Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power

Fellgett Revisited: On the Nature of Noise in Two-Dimensional Mass Spectrometry

Two-dimensional mass spectrometry (2DMS) is a truly data-independent acquisition technique used in the analysis of complex mixtures; however, the nature of the noise within these spectra is not well understood. In this work, 2DMS is tested for conformity with the Fellgett principle: (signal/noise) ∝ √ (no. of data points). Since 2DMS functions through the modulation of ions through a fragmentation region across many scans, the individual scans are considered data points in this experiment. Random noise was shown to be prevalent as the main source of noise in this experiment with minor systematic noise. This means that the minimum size for a 2DMS spectrum that displays a target fragment ion can be determined using a fast-2D equation detailed herein. The effects of existing denoising algorithms were also found to change the relationship between the signal-to-noise ratio and the scan numbers to be of a quasi-linear nature rather than the square root trend observed before denoising.

Assessment of Accelerated Aging Effect of Bio-Oil Fractions Utilizing Ultrahigh-Resolution Mass Spectrometry and k-Means Clustering of van Krevelen Compositional Space

Bio-oils contain a substantial number of highly oxygenated hydrocarbons, which often exhibit low thermal stability during storage, handling, and refining. The primary objectives of this study are to characterize the hydroxyl group in bio-oil fractions and to investigate the relationship between the type of hydroxyl group and accelerated aging behavior. A bio-oil was fractionated into five solubility-based fractions, classified in two main groups: water-soluble and water-insoluble fractions. These fractions were then subjected to chemoselective reactions to tag molecules containing hydroxyl groups and analyzed by negative-ion electrospray ionization 21 T Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The fractions were also subjected to accelerated aging experiments and characterized by FT-ICR MS and bulk viscosity measurements. Extracting insightful information from ultrahigh-resolution data to aid in predicting upgrading methodologies and instability behaviors of bio-oils is challenging due to the complexity of the data. To address this, an unsupervised learning technique, k-means clustering analysis, was used to semiquantify molecular compositions with a close Euclidean distance within the (O/C, H/C) chemical space. The combination of k-means analysis with findings from chemoselective reactions allowed the distinctive hydroxyl functionalities across the samples to be inferred. Our results indicate that the hexane-soluble fraction contained numerous molecules containing primary and secondary alcohols, while the water-soluble fraction displayed diverse groups of oxygenated compounds, clustered near to carbohydrate-like and pyrolytic humin-like materials. Despite its high oxygen content, the water-soluble fraction showed minimal changes in viscosity during aging. In contrast, a significant increase in viscosity was observed in the water-insoluble materials, specifically, the low- and high-molecular-weight lignin fractions (LMWL and HMWL, respectively). Among these two fractions, the HMWL exhibited the highest increase in viscosity after only 4 h of accelerated aging. Our results indicate that this aging behavior is attributed to an increased number of molecular compositions containing phenolic groups. Thus, the chemical compositions within the HMWL are the major contributors to the viscosity changes in the bio-oil under accelerated aging conditions. This highlights the crucial role of oxygen functionality in bio-oil aging, suggesting that a high oxygen content alone does not necessarily correlate with an increase of viscosity. Unlike other bio-oil categorization methods based on constrained molecule locations within the van Krevelen compositional space, k-means clustering can identify patterns within ultrahigh-resolution data inherent to the unique chemical fingerprint of each sample.

An automated and high-throughput data processing workflow for PFAS identification in biota by direct infusion ultra-high resolution mass spectrometry

The increasing recognition of the health impacts from human exposure to per- and polyfluorinated alkyl substances (PFAS) has surged the need for sophisticated analytical techniques and advanced data analyses, especially for assessing exposure by food of animal origin. Despite the existence of nearly 15,000 PFAS listed in the CompTox chemicals dashboard by the US Environmental Protection Agency, conventional monitoring and suspect screening methods often fall short, covering only a fraction of these substances. This study introduces an innovative automated data processing workflow, named PFlow, for identifying PFAS in environmental samples using direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). PFlow's validation on a bream liver sample, representative of low-concentration biota, involves data pre-processing, annotation of PFAS based on their precursor masses, and verification through isotopologues. Notably, PFlow annotated 17 PFAS absent in the comprehensive targeted approach and tentatively identified an additional 53 compounds, thereby demonstrating its efficiency in enhancing PFAS detection coverage. From an initial dataset of 30,332 distinct m/z values, PFlow thoroughly narrowed down the candidates to 84 potential PFAS compounds, utilizing precise mass measurements and chemical logic criteria, underscoring its potential in advancing our understanding of PFAS prevalence and of human exposure.

Combining Advanced Analytical Methodologies to Uncover Suspect PFAS and Fluorinated Pharmaceutical Contributions to Extractable Organic Fluorine in Human Serum (Tromsø Study)

A growing number of studies have reported that routinely monitored per- and polyfluoroalkyl substances (PFAS) are not sufficient to explain the extractable organic fluorine (EOF) measured in human blood. In this study, we address this gap by screening pooled human serum collected over 3 decades (1986-2015) in Tromsø (Norway) for >5000 PFAS and >300 fluorinated pharmaceuticals. We combined multiple analytical techniques (direct infusion Fourier transform ion cyclotron resonance mass spectrometry, liquid chromatography-Orbitrap-high-resolution mass spectrometry, and total oxidizable precursors assay) in a three-step suspect screening process which aimed at unequivocal suspect identification. This approach uncovered the presence of one PFAS and eight fluorinated pharmaceuticals (including some metabolites) in human serum. While the PFAS suspect only accounted for 2-4% of the EOF, fluorinated pharmaceuticals accounted for 0-63% of the EOF, and their contribution increased in recent years. Although fluorinated pharmaceuticals often contain only 1-3 fluorine atoms, our results indicate that they can contribute significantly to the EOF. Indeed, the contribution from fluorinated pharmaceuticals allowed us to close the organofluorine mass balance in pooled serum from 2015, indicating a good understanding of organofluorine compounds in humans. However, a portion of the EOF in human serum from 1986 and 2007 still remained unexplained.

Effects of burning and photochemical degradation of Macondo surrogate oil on its composition and toxicity

Petroleum products in the environment can produce significant toxicity through photochemically driven processes. Burning surface oil and photochemical degradation were two mechanisms for oil removal after the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico. After burning, residual oil remains in the environment and may undergo further weathering, a poorly understood fate. Although photochemistry was a major degradation pathway of the DWH oil, its effect on burned oil residue in the environment is under studied. Here, we ignited Macondo surrogate crude oil and allowed it to burn to exhaustion. Water-accommodated fractions (WAFs) of the burn residue were created in full sunlight to determine the effects of photochemical weathering on the burned oil residue. Our findings show that increased dissolved organic carbon concentrations (DOC) for the light unburned and light burned after sunlight exposure positively correlated to decreased microbial growth and production inhibition (i.e. more toxic) when compared to the dark controls. Optical and molecular analytical techniques were used to identify the classes of compounds contributing to the toxicity in the dark and light burned and dark and light unburned WAFs. After light exposure, the optical composition between the light unburned and light burned differed significantly (p < 0.05), revealing key fluorescence signatures commonly identified as crude oil degradation products. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis showed more condensed aromatic, reduced oxygenated compounds present in the light burned than in the light unburned. FT-ICR MS also showed an increase in the percent relative abundance of carboxyl-rich alicyclic molecules (CRAM) like compounds in the light burned compared to light unburned. The increase in CRAM suggests that the composition of the light burned is more photorefractory, i.e., reduced, explaining the residual toxicity observed in microbial activity. Overall, these data indicate burning removes some but not all toxic compounds, leaving behind compounds which retain considerable toxicity. This study shows that burn oil residues are photolabile breaking down further into complex reduced compounds.

A Gated TIMS FTICR MS Instrument to Decipher Isomeric Content of Complex Organic Mixtures

Modern research faces increasingly complex materials with a constant need for new analytical strategies that can provide deeper levels of chemical insight. Ultrahigh resolution mass spectrometry (MS), particularly Fourier transform ion cyclotron resonance (FTICR) MS, has provided a robust analytical foundation. However, MS alone offers limited structural information. Here, we present the first implementation and results from an FTICR MS with fully integrated dual accumulation analysis with gated trapped ion mobility spectrometry (gTIMS) capability. The drastically extended charge capacity and parallel accumulation facilitate the analysis of complex mixtures. We achieved a high dynamic range of 4 orders of magnitude within a single FTICR acquisition event. Simultaneously, the valuable linear relationship between the TIMS elution voltage and reduced mobility was retained over a wide mobility range. Benchmarking the instrument performance with Suwannee River fulvic acid (SRFA) by variable ramp gTIMS analysis allowed separation and unambiguous assignment of different charge state distributions. Application to bio-oils has proven the capability to distinguish the isomeric diversity in these ultracomplex samples, while maintaining the expected FTICR MS resolving power and mass accuracy. Valuable information about the molecular distribution, isomeric diversity, and main molecular differences could directly be extracted within the analysis time of a classical "dilute and shoot" direct infusion experiment. The development of this fully integrated and flexible gTIMS with FTICR MS analysis possesses the potential to significantly change the current landscape of high-resolution mass spectrometric analysis of complex mixtures through the added insight of isomeric complexity afforded by TIMS. The exploration of the added IMS dimension promises transformative effects across diverse fields including energy transition, environmental studies, and biological research.

Tracking the history of polycyclic aromatic compounds in London through a River Thames sediment core and ultrahigh resolution mass spectrometry

Polycyclic aromatic compounds (PACs), including polycyclic aromatic hydrocarbons (PAHs) and heteroatom-containing analogues, constitute an important environmental contaminant class. For decades, limited numbers of priority PAHs have been routinely targeted in pollution investigations, however, there is growing awareness for the potential occurrence of thousands of PACs in the environment. In this study, untargeted Fourier transform ion cyclotron resonance mass spectrometry was used for the molecular characterisation of PACs in a sediment core from Chiswick Ait, in the River Thames, London, UK. Using complex mixture analysis approaches, including aromaticity index calculations, the number of molecular PAC components was determined for eight core depths, extending back to the 1930s. A maximum of 1676 molecular compositions representing PACs was detected at the depth corresponding to the 1950s, and a decline in PAC numbers was observed up the core. A case linking the PACs to London's coal consumption history is presented, alongside other possible sources, with some data features indicating pyrogenic origins. The overall core profile trend in PAC components, including compounds with oxygen, sulfur, nitrogen, and chlorine atoms, is shown to broadly correspond to the 16 priority PAH concentration profile trend previously determined for this core. These findings have implications for other industry-impacted environments.

From the grapevine to the glass: A wine metabolomics tale by FT-ICR-MS

Wine is one of the most consumed beverages around the world. Its unique characteristics arise from numerous processes, from the selection of grapevine varieties and grapes, the effect of the terroir and geographical origin, through the biochemical process of fermentation by microorganisms, until its aging. All molecules found in wine define its chemical fingerprint and can be used to tell the story of its origin, production, authenticity and quality. Wine's chemical composition can be characterized using an untargeted metabolomics approach based on extreme resolution mass spectrometry. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is currently the most powerful analytical technique to analyse such complex sample, providing the most comprehensive analysis of the chemical fingerprint of wine.

The formation, reactivity, and fate of oxygen-containing organic compounds in petroleum-contaminated groundwaters: A state of the science review and future research directions

Hydrocarbon (HC) contamination in groundwater (GW) is a widespread environmental issue. Dissolved hydrocarbons in water are commonly utilized as an energy source by natural microbial communities, which can produce water soluble intermediate metabolite compounds, herein referred to as oxygen containing organic compounds (OCOCs), before achieving complete mineralization. This review aims to provide a comprehensive assessment of the literature focused on the state of the science for OCOCs detected and measured in GW samples collected from petroleum contaminated aquifers. In this review, we discuss and evaluate two hypotheses investigating OCOC formation, which are major points of contention in the freshwater oil spill community that need to be addressed. We reviewed over 150 articles compiling studies investigating OCOC formation and persistence to uncover knowledge gaps in the literature and studies that recommend quantitative and qualitative measurements of OCOCs in petroleum-contaminated aquifers. This review is essential because no consensus exists regarding specific compounds and related concerns. We highlight the knowledge gaps to progressing the discussion of hydrocarbon conversion products.

Development and validation of a GC Orbitrap-MS method for the analysis of phthalate esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) in atmospheric particles and its application for screening PM2.5 from Curitiba, Brazil

Phthalates or phthalic acid esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) are ubiquitous chemicals often used as plasticisers and additives in many industrial products and are classified as both persistent organic pollutants (POPs) and new emerging pollutants (NEPs). Exposure to these chemicals, especially through inhalation, is linked to a wide range of negative health effects, including endocrine disruption. Air particulate matter (PM) with an aerodynamic diameter ≤ 2.5 μm can be enriched with PAEs and DEHA and if inhaled can cause multi-system human toxicity. Therefore, proper monitoring of PAEs and DEHA in PM is required to assess human exposure to these pollutants. In this work, we developed and validated a new and sensitive gas-chromatography high-resolution mass spectrometry (GC-HRMS) method for targeted analysis of PAEs including dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), benzyl butyl phthalate (BBP), bis(2-ethylhexyl)adipate (DEHA), bis(2-ethylhexyl)phthalate (DEHP), di-n-octyl phthalate (DOP), in PM. Analytical aspects including sample preparation steps and GC-HRMS parameters, e.g., quadrupole isolation window, to enhance method sensitivity have been assessed. The estimated limit of detection (LODs) of target PAEs and DEHA ranged from 5.5 to 17 pg μL-1, allowing their trace-level detection in PM. Extraction efficiencies of 78-101% were obtained for the target compounds. Low DMP and DEP extraction efficiencies from the spiked filter substrates indicated that significant losses of higher volatility PAEs can occur during the sample collection when filter-based techniques are used. This work is the first targeted method based on GC-Orbitrap MS for PAEs and DEHA in environmental samples. The validated method was successfully applied for the targeted analysis of PAEs and DEHA in PM2.5 samples from the eighth most populous city in Brazil, Curitiba. This work is the first to report DBP, DEHA, DEHP, and DOP in urban PM from Brazil. The observed concentrations of PAEs (up to 29 ng m-3) in PM2.5 from Curitiba may not represent the extent of pollution by these toxic compounds since the analysed samples were collected during a COVID-19 restriction when anthropogenic activities were reduced.

Graph-Based Method for Calibration of High-Resolution Mass Spectra of Natural Organic Matter

Inaccuracies in ion detection and signal processing can undermine confidence in the molecular formula assignment of high-resolution mass spectrometry, which relies on precise matching of the mass-to-charge ratio (m/z). This study proposes a novel graph-based spectra calibration method, MSCMcalib, which implements coordinate transformation and pattern detection. MSCMcalib maps uncalibrated m/z data onto a modified 2D mass defect plot, facilitating the automatic calibration of detected lines, i.e., the calibration of uncalibrated peaks aligned with these lines. The "propagation" method is subsequently employed to accurately and automatically calibrate 605 m/z values across multiple lines, encompassing 98% of the m/z range. The calibrated m/z values divide the m/z range of the spectrum into multiple subintervals, with each subinterval undergoing a process of "scaling" calibration. The utilization of narrower partitions effectively mitigates divergence issues at both ends that arise from the polynomial fitting of errors against m/z. The effectiveness of MSCMcalib is validated through the calibration of SRFA data with m/z error ranges spanning from -10 to -6 ppm, resulting in an additional assignment of 11%-30% more molecular formulas compared to the quadratic fitting calibration.

Unraveling the potential of segment scan mass spectral acquisition for chemical isotope labeling LC-MS-based metabolome analysis: Performance assessment across different types of biological samples

BACKGROUND

Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with high metabolomic coverage and quantification accuracy. In CIL LC-MS, the overall metabolite detection efficiency using Orbitrap MS can be further improved by employing a segment scan method where the full m/z range is divided into multiple segments for spectral acquisition with a significant increase in the in-spectrum dynamic range. Considering the metabolic complexity in different types of biological samples (e.g., feces, urine, serum/plasma, cell/tissue extracts, saliva, etc.), we report the development and evaluation of the segment scan method for metabolome analysis of different sample types.

RESULTS

It was found that sample complexity significantly influenced the performance of the segment scan method. In metabolically complex samples such as feces and urine, the method yielded a substantial increase (up to 94 %) in detected peak pairs or metabolites, compared to conventional full scan. Conversely, less complex samples like saliva exhibited more modest gains (approximately 25 %). Based on the observations, a 120-m/z segment scan method was determined as a routine approach for CIL LC-Orbitrap-MS-based metabolomics with good compatibility with different types of biological samples. For this method, a further investigation on relative quantification accuracy was done. The peak area ratios of 12C-/13-labeled metabolites were slightly reduced with 72%-84 % of peak pairs falling within the ±25 % range of the anticipated peak ratio of 1.0 among different samples, as opposed to 81%-90 % in the full scan, which was attributed to the inclusion of more low-abundance peak pairs within the narrow MS segments. However, the overall peak ratio measurement precision was not significantly affected by the segment scan.

SIGNIFICANCE AND NOVELTY

The segment scan method was found to be useful for CIL LC-Orbitrap-MS-based metabolome analysis of different types of samples with significant improvement in metabolite detectability (25-94 % increase), compared to the conventional full scan method.

Naturally Occurring Allotropes of Carbon

Carbon is one of the most important chemical elements, forming a wide range of important allotropes, ranging from diamond over graphite to nanostructural materials such as graphene, fullerenes, and carbon nanotubes (CNTs). Especially these nanomaterials play an important role in technology and are commonly formed in laborious synthetic processes that often are of high energy demand. Recently, fullerenes and their building blocks (buckybowls) have been found in natural fossil materials formed under geological conditions. The question arises of how diverse nature can be in forming different types of natural allotropes of carbon. This is investigated here, using modern analytical methods such as ultrahigh-resolution mass spectrometry and transmission electron microscopy, which facilitate a detailed understanding of the diversity of natural carbon allotropes. Large fullerenes, fullertubes, graphene sheets, and double- and multiwalled CNTs together with single-walled CNTs were detected in natural heavy fossil materials while theoretical calculations on the B3LYP/6-31G(d) level of theory using the ORCA software package support the findings.

Photochemistry of oil in marine systems: developments since the Deepwater Horizon spill

Oil spills represent a major source of negative environmental impacts in marine systems. Despite many decades of research on oil spill behavior, photochemistry was neglected as a major factor in the fate of oil spilled in marine systems. Subsequent to the Deepwater Horizon oil spill, numerous studies using varied approaches have demonstrated the importance of photochemistry, including short-term impacts (hours to days) that were previously unrecognized. These studies have demonstrated the importance of photochemistry in the overall oil transformation after a spill and more specifically the impacts on emulsification, oxygenation, and microbial interactions. In addition to new perspectives, advances in analytical approaches have allowed an improved understanding of oil photochemistry after maritime spill. Although the literature on the Deepwater Horizon spill is extensive, this review focuses only on studies relevant to the advances in oil photochemistry understanding since the Deepwater Horizon spill.

Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples

Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Deep Characterization of Serum Metabolome Based on the Segment-Optimized Spectral-Stitching Direct-Infusion Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Approach

Direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR MS) shows great promise for metabolomic analysis due to ultrahigh mass accuracy and resolution. However, most of the DI-FTICR MS approaches focused on high-throughput metabolomics analysis at the expense of sensitivity and resolution and the potential for metabolome characterization has not been fully explored. Here, we proposed a novel deep characterization approach of serum metabolome using a segment-optimized spectral-stitching DI-FTICR MS method integrated with high-confidence and database-independent formula assignments. With varied acquisition parameters for each segment, a highly efficient acquisition was achieved for the whole mass range with sub-ppm mass accuracy. In a pooled human serum sample, thousands of features were assigned with unambiguous formulas and possible candidates based on highly accurate mass measurements. Furthermore, a reaction network was used to select confidently unique formulas from possible candidates, which was constructed by unambiguous formulas and possible candidates connected by the formula differences resulting from biochemical and MS transformation. Compared with full-range and conventional segment acquisition, 8- and 1.2-fold increases in observed features were achieved, respectively. Assignment accuracy was 93-94% for both a standard mixture containing 190 metabolites and a spiked serum sample with the root mean square mass error of 0.15-0.16 ppm. In total, 3534 unequivocal neutral molecular formulas were assigned in the pooled serum sample, 35% of which are contained in the HMDB. This method offers great enhancement in the deep characterization of serum metabolome by DI-FTICR MS.

Chemoselective derivatisation and ultrahigh resolution mass spectrometry for the determination of hydroxyl functional groups within complex bio-oils

Bio-oils are a renewable alternative resource for the production of fine chemicals and fuels. Bio-oils are characterised by a high content of oxygenated compounds with a diverse array of different chemical functionalities. Here, we performed a chemical reaction to transform the hydroxyl group of the various components in a bio-oil prior to characterisation with ultrahigh resolution mass spectrometry (UHRMS). The derivatisations were first evaluated using twenty lignin-representative standards with different structural features. Our results indicate a highly chemoselective transformation of the hydroxyl group despite the presence of other functional groups. Mono- and di-acetate products were observed in acetone-acetic anhydride (acetone-Ac₂O) mixtures for non-sterically hindered phenols, catechols and benzene diols. Dimethyl sulfoxide-Ac₂O (DMSO-Ac₂O) reactions favoured the oxidation of primary and secondary alcohols and the formation of methylthiomethyl (MTM) products of phenols. The derivatisations were then performed in a complex bio-oil sample to gain insights into the hydroxyl group profile of the bio-oil. Our results indicate that the bio-oil before derivatisation is composed of 4500 elemental compositions containing 1-12 oxygen atoms. After the derivatisation in DMSO-Ac₂O mixtures, the total number of compositions increased approximately five-fold. The reaction was indicative of the variety of hydroxyl group profiles within the sample in particular the presence of phenols that were ortho and para substituted, non-hindered phenols (about 34%), aromatic alcohols (including benzylic and other non-phenolic alcohols) (25%), and aliphatic alcohols (6.3%) could be inferred. Phenolic compositions are known as coke precursors in catalytic pyrolysis and upgrading processes. Thus, the combination of chemoselective derivatisations in conjunction with UHRMS can be a valuable resource to outline the hydroxyl group profile in elemental chemical compositions in complex mixtures.

The isotope distribution: A rose with thorns

The isotope distribution, which reflects the number and probabilities of occurrence of different isotopologues of a molecule, can be theoretically calculated. With the current generation of (ultra)-high-resolution mass spectrometers, the isotope distribution of molecules can be measured with high sensitivity, resolution, and mass accuracy. However, the observed isotope distribution can differ substantially from the expected isotope distribution. Although differences between the observed and expected isotope distribution can complicate the analysis and interpretation of mass spectral data, they can be helpful in a number of specific applications. These applications include, yet are not limited to, the identification of peptides in proteomics, elucidation of the elemental composition of small organic molecules and metabolites, as well as wading through peaks in mass spectra of complex bioorganic mixtures such as petroleum and humus. In this review, we give a nonexhaustive overview of factors that have an impact on the observed isotope distribution, such as elemental isotope deviations, ion sampling, ion interactions, electronic noise and dephasing, centroiding, and apodization. These factors occur at different stages of obtaining the isotope distribution: during the collection of the sample, during the ionization and intake of a molecule in a mass spectrometer, during the mass separation and detection of ionized molecules, and during signal processing.

Analytical chemistry solutions to hazard evaluation of petroleum refining products

Products of petroleum refining are substances that are both complex and variable. These substances are produced and distributed in high volumes; therefore, they are heavily scrutinized in terms of their potential hazards and risks. Because of inherent compositional complexity and variability, unique challenges exist in terms of their registration and evaluation. Continued dialogue between the industry and the decision-makers has revolved around the most appropriate approach to fill data gaps and ensure safe use of these substances. One of the challenging topics has been the extent of chemical compositional characterization of products of petroleum refining that may be necessary for substance identification and hazard evaluation. There are several novel analytical methods that can be used for comprehensive characterization of petroleum substances and identification of most abundant constituents. However, translation of the advances in analytical chemistry to regulatory decision-making has not been as evident. Therefore, the goal of this review is to bridge the divide between the science of chemical characterization of petroleum and the needs and expectations of the decision-makers. Collectively, mutual appreciation of the regulatory guidance and the realities of what information these new methods can deliver should facilitate the path forward in ensuring safety of the products of petroleum refining.

Temporal chemical composition changes in water below a crude oil slick irradiated with natural sunlight

Photooxidation can alter the environmental fate and effects of spilled oil. To better understand this process, oil slicks were generated on seawater mesocosms and exposed to sunlight for 8 days. The molecular composition of seawater under irradiated and non-irradiated oil slicks was characterized using ion mobility spectrometry-mass spectrometry and polyaromatic hydrocarbons analyses. Biomimetic extraction was performed to quantify neutral and ionized constituents. Results show that seawater underneath irradiated oil showed significantly higher amounts of hydrocarbons with oxygen- and sulfur-containing by-products peaking by day 4-6; however, concentrations of dissolved organic carbon were similar. Biomimetic extraction indicated toxic units in irradiated mesocosms increased, mainly due to ionized components, but remained <1, suggesting limited potential for ecotoxicity. Because the experimental design mimicked important aspects of natural conditions (freshly collected seawater, natural sunlight, and relevant oil thickness and concentrations), this study improves our understanding of the effects of photooxidation during a marine oil spill.

How Well Do We Handle the Sample Preparation, FT-ICR Mass Spectrometry Analysis, and Data Treatment of Atmospheric Waters?

FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) analysis has shown great potential to aid in the understanding of the extremely high molecular diversity of cloud water samples. The main goal of this work was to determine the differences in terms of formula assignment for analytical (i.e., measurement replicates) and experimental replicates of a given cloud water sample. The experimental replicates, obtained by solid phase extraction, were also compared to the results obtained for freeze-dried samples to evaluate whether the presence of salts interferes with the analysis. Two S/N ratios, generally adopted for atmospheric samples, were evaluated, and three different algorithms were used for assignment: DataAnalysis 5.3 (Bruker), Composer (Sierra Analytics), and MFAssignR (Chemical Advanced Resolution Methods Lab). In contrast to other works, we wanted to treat this comparison from the point of view of users, who usually must deal with a simple list of m/z ratios and intensity with limited access to the mass spectrum characteristics. The aim of this study was to establish a methodology for the treatment of atmospheric aqueous samples in light of the comparison of three different software programs, to enhance the possibility of data comparison within samples.

Investigating the Influence of n-Heptane versus n-Nonane upon the Extraction of Asphaltenes

The composition of asphaltenes is of interest due to the challenges they pose for industry and their high complexity, encompassing a range of heteroatom contents, molecular weights, double bond equivalents (DBEs), and structural motifs. They are well-known for aggregating above critical concentrations, hindering the upstream and downstream processes. Asphaltenes are defined by solubility, as they are insoluble in light paraffins such as n-heptane and soluble in aromatic solvents such as toluene. Today, enormous efforts are being invested into the characterization of asphaltenes to shed light into their structural profiles to benefit the petroleum industry and environmental sustainability. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides molecular level analysis with unparalleled mass resolving power and mass accuracy, which is vital for the characterization of inherently complex crude oils and their asphaltene fractions. The aim of this research is to elucidate and compare the compositional profiles of asphaltene fractions of two petroleum samples, fractioned through two approaches: using n-heptane, as is typical practice, and n-nonane, for the purpose of testing extraction using higher molecular weight alkanes. The results highlight that the choice of solvents does indeed influence the accessibility of different species and therefore changes the observed molecular profiles of the extracted asphaltenes. n-Heptane afforded broader contributions of different heteroatomic classes and greater carbon number ranges of the observed components; the DBE distribution vs carbon number profiles were different, where the extracts produced using n-nonane displayed a greater prevalence of lower DBE species.

Development of a Novel HPLC-MS Method to Separate Polar and Non-Polar Compounds in Biodiesel/Petrodiesel Mixtures

Due to a trend to higher sustainability, biodiesel is often mixed into petrodiesel. The analysis of these blends on a molecular level is not trivial, since huge differences in concentrations and polarity of the analytes require a large dynamic range of the analytical method, as well as the ability to investigate molecules of widely different polarities. A combination of high-performance liquid chromatography (HPLC) with high resolution mass spectrometry (HRMS) was identified as a promising method and a normal-phase (NP)-HPLC using amino-functionalized silica gel-based stationary phase delivered the best results with very fast (under 4 min) measurements, with distinct separation of the compounds and clean mass spectra of singular compounds. This method can also be easily modified to elute all FAMEs (fatty acid methyl esters) in one singular peak, thus making the separation even faster (under 3 min).

Fine Structure in Isotopic Peak Distributions Measured Using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry: A Comparison between an Infinity ICR Cell and a Dynamically Harmonized ICR Cell

The fine structure of isotopic peak distributions of glutathione in mass spectra is measured using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) at 12 and 15 T magnetic field, with an infinity cell and a dynamically harmonized cell (DHC) respectively. The resolved peaks in the fine structure of glutathione consist of ²H, ¹³C, ¹⁵N, ¹⁷O, ¹⁸O, ³³S, ³⁴S, ³⁶S, and combinations of them. The positions of the measured fine structure peaks agree with the simulated isotopic distributions with the mass error less than 250 ppb in broadband mode for the infinity cell and no more than 125 ppb with the DHC after internal calibration. The 15 T FT-ICR MS with DHC cell also resolved around 30 isotopic peaks in broadband with a resolving power (RP) of 2 M. In narrowband (m/z 307-313), our current highest RP of 13.9 M in magnitude mode was observed with a 36 s transient length by the 15 T FT-ICR MS with the DHC and 2ω detection on the 15 T offers slightly higher RP (14.8 M) in only 18 s. For the 12 T FT-ICR MS with the infinity cell, the highest RP achieved was 15.6 M in magnitude mode with a transient length of 45 s. Peak decay was observed for low abundance peaks, which could be due to the suppression effects from the most abundant peak, as result of ion cloud Coulombic interactions (space-charge).

Characterization of Compositional Variability in Petroleum Substances

In the process of registration of substances of Unknown or Variable Composition, Complex Reaction Products or Biological Materials (UVCBs), information sufficient to enable substance identification must be provided. Substance identification for UVCBs formed through petroleum refining is particularly challenging due to their chemical complexity, as well as variability in refining process conditions and composition of the feedstocks. This study aimed to characterize compositional variability of petroleum UVCBs both within and across product categories. We utilized ion mobility spectrometry (IMS)-MS as a technique to evaluate detailed chemical composition of independent production cycle-derived samples of 6 petroleum products from 3 manufacturing categories (heavy aromatic, hydrotreated light paraffinic, and hydrotreated heavy paraffinic). Atmospheric pressure photoionization and drift tube IMS-MS were used to identify structurally related compounds and quantified between- and within-product variability. In addition, we determined both individual molecules and hydrocarbon blocks that were most variable in samples from different production cycles. We found that detailed chemical compositional data on petroleum UVCBs obtained from IMS-MS can provide the information necessary for hazard and risk characterization in terms of quantifying the variability of the products in a manufacturing category, as well as in subsequent production cycles of the same product.

Revealing the Reactivity of Individual Chemical Entities in Complex Mixtures: the Chemistry Behind Bio-Oil Upgrading

Bio-oils are precursors for biofuels but are highly corrosive necessitating further upgrading. Furthermore, bio-oil samples are highly complex and represent a broad range of chemistries. They are complex mixtures not simply because of the large number of poly-oxygenated compounds but because each composition can comprise many isomers with multiple functional groups. The use of hyphenated ultrahigh-resolution mass spectrometry affords the ability to separate isomeric species of complex mixtures. Here, we present for the first time, the use of this powerful analytical technique combined with chemical reactivity to gain greater insights into the reactivity of the individual isomeric species of bio-oils. A pyrolysis bio-oils and its esterified bio-oil were analyzed using gas chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry, and in-house software (KairosMS) was used for fast comparison of the hyphenated data sets. The data revealed a total of 10,368 isomers in the pyrolysis bio-oil and an increase to 18,827 isomers after esterification conditions. Furthermore, the comparison of the isomeric distribution before and after esterification provide new light on the reactivities within these complex mixtures; these reactivities would be expected to correspond with carboxylic acid, aldehyde, and ketone functional groups. Using this approach, it was possible to reveal the increased chemical complexity of bio-oils after upgrading and target detection of valuable compounds within the bio-oils. The combination of chemical reactions alongside with in-depth molecular characterization opens a new window for the understanding of the chemistry and reactivity of complex mixtures.

Solvent and Flow Rate Effects on the Observed Compositional Profiles and the Relative Intensities of Radical and Protonated Species in Atmospheric Pressure Photoionization Mass Spectrometry

Sample preparation and instrument parameters have regularly been demonstrated to impact upon the observed results in atmospheric pressure photoionization, mass spectrometry (MS), and analytical techniques in general but may be overlooked when such methods are applied to the characterization of real-world samples. An initial investigation into different solvent systems demonstrated that the inclusion of ethyl acetate inverted the ratio of relative intensities of radical and protonated species (R/P). Design of experiments was performed and indicated that the injection flow rate is also a significant factor. The impact of the solvent system and flow rate on signal intensity, the observed compositional profile, and R/P of selected molecular groups is demonstrated further. An inversion of R/P is observed at higher flow rates in solvent systems commonly used in petroleomics studies, effecting a loss of molecular speciation. The findings presented reiterate the critical importance in considering experimental parameters when interpreting the results of analytical procedures.

Unsupervised Structural Classification of Dissolved Organic Matter Based on Fragmentation Pathways

Dissolved organic matter (DOM) is considered an essential component of the Earth's ecological and biogeochemical processes. Structural information of DOM components at the molecular level remains one of the most extraordinary analytical challenges. Advances in determination of chemical formulas from the molecular studies of DOM have provided limited indications on structural signatures and potential reaction pathways. In this work, we extend the structural characterization of a wetland DOM sample using precursor and fragment molecular ions obtained by a sequential electrospray ionization-Fourier transform-ion cyclotron resonance tandem mass spectrometry (ESI-FT-ICR CASI-CID MS/MS) approach. The DOM chemical complexity resulted in near 900 precursors (P) and 24 000 fragment (F) molecular ions over a small m/z 261-477 range. The DOM structural content was dissected into families of structurally connected precursors based on neutral mass loss patterns (Pn-1 + F1:n + C) across the two-dimensional (2D) MS/MS space. This workflow identified over 1900 structural families of DOM compounds based on a precursor and neutral loss (H2O, CH4O, and CO2). The inspection of structural families showed a high degree of isomeric content (numerous identical fragmentation pathways), not discriminable with sole precursor ion analysis. The connectivity map of structural families allows for the visualization of potential biogeochemical processes that DOM undergoes throughout its lifetime. This study illustrates that integrating effective computational tools on a comprehensive high-resolution mass fragmentation strategy further enables the DOM structural characterization.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Extended characterization of petroleum aromatics using off-line LC-GC-MS

Characterization of crude oil remains a challenge for analytical chemists. With the development of multi-dimensional chromatography and high-resolution mass spectrometry, an impressive number of compounds can be identified in a single sample. However, the large diversity in structure and abundance makes it difficult to obtain full compound coverage. Sample preparation methods such as solid-phase extraction and SARA-type separations are used to fractionate oil into compound classes. However, the molecular diversity within each fraction is still highly complex. Thus, in the routine analysis, only a small part of the chemical space is typically characterized. Obtaining a more detailed composition of crude oil is important for production, processing and environmental aspects. We have developed a high-resolution fractionation method for isolation and preconcentration of trace aromatics, including oxygenated and nitrogen-containing species. The method is based on semi-preparative liquid chromatography. This yields high selectivity and efficiency with separation based on aromaticity, ring size and connectivity. By the separation of the more abundant aromatics, i.e., monoaromatics and naphthalenes, trace species were isolated and enriched. This enabled the identification of features not detectable by routine methods. We demonstrate the applicability by fractionation and subsequent GC-MS analysis of 14 crude oils sourced from the North Sea. The number of tentatively identified compounds increased by approximately 60 to 150% compared to solid-phase extraction and GC × GC-MS. Furthermore, the method was used to successfully identify an extended set of heteroatom-containing aromatics (e.g., amines, ketones). The method is not intended to replace traditional sample preparation techniques or multi-dimensional chromatography but acts as a complementary tool. An in-depth comparison to routine characterization techniques is presented concerning advantages and disadvantages.

Subsecond Time-Resolved Mass Spectrometry in Dynamic Structural Biology

Life at the molecular level is a dynamic world, where the key players-proteins, oligonucleotides, lipids, and carbohydrates-are in a perpetual state of structural flux, shifting rapidly between local minima on their conformational free energy landscapes. The techniques of classical structural biology, X-ray crystallography, structural NMR, and cryo-electron microscopy (cryo-EM), while capable of extraordinary structural resolution, are innately ill-suited to characterize biomolecules in their dynamically active states. Subsecond time-resolved mass spectrometry (MS) provides a unique window into the dynamic world of biological macromolecules, offering the capacity to directly monitor biochemical processes and conformational shifts with a structural dimension provided by the electrospray charge-state distribution, ion mobility, covalent labeling, or hydrogen-deuterium exchange. Over the past two decades, this suite of techniques has provided important insights into the inherently dynamic processes that drive function and pathogenesis in biological macromolecules, including (mis)folding, complexation, aggregation, ligand binding, and enzyme catalysis, among others. This Review provides a comprehensive account of subsecond time-resolved MS and the advances it has enabled in dynamic structural biology, with an emphasis on insights into the dynamic drivers of protein function.

Detailed chemical characterization of the composition and variability of soil gas at remediated residential heating oil discharges

Underground storage tanks containing petroleum or other hazardous substances are used widely for residential storage of home heating oil. Spills and leaks of fuel from these tanks are common, and resulting subsurface petroleum vapors may pose health risks. However, understanding of this risk is limited by a lack of observational data on the chemical composition of vapors from discharged fuel. We present here the composition of soil gas sampled at 66 remediated residential sites of underground heating oil discharges throughout Virginia using a newly developed data analysis technique that allows characterization of hydrocarbons by carbon number and degree of unsaturation. Measured concentrations of total petroleum hydrocarbons exceeded 100,000 μg/m³ at 12 sites, but its composition varied widely between sites. Concentrations of hydrocarbons from chemical classes differing by more than a few carbon numbers or degrees of unsaturation are found to be poorly correlated. Furthermore, differences in composition are poorly described by metrics expected to indicate subsurface weathering (e.g., discharge year, or ratio of n-heptadecane to pristane). These results suggest that the composition and magnitude of residual contamination at remediated subsurface discharges is driven by rarely documented spill characteristics (e.g., age and composition of source material, discharge rate, etc.).

Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS (^DTCCS_N2) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.

Combining Ultraviolet Photodissociation and Two-Dimensional Mass Spectrometry: A Contemporary Approach for Characterizing Singly Charged Agrochemicals

Ultraviolet photodissociation (UVPD) has been shown to produce extensive structurally informative data for a variety of chemically diverse compounds. Herein, we demonstrate the performance of the 193 nm UVPD fragmentation technique on structural/moiety characterization of 14 singly charged agrochemicals. Two-dimensional mass spectrometry (2DMS) using infrared multiphoton dissociation (IRMPD) and electron-induced dissociation (EID) have previously been applied to a select range of singly charged pesticides. The ≥80% moiety coverage achieved for the majority of the species by the UVPD and 2D-UVPD methods was on par with and, in some cases, superior to the data obtained by other fragmentation techniques in previous studies, demonstrating that UVPD is viable for these types of species. A three-dimensional (3D) peak picking method was implemented to extract the data from the 2DMS spectrum, overcoming the limitations of the line extraction method used in previous studies, successfully separating precursor specific fragments with milli-Dalton accuracy. Whole spectrum internal calibration combined with 3D peak picking obtained sub-part-per-million (ppm) to part-per-billion (ppb) mass accuracies across the entire 2DMS spectrum.

ESI-MS Analysis of Thiol-yne Click Reaction in Petroleum Medium

Petroleum contains a large number of heteroatomic compounds, but today, most of them are not efficiently utilized. The constant development of the sustainability concept recalls for rethinking the usage of fossil resources with improved chemical utility. In order to initiate research aimed at involving active petroleum compounds in chemical transformations, a new analytical method for product detection is needed. Here, we study the click reaction of thiols with alkynes, leading to the formation of α-vinyl sulfides directly in the petroleum environment. The reaction was carried out using an (IMes)Pd(acac)Cl catalyst, which demonstrated tolerance to petroleum components. In this study, the concentration of thiols ranged from 1 M to 0.01 M (from 8% to 0.1%). To detect products at low concentrations, a special alkyne labeled with an imidazole moiety was used. This approach made it possible to observe the formation of vinyl sulfides by electrospray ionization mass spectrometry (ESI-MS), which provides an opportunity for further optimization of the reaction conditions and future developments for the direct involvement of oil components in chemical reactions.

Studying the Complexity of Biomass Derived Biofuels

Biofuel produced from biomass pyrolysis is a good example of a highly complex mixture. Detailed understanding of its composition is a prerequisite for optimizing transformation processes and further upgrading conditions. The major challenge in understanding the composition of biofuel derived from biomass is the wide range of compounds with high diversity in polarity and abundance that can be present. In this work, a comprehensive analysis using mass spectrometry is reported. Different operation conditions are studied by utilizing multiple ionization methods (positive mode atmospheric pressure photo ionization (APPI), atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) and negative mode ESI) and applying different resolving power set-ups (120 k, 240 k, 480 k and 960 k) and scan techniques (full scan and spectral stitching method) to study the complexity of a pyrolysis biofuel. Using a mass resolution of 960 k and the spectral stitching scan technique gives a total of 21,703 assigned compositions for one ionization technique alone. The number of total compositions is significantly expanded by the combination of different ionization methods.

A feasible strategy to improve confident elemental composition determination of compounds in complex organic mixture such as natural organic matter by FTICR-MS without internal calibration

Confident elemental composition determination of compounds in complex samples such as natural organic matter (NOM) by ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is challenging due to the interference between multiple components in these samples during detection. Here the performance of Solarix 15T-FTICR-MS in terms of accurate relative natural isotope abundance (RIA) and mass measurements for elemental composition determination of compounds in complex samples such as NOM was systematically evaluated. The optimal sweep excitation power values ranging from 20% to 22% was found to significantly diminish the underestimation of RIA measurement for ¹³C₁ peaks of NOM components by FTICR-MS. Random error was found to be one of the main sources for the RIA errors of ¹³C₁ peaks with S/N ratios <25. The mean averaged RIA errors of less than 10% could be obtained by averaging the measured RIAs of each ¹³C₁ peaks in five replicated runs. By adjusting the total ion abundance of NOM complex sample between 3.8-E7 and 1.4-E8 which was simultaneously similar to that of external calibrant during detection, mass errors of lower than 1 ppm for NOM components with m/z lower than 700 Da could be obtained without internal calibration. Meanwhile, a linear correlation between mass errors of ions in NOM complex sample and their m/z values could be obtained. The mass error deviation derived from the linearity was firstly used as new criterion to reduce the number of false formula candidates. A novel strategy of combination of high mass accuracy, high spectral accuracy, and mass error deviation for elemental composition determination of unknown compounds in complex sample such as NOM by FTICR-MS was proposed and applied for different complex samples. Compared to the traditional method, about one fold increasement in the number of the unique formula assignments for measured ions was obtained by using our strategy.

Narrow Aperture Detection Electrodes ICR Cell with Quadrupolar Ion Detection for FT-ICR MS at the Cyclotron Frequency

Ion signal detection at the true (unperturbed) cyclotron frequency instead of the conventional reduced cyclotron frequency has remained a formidable challenge since the inception of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Recently, routine FT-ICR MS at the true cyclotron frequency has become a reality with the implementation of ICR cells with narrow aperture detection electrodes (NADEL). Here, we describe the development and implementation of the next generation of these cells, namely, a 2xNADEL ICR cell, which comprises four flat detect and four ∼45° cylindrical excite electrodes, enabling independent ion excitation and quadrupolar ion detection. The performance of the 2xNADEL ICR cell was evaluated on two commercial FT-ICR MS platforms, 10 T LTQ FT from Thermo Scientific and 9.4 T SolariX XR from Bruker Daltonics. The cells provided accurate mass measurements in the analyses of singly and multiply charged peptides (root-mean-square, RMS, mass error Δm/m of 90 ppb), proteins (Δm/m = 200 ppb), and petroleum fractions (Δm/m < 200 ppb). Due to the reduced influence of measured frequency on the space charge and external (trapping) electric fields, the 2xNADEL ICR cells exhibited stable performance in a wide range of trapping potentials (1-20 V). Similarly, in a 13 h rat brain MALDI imaging experiment, the RMS mass error did not exceed 600 ppb even for low signal-to-noise ratio analyte peaks. Notably, the same set of calibration constants was applicable to Fourier spectra in all pixels, reducing the need for recalibration at the individual pixel level. Overall, these results support further experimental development and fundamentals investigation of this promising technology.

Dynamics of Molecules Observed at Crude-Oil-Gas Interfaces by Time-of-Flight Secondary Ion Mass Spectrometry Imaging

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging provides molecular speciation at the micrometer scale, while the penetration depth of the primary ion beam is limited to the top-layers of a sample. These combined properties make TOF-SIMS potentially an ideal technique to study oil-gas interfaces. TOF-SIMS spectra of three crude oils were evaluated, and only low-mass fragment ions could be assigned to molecular structures unambiguously. Films of crude oils were incubated under air, oil vapor, or water vapor for various times. TOF-SIMS images of a polar crude oil revealed feeble structures of ∼10 μm large round patches that grew to ∼30 μm large crystals when incubated under air and oil vapor, respectively. Principal component analysis of the images showed that the continuous phase had typical aromatic signatures, while the patches and crystals had alkane-like characteristics. No features showed up when the oil film was incubated under water vapor, which indicated that saturated water vapor prevented the accumulation of nonpolar alkane-like compounds at the oil-gas interface. These examples showed that crude oils do not behave as dead fluids but that their constituents accumulate at the oil-gas interfaces in a dynamic way.

An Enhanced Isotopic Fine Structure Method for Exact Mass Analysis in Discovery Metabolomics: FIA-CASI-FTMS

A major bottleneck in metabolomics is the annotation of a molecular formula as a first step to a tentative structure assignment of known and unknown metabolites. The direct observation of an isotopic fine structure (IFS) provides the ability to confidently assign an unknown's molecular formula out of a complex mass spectrum. However, the majority of mass spectrometers deployed for metabolomic studies do not have sufficient resolving power and high-fidelity isotope ratios in the mass range of interest to determine molecular formulas from IFS data. To increase the number of unknowns for which IFS can be determined, a segmented "boxcar" approach using a selection quadrupole as a broadband mass filter is used. In this longer, enhanced dynamic range discovery experiment, selected ions in a specific mass range are accumulated before detection by the analyzer cell. The mass filter window is then moved across the entire mass range resulting in a composite mass spectrum covering the m/z range of interest for phenomics research. The effectiveness of the FIA-CASI-FTMS workflow utilizing IFS for molecular formula assignment is realized with the implementation of the dynamically harmonized cell, which distinguishes the approach from other segmented workflows because of the analytical properties of the cell. The discovery approach was applied to a human plasma sample to confidently assign an unknown molecular formula as part of the quest to illuminate its metabolic "dark matter" via high-fidelity IFS ratio determinations. The FIA-CASI-FTMS workflow showed a 2.6-fold increase in both matching with the Human Metabolome Database and an increase in the IFS pattern.

Studying Natural Buckyballs and Buckybowls in Fossil Materials

Buckyballs (fullerenes) were first reported over 30 years ago, but still little is known regarding their natural occurrence, since they have so far only been found at sites of high-energy incidents, such as lightning strikes or meteor impacts, but have not been reported in low-energy materials like fossil fuels. Using ultrahigh-resolution mass spectrometry, a wide range of fullerenes from C30 to C114 was detected in the asphaltene fraction of a heavy crude oil, together with their building blocks of C10n H10 stoichiometry. High-level DLPNO-CCSD(T) calculations corroborate their stability as spherical and hemispherical species. Interestingly, the maximum intensity of the fullerenes was found at C40 instead of the major fullerene C60 . Hence, experimental evidence supported by calculations show the existence of not only buckyballs but also buckybowls as 3-dimensional polyaromatic compounds in fossil materials.

Structural Characterization of Dissolved Organic Matter at the Chemical Formula Level Using TIMS-FT-ICR MS/MS

TIMS-FT-ICR MS is an important alternative to study the isomeric diversity and elemental composition of complex mixtures. While the chemical structure of many compounds in the dissolved organic matter (DOM) remains largely unknown, the high structural diversity has been described at the molecular level using chemical formulas. In this study, we further push the boundaries of TIMS-FT-ICR MS by performing chemical formula-based ion mobility and tandem MS analysis for the structural characterization of DOM. The workflow described is capable to mobility select (R ∼ 100) and isolate molecular ion signals (Δm/z = 0.036) in the ICR cell, using single-shot ejections after broadband ejections and MS/MS based on sustained off-resonance irradiation collision-induced dissociation (SORI-CID). The workflow results are compared to alternative TIMS-q-FT-ICR MS/MS experiments with quadrupole isolation at nominal mass (∼1 Da). The technology is demonstrated with isomeric and isobaric mixtures (e.g., 4-methoxy-1-naphthoic acid, 2-methoxy-1-naphthoic acid, decanedioic acid) and applied to the characterization of DOM. The application of this new methodology to the analysis of a DOM is illustrated by the isolation of the molecular ion [C₁₈H₁₈O₁₀-H]^- in the presence of other isobars at nominal mass 393. Five IMS bands were assigned to the heterogeneous ion mobility profile of [C₁₈H₁₈O₁₀-H]^-, and candidate structures from the PubChem database were screened based on their ion mobility and the MS/MS matching score. This approach overcomes traditional challenges associated with the similarity of fragmentation patterns of DOM samples (e.g., common neutral losses of H₂O, CO₂, and CH₂-H₂O) by narrowing down the isomeric candidate structures using the mobility domain.

Petroleomics: Tools, Challenges, and Developments

The detailed molecular characterization of petroleum-related samples by mass spectrometry, often referred to as petroleomics, continues to present significant analytical challenges. As a result, petroleomics continues to be a driving force for the development of new ultrahigh resolution instrumentation, experimental methods, and data analysis procedures. Recent advances in ionization, resolving power, mass accuracy, and the use of separation methods, have allowed for record levels of compositional detail to be obtained for petroleum-related samples. To address the growing size and complexity of the data generated, vital software tools for data processing, analysis, and visualization continue to be developed. The insights gained impact upon the fields of energy and environmental science and the petrochemical industry, among others. In addition to advancing the understanding of one of nature's most complex mixtures, advances in petroleomics methodologies are being adapted for the study of other sample types, resulting in direct benefits to other fields.

Evaluation of the combination of different atmospheric pressure ionization sources for the analysis of extremely complex mixtures

RATIONALE

Characterization of complex samples remains a challenging task due to the high number of compounds present. Matrix effects, ion discrimination and suppression are limiting factors which force the use of different methods for the same sample to gain a broad understanding of complex mixtures.

METHODS

Various ionization techniques such as electrospray ionization (ESI), atmospheric pressure photoionization (APPI) and atmospheric pressure chemical ionization (APCI) have been used in various problems for complex mixture analysis. Especially demanding is the analysis of energy-related hydrocarbon mixtures, such as crude oil. Here, the different ionization sources alone and in combination with each other have been used on an ultrahigh resolution Orbitrap mass spectrometer to study a light crude oil.

RESULTS

Despite the great variety of the available ionization sources, there is no single technique which can fully characterize the crude oil. Each ionization technique shows a selectivity towards specific types of compounds. While ESI is the method of choice for the detection of polar compounds, APPI and APCI favor the detection of nonpolar and low-to-medium polar compounds, respectively. The combination of ESI/APPI favors hydrocarbons and oxygen-containing species.

CONCLUSIONS

Combining different ionization methods can be used as an alternative in order to gain more information about compounds present in a complex mixture although a combination of different ion sources could enhance suppression effects.

Tackling the chemical diversity of microbial nonulosonic acids - a universal large-scale survey approach

Nonulosonic acids, commonly referred to as sialic acids, are a highly important group of nine-carbon sugars common to all domains of life. They all share biosynthetic and structural features, but otherwise display a remarkable chemical diversity. In humans, sialic acids cover all cells which makes them important for processes such as cellular protection, immunity and brain development. On the other hand, sialic acids and other nonulosonic acids have been associated with pathological processes including cancer and viral infections. In prokaryotes, nonulosonic acids are commonly associated with pathogens, which developed through molecular mimicry a strategy to circumvent the host's immune response. However, the remarkably large chemical diversity of prokaryotic nonulosonic acids challenges their discovery, and research on molecular characteristics essential for medical applications are often not feasible. Here, we demonstrate a novel, universal large-scale discovery approach that tackles the unmapped diversity of prokaryotic nonulosonic acids. Thereby, we utilize selective chemical labelling combined with a newly established mass spectrometric all-ion-reaction scanning approach to identify nonulosonic acids and other ulosonic acid-like sugars. In doing so, we provide a first molecular-level comparative study on the frequency and diversity across different phyla. We not only illustrate their surprisingly wide-spread occurrence in non-pathogenic species, but also provide evidence of potential higher carbon variants. Many biomedical studies rely on synthetic routes for sialic acids, which are highly demanding and often of low product yields. Our approach enables large-scale exploration for alternative sources of these highly important compounds.

A novel large-scale survey approach for microbial nonulosonic acids (sialic acids) including a first molecular level comparative study is presented.