Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum.

The past decades have marked the rise of metabolomics and lipidomics as the -omics sciences which reflect the most phenotypes in living systems. Mass spectrometry-based approaches are acknowledged for both quantification and identification of molecular signatures, the latter relying primarily on fragmentation spectra interpretation. However, the high structural diversity of biological small molecules poses a considerable challenge in compound annotation. Feature-based molecular networking (FBMN) combined with database searches currently sets the gold standard for annotation of large datasets. Nevertheless, FBMN is usually based on collision-induced dissociation (CID) data, which may lead to unsatisfying information. The use of alternative fragmentation methods, such as electron-activated dissociation (EAD), is undergoing a re-evaluation for the annotation of small molecules, as it gives access to additional fragmentation routes. In this study, we apply the performances of data-dependent acquisition mass spectrometry (DDA-MS) under CID and EAD fragmentation along with FBMN construction, to perform extensive compound annotation in the crude extracts of the freshwater sentinel organism Gammarus fossarum. We discuss the analytical aspects of the use of the two fragmentation modes, perform a general comparison of the information delivered, and compare the CID and EAD fragmentation pathways for specific classes of compounds, including previously unstudied species. In addition, we discuss the potential use of FBMN constructed with EAD fragmentation spectra to improve lipid annotation, compared to the classic CID-based networks. Our approach has enabled higher confidence annotations and finer structure characterization of 823 features, including both metabolites and lipids detected in G. fossarum extracts.

Ultrasensitive Immunosensor Array for TNF-α Detection in Artificial Saliva using Polymer-Coated Magnetic Microparticles onto Screen-Printed Gold Electrode.

Tumor necrosis factor-α (TNF-α) is a biomarker of inflammation that occurs in patients suffering from heart failure (HF). Saliva can be sampled in a non-invasive way, and it is currently gaining importance as matrix alternative to blood in diagnostic and therapy monitoring. This work presents the development of an immunosensor array based on eight screen-printed gold electrodes to detect TNF-α in saliva samples. Two different functionalization strategies of electrodes were compared. In the first, anti-TNF-α antibodies were chemically bonded onto the electrode by functionalization with 4-carboxymethylaniline. The other functionalization procedure involved the binding of antibodies onto polymer-coated magnetic microparticles, which were then deposited onto the electrode by pulsed chronoamperometry. Finally, the chronoamperometry technique was applied to characterize the modified SPEAu. The use of a secondary antibody anti-TNF-α (Ab-TNF-α-HRP) labelled with horseradish peroxidase (HRP, 2 µg·mL-1) was investigated using tetramethylbenzidine (TMB, pH = 3.75) as electrochemical substrate containing 0.2 mM of H2O2. A sandwich-type detection strategy with a secondary antibody anti-TNF-α provided chronoamperometric analyses in 10 s for each sample. Linearity, precision, limit of detection, and selectivity of devices were investigated. Interferences were evaluated by analyzing solutions containing other cytokine produced during the acute stage of inflammation. The immunosensor showed good performance within the clinically relevant concentration range, with a precision of 8%, and a limit of detection of 0.3 pg/mL. Therefore, it may represent a promising tool for monitoring HF in a non-invasive way.

Determination of surfactant bio-sourced origin by isotope-ratio mass spectrometry.

RATIONALE: To develop more eco-friendly laundry detergents, renewable surfactants synthesized from vegetal sources are increasingly being used. In a more stringent regulation context, the determination of bio-sourced surfactant origin thus appears essential to assess the claims of detergent manufacturers. Radiocarbon determination, the standard method for the analysis of bio-sourced materials, is an expensive technique, so there is a need for a cheaper method. METHODS: Here, the use of an elemental analyzer linked to isotope-ratio mass spectrometry (EA/IRMS) is evaluated as an alternative approach to the official method. The δ(18) O, δ(13) C and δ(2) H isotope-ratio values were determined to investigate the bio-sourced origin of surfactant raw materials and mixtures. RESULTS: A sample library of 26 commercial surfactants representative of detergent raw materials was first analyzed by EA/IRMS. The δ(18) O, δ(13) C and δ(2) H values allowed discrimination of synthetic and bio-sourced surfactants. Moreover, in this latter group, C4 plant-derived surfactants were distinguished by their δ(13) C values. Binary and ternary mixtures made of synthetic and bio-sourced surfactants were also analyzed and indicated a linear relationship between mixture isotope-ratio values and surfactant proportions. CONCLUSIONS: IRMS represents a viable alternative to radiocarbon determination for the evaluation of surfactant bio-sourced origin. It is a faster and cheaper technique, allowing discrimination of petroleum- and biomass-derived surfactants and identification of their carbon sources (C4 or C3 plants).

Total ApoE and ApoE4 isoform assays in an Alzheimer's disease case-control study by targeted mass spectrometry (n=669): a pilot assay for methionine-containing proteotypic peptides.

Allelic polymorphism of the apolipoprotein E (ApoE) gene (ApoE ε2, ApoE ε3 and ApoE ε4 alleles) gives rise to three protein isoforms (ApoE2, ApoE3 and ApoE4) that differ by 1 or 2 amino acids. Inheritance of the ApoE ε4 allele is a risk factor for developing Alzheimer's disease (AD). The potential diagnostic value of ApoE protein levels in biological fluids (i.e. cerebrospinal fluid, plasma and serum) for distinguishing between AD patients and healthy elderly subjects is subject to great controversy. Although a recent study reported subnormal total ApoE and ApoE4 levels in the plasma of AD patients, other studies have found normal or even elevated protein levels (versus controls). Because all previously reported assays were based on immunoenzymatic techniques, we decided to develop an orthogonal assay based on targeted mass spectrometry by tracking (i) a proteotypic peptide common to all ApoE isoforms and (ii) a peptide that is specific for the ε4 allele. After trypsin digestion, the ApoE4-specific peptide contains an oxidation-prone methionine residue. The endogenous methionine oxidation level was evaluated in a small cohort (n=68) of heterozygous ε3ε4 carriers containing both healthy controls and AD patients. As expected, the proportion of oxidized residues varied from 0 to 10%, with an average of 5%. We therefore developed a standardized strategy for the unbiased, absolute quantification of ApoE4, based on performic acid oxidization of methionine. Once the sample workflow had been thoroughly validated, it was applied to the concomitant quantification of total ApoE and ApoE4 isoform in a large case-control study (n=669). The final measurements were consistent with most previously reported ApoE concentration values and confirm the influence of the different alleles on the protein expression level. Our results illustrate (i) the reliability of selected reaction monitoring-based assays and (ii) the value of the oxidization step for unbiased monitoring of methionine-containing proteotypic peptides. Furthermore, a statistical analysis indicated that neither total ApoE and ApoE4 levels nor the ApoE/ApoE4 ratio correlated with the diagnosis of AD. These findings reinforce the conclusions of previous studies in which plasma ApoE levels had no obvious clinical significance.

Concomitant investigation of crustacean amphipods lipidome and metabolome during the molting cycle by Zeno SWATH data-independent acquisition coupled with electron activated dissociation and machine learning.

BACKGROUND: DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) initially developed for proteomics studies and recently emerging in metabolomics and lipidomics. It provides a comprehensive and unbiased coverage of molecules with improved reproducibility and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field. RESULTS: DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to characterize molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified significant features. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra database annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness. SIGNIFICANCE: Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing enhances detection sensitivity and targeted fragmentation with EAD in positive polarity provides orthogonal fragmentation information. In our study, Zeno-DIA and EAD thereby facilitated a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying informative biomarkers on the health status of an environmental sentinel species.

Comprehensive bile acid pool analysis during ex-vivo liver perfusion in a porcine model of ischemia-reperfusion injury.

Bile acids (BA) are key for liver regeneration and injury. This study aims at analyzing the changes in the BA pool induced by ischemia-reperfusion (IRI) and investigates the impact of hypothermic oxygenated perfusion (HOPE) on the BA pool compared to static cold storage (SCS). In a porcine model of IRI, liver grafts underwent 30 min of asystolic warm ischemia followed by 6 h of SCS (n = 6) ± 2 h of HOPE (n = 6) and 2 h of ex-situ warm reperfusion. The BA pool in bile samples was analyzed with liquid chromatography coupled with tandem mass spectrometry. We identified 16 BA and observed significant changes in response to ischemia-reperfusion, which were associated with both protective and injury mechanisms. Second, HOPE-treated liver grafts exhibited a more protective BA phenotype, characterized by a more hydrophilic BA pool compared to SCS. Key BA, such as GlycoCholic Acid, were identified and were associated with a decreased transaminase release and improved lactate clearance during reperfusion. Partial Least Square-Discriminant Analysis revealed a distinct injury profile for the HOPE group. In conclusion, the BA pool changes with liver graft IRI, and preservation with HOPE results in a protective BA phenotype compared to SCS.

Ultraviolet exposure regulates skin metabolome based on the microbiome.

Skin metabolites (< 1500 Da) play a critical role in barrier function, hydration, immune response, microbial invasion, and allergen penetration. We aimed to understand the global metabolic profile changes of the skin in relation to the microbiome and UV exposure and exposed germ-free (devoid of microbiome), disinfected mice (partially devoid of skin microbiome) and control mice with intact microbiome to immunosuppressive doses of UVB radiation. Targeted and untargeted lipidome and metabolome profiling was performed with skin tissue by high-resolution mass spectrometry. UV differentially regulated various metabolites such as alanine, choline, glycine, glutamine, and histidine in germ-free mice compared to control mice. Membrane lipid species such as phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin were also affected by UV in a microbiome-dependent manner. These results shed light on the dynamics and interactions between the skin metabolome, microbiome, and UV exposure and open new avenues for the development of metabolite- or lipid-based applications to maintain skin health.

Development of a multi-omics extraction method for ecotoxicology: investigation of the reproductive cycle of Gammarus fossarum.

Omics study exemplified by proteomics, lipidomics or metabolomics, provides the opportunity to get insight of the molecular modifications occurring in living organisms in response to contaminants or in different physiological conditions. However, individual omics discloses only a single layer of information leading to a partial image of the biological complexity. Multiplication of samples preparation and processing can generate analytical variations resulting from several extractions and instrumental runs. To get all the -omics information at the proteins, metabolites and lipids level coming from a unique sample, a specific sample preparation must be optimized. In this study, we streamlined a biphasic extraction procedure based on a MTBE/Methanol mixture to provide the simultaneous extraction of polar (proteins, metabolites) and apolar compounds (lipids) for multi-omics analyses from a unique biological sample by a liquid chromatography (LC)/mass spectrometry (MS)/MS-based targeted approach. We applied the methodology for the study of female amphipod Gammarus fossarum during the reproductive cycle. Multivariate data analyses including Partial Least Squares Discriminant Analysis and multiple factor analysis were applied for the integration of the multi-omics data sets and highlighted molecular signatures, specific to the different stages.

Early detection of ureteropelvic junction obstruction in neonates with prenatal diagnosis of renal pelvis dilatation using 1H NMR urinary metabolomics.

Renal pelvis dilatation (RPD) is diagnosed in utero on prenatal ultrasonography (US) and can resolve spontaneously. However, isolated RPD can also reflect ureteropelvic junction obstruction (UPJO), which requires surgical treatment to prevent progressive renal deterioration. The diagnosis of UPJO can only be confirmed after birth with repeat US and renal isotope studies. 1H Nuclear Magnetic Resonance spectroscopy (NMR) was performed on urine of newborns with prenatally diagnosed unilateral RPD and healthy controls to identify specific urinary biomarkers for UPJO. The original combination of EigenMS normalization and sparse partial-least-squares discriminant analysis improved selectivity and sensitivity. In total, 140 urine samples from newborns were processed and 100 metabolites were identified. Correlation network identified discriminant metabolites in lower concentrations in UPJO patients. Two main metabolic pathways appeared to be impaired in patients with UPJO i.e. amino acid and betaine metabolism. In this prospective study, metabolic profiling of urine samples by NMR clearly distinguishes patients who required surgery for UPJO from patients with transient dilatations and controls. This study will pave the way for the use of metabolomics for the diagnosis of prenatal hydronephrosis in clinical routine.

Determination of enantiomeric and stable isotope ratio fingerprints of active secondary metabolites in neroli (Citrus aurantium L.) essential oils for authentication by multidimensional gas chromatography and GC-C/P-IRMS.

Neroli essential oil (EO), extracted from bitter orange blossoms, is one of the most expensive natural products on the market due to its poor yield and its use in fragrance compositions, such as cologne. Multiple adulterations of neroli EO are found on the market, and several authentication strategies, such as enantioselective gas chromatography (GC) and isotope ratio mass spectrometry (IRMS), have been developed in the last few years. However, neroli EO adulteration is becoming increasingly sophisticated, and analytical improvements are needed to increase precision. Enantiomeric and compound-specific isotopic profiling of numerous metabolites using multidimensional GC and GC-C/P-IRMS was carried out. These analyses proved to be efficient for geographical tracing, especially to distinguish neroli EO of Egyptian origin. In addition, δ2H values and enantioselective ratios can identify an addition of 10% of petitgrain EO. These results demonstrate that enantioselective and stable isotopic metabolite fingerprint determination is currently a necessity to control EOs.

Shotgun lipidomics and mass spectrometry imaging unveil diversity and dynamics in Gammarus fossarum lipid composition.

Sentinel species are playing an indispensable role in monitoring environmental pollution in aquatic ecosystems. Many pollutants found in water prove to be endocrine disrupting chemicals that could cause disruptions in lipid homeostasis in aquatic species. A comprehensive profiling of the lipidome of these species is thus an essential step toward understanding the mechanism of toxicity induced by pollutants. Both the composition and spatial distribution of lipids in freshwater crustacean Gammarus fossarum were extensively examined herein. The baseline lipidome of gammarids of different sex and reproductive stages was established by high throughput shotgun lipidomics. Spatial lipid mapping by high resolution mass spectrometry imaging led to the discovery of sulfate-based lipids in hepatopancreas and their accumulation in mature oocytes. A diverse and dynamic lipid composition in G. fossarum was uncovered, which deepens our understanding of the biochemical changes during development and which could serve as a reference for future ecotoxicological studies.

In situ isobaric lipid mapping by MALDI-ion mobility separation-mass spectrometry imaging.

The highly diverse chemical structures of lipids make their analysis directly from biological tissue sections extremely challenging. Here, we report the in situ mapping and identification of lipids in a freshwater crustacean Gammarus fossarum using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) in combination with an additional separation dimension using ion mobility spectrometry (IMS). The high-resolution trapped ion mobility spectrometry (TIMS) allowed efficient separation of isobaric/isomeric lipids showing distinct spatial distributions. The structures of the lipids were further characterized by MS/MS analysis. It is demonstrated that MALDI MSI with mobility separation is a powerful tool for distinguishing and localizing isobaric/isomeric lipids.

Hexavalent chromium release from leather over time natural ageing vs accelerated ageing according to a multivariate approach.

European restriction limits the hexavalent chromium content to not more than 3 mg/kg in leather products. Owing to the evolution of hexavalent chromium content in leathers over time, it's difficult to guarantee the products will be harmless for consumers. The designing of an accelerated and representative artificial ageing procedure is therefore highly desirable. This article proposes a thorough study of the influence of storage conditions on the formation of hexavalent chromium in 4 bovine leathers. A factorial design of experiment was built with the following factors: temperature of 40-80 °C, relative humidity of 20-50%, presence or not of UV and exposure duration of 24-48 h. The results of these artificial ageings demonstrate that a high temperature, a dry atmosphere and the presence of light favor the formation of hexavalent chromium and that synergistic effects operate between temperature/humidity, temperature/UV and humidity/UV. At the same time, the leathers were subjected to a natural ageing for 12 months with a weekly hexavalent chromium analysis. The principal component analysis of the artificial ageing tests combined with the natural ageing tests, show that the artificial ageings 40 °C-50%RH-UV-48 h and 40 °C-20%RH-UV-24 h best simulate a natural ageing in the tannery, whatever the leather studied.

Antibacterial Properties of Polyphenols: Characterization and QSAR (Quantitative Structure-Activity Relationship) Models.

Besides their established antioxidant activity, many phenolic compounds may exhibit significant antibacterial activity. Here, the effect of a large dataset of 35 polyphenols on the growth of 6 foodborne pathogenic or food-spoiling bacterial strains, three Gram-positive ones (Staphylococcus aureus, Bacillus subtilis, and Listeria monocytogenes) and three Gram-negative ones (Escherichia coli, Pseudomonas aeruginosa, and Salmonella Enteritidis), have been characterized. As expected, the effects of phenolic compounds were highly heterogeneous ranging from bacterial growth stimulation to antibacterial activity and depended on bacterial strains. The effect on bacterial growth of each of the polyphenols was expressed as relative Bacterial Load Difference (BLD) between a culture with and without (control) polyphenols at a 1 g L-1 concentration after 24 h incubation at 37°C. Reliable Quantitative Structure-Activity Relationship (QSAR) models were developed (regardless of polyphenol class or the mechanism of action involved) to predict BLD for E. coli, S. Enteritidis, S. aureus, and B. subtilis, unlike for L. monocytogenes and P. aeruginosa. L. monocytogenes was generally sensitive to polyphenols whereas P. aeruginosa was not. No satisfactory models predicting the BLD of P. aeruginosa and L. monocytogenes were obtained due to their specific and quite constant behavior toward polyphenols. The main descriptors involved in reliable QSAR models were the lipophilicity and the electronic and charge properties of the polyphenols. The models developed for the two Gram-negative bacteria (E. coli, S. Enteritidis) were comparable suggesting similar mechanisms of toxic action. This was not clearly observed for the two Gram-positive bacteria (S. aureus and B. subtilis). Interestingly, a preliminary evaluation by Microbial Adhesion To Solvents (MATS) measurements of surface properties of the two Gram-negative bacteria for which QSAR models were based on similar physico-chemical descriptors, revealed that MATS results were also quite similar. Moreover, the MATS results of the two Gram-positive bacterial strains S. aureus and B. subtilis for which QSARs were not based on similar physico-chemical descriptors also strongly differed. These observations suggest that the antibacterial activity of most of polyphenols likely depends on interactions between polyphenols and bacterial cells surface, although the surface properties of the bacterial strains should be further investigated with other techniques than MATS.

Raman spectroscopy combined with advanced chemometric methods: A new approach for detergent deformulation.

Deformulation of a commercial surfactant mixture using Raman spectroscopy and advanced chemometric tools have been investigated. Since the use of surfactants is drastically expanding, their fine identification and quantification are required for quality control and regulation. Dilution of the detergent mixtures combined with Raman spectroscopy for signal extraction tools allowed the extraction of the first information concerning the composition of the mixture. The raw materials identified were thus used in an experimental design to obtain a robust model for the determination of detergent composition. The combination of chemometric tools (independent component analysis and Partial Least Square) and spectroscopic methods provided pertinent information for detergent composition. This methodology can easily be transposed to the industrial world.

Heavy Metal Pollution of Chari River Water during the Crossing of N'Djamena (Chad).

This study was carried out to identify and assess the water quality of the Chari River. The Chari, 1200 km long, is Chad's major water source. Municipal sewage, industrial wastewater discharge, and seasonal run-off from agriculture are regularly fed into the river. Several trace metals such as Cu, Zn, Fe, Ni, Cr, Mn, and Cd, were measured in different sampling stations located along the Chari River at N'Djamena in different campaigns from 2008 to 2010. Overall, manganese, zinc, chromium, and copper concentration levels were mainly in the range of the permissible limits prescribed by WHO guidelines (WHO 2011). Nickel, iron, and cadmium concentrations were still high. This preliminary study allowed us to identify the magnitude of toxic pollutants, which are responsible for Chari River water contamination in the study area. This study revealed that urgent measures must be taken to protect the local people from health problems resulting from high concentrations of heavy metals.

Characterization of surfactant complex mixtures using Raman spectroscopy and signal extraction methods: Application to laundry detergent deformulation.

This paper presents the analysis of surfactants in complex mixtures using Raman spectroscopy combined with signal extraction (SE) methods. Surfactants are the most important component in laundry detergents. Both their identification and quantification are required for quality control and regulation purposes. Several synthetic mixtures of four surfactants contained in an Ecolabel laundry detergent were prepared and analyzed by Raman spectroscopy. SE methods, Independent Component Analysis and Multivariate Curve Resolution, were then applied to spectral data for surfactant identification and quantification. The influence of several pre-processing treatments (normalization, baseline correction, scatter correction and smoothing) on SE performances were evaluated by experimental design. By using optimal pre-processing strategy, SE methods allowed satisfactorily both identifying and quantifying the four surfactants. When applied to the pre-processed Raman spectrum of the Ecolabel laundry detergent sample, SE models remained robust enough to predict the surfactant concentrations with sufficient precision for deformulation purpose. Comparatively, a supervised modeling technique (PLS regression) was very efficient to quantify the four surfactants in synthetic mixtures but appeared less effective than SE methods when applied to the Raman spectrum of the detergent sample. PLS seemed too sensitive to the other components contained in the laundry detergent while SE methods were more robust. The results obtained demonstrated the interest of SE methods in the context of deformulation.

Use of designed experiments for the improvement of pre-analytical workflow for the quantification of intracellular nucleotides in cultured cell lines.

The present study is focused on the development of a pre-analytical strategy for the quantification of intracellular nucleotides from cultured cell lines. Different protocols, including cell recovery, nucleotide extraction and purification, were compared on a panel of nucleoside mono-, di- and triphosphates from four cell lines (adherent and suspension cells). The quantification of nucleotides was performed using a validated technique with on-line solid-phase extraction coupled with liquid chromatography-triple quadrupole tandem mass spectrometry (LC-MS/MS). Designed experiments were implemented to investigate, in a rigorous and limited-testing experimental approach, the influence of several operating parameters. Results showed that the technique used to harvest adherent cells drastically affected the amounts of intracellular nucleotides. Scraping cells was deleterious because of a major leakage (more than 70%) of intracellular nucleotides during scraping. Moreover, some other tested conditions should be avoided, such as using pure methanol as extraction solvent (decrease over 50% of intracellular nucleotides extracted from NCI-H292 cells) or adding a purification step with chloroform. Designed experiments allowed identifying an interaction between the percentage of methanol and the presence of chloroform. The mixture methanol/water (70/30, v/v) was considered as the best compromise according to the nucleoside mono-, di-, or triphosphates and the four cell lines studied. This work highlights the importance of pre-analytical step combined with the cell lines studied associated to sensitive and validated assay for the quantification of nucleotides in biological matrices.