Automated Mass Spectral Deconvolution Research Articles

Untargeted GC-MS metabolomics to identify and classify bioactive compounds in Combretum platypetalum subsp. oatesii (Rolfe) Exell (Combretaceae).

Combretum platypetalum is used in traditional African healing practices against different infections. Unfortunately, no scientific knowledge of its phytochemical composition exists, except for the isolation of two compounds from the leaves. Scientific study has been limited to the leaves only, despite the applications of stems and roots in traditional medicine practice and natural product drug discovery programs. Omics was applied to identify and classify different volatile and semivolatile bioactive compounds in the leaf, stem, and root parts of C. platypetalum. The thermal stability of the plant constituents at 60-65°C extraction temperature by Soxhlet and maceration at room temperature on the type, class, and concentration of compounds in the leaf was further investigated. A GC-MS untargeted metabolomics approach, automated deconvolution by the Automated Mass Spectral Deconvolution and Identification System (AMDIS) for GC-MS data, preprocessing by Metab R, and multivariate statistical data analysis were employed in this study. A total of 97 phytoconstituents, including 17 bioactive compounds belonging to the terpenoids, flavonoids, long-chain fatty acids, and other unclassified structural arrangements distributed across C. platypetalum, were identified for the first time. A correlation (r = 0.782; P = 0.000) between Soxhlet and maceration extraction methods relative to resolved chromatographic peak areas of metabolites was established. Findings corroborate the reported bio-investigation of its leaf extracts, its traditional uses, and previous findings from the Combretum genus. The results substantiate the possible applications of C. platypetalum in natural product drug discovery and provide a guide for future investigations.

Determination of Bioactive Compounds Against Bacterial Wilt of Potato (Ralstonia pseudosolanacearum sp. nov.) in Psidium guajava and Pelargonium zonale Leaf Extracts

Common guava (Psidium guajava) and Pelargonium (Pelargonium zonale) have shown in-vitro antibacterial activity against Ralstonia pseudosolanacearum sp. nov. in previous studies. However, their phytochemical constituents and bioactive compounds against the pathogen have not been identified. The present study investigated the phytochemical components of P. guajava and P. zonale leaf extracts by phytochemical screening and gas chromatography-mass spectrometry (GC-MS). Phytochemical screening was done using different solvents while 100 mg of the dried ethanolic extract pastes from each plant sample was subjected to GC-MS analysis. Automated mass spectral deconvolution and identification system software (AMDIS, US) was used to analyze chromatograms and spectra representing individual compounds. Compound identification was performed by comparing each of the mass spectra with the database of NIST 11 (Gaithersburg, MD, USA), Wiley 7N (John Wiley, NY, USA) and by comparing the calculated Kovats linear retention indices using retention times of n-alkane series against the values in the NIST webbook. Flavonoids, phenols, alkaloids, saponins, terpenoids and tannins were detected in both plant samples. GC-MS analysis revealed presence of 35 and 26 compounds from P. zonale and P. guajava respectively. Both P. zonale and P. guajava had 7 similar compounds with antibacterial properties; Fumaric acid, Phytol, Pyrogallol, 4-Hydroxybenzoic acid, Shikimic acid, Protocatechuic acid and 3, 4, 5-Trihydroxybenzoic acid ethyl ester but P. zonale had one additional antibacterial compound; Lactic acid. In both cases, Shikimic acid had the highest percent peak areas of 3.2% for P. zonale and 6.8% P. guajava respectively. Therefore, P. zonale and P. guajava can serve as alternative sources of active ingredients for formulation of commercial botanicals for the management of bacterial wilt of potato.

Development and Validation of a Single Step GC/MS Method for the Determination of 41 Drugs and Drugs of Abuse in Postmortem Blood

A toxicology laboratory often receives a high number of samples from cases (autopsies or clinical) that may require the quick delivery of trustworthy, accurate results. Thus, there is a great need for a fast and reliable method that is capable of identifying and determining a large number of drugs and drugs of abuse in biological matrices, and especially in blood. In the present study, we describe the development of a fast and simple gas chromatography–mass spectrometry (GC-MS) method for the determination of 41 drugs and drugs of abuse (DOA) in blood. Sample pre-treatment by alkaline liquid–liquid extraction (LLE) was studied through the utilization of different solvents and solvent-to-sample ratios (v/v), which aimed to achieve a greater extraction efficiency and detection sensitivity with a decreased need for large sample volumes. Butyl acetate with a sample-to-solvent ratio of 4:1 (1 mL blood: 0.25 mL butyl acetate) was the most efficient. The method was validated for all analytes, and the evaluation parameters were within the acceptance criteria. The coefficient of determination (R2) was between 0.9934 and 1, the limits of detection (LODs) ranged between 1 ng/mL and 113 ng/mL, and the limits of quantification (LOQs) were between 4 ng/mL and 375 ng/mL for all analytes. The determinations were accurate (accuracy% from 84% to 114%) and precise (RSD% from 0.66% to 14.8% for low concentrations). Deconvolution Reporting Software (DRS) for GC-MS was optimized and applied for data analysis to enhance the identification potential, thereby avoiding false identifications (false positives) and increased productivity. The NIST Automated Mass Spectral Deconvolution and Identification Software (AMDIS) and the analytical utility Retention Time Lock (RTL) Database Library assisted in data evaluation. The method was applied to 89 postmortem cases (history of mental disorders and use of psychiatric pharmaceuticals) in which diazepam (0.13 to 4.34 μg/mL), citalopram (0.04 to 0.24 μg/mL), alprazolam (0.01 to 0.12 μg/mL), olanzapine (0.009 to 0.083 μg/mL), mirtazapine (0.01 to 0.33 μg/mL), venlafaxine (0.006 to 0.92 μg/mL), haloperidol (0.007 to 0.13 μg/mL), and zolpidem (0.01 to 0.16 μg/mL) were successfully quantitated.

Polar and non-polar fraction from Origanum vulgare spp. hirtum methanolic extract – differences in their bioactivity on Chlamydomonas reinhardtii test system

Aim: To compare the bioactivity of both polar and non-polar fraction of Origanum vulgare spp. hirtum methanolic extract on Chlamydomonas reinhardtii. Material and methods: The polar and non-polar fractions were derived from aerial parts of Origanum vulgare ssp. hirtum, collected during the flowering stage from the ex-situ collection of IBER-BAS. GC/MS analysis of both fractions was done following the standard protocol. The measured mass spectra were deconvoluted by the Automated Mass Spectral Deconvolution and Identification System (AMDIS), before comparison with the databases. Chlamydomonas reinhardtii 137C+ (WT) was used as a test system. Spot-test, cell survival fraction (SF), test of “visible mutations” and CFGE (for measurement of induced DNA double-strand breaks (DSBs)) were applied. Results: The polar fraction did not possess genotoxic, mutagenic as well as DNA-damaging effect. The situation with the non-polar fraction was quite different. Even at the lowest concentration of 250 ppm, cell survival was decreased by 60% (SF = 0.41 ± 0.08). Treatment with concentrations equal to/or greater than 500 ppm resulted in around 100% lethality. A mild mutagenic effect was obtained for the concentration of 250 ppm non-polar fraction (IM = 4.83 ± 0.004). Well-expressed and concentration-dependent induction of DSBs for even the strong DNA fragmentation was observed after the treatment with the non-polar fraction. Conclusions: The different bioactivity of the two fractions correlated well with their different chemical composition. The polar fraction, rich in sugars, organic acids and flavonoid glycosides, did not possess genotoxic and mutagenic potential. The strong genotoxic potential of the non-polar fraction might be related to carvacrol content (37.08%), which is not present in the composition of the polar fraction. To the best of our knowledge, this study provides the first information that the carvacrol-rich non-polar fraction of Origanum vulgare spp. hirtum methanolic extract possesses genotoxic, mutagenic and DNA damaging effect on some low eukaryotes, such as C. reinhardtii. Further experiments with carvacrol should be done in order to clarify the exact mechanism of action.

Open Characterization of Vaping Liquids in Canada: Chemical Profiles and Trends.

Currently, there is a lack of comprehensive data on the diversity of chemicals present in vaping liquids. To address this gap, a non-targeted analysis of 825 vaping liquids collected between 2017 and 2019 from Canadian retailers was conducted. Prior to mass spectrometry analysis, samples were diluted 1:500 v/v with methanol or acetonitrile. Chemical compound separation and analysis was carried out using gas chromatography and triple quadrupole mass spectrometry (GC-MS/MS) systems operated in the full scan mode and mass range of 35–450 m/z. Mass spectrum for each sample was obtained in electron ionization at 70 eV and processed. Non-targeted identification workflow included use of automated mass spectral deconvolution and identification system (AMDIS), where required, as well as a number of commercially available spectral libraries. In order to validate identities, an in-house database of expected compounds previously detected in vaping liquids was used along with genuine analytical standards for compounds of interest. This resulted in a dataset of over 1,500 unique detected chemicals. Approximately half of these chemical compounds were detected only once in a single product and not in multiple products analyzed. For any sample analyzed, on average, 40% of the chemical constituents appeared to have flavouring properties. The remainder were nicotine and related alkaloids, processing, degradation or indirect additives, natural extractives and compounds with unknown roles. Data published here from the project on the Open Characterization of vaping liquids is unique as it offers a detailed understanding of products’ flavour chemical profiles, the presence and frequency of chemicals of potential health concern, as well as trends and changes in products’ chemical complexity over a three-year period. Non-targeted chemical surveillance such as this present valuable tools to public health officials and researchers in responding to emergent issues such as vaping associated lung injury or informing chemical based strategies which may be aimed at addressing product safety or appeal.

The Stool Volatile Metabolome of Pre-Term Babies.

The fecal metabolome in early life has seldom been studied. We investigated its evolution in pre-term babies during their first weeks of life. Multiple (n = 152) stool samples were studied from 51 babies, all <32 weeks gestation. Volatile organic compounds (VOCs) were analyzed by headspace solid phase microextraction gas chromatography mass spectrometry. Data were interpreted using Automated Mass Spectral Deconvolution System (AMDIS) with the National Institute of Standards and Technology (NIST) reference library. Statistical analysis was based on linear mixed modelling, the number of VOCs increased over time; a rise was mainly observed between day 5 and day 10. The shift at day 5 was associated with products of branched-chain fatty acids. Prior to this, the metabolome was dominated by aldehydes and acetic acid. Caesarean delivery showed a modest association with molecules of fungal origin. This study shows how the metabolome changes in early life in pre-term babies. The shift in the metabolome 5 days after delivery coincides with the establishment of enteral feeding and the transition from meconium to feces. Great diversity of metabolites was associated with being fed greater volumes of milk.

High-throughput identification of volatile and semi-volatile organic compounds in archaeological samples by gas chromatography–mass spectrometry combined with advanced chemometrics methodology

Identification of compounds in food residues from archaeological samples is important to determine their origin. However, high-throughput and accurate identification of compounds in archaeological samples is challenging. In this work, we propose the use of gas chromatography–mass spectrometry (GC–MS) combined with the recently developed chemometric tool autoGCMSDataAnal to identify compounds in archaeological samples. Samples excavated from a tomb of the Xihan dynasty about 2000 BP were used to demonstrate the performance of our proposed methodology. Under the optimized GC–MS instrumental conditions, more than 300 total ion chromatogram peaks were automatically extracted for each sample. Coeluted components were automatically resolved and registered to construct respective mass spectra, based on which compounds were accurately identified. Finally, more than 70 compounds were identified, among which more than 57% were confirmed by standards. A comparison with the automated mass spectral deconvolution and identification system indicates that the combination of GC–MS with autoGCMSDataAnal is suitable for compound identification in archaeological samples.

AMDIS-Metab R data manipulation for the geographical and floral differentiation of selected honeys from Zambia and Botswana based on volatile chemical compositions using SPME–GC–MS

A metabolomic classification of commercial and unprocessed organic honeys from Zambia and Botswana based on geographic and floral origins was done forthwith. Classification using gas chromatography–mass spectrometry/solid phase microextraction (GC–MS/SPME) was accomplished on three commercial and three unprocessed organic honeys. The Automated Mass spectral Deconvolution and Identification System (AMDIS), Metab R, an R platform application and MINITAB version 14 partial least squares (PLS) were used for data processing. Sixteen volatile metabolites in three commercial and 40 in three unprocessed organic honeys were identified, confirmed and formed the basis for differentiation. Database search showed that the honeys were polyfloral with major ingredients coming from common flowering plants, conifers and other gymnosperms such as Carica papaya L. (papaya), Monstera deliciosa (ceriman) and fruits, i.e., guava, melon and pineapple, endemic in the areas from which the honeys originated from.

Toxic compounds in a cutlery microenterprise: A case study.

The aim of this study was to characterize solid particulate aerosol derived from a cutlery microenterprise and to investigate substances associated with activities performed within the work environment. Suspended particulate matter (SPM) was collected at different locations in the cutlery workshop and near machines used by workers, using passive sampling devices fitted with polytetrafluoroethylene filters, onto which total particulate material was deposited. The substances present in the SPM were analyzed using gas chromatography-mass spectrometry (GC-MS). Identification of the substances was performed using the National Institute of Standards (NIST) library and automated mass spectral deconvolution and identification system. (AMDIS) software, considering at least 70% probability. The concentration of total dust, obtained using a gravimetric method, was approximately 1 mg.m-3. The toxic substances found in the SPM included halogenated hydrocarbons (containing chlorine, fluorine, and iodine) and aromatic hydrocarbons. The toxic substances included naphthalene, which is classified as carcinogenic.

Metabolomics Profile of Patients with Chronic Myeloid Leukemia and Cardiovascular Adverse Events after Treatment with Tyrosine Kinase Inhibitors

Background. Cardiovascular adverse events (CV-AE) are emerging complications in chronic myeloid leukemia (CML) patients treated with second and third generation tyrosine kinase inhibitors (TKIs). Despite the importance of CV risk factors,predictive CV-AE biomarkers are still lacking. Further understanding of the molecular pathways underlying CV-AE may promote novel strategies to prevent its initiation prior to clinical disease. In this scenario, the use of a novel tool such as metabolomics may be useful for the identification of new metabolic pathways related to CV-AE. Metabolites are the output of cellular metabolism, accounting for expression and activity of genes, transcripts, and proteins, and offering unique insights into small molecule regulation. For the first time we evaluated the correlation between CV-AE and metabolomic profile in CML patients treated with TKIs. Methods. We considered 39 adult CP-CML patients (mean age 49, range 24-70), without comorbidity at baseline, consecutively diagnosed and treated with imatinib, dasatinib nilotinib and ponatinib, at the Haematology Unit of "Businco Hospital", Cagliari, Italy. All patients underwent a metabolomic profile detection, after CV-AE or during follow-up, and were stratified in 2 groups (with or without CV-AE). Plasma samples were collected and acquired chromatogram was analysed by means of the free software AMDIS (Automated Mass Spectral Deconvolution and Identification System; http://chemdata.nist.gov/mass-spc/amdis) that identified each peak by comparison of the relative mass spectra and the retention times with those stored in an in-house made library comprising 255 metabolites. Data were investigated by applying the supervised multivariate statistical approach OPLS-DA (Orthogonal partial least square discriminant analysis) (SIMCA, version 13.0, Umetrics, Umea, Sweden). Results. The mean follow-up since CML diagnosis was 3.7 years (range 0.9-5); 22 (56.4%) patients were treated frontline, while 17 (43.5%) underwent second or subsequent TKI lines of treatments. The reason for switching was inefficacy in 15.3% and intolerance in 28.2%. At CV-AE or last follow-up 16 (41%) patients were treated with imatinib, 8 (20.5%) with dasatinib, 14 (35.8%) with nilotinib and 1 patient with ponatinib (2.7%). Overall, 17 CV-AE were recorded: 7 cases of hypercholesterolemia, 5 pleural or pericardial effusions, one episode of hypertension and 4 cardiac events (atrial fibrillation,ST-segment elevation myocardial infarction, reduction of cardiac ejection fraction and dissecting aneurysm of the aorta); 7 CV-AE were graded as 3 according to the common toxicity criteria and one patient died from dissecting aneurysm of the aorta). The 60-month cumulative CV-AE incidence was 54.4±9.1%. The mean time between the start of the treatment and the occurrence of a CV-AE was 44.4 months (range 19-60). OPLS-DA showed that patient's samples were clearly separated into 2 groups indicating that CV-AE patients (blue dots) presented a markedly distinct metabolic profile compared with patients without CV-AE (green dots); (figure 1). The parameters of the model were R2Y = 0.76 and Q2 = 0.44. To validate the OPLS-DA model, a permutation was performed resulting statistically significant (p=0,002). The main discriminant metabolites were tyrosine, lysine, ornithine, glutamic acid, 2-piperdincarboxylic acid, proline, citric acid, phenylalanine, mannitol, threonine, leucine, creatine, serine, 4-hydroxyproline, and alanine (more represented in CV-AE group); while unknown 204, myristic acid, arabitol, oxalic acid, 4-deoxyrithronic acid, elaidic acid and ribose resulted less expressed in CV-AE group. Conclusions. This exploratory study showed different metabolomic profile of CML patients with CV-AE underwent TKI treatment, suggesting possible mechanisms of endothelial damage mediated by the accumulation of metabolites. Tyrosine, highly expressed in the CV-AE CML group, is a reliable marker of oxidative stress in various acute and chronic diseases.Metabolomics research has considerable potential for translating the metabolic fingerprint into personalized therapeutic strategies. These preliminary data should be confirmed in prospective clinical trials. Figure 1 Disclosures No relevant conflicts of interest to declare.

AMDIS & EXCEL: A Powerful Combination for Evaluating THM-Py-GC/MS Results from European Lacquers

ABSTRACTPyrolysis gas chromatography/mass spectrometry using tetramethylammonium hydroxide (TMAH) for thermally-assisted hydrolysis and methylation (THM-Py-GC/MS) is a powerful analytical technique for comprehensive characterization of organic materials in European lacquers. A daunting challenge, though, is systematically sorting through the vast number of chromatographic peaks in order to accurately locate marker compounds that are characteristic of lacquer artists’ materials. AMDIS (Automated Mass spectral Deconvolution and Identification System) software, developed by NIST, is proven to be capable of extracting and locating library marker compounds in highly complex GC/MS data files. An AMDIS marker compound library of more than 1400 compounds representing Asian and European lacquer and a number of other artists’ materials has been compiled from information in various publications and private communications. A customized Excel workbook was developed to semi-automatically analyse and interpret the marker compound information in the AMDIS search report, using interpretation guides based upon knowledge shared by experts in material characterization that aid in accurate identification. These software tools have been used in training workshops, organized by the Getty Conservation Institute, by scientists with varying levels of GC/MS experience to successfully identify artists’ materials in complex samples from lacquered works of art. Based upon positive feedback from the workshop participants and successful application in their laboratories, we have concluded that the tools may be considered as an Expert System for Characterization with AMDIS Plus Excel (ESCAPE). Examples will be shown for using ESCAPE to identify a wide range of natural products in samples from lacquered objects and easel paintings.

Metabolic Fingerprinting of Sauropus androgynus (L.) Merr. Leaf Extracts

INTRODUCTION The leaves of Sauropus androgynus have been traditionally used in Malaysia, Thailand and Indonesia as food and herbal supplement for increasing human breast milk production. It is worth noting that different concentrations of metabolites in herbal medicine, cultivated in several different geographic locations, may result in different therapeutic effects. OBJECTIVES The present study was aimed to identify the metabolic profiles of S.androgynus extracts. This is the first report on metabolomic study of S.androgynus leaf extracts from different geographic locations. MATERIALS AND METHODS S. androgynus leaf extracts were subjected to study the metabolic fingerprinting using Gas Chromatography - Mass Spectroscopy (GC-MS) method. The chemical compositions of the extracts were investigated using GC-MS (Agilent 6890) coupled to a Agilent mass spectrometry detector (5973 network) and NIST mass spectrometer database (Wiley, W8N05ST.L). Chromatogram acquisition, automated peak deconvolution and library searches were performed using Agilent GC-MS workstation in combination with the Automated Mass Spectral Deconvolution and Identification System (AMDIS 32, version 2.69, 2010). S.androgynus data from various locations were grouped and classified by Principle Component Analysis (PCA) and Cluster Analysis, respectively. RESULTS The largest part of the metabolic profile of S.androgynus was composed of fatty acids and their esters, such as myristic acid, palmitic acid, methyl-linoleic, methyl-stearic; diterpene and vitamin. Other major components such as phytol and isophytol were also found in the S.androgynus leaf extracts. The samples from Purwosari alone was merged into one group or a cluster and the other samples were merged into the other cluster, while samples from East Surabaya and Trenggalek showed the close relationship in score plot of PCA and in the dendogram. CONCLUSION From this study it is obvious that S.androgynus leaf extracts from several various different geographic locations contain many biologically active compounds in various concentrations. This clearly indicated that different geographical conditions could influence the metabolic process in S.androgynus, by changing the metabolic pathway or modifying the enzyme responsible for the metabolic process.

Collection, Identification, and Statistical Analysis of Volatile Organic Compound Patterns Emitted by Phytoplasma Infected Plants.

In this chapter, we give an introduction to innovative attempts for the collection, identification, and statistical analysis of volatile organic compound (VOC) patterns emitted by phytoplasma-infected plants compared to healthy plants by the use of state-of-the-art techniques. This encompasses headspace-sampling techniques, gas chromatography coupled with mass spectrometry, and identification of VOC patterns by the "Automated Mass Spectral Deconvolution and Identification System" (AMDIS) followed by appropriate statistical analysis.

Benefit of the Use of GCxGC/MS Profiles for 1D GC/MS Data Treatment Illustrated by the Analysis of Pyrolysis Products from East Asian Handmade Papers.

In this study, we report the use of pyrolysis-GCxGC/MS profiles for an optimized treatment of data issued from pyrolysis-GC/MS combined with the automatic deconvolution software Automated Mass Spectral Deconvolution and Identification System (AMDIS). The method was illustrated by the characterization of marker compounds of East Asian handmade papers through the examination of pyrolysis-GCxGC/MS data to get information which was used for manually identifying low concentrated and co-eluting compounds in 1D GC/MS data. The results showed that the merits of a higher separation power for co-eluting compounds and a better sensitivity for low concentration compounds offered by a GCxGC system can be used effectively for AMDIS 1D GC/MS data treatment: (i) the compound distribution in pyrolysis-GCxGC/MS profiles can be used as "peak finder" for manual check of low concentration and co-eluting compound identification in 1D GC/MS data, and (ii) pyrolysis-GCxGC/MS profiles can provide better quality mass spectra with observed higher match factors in the AMDIS automatic match process. The combination of 2D profile with AMDIS was shown to contribute efficiently to a better characterization of compound profiles in the chromatograms obtained by 1D analysis in focusing on the mass spectral identification. Graphical abstract.

Influence of sublethal doses of acetamiprid and halosulfuron-methyl on metabolites of zebra fish (Brachydanio rerio)

Acetamiprid, a neonicotinoid pesticide, is reported to have adverse sublethal effects on non-target beneficial organisms. Halosulfuron-methyl (HM), one of the most widely used herbicides in agriculture, has high ecotoxicity to aquatic plants and animals. In this study, a GC–MS-based metabolomics approach was used to investigate the toxicity of acetamiprid and HM. The Automated Mass Spectral Deconvolution and Identification System (AMDIS) software program and the retention index method were used to identify 51 metabolites in zebra fish (Brachydanio rerio). Changes in metabolites showed that acetamiprid and HM disturbed amino acid (e.g., leucine, valine, serine, glycine, proline, and alanine) metabolism, the TCA cycle (malic acid and fumaric acid), and the balance of neurotransmitters (glutamic acid, taurine, and glycine). The change in metabolites in the liver, head, and blood indicated that metabolites in the liver were more sensitive than those in the head and blood. Overall, on the basis of the change in metabolites, we identified a potential risk to zebra fish exposed to sublethal doses of acetamiprid and/or HM.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Beyond the basics: A systematic approach for comprehensive analysis of organic materials in Asian lacquers

Identification of organic materials in Asian lacquers presents many challenges due to their complex formulations and the limited solubility of the main component, which is catechol-rich sap from three species of Anacardiaceae trees that crosslinks to form a hard film. Pyrolysis-gas chromatography–mass spectrometry with thermally assisted hydrolysis and methylation using tetramethylammonium hydroxide (THM-Py-GC–MS) has been shown to produce a wide range of marker compounds useful for identifying the catechol components and lacquer additives such as drying oils, natural resins, proteins, starch, and colorants. However, interpreting the test results is quite challenging because of the sheer number of compounds produced by pyrolysis and the wide range of materials that have been used in traditional Asian lacquer formulations. An expert system developed by scientists at the Getty Conservation Institute and conservators at the J. Paul Getty Museum for a workshop entitled ‘Recent Advances In Characterizing Asian Lacquers’ (RAdICAL) utilizes software tools to overcome challenges in data analysis and marker compound interpretation, making it possible for even relative newcomers to Py-GC–MS to identify materials in lacquered objects systematically. Automated Mass spectral Deconvolution and Identification System (AMDIS), a freeware program developed by the National Institute of Standards and Technology (NIST), systematizes GC–MS data analysis by rapidly deconvoluting chromatograms, identifying individual peaks, and then searching the results against a user library of marker compounds, producing a simple report that lists the names, retention indices, and peak areas for all the compounds identified in the sample. The authors have produced a custom RAdICAL compound library, compiled from in-house studies of reference samples made from mixtures of raw or processed lacquer mixed with additives, and supplemented by published work from other researchers. The lists include numerous oxidation products of the alkyl- and alkenyl-substituted catechols, and alkyl- and alkenyl-substituted benzenes in the tree saps identified in studies of aged lacquer replicas, many of which have diagnostic purposes. A specialized Excel workbook developed for RAdICAL can import the AMDIS report, organize the marker compound results by class of artists’ materials, and perform automatic calculations to display sorted information for each material in specialized diagnostic graphs. Expert knowledge relating raw materials to their associated marker compounds, obtained from in-house research, publications and personal communications has been embedded into the individual Excel worksheets. This aids users of the workbook in verifying the presence or absence of materials in their lacquer samples, based on the marker compound distributions. All of the final results are presented in a pre-formatted comprehensive analytical report. Extensive lists of analytical data for marker compounds from the major classes of organic additives used in Asian lacquer formulations provide researchers the information needed to identify these markers in unknown lacquer samples. As other researchers contribute marker compound information for further lacquer materials and the knowledge for interpreting them, the capabilities of the RAdICAL expert system will continue to expand.

Compound identification in metabolomics: a study with the use of two different GC data processing systems

The present paper reports a comparison study of two data processing procedures in GC–MS metabolome components investigation based on two modern softwares: Automated Mass Spectral Deconvolution and Identification System (AMDIS) and GC–MS Solution Postrun Analysis (GC–MS SPA). GC–MS SPA is intended for manual integration and identification, while AMDIS is proposed as a fast, and automatic data analysis tool. Both methods are based on the same free-access library. In the present study, 12 compounds previously detected in a metabolomic fingerprint of grasshopper abdominal secretion, were tested at three concentration levels: 2.5, 5 and 10 μg/mL. The processing procedures were evaluated by comparison of peak area ratio for each tested concentration. The obtained results proved that processing with the use of AMDIS was more sensitive and enabled the identification of all compounds at the lowest selected concentration. Additionally, the differentiation of structurally similar compounds was possible with the use of AMDIS software.

Characterization of Carbon Monoxide Fatalities by Metabolomics

ABSTRACTMetabolite profiling of postmortem blood in carbon monoxide poisoning cases was performed with gas chromatography-mass spectrometry based on metabolomics. All data were processed with an automated mass spectral deconvolution and identification system and the metabolites were characterized using the National Institute of Standards and Technology library. Discriminant analysis was performed and the carbon monoxide-induced biomarkers were determined with a variable importance parameter in the projection plot obtained from partial least square discriminant analysis. This metabolomics approach, including global metabolites profiling, is useful in improving the interpretation of metabolism in carbon monoxide poisoning deaths.

Study on composition of essential oils in three different origins' Curcumae Rhizoma by AMDIS and retention index

To compare the differences of essential oils extracted from Curcumae Rhizoma with different origins. The TIC of the essential oils of Curcumae Rhizoma from three different origins recorded by CP(2010) , were investigated by GC-MS combined with automated mass spectral deconvolution and identification system(AMDIS),steps as follow： firstly, overlapped peaks were resolved by AMDIS,secondly, NIST11.L standard MS spectral database combined with retention index were used to assist qualitative analysis, thirdly, the peak area of each split peak were determined by choosing the characteristic fragment ion peak, finally, the relative percentage contents of each compounds were determined through peak area normalization method. The results showed that the components of the essential oils of Curcumae Rhizoma from three origins were different from each other at various degree. In conclusion, the types and content of essential oils could be an indicator to evaluate the quality of Curcumae Rhizoma from different origins and its geoherbalism.