Liquid Chromatography Coupled With Mass Spectrometry Research Articles

Ultrasensitive method for profiling host cell proteins by coupling limited digestion to ProteoMiner technology

Host cell proteins (HCPs) are process-related impurities that remain in therapeutic protein -at trace levels. HCPs must be closely monitored because they may be detrimental to drug product quality. Liquid chromatography coupled to mass spectrometry (LC-MS) is a powerful tool for detecting individual HCPs; however, HCP-derived peptides can be four to ten orders of magnitude less abundant than therapeutic protein-derived peptides in drug products, thus posing a major challenge in LC-MS detection. We previously demonstrated that low abundant HCPs can be enriched several hundreds fold through ProteoMiner. This study further improved the degree of enrichment by coupling limited digestion to ProteoMiner technology (PMLD). HCPs with low abundance were enriched 7694-fold, thus enabling detection of HCPs at concentrations as low as 0.002 ppm. A total of 850 HCPs were detected with high confidence from a NIST monoclonal antibody preparation, a number 40% higher than previously reported.

Instrument comparability of non-targeted UHPLC-HRMS for wine authentication

Instrument comparability is a major prerequisite for the harmonization of non-targeted analytical approaches for food authentication. While non-targeted liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful and widely used technique in authenticity studies, inter-laboratory or instrument comparison exercises are rare. For the first time, in the present study a comparison of two LC-MS platforms using identical setups and conditions except for the mass spectrometer (Orbitrap Q Exactive™ Focus vs. Plus) was carried out in order to assess the impact of instrumental differences on the classification of grape varieties in wine. A set of 201 red and white wine samples comprising 10 grape varieties was analyzed with both platforms and subjected to multivariate statistical analysis. Using unsupervised and supervised methods, the same correlation pattern between samples was observed with both platforms. Partial Least Squares – Discriminant Analysis (PLS-DA) classification models achieved comparable accuracies in the internal validation (90–95%). The percentage of common discriminating features was about 46–69% between both platforms. The common features were used to merge data from both instruments and joint PLS-DA models produced excellent results. The prediction of data from one platform with the model from the other platform, as well as a model using data from both platforms, resulted in correct classification rates of 92–98%. Putative identification of common features was performed to determine potential marker substances for grape varieties. With this study, a first step towards harmonization of non-targeted LC-MS approaches for wine authentication is taken, advancing their potential application in official food control.

Postinfection Metabolic Reprogramming of the Murine Trigeminal Ganglion Limits Herpes Simplex Virus-1 Replication.

ABSTRACTHerpes simplex virus type-1 (HSV-1) infections are known to alter the host metabolism for efficient propagation in vitro. However, in vivo metabolic perturbations upon prolonged HSV-1 infection remain poorly understood. We used high-resolution liquid chromatography coupled with mass spectrometry (LC-MS) and functional assays to determine the state of the trigeminal ganglion (TG) tissue metabolism upon prolonged corneal HSV-1 infection in a murine model. The metabolomics data indicated significant alterations in the host metabolic profile. After HSV-1 infection, the TG microenvironment assumed downregulation of central carbon metabolism and nucleotide synthesis pathways. We validated our observations using in vitro and ex vivo models through targeted inhibition of crucial metabolic polyamine pathways identified in our metabolomics screen. Our findings collectively suggested that HSV-1 infection altered the host metabolic product regulations that limit the energy and macromolecular precursors required for viral replication.

Polyphenols from Dichrostachys cinerea Fruits Anti-Inflammatory, Analgesic, and Antioxidant Capacity in Freund's Adjuvant-Induced Arthritic Rat Model.

Dichrostachys cinerea (L.) Wigth & Arn. (DC) is widely used in traditional medicine against several inflammatory diseases, especially rheumatoid arthritis, because of its antioxidant and anti-inflammatory effects. This study aimed to characterize the polyphenol-rich DC fruit extracts and investigate the analgesic, anti-inflammatory, and antioxidant effects in a rat inflammation model induced by complete Freund’s adjuvant (CFA). Water and ethanolic extracts were characterized using liquid chromatography coupled with mass spectrometry (LC-MS), Fourier-transform infrared (FTIR) spectroscopy, and gas chromatography coupled with mass spectrometry (GC-MS). The polyphenol-rich extracts were administered in three different concentrations for 30 days. Pain threshold, thermal hyperalgesia, edema, and serum biomarkers specific to inflammatory processes or oxidative stress were evaluated. Both extracts were rich in polyphenolic compounds, mainly flavan-3-ols, proanthocyanidins, and flavone glycosides, which had important in vitro antioxidant capacity. DC fruit extracts administration had the maximum antinociceptive and anti-inflammatory effects after one day since the CFA injection and showed promising results for long-term use as well. The measurement of pro-inflammatory cytokines, cortisol, and oxidative stress parameters showed that DC extracts significantly reduced these parameters, being dose and extract-type dependent. These results showed potential anti-inflammatory, analgesic, and antioxidative properties and revealed the necessity of using a standardized polyphenolic DC extract to avoid result variability.

The organic coating unit, an all-in-one system for reproducible generation of secondary organic matter aerosol

We report on a novel automated oxidation flow reactor to generate a wide variety of organic aerosol samples. The instrument is equipped with a humidifier, a dosing system for volatile organic precursors and an oxidation flow reactor (OFR) for generation of secondary organic matter (SOM). The instrument, known as organic coating unit (OCU), can produce homogeneously nucleated SOM particles or, used in combination with a standard combustion generator (e.g., a diffusion flame soot generator or any other seed particle), particles coated with a controlled amount of SOM. The physical and chemical properties of the generated particles can be controlled in a simple manner by selecting through a touch-screen target values for parameters, such as organic gaseous precursor concentration, humidity, and UV (ultraviolet) light intensity. Parameters and measured quantities are automatically stored in text files for easy export and analysis. Furthermore, we provide stable operation conditions and characterize the physicochemical properties of the generated aerosols with an array of methods, including transmission electron microscopy (TEM), thermal-optical analysis and liquid chromatography coupled with mass spectrometry (LC-MS). This all-in-one instrument is robust, compact, portable, and user-friendly, making it ideal for laboratory or field-based aerosol studies.

Impact of microcin J25 on the porcine microbiome in a continuous culture model.

The increased prevalence of Salmonella spp. resistance in swine spurs the search for alternatives to antibiotics. Microcin J25 (MccJ25), a bacteriocin produced by Escherichia coli, is a potent inhibitor of several pathogenic bacteria including Salmonella enterica. In this study, we aimed to evaluate in vitro the impact of MccJ25 on the composition and the metabolic activity of the swine colonic microbiota. The PolyFermS in vitro continuous fermentation model was used here with modified Macfarlane medium to simulate the porcine proximal colon. During 35 days of fermentation, a first-stage reactor containing immobilized swine fecal microbiota fed two second-stage control and test reactors operated in parallel and used to test the effects of MccJ25 on the composition and the metabolic activity of the microbiota. Reuterin, a broad-spectrum antimicrobial compound produced by Limosilactobacillus reuteri, a lactic acid bacterium naturally present in the gastro-intestinal tract of human and animals, and the antibiotic rifampicin were tested for comparison. Sequencing of 16S rRNA was performed using the Illumina MiSeq technology to evaluate microbial diversity, and liquid chromatography coupled to mass spectrometry (LC-MS) followed by multivariate analysis was used to assess the bacteriocin/antibiotic degradation products and to monitor changes in the swine colonic microbiota metabolome. The results show that MccJ25 or reuterin treatments only induce subtle changes of both the microbial diversity and the metabolome of the swine colon microbiota, while rifampicin induces significant modification in amino acid levels. Although these findings need being validated in vivo, this study affords a first proof of concept for considering MccJ25 as a possible alternative to antibiotics for veterinary and farming applications, taking into account its pathogen-selective and potent inhibitory activity.

Exploring Gut Microenvironment in Colorectal Patient with Dual-Omics Platform: A Comparison with Adenomatous Polyp or Occult Blood

The gut mucosa is actively absorptive and functions as the physical barrier to separate the gut ecosystem from host. Gut microbiota-utilized or food-derived metabolites are closely relevant to the homeostasis of the gut epithelial cells. Recent studies widely suggested the carcinogenic impact of gut dysbiosis or altered metabolites on the development of colorectal cancer (CRC). In this study, liquid chromatography coupled-mass spectrometry and long-read sequencing was applied to identify gut metabolites and microbiomes with statistically discriminative abundance in CRC patients (n = 20) as compared to those of a healthy group (n = 60) ofenrolled participants diagnosed with adenomatous polyp (n = 67) or occult blood (n = 40). In total, alteration in the relative abundance of 90 operational taxonomic units (OTUs) and 45 metabolites were identified between recruited CRC patients and healthy participants. Among the candidates, the gradual increases in nine OTUs or eight metabolites were identified in healthy participants, patients diagnosed with occult blood and adenomatous polyp, and CRC patients. The random forest regression model constructed with five OTUs or four metabolites achieved a distinct classification potential to differentially discriminate the presence of CRC (area under the ROC curve (AUC) = 0.998 or 0.975) from the diagnosis of adenomatous polyp (AUC = 0.831 or 0.777), respectively. These results provide the validity of CRC-associated markers, including microbial communities and metabolomic profiles across healthy and related populations toward the early screening or diagnosis of CRC.

Mapping Protein-Protein Interactions Using Data-Dependent Acquisition without Dynamic Exclusion.

Systematic analysis of affinity-purified samples by liquid chromatography coupled to mass spectrometry (LC-MS) requires high coverage, reproducibility, and sensitivity. While data-independent acquisition (DIA) approaches improve the reproducibility of protein-protein interaction detection as compared to standard data-dependent acquisition approaches, the need for library generation reduces their throughput, and analysis pipelines are still being optimized. In this study, we report the development of a simple and robust approach, termed turboDDA, to improve interactome analysis using spectral counting and data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step and optimizing the acquisition parameters. Using representative interaction and proximity proteomics samples, we detected increases in identified interactors of 18-71% compared to all samples analyzed by standard DDA with dynamic exclusion and for most samples analyzed by DIA with the MSPLIT-DIA spectral counting approach. In summary, turboDDA provides better sensitivity and identifies more high-confident interactors than the optimized DDA with DE and comparable or better sensitivity than DIA spectral counting approaches.

18O-Enabled High-Throughput Acyl Glucuronide Stability Assay.

Acyl glucuronides (AGs) are common metabolites of carboxylic acid-containing compounds. In some circumstances, AGs are suspected to be involved in drug toxicity due to formation of acyl migration products that bind covalently to cellular components. The risk of this adverse effect has been found to be correlated with the chemical stability of the AG, and assays have been described that monitor acyl migration by liquid chromatography coupled with mass spectrometry (LC-MS). This analysis can be challenging as it requires baseline chromatographic separation of the unmigrated 1-β-acyl glucuronide from the migrated isomers and thus needs to be individually optimized for each aglycone. Therefore, a high-throughput assay that eliminates LC method development is desirable. Herein, we report an improved acyl glucuronide stability assay based on the rate of 18O-incorporation from [18O] water, which is compatible with high-throughput bioanalytical LC-MS workflows. Synthetic AGs with shorter migration half-lives showed faster incorporation of 18O. The level of differential incorporation of 18O following a 24 h incubation correlates well with the migration tendency of AGs. This assay was developed further, exploring in situ generation of AGs by human hepatic microsomal fraction. The results from 18 in situ-formed acyl glucuronides were similar to those obtained using authentic reference standards. In this format, this new 18O-labeling method offers a simplified workflow, requires no LC method development or AG reference standard, and thus facilitates AG liability assessment in early drug discovery.

Metabolomics Analysis Reveals the Differences Between Bupleurum chinense DC. and Bupleurum scorzonerifolium Willd.

Bupleurum chinense DC. and Bupleurum scorzonerifolium Willd. are two varieties of Bupleuri Radix in Chinese Pharmacopoeia 2020. The clinical efficacy of the two bupleurum species is different. The difference in clinical efficacy is closely related to the composition of plant metabolites. In order to analyze the difference in metabolites, we used liquid chromatography coupled with mass spectrometry (LC-MS) for untargeted metabolome and gas chromatography coupled with mass spectrometry (GC-MS) for widely targeted metabolome to detect the roots (R), stems (S), leaves (L), and flowers (F) of two varieties, and detected 1,818 metabolites in 25 classes. We performed a statistical analysis of metabolites. Differential metabolites were screened by fold-change and variable importance in the projection values of the OPLS-DA model, and significant differences were found among different groups. The content of active components (triterpenoid saponins) was found to be high in the BcR group than in the BsR group. Other pharmacological metabolites were significantly different. By Kyoto Encyclopedia of Genes and Genomes annotation and enrichment analysis, we found that differential metabolites of the aboveground parts mainly concentrated in monoterpenoid biosynthesis, while the differential metabolites of the root mainly concentrated in sesquiterpenoid and triterpenoid biosynthesis. Differences in metabolic networks may indirectly affect the metabolic profile of Bc and Bs, leading to differences in clinical efficacy. Our study provides a scientific basis for subsequent biosynthesis pathway and related bioactivity research, and provides a reference for developing non-medicinal parts and guiding the clinical application of Bupleuri Radix.

Al/Cu-PILC as a Photo-Fenton Catalyst: Paracetamol Mineralization.

Pillared clays have shown to effectively catalyze the photo-Fenton process without the necessity of acidic conditions, which is a very attractive feature from the perspective of environmentally friendly processes, especially when high natural abundance of chemical elements are incorporated. In this work, the catalytic activity of Al/Cu interlayered pillared clays for the degradation and mineralization of paracetamol through a photo-Fenton-like process was investigated. Al/Cu-pillared clays were prepared by adding ane Al/Cu pillaring solution to a bentonite suspension. X-ray diffraction (XRD) confirmed the enlargement of the interlayer space of the clay provoked by the pillaring process and Al and Cu species in the prepared samples were verified by atomic absorption spectroscopy (AAS). The specific surface area of pure bentonite was 2-fold increased after the Al/Cu pillaring process. A synthetic paracetamol solution with an initial concentration of 100 ppm was prepared for the assessment of the activity of the prepared materials. Different catalyst concentrations were tested (0.2, 0.5, 0.75, and 1 g L–1) and the complete removal of paracetamol was achieved in all cases, but the highest mineralization rate (69.8 mg total organic carbon (TOC) gcat–1 h–1) corresponds to the catalyst loading of 0.5 g L–1. An ultraviolet-C (UVC) light source was employed, and no adjustment of the pH to acidic conditions was needed to achieve these results. Liquid chromatography coupled to mass spectroscopy (LC-MS) was employed to identify the reaction intermediates of paracetamol degradation. A proposed pathway for the oxidation of paracetamol molecule is presented. The effect of Cu content in the pillared clay and the stability and reusability of the catalyst were also assessed. The kinetic constants of paracetamol removal were 0.2318 and 0.0698 min–1, under photo-Fenton and UV + H2O2 processes, respectively.

PH regulated rapid photocatalytic degradation of methylene blue dye via niobium-nitrogen co-doped titanium dioxide nanostructures under sunlight

Niobium and nitrogen co-doped titanium dioxide (Nb-N-TiO2) semiconductor nanostructures were synthesized through a facile sol-gel protocol using titanium tetra iso-propoxide (TTIP), urea and niobium pentoxide as precursors followed by calcination at 450 °C for 4 h. The synthesized nanomaterial (Nb-N-TiO2) was characterized via Fourier Transform Infrared (FTIR) and Raman spectroscopy, UV-Visible (UV-Vis) Spectroscopy, Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET) technique, Dynamic Light Scattering (DLS) technique and ZETA Potential analysis. The band gap of Nb-N-TiO2 was reduced as compared to TiO2 due to reduced space between valance and conduction band which also reduced the electron-hole (e-, h+) recombination and led to better photocatalytic activity of the Nb-N-TiO2 as confirmed by TAUC plot. Photocatalytic activity of Nb-N-TiO2 was investigated for degradation of methylene blue (MB) dye under sunlight as cheaper light source. Factors like dye concentration, dosage of catalyst, volume of solution time and pH were studied and optimized for MB degradation. Under finally optimized conditions, 97% of 25 ppm MB was degraded just in one minute using 45 mg of photocatalyst. The co-doped nanocatalyst, was re-used for MB degradation upto 4th cycle with its efficiency reduced to 75% which shows a better catalytic role by the catalyst. Degradation products of MB were recognized through electrospray ionization coupled mass spectroscopy (ESI-MS) and liquid chromatography coupled mass spectroscopy (LC-MS) techniques. The catalyst was also applied for MB degradation in tap water sample.

Convolutional Neural Network-Based Compound Fingerprint Prediction for Metabolite Annotation.

Metabolite annotation has been a challenging issue especially in untargeted metabolomics studies by liquid chromatography coupled with mass spectrometry (LC-MS). This is in part due to the limitations of publicly available spectral libraries, which consist of tandem mass spectrometry (MS/MS) data acquired from just a fraction of known metabolites. Machine learning provides the opportunity to predict molecular fingerprints based on MS/MS data. The predicted molecular fingerprints can then be used to help rank putative metabolite IDs obtained by using either the precursor mass or the formula of the unknown metabolite. This method is particularly useful to help annotate metabolites whose corresponding MS/MS spectra are missing or cannot be matched with those in accessible spectral libraries. We investigated a convolutional neural network (CNN) for molecular fingerprint prediction based on data acquired by MS/MS. We used more than 680,000 MS/MS spectra obtained from the MoNA repository and NIST 20, representing about 36,000 compounds for training and testing our CNN model. The trained CNN model is implemented as a python package, MetFID. The package is available on GitHub for users to enter their MS/MS spectra and corresponding putative metabolite IDs to obtain ranked lists of metabolites. Better performance is achieved by MetFID in ranking putative metabolite IDs using the CASMI 2016 benchmark dataset compared to two other machine learning-based tools (CSI:FingerID and ChemDistiller).

RNA Cleavage Properties of Nucleobase-Specific RNase MC1 and Cusativin Are Determined by the Dinucleotide-Binding Interactions in the Enzyme-Active Site.

Knowledge of the cleavage specificity of ribonucleases is critical for their application in RNA modification mapping or RNA-protein binding studies. Here, we detail the cleavage specificity and efficiency of ribonuclease MC1 and cusativin using a customized RNA sequence that contained all dinucleotide combinations and homopolymer sequences. The sequencing of the oligonucleotide digestion products by a semi-quantitative liquid chromatography coupled with mass spectrometry (LC-MS) analysis documented as little as 0.5–1% cleavage levels for a given dinucleotide sequence combination. While RNase MC1 efficiently cleaved the [A/U/C]pU dinucleotide bond, no cleavage was observed for the GpU bond. Similarly, cusativin efficiently cleaved Cp[U/A/G] dinucleotide combinations along with UpA and [A/U]pU, suggesting a broader specificity of dinucleotide preferences. The molecular interactions between the substrate and active site as determined by the dinucleotide docking studies of protein models offered additional evidence and support for the observed substrate specificity. Targeted alteration of the key amino acid residues in the nucleotide-binding site confirms the utility of this in silico approach for the identification of key interactions. Taken together, the use of bioanalytical and computational approaches, involving LC-MS and ligand docking of tertiary structural models, can form a powerful combination to help explain the RNA cleavage behavior of RNases.

Identification of Anti-Proliferative Compounds from Genista monspessulana Seeds through Covariate-Based Integration of Chemical Fingerprints and Bioactivity Datasets.

Genista monspessulana (L.) L.A.S. Johnson (Fabaceae) is a Mediterranean plant introduced to South America and other regions for ornamental purposes. However, it is considered an invasive shrub due to its reproductive vigor in many areas. Unlike other Genista plants, G. monspessulana has few studies disclosing its biologically active components, particularly cytotoxic agents against cancer cells. Thus, as part of our research on anti-proliferative bioactives, a set of ethanolic seed extracts from ten accessions of G. monspessulana, collected in the Bogotá plateau, were evaluated against four cell lines: PC-3 (prostate adenocarcinoma), SiHa (cervical carcinoma), A549 (lung carcinoma), and L929 (normal mouse fibroblasts). Extracts were also analyzed through liquid chromatography coupled with mass spectrometry (LC/MS) to record chemical fingerprints and determine the composition and metabolite variability between accessions. Using multiple covariate statistics, chemical and bioactivity datasets were integrated to recognize patterns and identify bioactive compounds among studied extracts. G. monspessulana seed-derived extracts exhibited dose-dependent antiproliferative activity on PC-3 and SiHa cell lines (>500 µg/mL < IC50 < 26.3 µg/mL). Seven compounds (1–7) were inferred as the compounds most likely responsible for the observed anti-proliferative activity and subsequently isolated and identified by spectroscopic techniques. A tricyclic quinolizidine (1) and a pyranoisoflavone (2) were found to be the most active compounds, exhibiting selectivity against PC-3 cell lines (IC50 < 18.6 µM). These compounds were used as precursors to obtain a quinolizidine-pyranoisoflavone adduct via Betti reaction, improving the activity against PC-3 and comparable to curcumin as the positive control. Results indicated that this composition–activity associative approach is advantageous to finding those bioactive principles efficiently within active extracts. This correlative association can be employed in further studies focused on the targeted isolation of anti-proliferative compounds from Genista plants and accessions.

A Divergent Selection on Breast Meat Ultimate pH, a Key Factor for Chicken Meat Quality, is Associated With Different Circulating Lipid Profiles.

Background: Chicken meat has become a major source of protein for human consumption. However, the quality of the meat is not yet under control, especially since pH values that are too low or too high are often observed. In an attempt to get a better understanding of the genetic and biochemical determinants of the ultimate pH, two genetic lines of broilers were divergently selected for low (pHu−) or high (pHu+) breast meat pHu. In this study, the serum lipidome of 17-day-old broilers from both lines was screened for pHu markers using liquid-chromatography coupled with mass spectrometry (LC-HRMS). Results: A total of 185 lipids belonging to 4 groups (glycerolipids, glycerophospholipids, sterols, sphingolipids) were identified in the sera of 268 broilers from the pHu lines by targeted lipidomics. The glycerolipids, which are involved in energy storage, were in higher concentration in the blood of pHu− birds. The glycerophospholipids (phosphatidylcholines, phosphatidylethanolamines) with long and polyunsaturated acyl chains were more abundant in pHu+ than in pHu− while the lysophosphatidylcholines and lysophosphatidylethanolamines, known to be associated with starch, were observed in higher quantity in the serum of the pHu− line. Finally, the concentration of the sterols and the ceramides, belonging to the sphingolipids class, were higher in the pHu+ and pHu−, respectively. Furthermore, orthogonal partial least-squares analyses highlighted a set of 68 lipids explaining 77% of the differences between the two broilers lines (R2Y = 0.77, Q2 = 0.67). Among these lipids, a subset of 40 predictors of the pHu value was identified with a Root Mean Squared Error of Estimation of 0.18 pH unit (R2Y = 0.69 and Q2 = 0.62). The predictive model of the pHu value was externally validated on 68 birds with a Root Mean Squared Error of Prediction of 0.25 pH unit. Conclusion: The sets of molecules identified will be useful for a better understanding of relationship between serum lipid profile and meat quality, and will contribute to define easily accessible pHu biomarkers on live birds that could be useful in genetic selection.

Evolution of 17-β-estradiol, estrone and estrone-sulfate concentrations in late pregnancy of different breeds of mares using Liquid Chromatography and Mass Spectrometry

This study describes 17-β-estradiol (E2), estrone (E1) and estrone-sulfate (E1S) concentrations between 4 and 11 months in healthy equine pregnancies of two different breeds using Liquid Chromatography coupled to Mass-Spectrometry (LC-MS).In 2 stud-farms including 15 Spanish PureBred (SPB) and 11 Showjumping (SJ) types mares, combined thickness of the uterus and the placenta (CTUP) was measured and blood was sampled monthly between 4 and 11 months of gestation. Concentrations of E2, E1 and E1S were assayed with LC-MS in mares with normal CTUP. Effects of breed, day of pregnancy and mare's parity and age on estrogens concentrations were investigated.Peak of E2 was observed at 5 months (median: 46.4 pg/mL; maximum: 201.5 pg/mL). A strong correlation was observed between E1 and E1S (p < 0.0001, r = 0.85). Peak of E1 (median: 571.0 pg/mL; maximum: 1641.9 pg/mL) and E1S (median: 573.6 ng/mL; maximum: 997.6 ng/mL) concentrations was observed at the 5th month and then E1S decreased quicker than E1 until the end of pregnancy. Higher E2 and E1 concentrations were observed in SJ than in SPB mares between the 6th and the 8th months. No difference between breeds was observed for E1S monthly evolution.Estrogen peak values were all observed at 5 months. Unlike recent LC-MS studies, E1S values observed here were in the same range than those previously established using immuno-assays. After the 6th month, E1S decreased quicker than E1. Effect of breed only observed on non-sulfonated estrogens should be further confirmed. These findings confirm that sulfonation activity of the allantochorion may be limited after the 6th month.

Proteomic insight into the venom composition of the largest European rear-fanged snake, Malpolon monspessulanus monspessulanus

Snake envenomations constitute a worldwide neglected tropical disease, with the vast majority of lethal bites inflicted by front-fanged snakes from the viperid and elapid groups. Rear-fanged snakes (colubrids) were often considered harmless and as a result, are much less studied, but several documented deaths have suggested potent venom in this group as well. The largest European snake (Malpolon monspessulanus monspessulanus), known as the “Montpellier snake”, is such a rear-fanged snake that belongs to the Lamprophiidae family. Its venom remains largely unknown but cases of envenomation with neurological symptoms have been reported. Here, we provide the first insights into the composition of its venom using mass spectrometry methods. First, liquid chromatography coupled mass spectrometry analysis of the manually collected venom samples reveals a complex profile, with the majority of masses encompassing the range 500–3000 Da, 4000–8000 Da, and 10 000–30 000 Da. Next, shotgun proteomics allowed the identification of a total of 42 different known families of proteins, including snake venom metalloproteinases, peptidase M1, and cysteine-rich secretory proteins, as the most prominent. Interestingly, three-finger toxins were not detected, suggesting that neurotoxicity may occur via other, yet to be determined, toxin types. Overall, our results provide the basis for a better understanding of the effects of a peculiar snake venom on human symptomatology, but also on the main prey consumed by this species.

Development of a Novel Analytical Method for Determining Trazodone in Human Plasma by Liquid Chromatography Coupled With Mass Spectrometry Coupled With Automatic 2-Dimensional Liquid Chromatograph-Mass Spectrometer Coupler 9500 and Its Application to Therapeutic Drug Monitoring.

Trazodone (TZD) is a tetracyclic serotonin antagonist and reuptake inhibitor that is used as a second-generation phenylpiperazine antidepressant. However, the plasma concentrations of TZD have shown individual variations in clinical practice. Quantification of TZD plasma concentrations may be an effective and valuable method to balance the clinical efficacy and adverse reactions. This study aimed to establish a novel liquid chromatography coupled with mass spectrometry (LC-MS) assay for measuring TZD concentrations in human plasma for therapeutic drug monitoring (TDM). After protein precipitation with acetonitrile, LC-MS quantification of TZD was performed in the multiple reaction monitoring mode with chromatographic separation using a mobile phase of MeOH and 0.1% formic acid in water. This method validation intends to investigate specificity, sensitivity, linearity, precision, accuracy, recovery, matrix effect, and stability according to United states food and drug administration guidelines. This method showed good selectivity because no interfering peaks were observed in the plasma samples during the 2-minute run time. The range of the calibration curve was 1-3000 ng/mL. The detection and quantification limits were 0.3 and 1 ng/mL, respectively. The intraday and interday accuracies were 96.5%-103.4%, with precision relative SD% values of <5%, except for the limit of quality. The mean TZD recovery from human plasma was 95.4%-104.5%. Finally, this method was successfully applied to TDM in 20 patients. The TZD plasma concentrations of the patients ranged between 21.5 and 2267.3 ng/mL. A novel analytical method was established to measure TZD by LC-MS coupled with an automatic 2-dimensional liquid chromatograph mass spectrometer coupler 9500 (LC-MS/MS-Mate 9500), which is superior to the ordinary LC-MS system in separation, transport, anti-interference, sensitivity, and quantitative analysis stability.

Elucidation of the Lipid Composition of Hemp (Cannabis sativa L.) Products by Means of Gas Chromatography and Ultra-High Performance Liquid Chromatography Coupled to Mass Spectrometry Detection.

The growing demand in natural matrices that represent a source of dietary and nutraceutical molecules has led to an increasing interest in Cannabis sativa, considered to be a multipurpose, sustainable crop. Particularly, the considerable content in essential fatty acids (FAs) makes its derived-products useful food ingredients in the formulation of dietary supplements. In this research, the FA and triacylglycerol (TAG) composition of hempseed oils and flours were investigated using gas chromatography coupled to mass spectrometry and flame ionization detection as well as liquid chromatography coupled to mass spectrometry (LC-MS), respectively. Furthermore, a recently introduced linear retention index (LRI) approach in LC was successfully employed as a useful tool for the reliable identification of TAG species. A total of 30 FAs and 62 glycerolipids were positively identified in the investigated samples. Relative quantitative analyses confirmed linoleic acid as the most abundant component (50–55%). A favorable omega6/omega3 ratio was also measured in hemp-derived products, with the α-linolenic acid around 12–14%. Whereas, γ-linolenic acid was found to be higher than 1.70%. These results confirm the great value of Cannabis sativa as a source of valuable lipids, and the further improvement of the LRI system paves the way for the automatization of the identification process in LC.