Metabolomics as a valid analytical technique in environmental exposure research: application and progress

Microalgal multiomics-based approaches in bioremediation of hazardous contaminants

The enhanced industrial growth and higher living standards owing to the incessant population growth have caused heightened production of various chemicals in different manufacturing sectors globally, resulting in pollution of aquatic systems and soil with hazardous chemical contaminants. The bioremediation of such hazardous pollutants through microalgal processes is a viable and sustainable approach. Accomplishing microalgal-based bioremediation of polluted wastewater requires a comprehensive understanding of microalgal metabolic and physiological dynamics. Microalgae-bacterial consortia have emerged as a sustainable agent for synergistic bioremediation and metabolite production. Effective bioremediation involves proper consortium functioning and dynamics. The present review highlights the mechanistic processes employed through microalgae in reducing contaminants present in wastewater. It discusses the multi-omics approaches and their advantages in understanding the biological processes, monitoring, and dynamics among the partners in consortium through metagenomics. Transcriptomics, proteomics, and metabolomics enable an understanding of microalgal cell response toward the contaminants in the wastewater. Finally, the challenges and future research endeavors are summarised to provide an outlook on microalgae-based bioremediation.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

Mercury species induce metabolic reprogramming in freshwater diatom Cyclotella meneghiniana

Mercury is a hazardous pollutant of global concern. While advances have been made in identifying the detrimental effects caused by Hg species in phytoplankton, knowledge gaps remain regarding the metabolomic perturbations induced by inorganic mercury (Hg(II)) and monomethylmercury (MeHg) in these organisms. Diatoms represent a major phytoplankton group essential in various global biogeochemical cycles. The current study combined targeted metabolomics, bioaccumulation, and physiological response assays to investigate metabolic perturbations in diatom Cyclotella meneghiniana exposed for 2 h to nanomolar concentrations of Hg(II) and MeHg. Our findings highlight that such exposures induce reprogramming of the metabolism of amino acids, nucleotides, fatty acids, carboxylic acids and antioxidants. These alterations were primarily mercury-species dependent. MeHg exposure induced more pronounced reprogramming of the metabolism of diatoms than Hg(II), which led to less pronounced effects on ROS generation, membrane permeability and chlorophyll concentrations. Hg(II) treatments presented distinct physiological responses, with more robust metabolic perturbations at higher exposures. The present study provides first-time insights into the main metabolic alterations in diatom C. meneghiniana during short-term exposure to Hg species, deepening our understanding of the molecular basis of these perturbations.

Transcriptome analysis reveal the effect of freshwater sediments containing 2,3,7,8-tetrachlorodibenzo-p-dioxin on the Macrobrachium rosenbergii hepatopancreas, intestine, and muscle

This research evaluated the hepatopancreas, intestine, and muscle transcriptome alternation of Macrobrachium rosenbergii, and to confirm the relative glycerophospholipid, cytochrome P450 system, and fatty acid metabolism gene expression in sediments containing 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) of 60 ng/sediment (g) and 700 ng/sediment (g) for 90 days of culture. Transcriptome analysis revealed that the TCDD sediment affected the hepatopancreatic metabolism of xenobiotics in M. rosenbergii via the cytochrome P450 system, drug metabolism-other enzymes, drug metabolism-cytochrome P450, chemical carcinogenesis, and lysosome function. Intestinal analysis also showed a similar phenomenon, but this finding was not observed in the muscle tissue. qPCR analysis indicated that the expression levels of APTG4, LPGAT1, ACHE, GPX4, ECHS1, ATP5B, FABP, and ACC in the hepatopancreatic and intestinal tissues decreased, but those in the muscle tissues did not. In summary, TCDD sediment induced tissue metabolism, especially in the hepatopancreas and intestine. TCDD sediment mainly affected the digestive enzyme gene expression with concentration. These results indicated that the presence of TCDD in the sediment played a major role in the hepatopancreatic and intestinal metabolism system of M. rosenbergii.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Characterization of chemical constituents and metabolites in vivo and in vitro after oral administration of Wuteng tablets in rats by UHPLC-Q/TOF-MS

Waste medicinal plants are widely used in drug production. With the increasing demand for botanical drugs, there is an urgent need to identify new and effective drugs and improve the utilization of medicinal plant resources. Wuteng tablets (WTP) are extracted from the stem of Schisandra chinensis and have a good therapeutic effect on Alzheimer's disease. In this study, a holistic identification strategy based on UHPLC-Q/TOF-MS was developed for the first time to investigate the metabolites and metabolic pathways involved in the in vitro metabolism and liver microsomal incubation and in the in vivo metabolic system of rats after WTP administration. After the oral administration of WTP, 21 metabolites were identified in the serum and 25 metabolites were identified in the urine, of which six were new metabolites; 33 metabolites were inferred from the microsomal metabolites in vitro. The metabolic pathways related to WTP mainly involve demethylation, hydroxylation, dehydroxylation and dehydrogenation. In this study, the metabolites and metabolic pathways of WTP were elucidated via UHPLC-Q/TOF-MS, which provided a basis for an in-depth study of the pharmacodynamic and pharmacotoxicological effects of WTP.

The Rehabilitation Potential of Neurostimulation for Mild Traumatic Brain Injury in Animal and Human Studies

Neurostimulation carries high therapeutic potential, accompanied by an excellent safety profile. In this review, we argue that an arena in which these tools could provide breakthrough benefits is traumatic brain injury (TBI). TBI is a major health problem worldwide, with the majority of cases identified as mild TBI (mTBI). MTBI is of concern because it is a modifiable risk factor for dementia. A major challenge in studying mTBI is its inherent heterogeneity across a large feature space (e.g., etiology, age of injury, sex, treatment, initial health status, etc.). Parallel lines of research in human and rodent mTBI can be collated to take advantage of the full suite of neuroscience tools, from neuroimaging (electroencephalography: EEG; functional magnetic resonance imaging: fMRI; diffusion tensor imaging: DTI) to biochemical assays. Despite these attractive components and the need for effective treatments, there are at least two major challenges to implementation. First, there is insufficient understanding of how neurostimulation alters neural mechanisms. Second, there is insufficient understanding of how mTBI alters neural function. The goal of this review is to assemble interrelated but disparate areas of research to identify important gaps in knowledge impeding the implementation of neurostimulation.

Miniaturized method for the quantification of persistent organic pollutants and their metabolites in HepG2 cells: assessment of their biotransformation

Biotransformation can greatly influence the accumulation and, subsequently, toxicity of substances in living beings. Although traditionally these studies to quantify metabolization of a compound have been carried out with in vivo species, currently, in vitro test methods with very different cell lines are being developed for their evaluation. However, this is still a very limited field due to multiple variables of a very diverse nature. So, an increasing number of analytical chemists are working with cells or other similar biological samples of very small size. This makes it necessary to address the development of analytical methods that allow determining their concentration both inside the cells and in their exposure medium. The aim of this study is to develop a set of analytical methodologies for the quantification of polycyclic aromatic hydrocarbons, PAHs (phenanthrene, PHE), and polybrominated diphenyl ethers, PBDEs (2,2',4,4'-tetrabromodiphenyl ether, BDE-47), and their major metabolites in cells and their exposure medium. Analytical methodologies, based on miniaturized ultrasound probe-assisted extraction, gas chromatography-mass spectrometry-microelectron capture detector (GC-MS-µECD), and liquid chromatography-fluorescence detector (LC-FL) determination techniques, have been optimized and then applied to a biotransformation study in HepG2 at 48 h of exposure. Significant concentrations of the major metabolites of PHE (1-OH, 2-OH, 3-OH, 4-OH-, and 9-OH-PHE) and BDE-47 (5-MeO-, 5-OH-, and 3-OH-BDE-47) were detected and quantified inside the cells and in the exposure medium. These results provide a new method for determination and improve information on the metabolization ratios for a better knowledge of the metabolic pathways and their toxicity.

A precision environmental health approach to prevention of human disease

Human health is determined by the interaction of our environment with the genome, epigenome, and microbiome, which shape the transcriptomic, proteomic, and metabolomic landscape of cells and tissues. Precision environmental health is an emerging field leveraging environmental and system-level ('omic) data to understand underlying environmental causes of disease, identify biomarkers of exposure and response, and develop new prevention and intervention strategies. In this article we provide real-life illustrations of the utility of precision environmental health approaches, identify current challenges in the field, and outline new opportunities to promote health through a precision environmental health framework.

Developmental programming: Preconceptional and gestational exposure of sheep to a real-life environmental chemical mixture alters maternal metabolome in a fetal sex-specific manner

BACKGROUND

Everyday, humans are exposed to a mixture of environmental chemicals some of which have endocrine and/or metabolism disrupting actions which may contribute to non-communicable diseases. The adverse health impacts of real-world chemical exposure, characterized by chronic low doses of a mixture of chemicals, are only recently emerging. Biosolids derived from human waste represent the environmental chemical mixtures humans are exposed to in real life. Prior studies in sheep have shown aberrant reproductive and metabolic phenotypes in offspring after maternal biosolids exposure.

OBJECTIVE

To determine if exposure to biosolids perturbs the maternal metabolic milieu of pregnant ewes, in a fetal sex-specific manner.

METHODS

Ewes were grazed on inorganic fertilizer (Control) or biosolids-treated pastures (BTP) from before mating and throughout gestation. Plasma from pregnant ewes (Control n = 15, BTP n = 15) obtained mid-gestation were analyzed by untargeted metabolomics. Metabolites were identified using Agilent MassHunter. Multivariate analyses were done using MetaboAnalyst 5.0 and confirmed using SIMCA.

RESULTS

Univariate and multivariate analysis of 2301 annotated metabolites identified 193 differentially abundant metabolites (DM) between control and BTP sheep. The DM primarily belonged to the super-class of lipids and organic acids. 15-HeTrE, oleamide, methionine, CAR(3:0(OH)) and pyroglutamic acid were the top DM and have been implicated in the regulation of fetal growth and development. Fetal sex further exacerbated differences in metabolite profiles in the BTP group. The organic acids class of metabolites was abundant in animals with male fetuses. Prenol lipid, sphingolipid, glycerolipid, alkaloid, polyketide and benzenoid classes showed fetal sex-specific responses to biosolids.

DISCUSSION

Our study illustrates that exposure to biosolids significantly alters the maternal metabolome in a fetal sex-specific manner. The altered metabolite profile indicates perturbations to fatty acid, arginine, branched chain amino acid and one‑carbon metabolism. These factors are consistent with, and likely contribute to, the adverse phenotypic outcomes reported in the offspring.

Dietary exposure assessment of infant formula and baby foods' oxidized lipids in the US population

Baby Foods (BFs) and Infant formulas (IFs) are the main sources of nutrition for an infant throughout the 1st year of life. Various enriched products are commercially available for parents seeking to fulfill their baby's nutritional needs. Consequently, different bioactive lipids are present in BFs and IFs, including dietary oxysterols (DOxS), whose known toxicity has been associated with mutagenicity, cancer, and other chronic diseases. In this work, we performed an exposure assessment of 25 bioactive lipids on IFs (n = 30) and BFs (n = 13) commercially available in the US. To determine dietary exposure, we used EPA's SHEDS-HT probabilistic model. Even though β-Sitosterol was the most exposed bioactive lipid with 75,410 μg/day, cholesterol was the most absorbed compound during the entire first year (19.3 mg/day). Additionally, we found 7α-hydroxycholesterol (7α-OH) as a potential DOxS biomarker of the BFs manufacturing process. This is the first time an infant's exposure assessment (including DOxS) after BFs and IFs consumption is performed, enabling much-needed information regarding these hazardous compounds and their potential effects on infants' health.

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography-high-resolution mass spectrometry (UPHLC-HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000's of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.