Comprehensive Lists of Internal Calibrants for Ultrahigh-Resolution Mass Spectrometry Analysis of Crude Oil and Natural Organic Matter and Their Preparation Recipes

Toward a More Comprehensive Approach for Dissolved Organic Matter Chemical Characterization Using an Orbitrap Fusion Tribrid Mass Spectrometer Coupled with Ion and Liquid Chromatography Techniques

Dissolved organic matter (DOM) represents one of the largest active organic carbon pools in the global carbon cycle. Although extensively studied, only <10% of DOM has been chemically characterized into individual dissolved compounds due to its molecular complexity. This study introduced a more comprehensive DOM characterization method by coupling both ion chromatography (IC) and liquid chromatography (LC) with high mass accuracy and resolution mass spectrometry. We presented a new on-the-fly mass calibration of the Orbitrap technique by utilizing the "lock mass" function in the Orbitrap Fusion Tribrid mass spectrometer (OT-FTMS), which assures high mass accuracy at every scan by a postcolumn introduction of internal labeled standards. With both IC and LC, tested unlabeled standards of amino acids, small peptides, and organic acids were consistently below 1.0 ppm mass error, giving the OT-FTMS the potential of reaching mass accuracy of the Fourier-transform ion cyclotron resonance mass spectrometer. In addition to mass accuracy, a pooled quality control sample (QC) was used to increase reproducibility by applying systematic error removal using random forest (SERRF). Using an untargeted mass spectrometry approach, estuarine DOM samples were analyzed by OT-FTMS coupled to IC in negative mode and LC in positive mode detection to cover a wide range of highly cationic to highly anionic molecules. As a proof of concept, we focused on elucidating the structures of three distinct DOM compound classes with varied acidities and basicities. In UPLC-OT-FTMS, a total of 915 compounds were detected. We putatively elucidated 44 small peptides and 33 deaminated peptides of these compounds. With IC-OT-FTMS, a total of 1432 compounds were detected. We putatively elucidated 20 peptides, 268 deaminated peptides, and 188 organic acids. Except for five compounds, all putatively elucidated compounds were uniquely detected in their corresponding chromatography technique. These results highlight the need for combining these two techniques to provide a more comprehensive method for DOM characterization. Application of the combined IC and LC techniques is not limited to DOM chemical characterization. It can analyze other complex compound mixtures, such as metabolites, and anthropogenic pollutants, such as pesticides and endocrine-disrupting chemicals, in environmental and biological samples.

Comparative analysis of organic chemical compositions in airborne particulate matter from Ulaanbaatar, Beijing, and Seoul using UPLC-FT-ICR-MS and artificial neural network

This paper presents comparative study on the composition and sources of PM2.5 in Ulaanbaatar, Beijing, and Seoul. Ultrahigh performance liquid chromatography (UPLC) combined with ultrahigh resolution mass spectrometry (UHR-MS) were employed to analyze 85 samples collected in winter. The obtained 340 spectra were interpreted with artificial neural network (ANN). PM2.5 mass concentrations in Ulaanbaatar were significantly higher than those in Beijing and Seoul. ANN based interpretation of UPLC UHR-MS data showed that aliphatic/lipid derived organo‑sulfur compounds, polycyclic aromatic and organo‑oxygen compounds were characteristic to Ulaanbaatar. Whereas, aliphatic/lipid-derived organo‑oxygen compounds were major components in Beijing and Seoul. Aromatic organo‑nitrogen compounds were the main contributors to differentiating the spectra obtained from Beijing from the other cities. Based on two-dimensional gas chromatography/high resolution mass spectrometric (GCxGC/HRMS) data, it was determined that the concentrations of the polycyclic aromatic hydrocarbon (PAH) and polycyclic aromatic sulfur heterocycle (PASH) containing sulfur were highest in Ulaanbaatar, followed by Beijing and Seoul. Coal/biomass combustion was identified as the primary source of contamination in Ulaanbaatar, while petroleum combustion was the main contributor to PM2.5 in Beijing and Seoul. The conclusion that diesel-powered heavy-duty trucks and buses are the main contributors to NOx emissions in Beijing is consistent with previous reports. This study provides a more comprehensive understanding of the composition and sources of PM2.5 in the three cities, with a focus on the differences in their atmospheric pollution profiles based on the UPLC UHR-MS and ANN analysis. It is notable that this study is the first to utilize this method on a large-scale sample set, providing a more detailed and molecular-level understanding of the compositional differences among PM2.5. Overall, the study contributes to a better understanding of the sources and composition of PM2.5 in Northeast Asia, which is essential for developing effective strategies to reduce air pollution and improve public health.

MnO2-Induced Oxidation of Iodide in Frozen Solution

Metal oxides play a critical role in the abiotic transformation of iodine species in natural environments. In this study, we investigated iodide oxidation by manganese dioxides (β-MnO₂, γ-MnO₂, and δ-MnO₂) in frozen and aqueous solutions. The heterogeneous reaction produced reactive iodine (RI) in the frozen phase, and the subsequent thawing of the frozen sample induced the gradual transformation of in situ-formed RI to iodate or iodide, depending on the types of manganese dioxides. The freezing-enhanced production of RI was observed over the pH range of 5.0-9.0, but it decreased with increasing pH. Fulvic acid (FA) can be iodinated by I^-/MnO₂ in aqueous and frozen solutions. About 0.8-8.4% of iodide was transformed to organoiodine compounds (OICs) at pH 6.0-7.8 in aqueous solution, while higher yields (10.4-17.8%) of OICs were obtained in frozen solution. Most OICs generated in the frozen phase contained one iodine atom and were lignin-like compounds according to Fourier transform ion cyclotron resonance/mass spectrometry analysis. This study uncovers a previously unrecognized production pathway of OICs under neutral conditions in frozen environments.

Advances and key considerations of liquid chromatography–mass spectrometry for porcine authentication in halal analysis

The halal food industries are rapidly expanding to fulfill global halal demands. Non-halal substances such as porcine proteins are often added intentionally or unintentionally to products. The development of highly selective and sensitive analytical tools is necessary, and liquid chromatography–mass spectrometry is a powerful tool that can cope with the challenge. The LC–MS method has great potential for halal authentication, because it has high sensitivity and low detection limit and detects several species markers and different tissue origins at once within one species. This article provides an understanding of recent advances in the application of LC–MS for the improvement of porcine authentication. Sample preparation, marker selection, separation and mass spectrometry conditions, quantitative assessment, and data processing for protein identification were all covered in detail to choose the most suitable method for the analytical needs.

Assessment of artificial neural network to identify compositional differences in ultrahigh-resolution mass spectra acquired from coal mine affected soils

This study assessed the applicability of artificial neural networks (ANNs) as a tool to identify compounds contributing to compositional differences in coal-contaminated soils. An artificial neural network model was constructed from laser desorption ionization ultrahigh-resolution mass spectra obtained from coal contaminated soils. A good correlation (R² = 1.00 for model and R² = 0.99 for test) was observed between the measured and predicted values, thus validating the constructed model. To identify chemicals contributing to the coal contents of the soils, the weight values of the constructed model were evaluated. Condensed hydrocarbon and low oxygen containing compounds were found to have larger weight values and hence they were the main contributors to the coal contents of soils. In contrast, compounds identified as lignin did not contribute to the coal contents of soils. These findings were consistent with the conventional knowledge on coal and results from the conventional partial least square method. Therefore, we concluded that the weight interpretation following ANN analysis presented herein can be used to identify compounds that contribute to the compositional differences of natural organic matter (NOM) samples.

Improved coverage of plant metabolites using powder laser desorption/ionization coupled with Fourier-transform ion cyclotron mass spectrometry

In this study, the effectiveness of powder laser desorption/ionization (LDI) coupled with Fourier-transform ion cyclotron mass spectrometry (FT-ICR MS) was evaluated for the improved coverage of plant metabolites. Ground plant (powder) was fixed on a metal plate using double-sided tape. Compared with the conventional approach involving liquid extraction, which is followed by electrospray ionization MS analysis, a smaller amount of sample (∼200 µg) was required in the proposed method. Additionally, the laborious steps of liquid extraction, concentration, and solid-phase extraction were avoided. Employing the proposed method in Centella asiatica leaves analysis, higher number of reproducible molecular formulas (>5000) and metabolites (>650) were obtained than the conventional methods. Flavonoids, phenolic acids, xanthones, lipids, carbohydrates, terpenoids, and alkaloids compounds were detected from leaves, stems, and roots of C. asiatica. This study indicates that LDI FT-ICR MS is a quick and effective tool for enhanced plant metabolite profiling in the solid phase.

Determination of anthropogenic organics in dichlomethane extracts of aerosol particulate matter collected from four different locations in China and Republic of Korea by GC-MS and FTICR-MS

In this study, the hypothesis that particulate matter in east of Korea peninsula would be significantly influenced by particulate matter originated from east of China was evaluated. To test the hypothesis, water-insoluble compounds in particulate matter samples collected from three different locations in Korea and one in China were characterized by atmospheric pressure photoionization (APPI) coupled with Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and gas chromatography mass spectrometry (GC-MS). Each sample was collected twice, in winter and in spring. The GC-MS data revealed the presence of high levels of polycyclic aromatic hydrocarbons (PAHs), such as benzo[a]anthracene in the samples from Tianjin, China. The sample collected in the winter from Baengnyeong Island, which is the location in Korea that is geographically closest to the east coast of China was also rich in aromatic compounds. Meanwhile, the APPI FTICR-MS data showed that polycondensed PAHs and two- to four-ring PAHs with long alkyl chains were abundant in the winter samples from Tianjin and Baengnyeong Island which stems most likely from coal combustion in the eastern China. In contrast, nonaromatic compounds with a biogenic origin were mostly observed in samples collected from islands located in eastern (Ulleung Island) and southern (Jeju Island) Korea. A principal component analysis by FTICR-MS and GC-MS also showed that the samples from Tianjin and those collected from Baengnyeong Island in the winter are strongly associated with coal combustion, whereas the other samples are mainly influenced by vehicle emissions. Therefore, it is concluded that the atmosphere from east of China has significant influence over atmosphere in west of Korea peninsula.