1.7 Organische Spuren- und Lebensmittelanalytik
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Metabolomics
(2024)
Oxidative degradation processes of tetrabromobisphenol A (TBBPA), a brominated flame retardant (BFR) in wood, plastics and electronics, were investigated by electrochemistry (EC) coupled online to electrospray ionization mass spectrometry (ESI/MS). Oxidative phase I and II metabolites production was achieved using an electrochemical flow-through cell equipped with a boron doped diamond electrode. Structural elucidation and prediction of oxidative metabolism pathways of TBBPA according to type II ipso-substitution were based on retention time, m/z ratio in negative mode and fragmentation pattern. Using the data obtained through high resolution MS analysis and the identification of single electron transfer (SET) as the initial step of a two-electron oxidation provided the necessary information to propose a mechanism for the electrochemical oxidation of TBBPA. Oxidation reactions involving aromatic hydroxylation and β-scission were the main degradation observed when studying the electrochemical behavior of TBBPA. Computational chemistry experiments using density functional theory (DFT) allowed to identify mono-hydroxylated reaction intermediate and dismissed the mechanism involving two concurrent hydroxylation. TBBPA oxidation products were compared to known metabolites of its biological and environmental degradation confirming the ability of electrochemistry to simulate β-scission reactions.
We report an analytical methodology for the quantification of sulfur in biological molecules via a speciesunspecific postcolumn isotope dilution (online ID) approach using capillary electrophoresis (CE) coupled online with inductively coupled plasma−mass spectrometry (online ID CE/ICP−MS).
The method was optimized using a mixture of standard compounds including sulfate, methionine, cysteine, cystine, and albumin, yielding compound recoveries between 98 and 105%. The quantity of sulfur is further converted to the quantity of the compounds owing to the prior knowledge of the sulfur content in the molecules. The limit of detection and limit of quantification of sulfur in the compounds were 1.3−2.6 and 4.1−8.4 mg L−1, respectively, with a correlation coefficient of 0.99 within the concentration range of sulfur of 5−100 mg L−1. The capability of the method was extended to quantify albumin in its native matrix (i.e., in serum) using experimentally prepared serum spiked with a pure albumin standard for validation. The relative expanded uncertainty of the method for the quantification of albumin was 6.7% (k = 2). Finally, we tested the applicability of the method on real samples by the analysis of albumin in bovine and human sera. For automated data assessment, a software application (IsoCor) which was developed by us in a previous work was developed further for handling of online ID data. The method has several improvements compared to previously published setups: (i) reduced adsorption of proteins onto the capillary wall owing to a special capillary-coating procedure, (ii) baseline separation of the compounds in less than 30 min via CE, (iii) quantification of several sulfur species within one run by means of the online setup, (iv) SI traceability of the quantification results through online ID, and (v) facilitated data processing of the transient signals using the IsoCor application. Our method can be used as an accurate approach for quantification of proteins and other biological molecules via sulfur analysis in complex matrices for various fields, such as environmental, biological, and pharmaceutical studies as well as clinical diagnosis.
Sulfur is an essential element in living organisms, where it plays important roles in various biological processes, such as protein synthesis, enzyme activity, and antioxidant defense. However, the biological effects of different sulfur species can vary widely, and imbalances in sulfur speciation have been observed in a range of diseases, including cancer, Alzheimer’s disease, and diabetes.1−3 The accurate quantification of sulfur and its species in biological samples requires sensitive and selective analytical techniques. In recent years, separation techniques coupled online with inductively coupled plasma−mass spectrometry (ICP−MS) have emerged as powerful online analytical tools complementary to molecular spectrometric methods for speciation analysis of biological compounds.
External calibration4−9 and isotope dilution (ID)10−15 are common calibration approaches applied for online quantification of sulfur species in complex samples. The ID analysis is advantageous over.
Here, we report a comparative study of different sum parameter analysis methods for the extraction of per- and polyfluoroalkyl substances (PFAS) from manufactured consumer products, which can be measured by combustion ion chromatography (CIC). Therefore, a hydrolysis-based extraction method was further developed, which accounts for the addition of hydrolyzable covalently bound polyfluoroalkylated side-chain polymers (SFPs) to the extractable organic fluorine portion of the mass balance proposed as "hydrolyzable organically bound fluorine" (HOF). To test this hypothesis, the method was applied to 39 different consumer products containing fluoropolymers or monomeric PFAS taken from four different categories: outdoor textiles, paper packaging, carpeting, and permanent baking sheets. We also evaluated the method's efficiency by extracting four synthesized fluorotelomer polyacrylate reference compounds. The total fluorine (TF) and extractable organically bound fluorine (EOF) values were measured through CIC using established protocols. The TF values ranged from sub-ppb to %-levels, depending on the compound class. All samples showed results for hydrolyzed organofluorine (HOF) between 0.03 and 76.3 μg/g, while most EOF values were lower (<LOD to 58.1 μg/g). Moreover, the methods were contrasted with the "total hydrolyzable precursor" (THP) assay analyzed using gas-chromatography coupled mass spectrometry (GC-MS), which yielded concentrations of 6:2–10:2 fluorotelomer alcohols (<LOD-568 μg/g) for textile and paper samples. Furthermore, targeted analytical investigation of 25 compounds via liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was conducted and accounted for significantly lower sum amounts (<LOD-0.98 μg PFAS/g). To estimate the fluorine mass balance of all methods, the fluorine levels of target analytical data were calculated and compared to the sum parameter values and evaluated. Finally, the efficiency of the extraction method was approximated by the recovery analysis of four selected SFP model compounds compared to their TF values, yielding 36.7–74.0% after extraction and 3.8–36.3% after processing the extract for the HOF sum parameter.
Ergot alkaloids form a toxicologically relevant group of mould toxins (mycotoxins) that are among the most common contaminants of foodstuff and animal feed worldwide. Reliable controls are essential to minimise health risks and economic damage. Due to their toxicological relevance, EU limit values for 12 priority ergot alkaloids have been introduced for the first time in 2022 and range from 500 μg/kg in rye milling products down to 20 ug/kg Processed cereal-based foods for infants and young children[1]. High-performance liquid chromatography - mass spectrometry is used to quantify low concentrations of ergots in food, however the European standard analytical procedure cannot be applied due to the lack of isotopically labelled reference standards.
The complex structure of the ergot alkaloids makes a total synthesis extremely challenging, expensive and time-consuming. Therefore, we are focusing on different semi-preparative methods (electrochemistry, organic synthesis, heterogeneous catalysis) to specifically N-demethylate the C8 carbon atom of the lysergic acid moiety. The norergot alkaloid formed is then isotopically labelled using an electrophilic methyl source, i.e. iodomethane or dimethyl sulphate to obtain the specific isotopic labelled ergot alkaloid. Initial experiments have shown that N-demethylation of the ergot alkaloid ergotamine is possible by both electrochemical and wet-chemical organic synthesis. The next step is to improve the previously determined reaction conditions to enable the synthesis of norergotamine on a mg scale for further reactions.
Ergot alkaloids form a toxicologically relevant group of mould toxins (mycotoxins) that are among the most common contaminants of food and animal feed worldwide. Reliable controls are essential to minimise health risks and economic damage. Due to their toxicological relevance, EU limit values for 12 priority ergot alkaloids have been introduced for the first time in 2022 and range from 500 µg/kg in rye milling products down to 20 ug/kg Processed cereal-based foods for infants and young children[1]. High-performance liquid chromatography - mass spectrometry is used to quantify low concentrations of ergots in food, however the European standard analytical procedure cannot be applied due to the lack of isotopically labelled reference standards.
The complex structure of the ergot alkaloids makes a total synthesis extremely challenging, expensive and time-consuming. Therefore, we are focusing on different semi-preparative methods (electrochemistry, organic synthesis, heterogeneous catalysis) to specifically N-demethylate the C8 carbon atom of the lysergic acid moiety. The norergot alkaloid formed is then isotopically labelled using an electrophilic methyl source, i.e. iodomethane or dimethyl sulphate to obtain the specific isotopic labelled ergot alkaloid. Initial experiments have shown that N-demethylation of the ergot alkaloid ergotamine is possible by both electrochemical and wet-chemical organic synthesis. The next step is to adapt the previously determined reaction conditions to enable the synthesis of norergotamine on a mg scale.
The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials.
Demonstrating competency and equivalence for the measurement capacity of contaminants and nutrients in primary foodstuffs is a priority of the OAWG 10-year strategy for Track A core comparisons. Such measurements have posed significant challenges for reference material producers and calibration service providers. This key comparison (KC), under the topic of “non- polar analyte in high carbohydrate food matrix: trans-Zearalenone (trans-ZEN) in maize powder” , was a sector of the model system selected to align with this class within the OAWG strategy. Evidence of successful participation in formal, relevant international comparisons is needed to demonstrate the Calibration and Measurement Capabilities (CMCs) of national metrology institutes (NMIs) and designated institutes (DIs).
17 NMIs and DIs participated in the Track A KC CCQM- 168 “non-polar analyte in high carbohydrate food matrix: trans-ZEN in maize powder” . Participants were requested to evaluate the mass fraction (μg/kg) of trans-ZEN in maize powder material. Methods like liquid-liquid extraction and SPE were applied in the pre-treatment, and HPLC-MS/MS and HPLC-FLD were used for detection by the participants. The mass fractions for trans-ZEN were in the range of (91.8 to 169) μg/kg with standard uncertainties of (1.5 to 24.7) μg/kg, and corresponding relative standard uncertainties from 1.5% to 14.6%. Two labs, INTI and BAM were excluded from the KCRV evaluation. INTI result was identified as an outlier and confirmed their method had insufficient specificity. For BAM the calibration approach they used does not meet the CIPM traceability requirements. The other 15 labs included in the calculation of the consensus KCRV all agreed within their standard uncertainties. Hierarchical Bayes was used as estimators in calculating KCRV and standard uncertainty.
Successful participation in CCQM-K168 demonstrates the measurement capabilities in determining mass fraction of organic compounds, with molecular mass of 100 g/mol to 500 g/mol, having low polarity pKow < -2, in mass fraction range from 1 μg/kg to 1000 μg/kg in a high carbohydrate food matrix.
Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425).
A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69% of spiked compounds using LC-HRMS and 20-60% of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants’ own suspect lists led to putative identification of on average ~145 and ~20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ~42 and ~56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values ranging from -9.9 to 16 and mass-to-charge ratio (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.
Per- and polyfluoroalkyl substances (PFAS) are a large group of organofluorine surfactants used in the formulations of thousands of consumer goods. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system have been resulted in contaminated effluents and sewage sludge from wastewater treatment plants (WWTPs) which became an important pathway for PFAS into the environment. Because sewage sludge is often used as fertilizer its application on agricultural soils has been observed as significant input path for PFAS into our food chain. To produce high-quality phosphorus fertilizers for a circular economy from sewage sludge, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Normally, PFAS are analyzed using PFAS protocols typically with time-consuming extraction steps and LC-MS/MS target quantification. However, for screening of PFAS contaminations in wastewater-based fertilizers also the DGT technique can be used for the PFAS extraction. Afterwards, combustion ion chromatography (CIC) can be applied to analyze the “total” amount of PFAS on the DGT binding layer. The DGT method was less sensitive and only comparable to the extractable organic fluorine (EOF) method values of the fertilizers in samples with >150 µg/kg, because of different diffusion properties for various PFAS, but also kinetic exchange limitations. However, the DGT approach has the advantage that almost no sample preparation is necessary. Moreover, the PFAS adsorption on the DGT binding layer was investigated via surface sensitive spectroscopical methods, such as Fourier-transform infrared (FT-IR) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
Lithium-based batteries (LiBs) have become increasingly important in modern society, as cutting-edge portable energy storage systems and as a crucial component in the energy revolution. However, they still face challenges such as safety concerns, capacity degradation, and the ever-growing demand for higher energy density. To address these issues, researchers have turned their attention to fluorinated organic compounds (FOCs) as part of LiBs electrolytes. These substances, closely related to per- and polyfluorinated alkyl substances (PFAS), have shown great potential in optimizing LiBs. Specifically, their strong fluorine-carbon bond offers enhanced oxidative and chemical resistance. Nevertheless, their environmental impact is a cause for concern. Fluorinated organics can persist in the environment or can lead to the formation of persistent end-products, which accumulate and contribute to global health problems.
To study the fate of fluorinated organic electrolytes in different environmental and application scenarios, a range of simulation methods are employed, including the TOP (Total Oxidizable Precursor) Assay, electrochemistry, photo-induced degradation, and cycling of self-assembled coin cells prepared with FOCs. Transformation products (TP) are identified using gas chromatography and liquid chromatography coupled with high resolution mass spectrometry (GC/LC-HRMS).
Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-A001 containing Polycyclic Aromatic Hydrocarbons (PAH) in olive oil. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto.
Per- and polyfluoroalkyl substances (PFAS) are chemicals which were developed to improve humanity’s quality of life. Due to their high chemical stability and resistance to degradation by heat or acids, PFAS were used in a variety of consumer products. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system resulted in the contamination of effluents and sewage sludge from wastewater treatment plants (WWTPs) (Roesch et al. 2022). Since sewage sludge is often used as fertilizer, its application on agricultural soils has been observed as a significant entry path for PFAS into the environment, specifically in our food chain. In Germany the sewage sludge/biosolid application on agricultural land was banned with the amendment of the German Sewage Sludge Ordinance and by 2029 sewage sludge application will be totally prohibited. However, phosphorus (P) from sewage sludge should still be recycled in WWTPs of cities with a population larger than 50,000 residents. To produce high-quality P-fertilizers for a circular economy, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Due to the strong diversity of industrial PFAS usage it is not clear if a safe application of novel recycled P-fertilizers from WWTPs can be guaranteed. Therefore, we analyzed various sewage sludges and wastewater-based fertilizers. Sewage sludge (SL) samples from various WWTPs in Germany and Switzerland, six sewage sludge ashes (SSA) from Germany, six thermally treated SL and SSA samples with different additives (temperatures: 700-1050 °C), two pyrolyzed SL samples (temperature: 400 °C) and two struvite samples from Germany and Canada were analyzed. The goal was to quantify PFAS in sewage sludges and wastewater-based P-fertilizers with the sum parameter extractable organic fluorine (EOF) by combustion ion chromatography (CIC). The results were compared with data from classical LC-MS/MS target analysis as well as selected samples by HR-MS suspect screening. The EOF values of the SLs mainly range between 154 and 538 µg/kg except for one SL which showed an elevated EOF value of 7209 µg/kg due to high organofluorine contamination. For the SSA samples the EOF values were lower and values between LOQ (approx. 60 µg/kg) and 121 µg/kg could be detected. For the pyrolyzed SLs no EOF values above the LOQ were detected. Moreover, the two wastewater-based struvite fertilizers contain 96 and 112 µg/kg EOF, respectively. In contrast to the EOF values, the sum of PFAS target values were relatively low for all SLs. Additional applied PFAS HR-MS suspect screening aimed to tentatively identify PFAS that could contribute to the hitherto unknown part of the EOF value. The majority of the detected fluorinated compounds are legacy PFAS such as short- and long-chain perfluorocarboxylic acids (PFCA), perfluorosulfonic acids (PFSA), polyfluoroalkyl phosphate esters (PAPs) and perfluorophosphonic acids (PFPA). Moreover, fluorinated pesticides, pharmaceutical as well as aromatic compounds were also identified, which are all included in the EOF parameter. Our research revealed that the current PFAS limit of 100 µg/kg for the sum of PFOS + PFOA in the German Fertilizer Ordinance is no longer up to date. Since the number of known PFAS already exceeds 10,000, the ordinance limit should be updated accordingly. Recent regulations and restrictions on using long-chain PFAS (≥C8) have resulted in a significant shift in the industry towards (ultra-)short-chain alternatives, and other, partly unknown, emerging PFAS. Ultimately, also fluorinated pesticides and pharmaceuticals, which end up as ultrashort PFAS in the WWTPs, have to be considered as possible pollutants in fertilizers from wastewater, too.
Solid wastewater-based fertilizers were screened for per- and polyfluoroalkyl substances (PFAS) by the extractable organic fluorine (EOF) sum parameter method. The EOF values for ten sewage sludges from Germany and Switzerland range from 154 to 7209 mg kg−1. For thermal treated sewage sludge and struvite the EOF were lower with values up to 121 mg kg−1. Moreover, the application of PFAS targeted
and suspect screening analysis of selected sewage sludge samples showed that only a small part of the EOF sum parameter values can be explained by the usually screened legacy PFAS. The hitherto unknown part of EOF sum parameter contains also fluorinated pesticides, pharmaceutical and aromatic compounds. Because these partly fluorinated compounds can degrade to (ultra-)short PFAS in wastewater treatment plants they should be considered as significant sources of organic fluorine in the environment. The combined results of sum parameter analysis and suspect screening reveal the need to update current regulations, such as the German fertilizer ordinance, to focus not solely on a few selected PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) but
consider an additional sum parameter approach as a more holistic alternative. Moreover, diffusion gradient in thin-films (DGT) passive samplers were utilized as an alternative simplified extraction method for PFAS in solid wastewater-based fertilizers and subsequently quantified via combustion ion chromatography. However, the DGT method was less sensitive and only comparable to the EOF values
of the fertilizers in samples with >150 mg kg−1, because of different diffusion properties for various PFAS, but also kinetic exchange limitations.
Lithium-ion battery (LiB) operation remains challenging, particularly in terms of safety, cycling stability, capacity rates and high-voltage applications. Although the electrolytes of LiBs account for 10-15% of the total battery weight, they are still an underestimated part. Data suggest that the composition of electrolytes offers great potential to deal with all these issues. In particular, fluorinated electrolyte solvents or even fluorinated additives offer several advantages due to the strength of the C-F bond, providing chemical and oxidative stability and increased electronegativity, exhibiting flame retardant properties and facilitating anode-mediated degradation, resulting in a LiF-rich and more stable solid electrolyte interphase (SEI), enabling more efficient surface passivation. Therefore, studies suggest that fluorinated equivalents, as well as entirely new compounds, are promising for solving battery-related problems.
But what happens to fluorinated organic compounds (FOCs) during usage? And what are the new potential risks associated with their release into the environment? The environmental and application-specific fate of FOCs is investigated by a selection of different fluorinated electrolytes, the application of various simulation methods, including the TOP (Total Oxidizable Precursor) Assay, electrochemistry, photo-induced degradation, and cycling of FOC-prepared self-assembled coin cells.
Gas chromatography and liquid chromatography coupled with high resolution mass spectrometry (GC/LC-HRMS) are used to identify transformation products (TP).
Non-target (NT) mass spectrometry techniques play a crucial role in metabolomics applications, particularly in areas such as environmental safety. Soft ionization methods, such as electrospray ionization (ESI), are commonly employed due to their ability to generate spectra containing molecular ions, aiding in the identification of unknown peaks. However, ESI may fail to ionize certain compounds effectively, resulting in their absence in NT approaches. In contrast, hard ionization methods like electron impact (EI) can ionize a wide range of compounds but often lack information about the molecular ion. Although extensive databases of EI spectra exist, their nominal mass resolution (NR) limits their utility for modern high-resolution (HR) EI mass spectrometers. Here, the often-applied conversion of HR spectra to nominal mass leads to the loss of unique characteristics, i.e. by grouping distinct masses into more ambiguous nominal masses.
Our study aims to (i) quantify the negative impact of such a binning approach and (ii) develop a machine learning (ML) tool capable of enhancing existing nominal mass spectral libraries. In the initial phase, we employed the RECETOX Exposome HR-[EI+]-MS library to assess the influence of HR spectra on identification. We compared the dot product of each spectrum against all others, utilizing bin sizes of 0.001 and 1 Da. The difference in dot product between the second-best candidate and the query spectrum (the best candidate, with a score of 1) was calculated for both HR and nominal mass spectra. Subsequently, we explored the application of ML techniques to predict HR spectra from nominal mass spectra using the before mentioned dataset.
Preliminary findings demonstrate the potential of high-resolution spectral libraries. As anticipated, HR spectra consistently exhibited lower similarity scores for the second candidate. This observation likely stems from the high redundancy and resulting ambiguity associated with nominal masses. Even after eliminating spectra containing multiple HR masses mapped to the same nominal mass, the aforementioned trend persisted. Furthermore, initial investigations into ML have revealed its ability to predict up to 40% of HR masses within a 10 mDa precision window.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.