Electrospray Ionization and samples complexity in Meta-metabolomics: a biomarker or a suppressed ion?

International audienceIntroductionElectrospray Ionization is one of the most utilized ionization techniques for LC-MS-based metabolomics [1]. However, it presents several drawbacks, e.g. the ion suppression phenomenon, causing ion intensity decrease [2]. The occurrence of the phenomenon is higher if the sample is more complex. Thus, studying samples with different complexities may lead to consider some non-significant molecular features as markers of discrimination. This is due to ion suppression in samples with higher complexity.Material and MethodsThe issue is reported in an environmental context [3,4]. The study is performed on control non-spiked sediment samples and sediments spiked with a complex biopesticide; Bacillus thuringiensis israelensis. Meta-metabolome (endometabolome + xenometabolome) is extracted with QuEChERS method, then analyzed by LC-QToF in order to perform untargeted metabolic profiling, to discover the biomarkers of exposure. This to understand the pesticide impact on spiked sediments compared to control sediments.Results and DiscussionResults revealed several markers with lower intensity in the spiked group. They were co-eluting with multi-charged xenometabolites. Hence, these markers are either less concentrated due to a biological impact, or suppressed by the co-eluted molecules. Thus, to discriminate between biomarkers and suppressed ions, samples are diluted and analyzed. In fact, as dilution decreases the ion suppression, suppressed features are no more significantly discriminant between the two groups of samples.References[1] Bedair et al. 2008. Trends Anal. Chem. 27(3):238–250[2] Antignac et al. 2005. Anal. Chim. Acta. 529(1–2):129–136[3] Patil et al. 2016. Sci. Total Environ. 566–567:552–558[4] Salvia et al. 2018. Environ. Sci. Pollut. Res. 25(30):29841–2984

Improving the prevention, diagnosis and treatment of TB among people living with HIV: the role of operational research

Operational research is necessary to improve the access to and delivery of tuberculosis prevention, diagnosis and treatment interventions for people living with HIV. We conducted an extensive review of the literature and reports from recent expert consultations and research-related meetings organized by the World Health Organization and the Stop TB Partnership to identify a TB/HIV operational research agenda. We present critical operational research questions in a series of key areas: optimizing TB prevention by enhancing the uptake of isoniazid preventive therapy and the implementation of infection control measures; assessing the effectiveness of existing diagnostic tools and scaling up new technologies; improving service delivery models; and reducing risk factors for mortality among TB patients living with HIV. We discuss the potential impact that addressing the operational research questions may have on improving programmes’ performance, assessing new strategies or interventions for TB control, or informing global or national policy formulation. Financial resources to implement these operational research questions should be mobilized from existing and new funding mechanisms. National TB and HIV/AIDS programmes should develop their operational research agendas based on these questions, and conduct the research that they consider crucial for improving TB and HIV control in their settings in collaboration with research stakeholders

HS-SPME-GC-MS-based untargeted metabolomics for kinetics tracking of natural herbicides’ volatile residues: can we “footprint” the “Volatilome”??

International audienceDespite their known risks, herbicides are still essential for agriculture. Thus, natural herbicides are increasingly recommended to replace synthetic ones. However, there are still limitations in studying the environmental fate of several of them. The main reason is the lack of methods dedicated for this type of complex bio-herbicides. Hence, in the framework of the Environmental Metabolic Footprinting (EMF) approach, the current work presents a method dedicated to analyze the volatile residues of herbicides applied on soil. The aim is to track the evolution of the volatile compounds issued from the herbicide by an untargeted metabolomics-based kinetics, in order to determine the “resilience time” of the gaseous phase above the soil. The approach aims to explore the environmental fate of these herbicides. In fact, it will supplement other methods based on the EMF approach recently developed. Moreover, it can estimate the exposure of farmers, insects and plants to potential toxic volatile substances.The method is based on Headspace-Solid Phase Micro Extraction-Gas Chromatography-Electronic Impact Ionization-Quadrupole Mass Spectrometry (HS-SPME-GC-EI-Q MS). The HS-SPME provides a non-destructive extraction. This allows reducing the number of samples. The GC separation technique provides high reproducible analysis for volatile compounds. In addition, it allows the calculation of the Retention Index (RI) as a tool for the molecular characterization. On the other hand, despite the low resolution of the Quadrupole mass analyzer, the Electronic Impact Ionization provides reproducible MS fragmentation patterns used for spectral library search and fast putative identification of unknown compounds

Online HS-SPME-GC-MS-based Untargeted Volatile Metabolomics for Studying Emerging Complex Biopesticides: a Proof of Concept: W4M Workflow and Parameters

The current workflow was applied to pre-process GC-MS data (Ghosson, H. et al. Anal. Chim. Acta (2020), 1134:58-74) using Galaxy Workflow4Metabolomics platform. The automated processing workflow used the metaMS package (Galaxy Version 2.1.1) dedicated for GC-MS data. In brief, a “matchedFilter” algorithm was used for peak piking, with a Full Width at Half Maximum (FWHM) of 5 (Gaussian model peak). In addition, GC-MS peaks were considered for peak piking only if: i) their pseudo-spectra contained a minimum of 5 m/z features, ii) if these peaks were present in at least 70 % of samples belonging to a defined condition. Between the different injections/runs, the similarity threshold between peaks pseudo-spectra was set to 0.7, and maximum peak Retention Time (RT) variation was set to 15 sec in order to prevent any potential splitting of a metabolite feature into two different features.This work in­tro­duces a novel on­line Head­space-Solid Phase Mi­croex­trac­tion-Gas Chro­matog­ra­phy-Mass Spec­trom­e­try-based un­tar­geted metabolomics ap­proach, sug­gested as an al­ter­na­tive tool to study the en­vi­ron­men­tal fate of volatile xenometabo­lites in emerg­ing com­plex biopes­ti­cides, e.g. the Myrica gale methano­lic ex­tract her­bi­cide con­tain­ing sev­eral un­known metabo­lites. A “liv­ing” mi­cro­cosm sam­ple was de­signed for non-de­struc­tive analy­sis by a 35-min HS-SPME au­to­mated ex­trac­tion and a 36-min GC-MS run. A 38-day ki­net­ics study was then ap­plied on two groups of soil sam­ples: con­trol and spiked. Sta­tis­ti­cal tools were used for the com­par­a­tive ki­net­ics study. The Prin­ci­pal Com­po­nent Analy­sis re­vealed and ex­plained the evo­lu­tion and the dis­si­pa­tion of the her­bi­cide volatile xenometabolome over time. The time-se­ries Heatmap and Mul­ti­vari­ate Em­pir­i­cal Bayes Analy­sis of Vari­ance al­lowed the pri­or­i­ti­za­tion of 101 rel­e­vant com­pounds in­clud­ing 22 degra­da­tion by-prod­ucts. Out of them, 96 xenometabo­lites were pu­ta­tively iden­ti­fied. They in­cluded 63 com­pounds that are iden­ti­fied as her­bi­cide com­po­nents for the first time. The Or­thog­o­nal Pro­jec­tions to La­tent Struc­tures Dis­crim­i­nant Analy­sis and its Cross-Val­i­da­tion test were used to as­sess the to­tal dis­si­pa­tion of the her­bi­cide volatile residues and method de­tec­tion limit. The re­pro­ducibil­ity of the method was also as­sessed. The high­est in­ter-sam­ples (n = 3) Peak Area RSD was 7.75 %. The high­est in­ter-sam­ples (n = 3) and in­ter-days (n = 8) Re­ten­tion Time SD were 0.43 sec and 3.44 sec, re­spec­tively. The work pre­sents a green, non-la­bo­ri­ous and high-through­put ap­proach. It re­quired a small num­ber of en­vi­ron­men­tal sam­ples (6 mi­cro­cosms) that were an­a­lyzed 8 times and were not de­stroyed dur­ing the study.Please refer to Ghosson, H. et al. Anal. Chim. Acta (2020), 1134:58-74. doi:10.1016/j.aca.2020.08.016

Headspace-Solid Phase Micro Extraction-Gas Chromatography-Quadrupole Mass Spectrometry-based metabolomics for kinetics tracking of natural herbicides’ volatile residues: a simple non-destructive method

International audienceDespite their known risks, herbicides are still essential for agriculture. Thus, natural herbicides are increasingly recommended to replace synthetic ones. They are supposed less harmful on human health and ecosystem. However, there are still limitations in studying the environmental fate of several of them. The main reason is the lack of methods dedicated for this type of herbicides. In fact, they usually consist of complex mixtures of substances, of which several are unknown.Hence, in the framework of the Environmental Metabolic Footprinting (EMF) approach, the current work presents a method dedicated to analyze the volatile residues of herbicides applied on soil. The aim is to track the evolution of the volatile compounds issued from the herbicide by an untargeted metabolomics-based kinetics, in order to determine the “resilience time” of the gaseous phase above the soil. The approach aims to explore the environmental fate of these herbicides by combining it to other methods of the EMF. Moreover, it can estimate the exposure of farmers, insects and plants to potential toxic volatile substances.The method is based on Headspace-Solid Phase Micro Extraction-Gas Chromatography-Quadrupole Mass Spectrometry (HS-SPME-GC-Q MS). The HS-SPME provides a non-destructive extraction. This allows reducing the number of samples. The GC separation technique provides high reproducible analysis for volatile compounds. In addition, it allows the calculation of the Retention Index (RI) as a tool for the molecular characterization. On the other hand, despite the low resolution of the Quadrupole mass analyzer, the Electronic Impact provides reproducible MS fragmentation patterns used for spectral library search and putative identification of unknown compounds.The method was experimented for a pilot study. It was applied on a natural herbicide: the extract of Myrica gale, containing the Myrigalone A active substance. The setup of the analytical tool was performed by optimizing the system parameters. Then, a 38 days kinetics study was applied on control and spiked soil samples. Results proved the reliability of the method and demonstrated the robustness of the system and low matrix effect. Thus, new high scale experiments are planned. The integration of other natural and synthetic herbicides will be also considered

Untargeted metabolomics as a tool to monitor biocontrol product residues' fate on field-treated Prunus persica

International audienceEvidence of chemical plant protection products' (PPPs) long-term impact has been found in all environmental compartments. Therefore, other types of PPPs are developed to complement chemical PPPs like PPPs from natural sources, namely biocontrol products (BPs). Little is known about those new BPs, and it is important to assess their potential long-term environmental impact. Recently, the Environmental Metabolic Footprinting (EMF) approach was developed. It permits studying sample's entire meta-metabolome (endometabolome and xenometabolome) through a kinetics tracking of metabolomes of treated and untreated samples. Those metabolomes are compared time-by-time to estimate the “resilience time” of the samples after treatment. The current study aims to investigate BP residues' dissipation on peach fruits (Prunus persica). For that, an untargeted Liquid Chromatography-Mass Spectrometry metabolomics approach based on the EMF was optimised to separate the xenometabolome of the PPP from the endometabolome of the fruits. This “new version” of the EMF approach is able to target the BP treatment residues' (xenometabolome) dissipation exclusively. Thus, it is able to determine the time needed to have no more residues in the studied matrix: the “dissipation interval”. Field experiment was conducted on peach tree orchard against brown rot treated with (i) a plant extract BP (Akivi); (ii) a reference mineral extract BP (Armicarb®); and (iii) a Chemical reference treatment campaign. Formulated Akivi and its by-products' dissipation was monitored, a degradation kinetics appeared but the sampling did not last long enough to allow the determination of the “dissipation interval”. Armicarb® and the Chemical reference's residues and by-products showed a persistence pattern along the sampling kinetics. These results indicate that the EMF approach, formerly developed on soil and sediment, is applicable for fruit matrices and can be used to investigate the fate of complex BP treatment on the matrix through the xenometabolome tracking on treated fruits

LC-MS/HRMS-based untargeted metabolomics as a tool for analytical development: an application to biocontrol products’ analysis in soil

International audienceThe wide scope of our study is the set-up of a novel strategy called “Environmental Metabolic Footprinting” [1,2]. It aims to assess the environmental fate and impact of biocontrol products in soil, sediment and plants by tracking the evolution of their meta-metabolic profiles through the time. Thus, a broadband extraction covering a wide range of metabolites is required to allow for the best screening of those profiles.Hence, 5 extraction protocols (including 2 novel in-house-developed protocols) were tested on 3 environmental conditions (all applied on 2 soils of different types): control, spiked with the Glyphosate pesticide, spiked with Pelargonic acid formulation as a biocontrol product. However, determining the “optimal” extraction is not an easy task, as the experimental design is large, multi-factorial and complex (150 samples containing both soil biomolecules and pesticides components). Hence, an innovative LC-MS/HRMS-based untargeted approach was designed in order to evaluate the optimal protocol by using metabolomics computational tools (e.g. XCMS algorithm, OPLS-DA, Euclidean Distances, Heatmaps, van Krevelen, among others). Those tools provided easily-interpretable plots, comprehensive quantitative indices and chemical information based on ~500 metabolite annotations. They were used to assess 4 criteria defining the “optimal” conditions: 1) the ability of the extraction to cover a wide range of metabolites (qualitative), 2) its yield (quantitative), 3) its repeatability, and 4) its ability to allow for the discrimination between spiked and control samples.Therefore, the current presentation will introduce this innovative LC-MS/HRMS untargeted metabolomics-based approach as a powerful tool for methods development and will explain its different functions (“how it works”). The results of the large experiment mentioned above will be also highlighted. They allow promoting a novel broadband extraction (in-house-developed; based on solvent mixtures) as an optimal protocol for analyzing biocontrol products in soil samples.[1]: Patil et al. 2016. doi:10.1016/j.scitotenv.2016.05.071[2]: Salvia et al. 2018. doi:10.1007/s11356-017-9600-

LC-HRMS-based untargeted metabolomics as a tool for analytical development: In-depth assessment of exhaustive extraction protocols for pesticides-polluted soils

International audienceUntargeted metabolomics is an analytical chemistry approach dedicated for the analysis of small biomolecules called “metabolites”. One of its strengths is the ability of covering wide ranges of metabolic information in biological systems. However, exhaustive coverage of information is challenging from a chemical-analytical point of view. In fact, the widely different physical-chemical properties of molecules (e.g. polarity, acidity/basicity) make the study of various types of metabolites complicated. It demands critical methodological optimizations. Nevertheless, for untargeted approaches, “optimal conditions” are also hard to be defined and judged.The current work is focusing on the crucial step of meta-metabolome extraction. It seeks to develop an “exhaustive” extraction protocol able to extract different types of metabolites by covering a wide range of polarity. This is in the framework of developing the “Environmental Metabolic Footprinting” untargeted metabolomics-based approach [1-3], aiming to assess the environmental fate and impact of complex (bio)pesticides application on soil. Indeed, optimizing a method able to analyze diverse kind of metabolites can assure a wide range of information needed to assess the fate of the pesticide (xenometabolites) and its impact on soil’s biodiversity (endometabolites).Toward this objective, 5 extraction protocols based on solvents and mixtures with different polarities were developed and applied on 2 different types of soils, with 3 different environmental conditions (control, spiked with a synthetic pesticide, spiked with a natural pesticide). So far, 150 samples were extracted and analyzed with a broadband LC-HRMS method that was set-up for the purpose. The collected data were then handled and analyzed with various types of multivariate statistical analyses that were optimized in order to assess the “optimal” protocol, based on 4 main criteria, respectively: 1) the ability to widen the band of the extracted metabolites (qualitative), 2) the higher extraction yield (quantitative), 3) the repeatability of the extraction, and 4) the reliability in discriminating between spiked and control groups (the main aim of the EMF).The study showed that widening the polarity range for the extraction protocol, using a mix of solvents with different properties was applicable and demonstrated a significant ability in extracting a wide range of metabolites originating from both pesticide residues and soil endometabolome. It also showed comparable quantitative results and better repeatability comparing to other classical protocols. In addition, the study suggests multivariate analyses as a suitable tool not only for data processing for biological studies, but also for developing analytical methods and protocols, as it can give holistic explanations describing the large acquired datasets. Hence, in other words, untargeted metabolomics were used in order to improve the analytical method dedicated for an untargeted meta-metabolomics approach.[1]: Patil et al. 2016. Sci. Total Environ. 566–567:552–558[2]: Salvia et al. 2018. Environ. Sci. Pollut. Res. 25(30):29841–29847[3]: Ghosson 2020. Thesis. Université de Perpigna

LC–HRMS-Driven Computational Toolbox to Assess Extraction Protocols Dedicated to Untargeted Analysis: How to Ease Analyzing Pesticide-Contaminated Soils?

Metabolomics is a powerful approach that allows for high throughput analysis and the acquisition of large biochemical data. Nonetheless, it still faces several challenging requirements, such as the development of optimal extraction and analytical methods able to respond to its high qualitative and quantitative requisites. Hence, the objective of the present article is to suggest a LC–HRMS-based untargeted profiling approach aiming to provide performant tools that help assess the performance and the quality of extraction methods. It is applied in a herbicide-contaminated soil metabolomics context. The trifactorial experimental design consists of 150 samples issued from five different extraction protocols, two types of soils, and three contamination conditions (contaminated soils with two different formulated herbicides against uncontaminated soils). Four performance and quality criteria are investigated using adapted LC–HRMS-driven computational tools. First, 861 metabolic features are annotated, and then the width of metabolome coverage and quantitative performance of the five different extraction protocols are assessed in all samples using various optimized configurations of heatmaps as well as van Krevelen diagrams. Then, the reproducibility of LC–HRMS profiles issued from the five extractions is studied by two different approaches: Euclidean distances and relative standard deviations. The two methods are examined and compared. Their advantages and limitations are thus discussed. After, the capacity of the different extractions to discriminate between contaminated and uncontaminated soils will be evaluated using orthogonal projections to latent structures-discriminant analysis. Different data scaling parameters are tested, and the results are explored and discussed. All of the suggested computational and visualization tools are performed using public-access platforms or open-source software. They can be readapted by metabolomics developers and users according to their study contexts and fields of application

LC–HRMS-Driven Computational Toolbox to Assess Extraction Protocols Dedicated to Untargeted Analysis: How to Ease Analyzing Pesticide-Contaminated Soils?

Metabolomics is a powerful approach that allows for high throughput analysis and the acquisition of large biochemical data. Nonetheless, it still faces several challenging requirements, such as the development of optimal extraction and analytical methods able to respond to its high qualitative and quantitative requisites. Hence, the objective of the present article is to suggest a LC–HRMS-based untargeted profiling approach aiming to provide performant tools that help assess the performance and the quality of extraction methods. It is applied in a herbicide-contaminated soil metabolomics context. The trifactorial experimental design consists of 150 samples issued from five different extraction protocols, two types of soils, and three contamination conditions (contaminated soils with two different formulated herbicides against uncontaminated soils). Four performance and quality criteria are investigated using adapted LC–HRMS-driven computational tools. First, 861 metabolic features are annotated, and then the width of metabolome coverage and quantitative performance of the five different extraction protocols are assessed in all samples using various optimized configurations of heatmaps as well as van Krevelen diagrams. Then, the reproducibility of LC–HRMS profiles issued from the five extractions is studied by two different approaches: Euclidean distances and relative standard deviations. The two methods are examined and compared. Their advantages and limitations are thus discussed. After, the capacity of the different extractions to discriminate between contaminated and uncontaminated soils will be evaluated using orthogonal projections to latent structures-discriminant analysis. Different data scaling parameters are tested, and the results are explored and discussed. All of the suggested computational and visualization tools are performed using public-access platforms or open-source software. They can be readapted by metabolomics developers and users according to their study contexts and fields of application