Comparison Of Mass Spectra Research Articles

Characterization of a Novel Male Pheromone Compound in Leucoptera sinuella (Lepidoptera: Lyonetiidae) and Its Role in Courtship Behavior.

The poplar moth, Leucoptera sinuella (Lepidoptera: Lyonetiidae), is widely distributed across Europe, Asia, and parts of Africa. It was first identified in Chile in 2015 and has since become a significant pest in the agricultural sector. Additionally, economic losses are further aggravated by the presence of L. sinuella pupae in nearby fruit orchards. This study investigated the presence of a male-produced sex pheromone in L. sinuella, focusing on the hairpencil (HP) glands, which are known as dissemination structures for male pheromones in lepidopterans. Male HP glands were solvent-extracted and analyzed by gas chromatography-mass spectrometry. Chemical microderivatization and comparisons of mass spectra and retention indices of natural compounds with synthetic standards led to the identification of two compounds: (Z)-3-decenyl hexanoate (the major component) and (Z)-3-decen-1-ol (a minor component). Although electrophysiological assays did not show detectable antennal responses to (Z)-3-decenyl hexanoate, behavioral bioassays demonstrated its role as a short-range courtship signal in L. sinuella. Males with ablated hairpencils exhibited significantly reduced courtship success compared to controls; however, exposure of females to synthetic (Z)-3-decenyl hexanoate or HP extract restored male courtship success. To our knowledge, (Z)-3-decenyl hexanoate has not been previously reported as a sex pheromone component in any insect species, making this discovery an intriguing addition to the diversity of chemical communication in insects.

Production and Characterization of Bioethanol Using Native Microbial Isolates from Decomposed Maize Cob via Simultaneous Saccharification and Fermentation

Maize cob a major component of agricultural waste composed mainly of cellulose that can be converted to bioethanol through fermentation as means of waste management. Achieving enhances bioethanol yield without ascertaining proper conversion pathway may be subjective. Therefore, this research aimed at converting maize cob to bioethanol through fermentation using natives microbial isolates from decomposed maize cob via Response Surface Methodology. Microbial strains used were Pichia kudriavzevii strains with accession number KP998095.1 and MN861069.1. A pH value of 5.5 corresponded to bioethanol yield of 52.45 g/L, pH was observed to be sensitive to fermentation hence influence the extent of fermentation process. Optical density (O. D610nm) of 2.2 after eight (8) days of fermentation corresponded to bioethanol yield of 52.45 g/L. The growth pattern observed in most of the samples followed a typical microbial growth pattern depicting lag, log and stationary phases. Reducing soluble sugar of 23.5 mg/L on enzyme hydrolysis corresponded to bioethanol yield of 52.45 g/L, reducing soluble sugar content of the experimental samples were observed to decrease as the fermentation progresses. The infrared spectra of the optimum sample distillate of bioethanol from the fermentation revealed the presence of OH at 3311.7 cm-1 stretching band and C = C at 1636.3 cm−1 stretching band. The elemental compositions of the distillate were oxygen (31.03%), hydrogen (9.74%), carbon (56.85%), nitrogen (1.92%) and sulphur (0.46%) which confirmed the presence of bioethanol. The empirical formula of the best distillate using C, H, and O compositions (%) was found to be C2H5OH, hence revealed the presence of bioethanol. The result of the GC-MS analysis showed that mass spectra comparison of the various peaks revealed the presence of bioethanol as the largest peak with 76.38% ethanol by concentration. Maize cob can be said to be a promising feedstock for bioethanol production using native microbial isolates.

Non-Target Screening of Chemicals in Selected Cotton Products by GC/MS and Their Safety Assessment.

Cotton is used for the production of textiles, hygiene and cosmetic materials. During cultivation and technological processes, various types of substances (surfactants, softeners, lubricants, etc.) penetrate cotton, which can have a harmful effect on both the human body and the environment. The aim of this study was to analyze selected cotton products in order to identify the substances contained and to describe the potential possibilities of inducing textile contact dermatitis (CD). The impact of the identified compounds on the aquatic environment was also taken into account. Nine samples of cotton clothing and seven samples of cotton pads from various manufacturers were tested. Samples after extraction using the FUSLE (Focused Ultrasonic Liquid Extraction) technique were analyzed with GC/MS. Qualitative analysis was based on comparing mass spectra with library spectra using the following mass spectra deconvolution programs: MassHunter (Agilent), AMDIS (NIST), and PARADISE (University of Copenhagen). The parameter confirming the identification of the substance was the retention index. Through the non-target screening process, a total of 36 substances were identified, with an average AMDIS match factor of approximately 900 ("excellent match"). Analyzing the properties of the identified compounds, it can be concluded that most of them have potential properties that can cause CD, also due to the relatively high content in samples. This applies primarily to long-chain alkanes (C25-C31), saturated fatty acids, fatty alcohols (e.g., oleyl alcohol), and fatty acid amides (e.g., oleamide). However, there are not many reports describing cases of cotton CD. Information on the identified groups of compounds may be helpful in the case of unexplained sources of sensitization when the skin comes into contact with cotton materials. Some of the identified compounds are also classified as dangerous for aquatic organisms, especially if they can be released during laundering.

Proteomic analysis of nontuberculous bacteria protein spectra as the element of subtyping of strains.

For the present, matrix-assisted laser desorption/ionization-time-of-flight (MALDI-ToF) mass spectrometry is the fastest and the most correct method for species identification of microorganisms. Apart from species-level identification, it allows to use a variety of approaches for the analysis and comparison of protein spectra of microorganisms of the same species, which are isolated from a patient at various disease states, that can be used in routine microbiological practice in laboratories fitted with mass analyzers. Two strains of Mycobacterium fortuitum and two strains of Mycobacterium peregrinum were isolated from sputum samples, which were obtained from patients with different clinical aspects of mycobacteriosis, whereat were reinoculated on the universal chromogenic culture medium "UriSelect 4." Further, the MALDI-ToF mass spectrometry method was used, aiming to obtain protein profiles, which were analyzed using the FlexAnalysis 3.0 software package. Results of the statistical proteomic comparison of mass spectra were visualized using MALDI Biotyper 3.0 Offline Classification software. Presented clinical examples demonstrate that strains of the same species, which are isolated from the same patient at different times of infection, change their cultural properties. Dynamic changes in cultural properties are reflected in changes in protein profiles by comparison spectra of isolates at different stages of colonization, which is reflected in the correlation with the clinical condition of the patient. Thus, the mentioned examples of proteomic analysis, using MALDI-ToF mass spectrometry, demonstrate the possibility of subtyping of strains, that are isolated on a universal chromogenic culture medium, in case of detection in the culture signs of population's heterogeneity, based on cultural properties.

An analysis of Gursey-Radicati mass formula for tetraquark systems

In this work, the extended Gursey-Radicati mass formula is used to analyze the masses of the tetraquark system with configurations /, /, / and (Q = c, b). The discovery of two singly heavy tetraquark structures and at LHCb acts as a motivation for this work. They were observed in the and invariant mass spectra in two B-decay processes and , respectively. By using the SU(3) f flavor representation, we classified the recently observed singly heavy tetraquarks having quark content and in octet representation with J P value 0+ and forming the isospin triplet(I = 1). Our thorough comparison of mass spectra with both experimental and theoretical data demonstrates reasonable agreement. Further, decay channels and widths for the hidden-charm tetraquark states are computed in the framework of the diquark-antidiquark model. Our results may provide useful enlightenment for future experimental studies.

Evolution of organic carbon in the laboratory oxidation of biomass-burning emissions

Abstract. Biomass burning (BB) is a major source of reactive organic carbon into the atmosphere. Once in the atmosphere, these organic BB emissions, in both the gas and particle phases, are subject to atmospheric oxidation, though the nature and impact of the chemical transformations are not currently well constrained. Here we describe experiments carried out as part of the FIREX FireLab campaign, in which smoke from the combustion of fuels typical of the western United States was sampled into an environmental chamber and exposed to high concentrations of OH, to simulate the equivalent of up to 2 d of atmospheric oxidation. The evolution of the organic mixture was monitored using three real-time time-of-flight mass spectrometric instruments (a proton transfer reaction mass spectrometer, an iodide chemical ionization mass spectrometer, and an aerosol mass spectrometer), providing measurements of both individual species and ensemble properties of the mixture. The combined measurements from these instruments achieve a reasonable degree of carbon closure (within 15 %–35 %), indicating that most of the reactive organic carbon is measured by these instruments. Consistent with our previous studies of the oxidation of individual organic species, atmospheric oxidation of the complex organic mixture leads to the formation of species that on average are smaller and more oxidized than those in the unoxidized emissions. In addition, the comparison of mass spectra from the different fuels indicates that the oxidative evolution of BB emissions proceeds largely independent of fuel type, with different fresh smoke mixtures ultimately converging into a common, aged distribution of gas-phase compounds. This distribution is characterized by high concentrations of several small, volatile oxygenates, formed from fragmentation reactions, as well as a complex pool of many minor oxidized species and secondary organic aerosol, likely formed via functionalization processes.

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome.

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions. IMPORTANCE Metaproteomic analysis can provide valuable insights into the functions of microbial and cellular communities by identifying a broad, untargeted set of proteins. The databases used in the analysis of metaproteomic data influence results by defining what proteins can be identified. Moreover, the size of the database impacts the number of identifications after accounting for false discovery rates (FDRs). Few studies have tested the performance of different strategies for building a protein database to identify proteins from metaproteomic data and those that have largely focused on highly diverse microbial communities. We tested a range of databases on CVL samples and found that a hybrid sample-matched approach, using publicly available proteins from organisms present in the samples, as well as proteins translated from metagenomic sequencing of the samples, had the best performance. However, our results also suggest that public sequence databases will continue to improve as more bacterial genomes are published.

Essential Oils of <i>Etlingera acanthodes</i> A.D. Poulsen, An Endemic Ginger from Sulawesi Island

Etlingera acanthodes A.D. Poulsen is a ginger endemic to Sulawesi, and there is no research on its essential oils. The Essential oil information of E. acanthodes is the first reported and has a high novelty. The objective of the study is to analyze the component of E. acanthodes essential oils, which are endemic to Sulawesi. The essential oils obtained by hydrodistillation of the leaves, stems, flowers, and rhizomes of E. acanthodes A.D. Poulsen. The samples were analyzed by GC-MS method using the Agilent Technologies 7890 Gas Chromatograph with Auto Sampler. Data analysis of essential oils of GC-MS results were determined based on comparing mass spectra from the NIST 2005 v.2.0 library and Wiley 7 library 2003. The oils of E. acanthodes contain terpenoids, phenolic, steroids, and other compounds. Phenolic compounds (39.56%) predominate in leaves, other compounds (41.25%) on stems, diterpenes hydrocarbons (77.3%) in flowers, and other compounds (43.5%) and steroids (40.4%) on rhizomes. The five main compounds of E. acanthodes are Neophytadiene; (+)-De-O-Methylcentrolobine; Cholest-5-En-3-Ol,23-Ethyl-,(3. Beta.23S)-; 9,12-Octadecadienoic Acid, Phenol, 2-ethyl-. The analysis found several compounds that can be used for industry and medicine in the future.

Statistical Framework for Identifying Differences in Similar Mass Spectra: Expanding Possibilities for Isomer Identification.

Isomeric molecules are important analytes in many biological and chemical arenas, yet their similarity poses challenges for many analytical methods, including mass spectrometry (MS). Tandem-MS provides significantly more information about isomers than intact mass analysis, but highly similar fragmentation patterns are common and include cases where no unique m/z peaks are generated between isomeric pairs. However, even in such situations, differences in peak intensity can exist and potentially contain additional information. Herein, we present a framework for comparing mass spectra that differ only in terms of peak intensity and include calculation of a statistical probability that the spectra derive from different analytes. This framework allows for confident identification of peptide isomers by collision-induced dissociation, higher-energy collisional dissociation, electron-transfer dissociation, and radical-directed dissociation. The method successfully identified many types of isomers including various d/l amino acid substitutions, Leu/Ile, and Asp/IsoAsp. The method can accommodate a wide range of changes in instrumental settings including source voltages, isolation widths, and resolution without influencing the analysis. It is shown that quantification of the composition of isomeric mixtures can be enabled with calibration curves, which were found to be highly linear and reproducible. The analysis can be implemented with data collected by either direct infusion or liquid-chromatography MS. Although this framework is presented in the context of isomer characterization, it should also prove useful in many other contexts where similar mass spectra are generated.

DA_2DCHROM — a data alignment tool for applications on real GC × GC–TOF samples

Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC–MS) has great potential for analyses of complicated mixtures and sample matrices, due to its separation power and possible high resolution. The second component of the measurement results, the mass spectra, is reproducible. However, the reproducibility of two-dimensional chromatography is affected by many factors and makes the evaluation of long-term experiments or cross-laboratory collaborations complicated. This paper presents a new open-source data alignment tool to tackle the problem of retention time shifts — with 5 different algorithms implemented: BiPACE 2D, DISCO, MSort, PAM, and TNT-DA, along with Pearson’s correlation and dot product as optional methods for mass spectra comparison. The implemented data alignment algorithms and their variations were tested on real samples to demonstrate the functionality of the presented tool. The suitability of each implemented algorithm for significantly/non-significantly shifted data was discussed on the basis of the results obtained. For the evaluation of the “goodness” of the alignment, Kolmogorov–Smirnov test values were calculated, and comparison graphs were generated. The DA_2DChrom is available online with its documentation, fully open-sourced, and the user can use the tool without the need of uploading their data to external third-party servers.Graphical

Volatiles of the Apicomplexan Alga Chromera velia and Associated Bacteria.

Volatiles released by the apicomplexan alga Chromera velia CCAP1602/1 and their associated bacteria have been investigated. A metagenome analysis allowed the identification of the most abundant heterotrophic bacteria of the phycosphere, but the isolation of additional strains showed that metagenomics underestimated the complexity of the algal microbiome, However, a culture-independent approach revealed the presence of a planctomycete that likely represents a novel bacterial family. We analysed algal and bacterial volatiles by open-system-stripping analysis (OSSA) on Tenax TA desorption tubes, followed by thermodesorption, cryofocusing and GC-MS-analysis. The analyses of the alga and the abundant bacterial strains Sphingopyxis litoris A01A-101, Algihabitans albus A01A-324, "Coraliitalea coralii" A01A-333 and Litoreibacter sp. A01A-347 revealed sulfur- and nitrogen-containing compounds, ketones, alcohols, aldehydes, aromatic compounds, amides and one lactone, as well as the typical algal products, apocarotenoids. The compounds were identified by gas chromatographic retention indices, comparison of mass spectra and syntheses of reference compounds. A major algal metabolite was 3,4,4-trimethylcyclopent-2-en-1-one, an apocarotenoid indicating the presence of carotenoids related to capsanthin, not reported from algae so far. A low overlap in volatiles bouquets between C. velia and the bacteria was found, and the xenic algal culture almost exclusively released algal components.

Matrix Assisted Laser Desorption Ionisation/Time Of Flight (MALDI/TOF) mass spectrometry is not done revolutionizing clinical microbiology diagnostic

The introduction of MALDI TOF mass spectrometry (MALDI TOF MS) in clinical microbiology at the end of 2010 has been a revolution for microbial identification [1]. Unlike the conventional uses of MALDI TOF MS in clinical chemistry laboratories, detecting and quantifying specific peaks of known proteins, the routine use of MALDI TOF MS in clinical microbiology is based on the comparison of mass spectra (intensity of m/z values corresponding to peptides in the low m/z region) to a database of mass spectra, allowing the attribution of matching scores without any a priori on the corresponding proteins.

The Metabolite Content of the Post-Culture Medium of the Tree Fern Cyathea delgadii Sternb. Cell Suspension Cultured in the Presence of 2,4-D and BAP.

The aim of this study was to demonstrate the metabolic profile of post-culture medium as an expression of cell suspension metabolic activity of the tree fern Cyathea delgadii Sternb. The molecular profile of the tree fern’s cell culture has been never described, according to our knowledge. The cell suspension was established using ½ MS medium supplemented with various concentrations of 2,4-D and BAP. The optimal concentrations were 2.0 mg·L−1 and 0.2 mg·L−1, respectively. The cell suspension initially showed an organized system of cell division and later unorganized cell proliferation. LC-MS and GC-MS were used to identify the chemical composition of the post-culture medium. The LC-MS analysis results suggested that the color of liquid medium could be due to the presence of flavonoid derivatives, as this group of compounds was represented by eight compounds. After GC-MS analysis based on retention indexes and thanks to mass spectra comparison, 130 natural products were recognized, belonging to various classes of primary and secondary metabolites.

Application of rapid air sampling and non-targeted analysis using thermal desorption comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry to accidental fire.

To be able to gauge the health risks and biological effects of e-waste fires, it is of key importance to know what types and amounts of chemicals are released when they occur. In this case study, we pumped 6-24L of air from an accidental fire at a recycling depot through a Tenax-TA tube and conducted comprehensive (non-targeted) analysis by thermal desorption/comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (TD/GC×GC/ToFMS). A special focus was placed on the search for halogenated compounds. More than 5000 components were detected in the atmosphere around the fire; however, component separation was insufficient, even when using GC×GC. The number of organohalogen compounds retrieved was increased about 1.8-fold by the refinement process of the exact mass spectrum using mass defect filtering (MDF) software. After processed by MDF, 386 peaks were concluded to be halogenated compounds. The major retrieved substances included chlorinated (or chlorinated-brominated) dioxins, chlorinated (or brominated) phenols, benzene, and various other halogenated aromatic compounds. Direct comparison of mass spectra was carried out to investigate the potential for qualitative and quantitative comparison of detected peaks without specific identification. The approximate quantitative values are summarized for each compound in the estimated substance group. Their ratios were estimated to be halogenated phenols: 13%, benzenes: 9.6%, dibenzo-p-dioxins: 9.6%, dibenzofurans: 8.4%, biphenyls; 7.4% and toluenes: 6.4%.

Machine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites.

In gas chromatography–mass spectrometry-based untargeted metabolomics, metabolites are identified by comparing mass spectra and chromatographic retention time with reference databases or standard materials. In that sense, machine learning has been used to predict the retention time of metabolites lacking reference data. However, the retention time prediction of trimethylsilyl derivatives of metabolites, typically analyzed in untargeted metabolomics using gas chromatography, has been poorly explored. Here, we provide a rationalized framework for machine learning-based retention time prediction of trimethylsilyl derivatives of metabolites in gas chromatography. We compared different machine learning paradigms, in addition to exploring the influence of the computational molecular structure representation to train the prediction models: fingerprint class and fingerprint calculation software. Our study challenged predicted retention time when using chemical ionization and electron impact ionization sources in simulated and real cases, demonstrating a good correct identity ranking capability by machine learning, despite observing a limited false identity filtering power in cases where a spectrum or a monoisotopic mass match to multiple candidates. Specifically, machine learning prediction yielded median absolute and relative retention index (relative retention time) errors of 37.1 retention index units and 2%, respectively. In addition, fingerprint class and fingerprint calculation software, as well as the molecular structural similarity between the training and test or real case sets, showed to be critical modulators of the prediction performance. Finally, we leveraged the structural similarity between the training and test or real case set to determine the probability that the prediction error is below a specific threshold. Overall, our study demonstrates that predicted retention time can provide insights into the true structure of unknown metabolites by ranking from the most to the least plausible molecular identity, and sets the guidelines to assess the confidence in metabolite identification using predicted retention time data.

Electrospray Ionization-Mass Spectrometry of Synthetic Polymers Functionalized with Carboxylic Acid End-Groups.

Electrospray ionization-mass spectrometry (ESI-MS) of low-charging synthetic polymers typically produces mass spectra exhibiting a bias toward the low-mass region of the polymer mass distribution. To examine the origin(s) of this ionization bias, narrow dispersity polystyrene polymers (Đ < 1.10) were prepared with ionizable carboxylic acid end-groups at one or both chain termini. The mixture complexity was further reduced through preparative size-exclusion chromatography (SEC), and these well-defined polymers were subjected to negative ion ESI-MS on a high-resolution instrument with a mass-to-charge (m/z) range up to 8000. Incorporation of one carboxylic acid end-group facilitated the generation of singly charged [M - H]- ions across the entire range of the mass analyzer. The comparison of mass spectra with size-exclusion chromatograms of the same polymer revealed an ionization bias toward lower masses, which was partially overcome through fractionation, modification of electrospray solvent, and increased declustering potentials. Incorporation of a second ionizable moiety within polymers of equivalent size facilitated multiply charged [M - 2H]2- ion formation with significantly improved ionization efficiency, spectral coverage of the molar mass distribution, and minimal cluster ion formation. These findings indicate that increased charging of polymers through multiple, well-defined sites of ionization can enhance volatilization and ionization of higher-mass polymers. Generation of higher-molecular-weight polymers in low-charge states-while possible under ideal conditions-competes ineffectively with either nonspecific, multiple-charging of similar sized polymers or ionization of the smaller polymers in the distribution.

Novel methyl-branched alkenones with up to five double bonds in saline lakes

Long-chain alkenones, a class of highly specific and widely used lipid biomarkers found in ocean and lake sediments, have been so far found as straight-chain alkyl ketones with 2 to 4 double bonds. Jaraula et al. (2010) reported assignments of a series of tri- to penta-unsaturated alkenones as straight-chain C38 methyl (C38Me) and C39 ethyl (C39Et) alkenones in Lake Fryxell, Antarctica. The same series of compounds were later found in sediments from Lake Van (Randlett et al., 2014). The structure assignments by Jaraula et al (2010) were primarily based on strong ions at [M−43]+ for C38 alkenones and [M−57]+ for C39 alkenones, which were interpreted as a loss of CH3CO and CH3CH2CO groups. However, such fragmentation is atypical for common straight-chain methyl and ethyl alkenones. In this study, we reanalyzed Lake Van sediment samples. We show these new C38 and C39 alkenones elute earlier than the common straight-chain C38Me and C39Et alkenones on a mid-polarity GC column. After hydrogenation, mass spectra of these new alkenones show distinct peaks at m/z 72 or 86 caused by McLafferty rearrangement, indicating a methyl substitution at the α position of the carbonyl group in these C38 and C39 alkenones (i.e., α-methyl-branched C38Me and C39Et). Our new assignments as methyl-branched alkenones are further confirmed by the synthesis of an analog α-methyl C25 methyl ketone and comparison of mass spectra. Double bond positions for branched C38:5Me (brC38:5Me) are found to be Δ4, Δ7, Δ14, Δ21 and Δ28 based on the mass spectrum of corresponding dimethyl disulfide adducts. Analysis of Lake Van alkenone data reveals that Ubr38MeK∗ based on brC38Me shows a trend similar to U37K for the past 270 ka, suggesting that the degree of unsaturation of branched alkenones is also sensitive to temperature.

Untargeted lipidomics analysis of Mori Fructus polysaccharide on acute alcoholic liver injury in mice using ultra performance liquid chromatography-quadrupole-orbitrap-high resolution mass spectrometry

Ethnopharmacological relevanceMori Fructus (MF) is a traditional Chinese medicine with long application history, which has protective effects on liver diseases. Mori Fructus polysaccharide (MFP) is one of the active ingredients of MF and possesses therapeutic effects against acute alcoholic liver injury. Recent researches have reported that the therapeutic effects of MFP might be related to the regulation of several lipid metabolic pathways. However, the mechanism of lipid metabolism was still unclear. Aim of the studyThis study aimed to investigate the regulatory effect of MFP on lipid metabolism in mice with acute alcoholic liver injury, and to enrich the application of its hepatoprotective effect. Materials and methodsFifty Specific Pathogen Free (SPF) Kunming (KM) male mice were divided into five groups randomly, including normal control group, model group, bifendate positive group (220 mg/ kg), MFPA1 group (50 mg/ kg) and MFPB1 group (50 mg/ kg). A model of acute alcoholic liver injury was established by treating the mice with ethanol. The liver sections were processed and histopathological changes was observed with hematoxylin and eosin staining. The secretion levels of biochemical indexes in the liver and serum were assayed by ELISA. The untargeted lipidomics analysis was performed on a Q Exactive Focus quadrupole orbitrap high resolution mass spectrometry coupled with a Dionex Ultimate 3000 RSLC (HPG) ultra-performance liquid chromatography (UPLC-Q-Orbitrap-HRMS) system (Thermo Fisher Scientific), with a HESI ionization source. ResultsIt was observed that abnormal glutamic-pyruvic transaminase enzyme (ALT), glutamic-oxaloacetic aminotransferase (AST), triglyceride (TG), superoxide dismutase (SOD), and malondialdehyde (MDA) concentrations were ameliorated after irrigation of MFP or bifendate. Histopathology examination showed that intragastric infusion of MFP can be helpful in the repair of damaged liver in mice. The multivariate analysis of hepatic lipids showed segregation of ethanol-fed groups from the normal controls. After the comparison of mass spectra, 10 lipids were found to have different content in the normal control group and the model group. Differential lipids that were increased by ethanol exposure included fatty acids, phosphatidylcholine, and lyso-phosphatidylethanolamine, whereas lyso-phosphatidylcholine decreased. Among them, 4 lipids almost returned to the level of normal mice after MFP treatment. ConclusionThe therapeutic effect of MFP on acute alcoholic liver injury may be achieved by regulating a variety of metabolic pathways, including linoleic acid metabolism, α - linolenic acid metabolism, and glycerolphospholipid metabolism.These results revealed that MFP efficiently exerted hepatoprotective benefits, and its potential effect was associated with the amelioration of lipid metabolism.

Evaluation of open search methods based on theoretical mass spectra comparison

BackgroundMass spectrometry remains the privileged method to characterize proteins. Nevertheless, most of the spectra generated by an experiment remain unidentified after their analysis, mostly because of the modifications they carry. Open Modification Search (OMS) methods offer a promising answer to this problem. However, assessing the quality of OMS identifications remains a difficult task.MethodsAiming at better understanding the relationship between (1) similarity of pairs of spectra provided by OMS methods and (2) relevance of their corresponding peptide sequences, we used a dataset composed of theoretical spectra only, on which we applied two OMS strategies. We also introduced two appropriately defined measures for evaluating the above mentioned spectra/sequence relevance in this context: one is a color classification representing the level of difficulty to retrieve the proper sequence of the peptide that generated the identified spectrum ; the other, called LIPR, is the proportion of common masses, in a given Peptide Spectrum Match (PSM), that represent dissimilar sequences. These two measures were also considered in conjunction with the False Discovery Rate (FDR).ResultsAccording to our measures, the strategy that selects the best candidate by taking the mass difference between two spectra into account yields better quality results. Besides, although the FDR remains an interesting indicator in OMS methods (as shown by LIPR), it is questionable: indeed, our color classification shows that a non negligible proportion of relevant spectra/sequence interpretations corresponds to PSMs coming from the decoy database.ConclusionsThe three above mentioned measures allowed us to clearly determine which of the two studied OMS strategies outperformed the other, both in terms of number of identifications and of accuracy of these identifications. Even though quality evaluation of PSMs in OMS methods remains challenging, the study of theoretical spectra is a favorable framework for going further in this direction.

Metabolomics approach based on LC-HRMS for the fast screening of iron(II)-chelating peptides in protein hydrolysates.

Production of iron-chelating peptides from protein hydrolysates requires robust and adequate screening methods to optimize their purification and subsequently valorize their potential antioxidant properties. An original methodology was developed for direct and sensitive screening of iron(II)-chelating peptides based on ion-pair reverse phase liquid chromatography (IP-RPLC) coupled to high-resolution mass spectrometry (HRMS). Peptide mixture was first added to iron(II) solution to form iron(II)-peptide complexes. Then IP-RPLC-HRMS analysis was conducted on this iron-peptide mixture and on the iron-free peptide solution for comparative mass spectra analysis. This protocol, initially applied to a range of low molecular weight standard peptides, allowed detection of [(Peptide-H)+56FeII]+ complex ion for iron(II)-chelating peptides (GGH, EAH, DAH, βAH, DMH, DTH, DSH). GGH was added in complex peptide mixtures and targeted analysis of [(GGH-H)+56FeII]+ complex showed a limit of detection (LOD) below 0.77mgL-1 of GGH. This protocol was finally tested in combination with metabolomics software and additional digital processing for non-targeted search for iron(II)-chelating peptides. Applicability of this new screening methodology has been validated by detection of GGH as iron(II)-chelating peptide when added at 0.77mgL-1 in casein hydrolysate. Graphical abstract.