundamental knowledge for the rational development of its medicinal parts.

Eco-Metabolomics and Metabolic Modeling: Making the Leap From Model Systems in the Lab to Native Populations in the Field

Experimental high-throughput analysis of molecular networks is a central approach to characterize the adaptation of plant metabolism to the environment. However, recent studies have demonstrated that it is hardly possible to predict in situ metabolic phenotypes from experiments under controlled conditions, such as growth chambers or greenhouses. This is particularly due to the high molecular variance of in situ samples induced by environmental fluctuations. An approach of functional metabolome interpretation of field samples would be desirable in order to be able to identify and trace back the impact of environmental changes on plant metabolism. To test the applicability of metabolomics studies for a characterization of plant populations in the field, we have identified and analyzed in situ samples of nearby grown natural populations of Arabidopsis thaliana in Austria. A. thaliana is the primary molecular biological model system in plant biology with one of the best functionally annotated genomes representing a reference system for all other plant genome projects. The genomes of these novel natural populations were sequenced and phylogenetically compared to a comprehensive genome database of A. thaliana ecotypes. Experimental results on primary and secondary metabolite profiling and genotypic variation were functionally integrated by a data mining strategy, which combines statistical output of metabolomics data with genome-derived biochemical pathway reconstruction and metabolic modeling. Correlations of biochemical model predictions and population-specific genetic variation indicated varying strategies of metabolic regulation on a population level which enabled the direct comparison, differentiation, and prediction of metabolic adaptation of the same species to different habitats. These differences were most pronounced at organic and amino acid metabolism as well as at the interface of primary and secondary metabolism and allowed for the direct classification of population-specific metabolic phenotypes within geographically contiguous sampling sites.

MetaGOmics: A Web-Based Tool for Peptide-Centric Functional and Taxonomic Analysis of Metaproteomics Data

Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed "MetaGOmics") that automates the quantitative functional (using Gene Ontology) and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis-including comparing the functional makeup between samples. MetaGOmics is freely available at https://www.yeastrc.org/metagomics/.

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.

Effect of the environment on the secondary metabolic profile of Tithonia diversifolia: a model for environmental metabolomics of plants

Tithonia diversifolia is an invasive weed commonly found in tropical ecosystems. In this work, we investigate the influence of different abiotic environmental factors on the plant's metabolite profile by multivariate statistical analyses of spectral data deduced by UHPLC-DAD-ESI-HRMS and NMR methods. Different plant part samples of T. diversifolia which included leaves, stems, roots, and inflorescences were collected from two Brazilian states throughout a 24-month period, along with the corresponding monthly environmental data. A metabolomic approach employing concatenated LC-MS and NMR data was utilised for the first time to study the relationships between environment and plant metabolism. A seasonal pattern was observed for the occurrence of metabolites that included sugars, sesquiterpenes lactones and phenolics in the leaf and stem parts, which can be correlated to the amount of rainfall and changes in temperature. The distribution of the metabolites in the inflorescence and root parts were mainly affected by variation of some soil nutrients such as Ca, Mg, P, K and Cu. We highlight the environment-metabolism relationship for T. diversifolia and the combined analytical approach to obtain reliable data that contributed to a holistic understanding of the influence of abiotic environmental factors on the production of metabolites in various plant parts.

Extending the Concept of Diversity Partitioning to Characterize Phenotypic Complexity

Most components of an organism's phenotype can be viewed as the expression of multiple traits. Many of these traits operate as complexes, where multiple subsidiary parts function and evolve together. As trait complexity increases, so does the challenge of describing complexity in intuitive, biologically meaningful ways. Traditional multivariate analyses ignore the phenomenon of individual complexity and provide relatively abstract representations of variation among individuals. We suggest adopting well-known diversity indices from community ecology to describe phenotypic complexity as the diversity of distinct subsidiary components of a trait. Using a hierarchical framework, we illustrate how total trait diversity can be partitioned into within-individual complexity (α diversity) and between-individual components (β diversity). This approach complements traditional multivariate analyses. The key innovations are (i) addition of individual complexity within the same framework as between-individual variation and (ii) a group-wise partitioning approach that complements traditional level-wise partitioning of diversity. The complexity-as-diversity approach has potential application in many fields, including physiological ecology, ecological and community genomics, and transcriptomics. We demonstrate the utility of this complexity-as-diversity approach with examples from chemical and microbial ecology. The examples illustrate biologically significant differences in complexity and diversity that standard analyses would not reveal.

A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc

Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography-mass spectrometry (GC-MS) analysis and a targeted liquid chromatography-mass spectrometry (LC-MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary metabolomics analytical approaches was particularly useful for understanding the effects of zinc exposure and importantly, identified a suite of candidate biomarkers of zinc exposure useful for the development of biomonitoring programs.

Entometabolomics: applications of modern analytical techniques to insect studies

Metabolomic analyses can reveal associations between an organism's metabolome and further aspects of its phenotypic state, an attractive prospect for many life-sciences researchers. The metabolomic approach has been employed in some, but not many, insect study systems, starting in 1990 with the evaluation of the metabolic effects of parasitism on moth larvae. Metabolomics has now been applied to a variety of aspects of insect biology, including behaviour, infection, temperature stress responses, CO 2 sedation, and bacteria-insect symbiosis. From a technical and reporting standpoint, these studies have adopted a range of approaches utilising established experimental methodologies. Here, we review current literature and evaluate the metabolomic approaches typically utilised by entomologists. We suggest that improvements can be made in several areas, including sampling procedures, the reduction in sampling and equipment variation, the use of sample extracts, statistical analyses, confirmation, and metabolite identification. Overall, it is clear that metabolomics can identify correlations between phenotypic states and underlying cellular metabolism that previous, more targeted, approaches are incapable of measuring. The unique combination of untargeted global analyses with high-resolution quantitative analyses results in a tool with great potential for future entomological investigations.

The use of metabolomics in the study of metals in biological systems

Metabolomics and systems biology/toxicology can elucidate novel pathways and mechanistic networks of metals and metalloids in biological systems, as well as providing useful biomarkers of the metal status of organisms.

(1)H NMR metabolomics reveals contrasting response by male and female mussels exposed to reduced seawater pH, increased temperature, and a pathogen

Human activities are fundamentally altering the chemistry of the world's oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, (1)H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.

Metabolomic analysis of soil communities can be used for pollution assessment

Metabolic profiling can be used to assess the changes in biochemical profiles of soil communities living in contaminated sites. The term "community metabolomics" is proposed for the application of metabolomics techniques to the study of the entire community of a soil sample. The authors anticipate the present study to be a starting point for the use of this technique to assess how communities respond to factors such as pollution and climate change.