Next Challenges for the Comprehensive Molecular Characterization of Complex Organic Mixtures in the Field of Sustainable Energy

Steps toward clinical validation of exhaled volatile organic compound biomarkers for hypoglycemia in persons with type 1 diabetes

Persons with type 1 diabetes (T1D) must track/control their blood glucose (BG) levels to avoid hypoglycemic events (BG < 70 mg/dL), which in the most severe cases can lead to seizures or even death. Canines may lead the way toward innovative testing solutions, as they can be trained to identify hypoglycemia simply and noninvasively by smelling exhaled volatile organic compounds (VOCs). To identify breath-based biomarkers of hypoglycemia, samples were collected during two consecutive summers at a diabetes camp (Cohort 1 and Cohort 2), and VOCs were analyzed by gas chromatography-mass spectrometry. Conserved VOCs between the two cohorts were identified, but individual VOCs alone had low accuracies for detection. Therefore, supervised multivariate statistical analysis was undertaken to identify a biosignature in the training data set (Cohort 1) that could detect hypoglycemia with higher accuracy (sensitivity = 94.8%/specificity = 95.0%). When this model was blindly tested on Cohort 2, hypoglycemia was classified with sensitivity = 90.0%/specificity = 89.9%. Ultimately, this study makes strides toward clinical validation through verifying biomarkers of hypoglycemia in hundreds of breath samples. These results may be translated to design a sensor array that could be integrated into a portable breathalyzer to increase glycemic control in persons with T1D.

HRMS-Viewer: Software for High Resolution Mass Spectrometry Formula Assignment and Data Visualization

Accurately assigning formulas to thousands of peaks generated by ultrahigh resolution mass spectrometry in a single analysis poses a significant challenge, especially when dealing with diverse molecular compositions across complex mixtures. This difficulty is further compounded by the lack of an established universal mass calibration and formula assignment method. We have developed HRMS-Viewer, a Python-based software tool designed for processing ultrahigh resolution mass spectrometry data specific to petroleum and natural organic matter (NOM). The software employs an efficient, experience-driven approach for small molecule formula assignment, offering a streamlined yet intuitive workflow. Key features include advanced noise reduction, automatic or manual recalibration, real-time visualization of formula assignment results, and options for manual correction. During the workflow, HRMS-Viewer enables the visualization and manual control of critical steps including noise reduction, recalibration, peak identification, and data review.

Studying Structural Details in Complex Samples: II. High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Coupled to High Resolution Tandem Mass Spectrometry (MS/MS)

The elucidation of structural motifs in extremely complex mixtures is very difficult since the standard methods for structural elucidation are not capable to provide significant information on a single molecule. The best method for the analysis of complex mixtures is ultrahigh resolution mass spectrometry, but the utilization of this method alone does not provide significant information about structural details. Here, a combination with a separation method is necessary. While chromatography is a well-established technique, it has some disadvantages in regard to the separation of complex mixtures, as often no separation of individual isomers is possible. Therefore, here the combination of an ion mobility separation with ultrahigh resolution mass spectrometry is evaluated. As a sample matrix, crude oil is used because it is an excellent matrix to develop new analytical techniques on complex samples. Crude oil is the most complex natural sample known, but only little information is available on the structural identity or functionalities due to a high number of structural isomers or isobars. A lab-built APPI/APLI-FAIMS source was revised to optimize ion transmission and used to follow up on the ion mobility of crude oil constituents after photoionization. An MS/MS approach using collision-induced dissociation (CID) was used to elucidate structural motifs of the transmitted isomers.

Fast, Easy, and Reproducible Fingerprint Methods for Endotoxin Characterization in Nanocellulose and Alginate-Based Hydrogel Scaffolds

Nanocellulose- and alginate-based hydrogels have been suggested as potential wound-healing materials, but their utilization is limited by the Food and Drug Administration (FDA) requirements regarding endotoxin levels. Cytotoxicity and the presence of endotoxin were assessed after gel sterilization using an autoclave and UV treatment. A new fingerprinting method was developed to characterize the compounds detected in cellulose nanocrystal (CNC)- and cellulose-nanofiber (CNF)-based hydrogels using both positive- and negative-ion mode electrospray ionization Fourier transform ion cyclotron resonance mass spectroscopy (ESI FT-ICR MS). These biobased hydrogels were used as scaffolds for the cultivation and growth of human dermal fibroblasts to test their biocompatibility. A resazurin-based assay was preferred over all other biocompatibility methodologies since it allowed for the evaluation of viability over time in the same sample without causing cell lysis. The CNF dispersion of 6 EU mL-1 was slightly above the limits, and it did not affect the cell viability, whereas CNC hydrogels induced a reduction of metabolic activity by the fibroblasts. The chemical structure of the detected endotoxins did not contain phosphates, but it encompassed hydrophobic sulfonate groups, requiring the development of new high-pressure sterilization methods for the use of cellulose hydrogels in medicine.

Ion Source Complementarity for Characterization of Complex Organic Mixtures Using Fourier Transform Mass Spectrometry: A Review

Complex organic mixtures are found in many areas of research, such as energy, environment, health, planetology, and cultural heritage, to name but a few. However, due to their complex chemical composition, which holds an extensive potential of information at the molecular level, their molecular characterization is challenging. In mass spectrometry, the ionization step is the key step, as it determines which species will be detected. This review presents an overview of the main ionization sources employed to characterize these kinds of samples in Fourier transform mass spectrometry (FT-MS), namely electrospray (ESI), atmospheric pressure photoionization (APPI), atmospheric pressure chemical ionization (APCI), atmospheric pressure laser ionization (APLI), and (matrix-assisted) laser desorption ionization ((MA)LDI), and their complementarity in the characterization of complex organic mixtures. First, the ionization techniques are examined in the common direct introduction (DI) usage. Second, these approaches are discussed in the context of coupling chromatographic techniques such as gas chromatography, liquid chromatography, and supercritical fluid chromatography.

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.

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.

Continuous rotary kiln pyrolysis of cassava plant shoot system and wide speciation of oxygenated and nitrogen-containing compounds in bio-oil by HESI and APPI-Orbitrap MS

This work proposes the pyrolysis of the cassava plant shoot system biomass and a comprehensive chemical characterization of the resulting bio-oil. The highest yields of liquid products were obtained at 600 °C, with 12.6 % bio-oil (organic fraction), which presented the lowest total acid number of 65.7 mg KOH g-1. The bio-oil produced at 500 °C exhibited the highest total phenolic content of approximately 41 % GAE, confirmed by GC/MS analysis (33.8 % of the total area). FT-Orbitrap MS analysis found hundreds of oxygenated constituents in the bio-oils, belonging to the O2-7 classes, as well as nitrogen compounds from the Ny and OxNy classes. Higher pyrolysis temperatures resulted in more oxygenated phenolics (O4-7) undergoing secondary degradation and deoxygenation reactions, generating O2-3 compounds. Additional classes affected were O3-5N2-3, while O1-2N1 presented more stable compounds. These findings show that cassava bio-oils are promising sources of renewable chemicals.

Chemometric Combination of Ultrahigh Resolving Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy for a Structural Characterization of Lignin Compounds

In recent years, the potential of lignins as a resource for material-based applications has been highlighted in many scientific and nonscientific publications. But still, to date, a lack of detailed structural knowledge about this ultracomplex biopolymer undermines its great potential. The chemical complexity of lignin demands a combination of different, powerful analytical methods, in order to obtain these necessary information. In this paper, we demonstrate a multispectroscopic approach using liquid-state and solid-state Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and nuclear magnetic resonance (NMR) spectroscopy to characterize a fractionated LignoBoost lignin. Individual FT-ICR-MS, tandem MS, and NMR results helped to determine relevant information about the different lignin fractions, such as molecular weight distributions, oligomer sizes, linkage types, and presence of specific functional groups. In addition, a hetero spectroscopic correlation approach was applied to chemometrically combine MS, MS/MS, and NMR data sets. From these correlation analyses, it became obvious that a combination of tandem MS and NMR data sets gives the opportunity to comprehensively study and describe the general structure of complex biopolymer samples. Compound-specific structural information are obtainable, if this correlation approach is extended to 1D-MS and NMR data, as specific functional groups or linkages are verifiable for a defined molecular formula. This enables structural characterization of individual lignin compounds without the necessity for tandem MS experiments. Hence, these correlation results significantly improve the depth of information of each individual analysis and will hopefully help to structurally elucidate entire lignin structures in the near future.

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.

Sugars and Organic Acids in 25 Strawberry Cultivars: Qualitative and Quantitative Evaluation

(1) The nutritional quality of strawberry (Fragaria × ananassa Duch) fruits, among others, is largely maintained by the presence of soluble sugars and organic acids. As the primary products of photosynthesis, they are energy depots in plants, necessary for the construction of cell constituents, but also serve as precursors of aromatic compounds and signaling molecules. (2) In this study, fruits of 25 strawberry cultivars were qualitatively and quantitatively characterized concerning individual sugars and organic acids by HPLC, FT-ICR-MS, and MS imaging analysis. In addition, the total quality index (TQI), as a novel mathematical model, was used to compare all individual parameters evaluated to obtain a quantitative single score, as an indicator of overall fruit quality. (3) Regardless of a large number of cultivars and monitored parameters that were studded, several cultivars stood out in terms of selected primary metabolites, such as 'Rumba', 'Jeny', and 'Sandra', while the latter had the best TQI score. (4) Intercultivar variations in sugars and organic acids profiles, along with other bioactive compounds, should be considered for selection of promising cultivars with improved naturally occurring nutraceutical traits. Besides the search for a pleasant taste, increased awareness of healthy nutrition resulted in heightening consumer demand for high-quality fruit.