Evaluation of a high resolving power time-of-flight mass spectrometer for drug analysis in terms of resolving power and acquisition rate

Climate-Affected Australian Tropical Montane Cloud Forest Plants: Metabolomic Profiles, Isolated Phytochemicals, and Bioactivities

The Australian Wet Tropics World Heritage Area (WTWHA) in northeast Queensland is home to approximately 18 percent of the nation's total vascular plant species. Over the past century, human activity and industrial development have caused global climate changes, posing a severe and irreversible danger to the entire land-based ecosystem, and the WTWHA is no exception. The current average annual temperature of WTWHA in northeast Queensland is 24 °C. However, in the coming years (by 2030), the average annual temperature increase is estimated to be between 0.5 and 1.4 °C compared to the climate observed between 1986 and 2005. Looking further ahead to 2070, the anticipated temperature rise is projected to be between 1.0 and 3.2 °C, with the exact range depending on future emissions. We identified 84 plant species, endemic to tropical montane cloud forests (TMCF) within the WTWHA, which are already experiencing climate change threats. Some of these plants are used in herbal medicines. This study comprehensively reviewed the metabolomics studies conducted on these 84 plant species until now toward understanding their physiological and metabolomics responses to global climate change. This review also discusses the following: (i) recent developments in plant metabolomics studies that can be applied to study and better understand the interactions of wet tropics plants with climatic stress, (ii) medicinal plants and isolated phytochemicals with structural diversity, and (iii) reported biological activities of crude extracts and isolated compounds.

High-Resolution Native Mass Spectrometry

Native mass spectrometry (MS) involves the analysis and characterization of macromolecules, predominantly intact proteins and protein complexes, whereby as much as possible the native structural features of the analytes are retained. As such, native MS enables the study of secondary, tertiary, and even quaternary structure of proteins and other biomolecules. Native MS represents a relatively recent addition to the analytical toolbox of mass spectrometry and has over the past decade experienced immense growth, especially in enhancing sensitivity and resolving power but also in ease of use. With the advent of dedicated mass analyzers, sample preparation and separation approaches, targeted fragmentation techniques, and software solutions, the number of practitioners and novel applications has risen in both academia and industry. This review focuses on recent developments, particularly in high-resolution native MS, describing applications in the structural analysis of protein assemblies, proteoform profiling of─among others─biopharmaceuticals and plasma proteins, and quantitative and qualitative analysis of protein-ligand interactions, with the latter covering lipid, drug, and carbohydrate molecules, to name a few.

High-Performance Data Processing Workflow Incorporating Effect-Directed Analysis for Feature Prioritization in Suspect and Nontarget Screening

Effect-directed analysis (EDA) aims at the detection of bioactive chemicals of emerging concern (CECs) by combining toxicity testing and high-resolution mass spectrometry (HRMS). However, consolidation of toxicological and chemical analysis techniques to identify bioactive CECs remains challenging and laborious. In this study, we incorporate state-of-the-art identification approaches in EDA and propose a robust workflow for the high-throughput screening of CECs in environmental and human samples. Three different sample types were extracted and chemically analyzed using a single high-performance liquid chromatography HRMS method. Chemical features were annotated by suspect screening with several reference databases. Annotation quality was assessed using an automated scoring system. In parallel, the extracts were fractionated into 80 micro-fractions each covering a couple of seconds from the chromatogram run and tested for bioactivity in two bioassays. The EDA workflow prioritized and identified chemical features related to bioactive fractions with varying levels of confidence. Confidence levels were improved with the in silico software tools MetFrag and the retention time indices platform. The toxicological and chemical data quality was comparable between the use of single and multiple technical replicates. The proposed workflow incorporating EDA for feature prioritization in suspect and nontarget screening paves the way for the routine identification of CECs in a high-throughput manner.

Targeted and Nontargeted Detection and Characterization of Trace Organic Chemicals in Human Serum and Plasma Using QuEChERS Extraction

Humans are exposed to a broad range of organic chemicals. Although targeted gas chromatography mass spectrometry techniques are used to quantify a limited number of persistent organic pollutants and trace organic contaminants in biological samples, nontargeted, high-resolution mass spectrometry (HRMS) methods assess the human exposome more extensively. We present a QuEChERS extraction for targeted and nontargeted analysis of trace organic contaminants using HRMS and compare this method to a traditional, cartridge-based solid-phase extraction (SPE). Following validation using reference and spiked serum samples, the method was applied to plasma samples (n = 75) from the Prospective investigation of Obesity, Energy, and Metabolism (POEM) study. We quantified 44 analytes using targeted analysis and 6247 peaks were detected using the nontargeted approach. Over 90% of targeted analytes were at least 90% recovered using the QuEChERS method in spiked serum samples. In nontargeted analysis, 84% of the peaks were above the method detection limit with area counts up to 3.0 × 105 times greater using the QuEChERS method. Of the targeted compounds, 88% were also identified in the nontargeted analysis. We categorized the 4212 chemicals assigned an identity in using EPA's CompTox Dashboard and 1076 chemicals were found in at least one list. The category with the highest number of chemicals was "androgen or estrogen receptor activity." The findings demonstrate that a QuEChERS technique is suitable for both targeted and nontargeted analysis of trace organic contaminants in biological samples.

FT-ICR-MS-based metabolomics: A deep dive into plant metabolism

Metabolomics involves the identification and quantification of metabolites to unravel the chemical footprints behind cellular regulatory processes and to decipher metabolic networks, opening new insights to understand the correlation between genes and metabolites. In plants, it is estimated the existence of hundreds of thousands of metabolites and the majority is still unknown. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a powerful analytical technique to tackle such challenges. The resolving power and sensitivity of this ultrahigh mass accuracy mass analyzer is such that a complex mixture, such as plant extracts, can be analyzed and thousands of metabolite signals can be detected simultaneously and distinguished based on the naturally abundant elemental isotopes. In this review, FT-ICR-MS-based plant metabolomics studies are described, emphasizing FT-ICR-MS increasing applications in plant science through targeted and untargeted approaches, allowing for a better understanding of plant development, responses to biotic and abiotic stresses, and the discovery of new natural nutraceutical compounds. Improved metabolite extraction protocols compatible with FT-ICR-MS, metabolite analysis methods and metabolite identification platforms are also explored as well as new in silico approaches. Most recent advances in MS imaging are also discussed.

Proposed Confidence Scale and ID Score in the Identification of Known-Unknown Compounds Using High Resolution MS Data

High-resolution (HR) MS instruments recording HR-full scan allow analysts to go further beyond pre-acquisition choices. Untargeted acquisition can reveal unexpected compounds or concentrations and can be performed for preliminary diagnosis attempt. Then, revealed compounds will have to be identified for interpretations. Whereas the need of reference standards is mandatory to confirm identification, the diverse information collected from HRMS allows identifying unknown compounds with relatively high degree of confidence without reference standards injected in the same analytical sequence. However, there is a necessity to evaluate the degree of confidence in putative identifications, possibly before further targeted analyses. This is why a confidence scale and a score in the identification of (non-peptidic) known-unknown, defined as compounds with entries in database, is proposed for (LC-) HRMS data. The scale is based on two representative documents edited by the European Commission (2007/657/EC) and the Metabolomics Standard Initiative (MSI), in an attempt to build a bridge between the communities of metabolomics and screening labs. With this confidence scale, an identification (ID) score is determined as [a number, a letter, and a number] (e.g., 2D3), from the following three criteria: I, a General Identification Category (1, confirmed, 2, putatively identified, 3, annotated compounds/classes, and 4, unknown); II, a Chromatography Class based on the relative retention time (from the narrowest tolerance, A, to no chromatographic references, D); and III, an Identification Point Level (1, very high, 2, high, and 3, normal level) based on the number of identification points collected. Three putative identification examples of known-unknown will be presented. Graphical Abstract ᅟ.

Targeted toxicological screening for acidic, neutral and basic substances in postmortem and antemortem whole blood using simple protein precipitation and UPLC-HR-TOF-MS

A broad targeted screening method based on broadband collision-induced dissociation (bbCID) ultra-performance liquid chromatography high-resolution time-of-flight mass spectrometry (UPLC-HR-TOF-MS) was developed and evaluated for toxicological screening of whole blood samples. The acidic, neutral and basic substances covered by the method were identified in postmortem and antemortem whole blood samples from forensic autopsy cases, clinical forensic cases and driving under the influence of drugs (DUID) cases by a reverse target database search. The screening method covered 467 substances. Validation was performed on spiked whole blood samples and authentic postmortem and antemortem whole blood samples. For most of the basic drugs, the established cut-off limits were very low, ranging from 0.25ng/g to 50ng/g. The established cut-off limits for most neutral and acidic drugs, were in the range from 50ng/g to 500ng/g. Sample preparation was performed using simple protein precipitation of 300μL of whole blood with acetonitrile and methanol. Ten microliters of the reconstituted extract were injected and separated within a 13.5min UPLC gradient reverse-phase run. Positive electrospray ionization (ESI) was used to generate the ions in the m/z range of 50-1000. Fragment ions were generated by bbCID. Identification was based on retention time, accurate mass, fragment ion(s) and isotopic pattern. A very sensitive broad toxicological screening method using positive electrospray ionization UPLC-HR-TOF-MS was achieved in one injection. This method covered basic substances, substances traditionally analyzed in negative ESI (e.g., salicylic acid), small highly polar substances such as beta- and gamma-hydroxybutyric acid (BHB and GHB, respectively) and highly non-polar substances such as amiodarone. The new method was shown to combine high sensitivity with a very broad scope that has not previously been reported in toxicological whole blood screening when using only one injection.

Cardiovascular drug determination in bioanalysis: an update

The great impact of cardiovascular diseases in human health has led to the development of a huge number of drugs and therapies to improve the treatment of these diseases. Cardiovascular drug analysis in biological fluids constitutes an important challenge for analytical scientists. There is a clear need for reliable methods to carry out both qualitative and quantitative analysis in a short time of analysis. Different problems such as drug monitoring, analysis of metabolites, study of drugs interactions, drugs residues or degradation products, chiral separation, and screening and confirmation of drugs of abuse in doping control must be solved. New trends in sample preparation, instrumental and column technology advances in LC and innovations in MS are described in this work.

Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry

The majority of analytical methods for food safety monitor the presence of a specific compound or defined set of compounds. Non-targeted screening methods are complementary to these approaches by detecting and identifying unexpected compounds present in food matrices that may be harmful to public health. However, the development and implementation of generalized non-targeted screening workflows are particularly challenging, especially for food matrices due to inherent sample complexity and diversity and a large analyte concentration range. One approach that can be implemented is liquid chromatography coupled to high-resolution mass spectrometry, which serves to reduce this complexity and is capable of generating molecular formulae for compounds of interest. Current capabilities, strategies, and challenges will be reviewed for sample preparation, mass spectrometry, chromatography, and data processing workflows. Considerations to increase the accuracy and speed of identifying unknown molecular species will also be addressed, including suggestions for achieving sufficient data quality for non-targeted screening applications.

Mass accuracy and isotopic abundance measurements for HR-MS instrumentation: capabilities for non-targeted analyses

The development of automated non-targeted workflows for small molecule analyses is highly desirable in many areas of research and diagnostics. Sufficient mass and chromatographic resolution is necessary for the detectability of compounds and subsequent componentization and interpretation of ions. The mass accuracy and relative isotopic abundance are critical in correct molecular formulae generation for unknown compounds. While high-resolution instrumentation provides accurate mass information, sample complexity can greatly influence data quality and the measurement of compounds of interest. Two high-resolution instruments, an Orbitrap and a Q-TOF, were evaluated for mass accuracy and relative isotopic abundance with various concentrations of a standard mixture in four complex sample matrices. The overall average ± standard deviation of the mass accuracy was 1.06 ± 0.76 ppm and 1.62 ± 1.88 ppm for the Orbitrap and the Q-TOF, respectively; however, individual measurements were ± 5 ppm for the Orbitrap and greater than 10 ppm for the Q-TOF. Relative isotopic abundance measurements for A + 1 were within 5% of the theoretical value if the intensity of the monoisotopic peak was greater than 1E7 for the Orbitrap and 1E5 for the Q-TOF, where an increase in error is observed with a decrease in intensity. Furthermore, complicating factors were found in the data that would impact automated data analysis strategies, including coeluting species that interfere with detectability and relative isotopic abundance measurements. The implications of these findings will be discussed with an emphasis on reasonable expectations from these instruments, guidelines for experimental workflows, data analysis considerations, and software design for non-targeted analyses.

Boundaries of mass resolution in native mass spectrometry

Over the last two decades, native mass spectrometry (MS) has emerged as a valuable tool to study intact proteins and noncovalent protein complexes. Studied experimental systems range from small-molecule (drug)-protein interactions, to nanomachineries such as the proteasome and ribosome, to even virus assembly. In native MS, ions attain high m/z values, requiring special mass analyzers for their detection. Depending on the particular mass analyzer used, instrumental mass resolution does often decrease at higher m/z but can still be above a couple of thousand at m/z 5000. However, the mass resolving power obtained on charge states of protein complexes in this m/z region is experimentally found to remain well below the inherent instrument resolution of the mass analyzers employed. Here, we inquire into reasons for this discrepancy and ask how native MS would benefit from higher instrumental mass resolution. To answer this question, we discuss advantages and shortcomings of mass analyzers used to study intact biomolecules and biomolecular complexes in their native state, and we review which other factors determine mass resolving power in native MS analyses. Recent examples from the literature are given to illustrate the current status and limitations.

Multi-target screening of biological samples using LC–MS/MS: focus on chromatographic innovations

Multi-target screening of biological fluids is a key tool in clinical and forensic toxicology. A complete toxicological analysis encompasses the sample preparation, the chromatographic separation and the detection. The present review briefly covers the new trends in sample preparation and detection and mainly focuses on the chromatographic stage, since a lot of technical improvements have been proposed over the last years. Among them, columns packed with sub-2 μm fully porous particles and sub-3 μm core-shell particles allow for significant improvements of resolution and higher throughput. Even if reversed-phase LC remains the most widely used chromatographic mode for toxicological screening, hydrophilic interaction chromatography and supercritical fluid chromatography appear as promising alternatives for attaining orthogonal selectivity, retention of polar compounds, and enhanced MS sensitivity.

Metabolite profiling and quantification of phytochemicals in potato extracts using ultra-high-performance liquid chromatography-mass spectrometry

BACKGROUND

Potatoes contain a diverse range of phytochemicals which have been suggested to have health benefits. Metabolite profiling and quantification were conducted on plant extracts made from a white potato cultivar and 'Urenika', a purple potato cultivar traditionally consumed by New Zealand Maori. There is limited published information regarding the metabolite profile of Solanum tuberosum cultivar 'Urenika'.

RESULTS

Using ultra-high- performance liquid chromatography-mass spectrometry (UHPLC-MS), a total of 31 compounds were identified and quantified in the potato extracts. The majority of the compounds were identified for the first time in 'Urenika'. These compounds include several types of anthocyanins, hydroxycinnamic acid (HCA) derivatives, and hydroxycinnamic amides (HCAA). Six classes of compounds, namely organic acids, amino acids, HCA, HCAA, flavonols and glycoalkaloids, were present in both extracts but quantities varied between the two extracts.

CONCLUSIONS

The unknown plant metabolites in both potato extracts were assigned with molecular formulae and identified with high confidence. Quantification of the metabolites was achieved using a number of appropriate standards. High-resolution mass spectrometry data critical for accurate identification of unknown phytochemicals were achieved and could be added to potato or plant metabolomic database.

Metabolite structure analysis by high-resolution MS: supporting drug-development studies

Effective characterization of drug metabolites in complex biological matrices is facilitated by mass spectrometers with high resolving power, mass accuracy and sensitivity. This review begins with an overview of high-resolution MS terminology and the different types of instrumentation that are currently available. Metabolite structure analysis offers unique challenges and, therefore, the different types of approaches used to solve problems are highlighted through specific examples. Overall, this review describes the value that high-resolution MS brings to drug-metabolism studies.

Evaluation of the interrelationship between mass resolving power and mass error tolerances for targeted bioanalysis using liquid chromatography coupled to high-resolution mass spectrometry

The determination of acceptable mass error tolerances for high-resolution mass spectrometry based signals has been evaluated in a comprehensive way. This was achieved by using a technical approach which is based on the post-column infusion of an analyte containing solution. This well-known experimental setup was not used to spot signal suppression regions of a particular analyte, but to spot regions of the chromatogram where a systematic mass drift of the analyte ion can be observed (isobaric interference plot). Not the changing signal intensity but the stability of the measured analyte mass was observed. A wide range of different analytes in combinations with potentially interfering matrices has been evaluated. Furthermore, different mass resolving power settings were evaluated. Isobaric interferences between matrix compounds and analytes were common at mass resolving powers <50,000 full width at half maximum. The proposed post-column infusion technique is a useful tool for the determination of the assay and matrix-specific mass error tolerances. It aims to ensure the highest possible selectivity, at the same time preventing the encounter of detrimental mass error related peak deformations as well as false negative findings. Unlike conventional matrix spiking approaches, isobaric interference plots provide information of potential interferences across the whole chromatographic time range. This becomes relevant when there is a relative retention time shift between the analyte and potential interfering matrix compounds. Furthermore, the described setup can be used to study how the mass accuracy of any mass spectrometer is affected by a widely varying total ion current.

Protein aggregation caused by aminoglycoside action is prevented by a hydrogen peroxide scavenger

Protein mistranslation causes growth arrest in bacteria, mitochondrial dysfunction in yeast, and neurodegeneration in mammals. It remains poorly understood how mistranslated proteins cause such cellular defects. Here we demonstrate that streptomycin, a bactericidal aminoglycoside that increases ribosomal mistranslation, induces transient protein aggregation in wild-type Escherichia coli. We further determined the aggregated proteome using label-free quantitative mass spectrometry. To identify genes that reduce cellular mistranslation toxicity, we selected from an overexpression library protein products that increased resistance against streptomycin and kanamycin. The selected proteins were significantly enriched in members of the oxidation-reduction pathway. Overexpressing one of these proteins, alkyl hydroperoxide reductase subunit F (a protein defending bacteria against hydrogen peroxide), but not its inactive mutant suppressed aggregated protein formation upon streptomycin treatment and increased aminoglycoside resistance. This work provides in-depth analyses of an aggregated proteome caused by streptomycin and suggests that cellular defense against hydrogen peroxide lowers the toxicity of mistranslation.

Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present

Mass-spectrometry-based proteomics is continuing to make major contributions to the discovery of fundamental biological processes and, more recently, has also developed into an assay platform capable of measuring hundreds to thousands of proteins in any biological system. The field has progressed at an amazing rate over the past five years in terms of technology as well as the breadth and depth of applications in all areas of the life sciences. Some of the technical approaches that were at an experimental stage back then are considered the gold standard today, and the community is learning to come to grips with the volume and complexity of the data generated. The revolution in DNA/RNA sequencing technology extends the reach of proteomic research to practically any species, and the notion that mass spectrometry has the potential to eventually retire the western blot is no longer in the realm of science fiction. In this review, we focus on the major technical and conceptual developments since 2007 and illustrate these by important recent applications.

High-resolution plant metabolomics: from mass spectral features to metabolites and from whole-cell analysis to subcellular metabolite distributions

The main goal of metabolomics is the comprehensive qualitative and quantitative analysis of the time- and space-resolved distribution of all metabolites present in a given biological system. Because metabolite structures, in contrast to transcript and protein sequences, are not directly deducible from the genomic DNA sequence, the massive increase in genomic information is only indirectly of use to metabolomics, leaving compound annotation as a key problem to be solved by the available analytical techniques. Furthermore, as metabolites vary widely in both concentration and chemical behavior, there is no single analytical procedure allowing the unbiased and comprehensive structural elucidation and determination of all metabolites present in a given biological system. In this review the different approaches for targeted and non-targeted metabolomics analysis will be described with special emphasis on mass spectrometry-based techniques. Particular attention is given to approaches which can be employed for the annotation of unknown compounds. In the second part, the different experimental approaches aimed at tissue-specific or subcellular analysis of metabolites are discussed including a range of non-mass spectrometry based technologies.

Mass spectrometry-based proteomics: qualitative identification to activity-based protein profiling

Mass spectrometry has become the method of choice for proteome characterization, including multicomponent protein complexes (typically tens to hundreds of proteins) and total protein expression (up to tens of thousands of proteins), in biological samples. Qualitative sequence assignment based on MS/MS spectra is relatively well-defined, while statistical metrics for relative quantification have not completely stabilized. Nonetheless, proteomics studies have progressed to the point whereby various gene-, pathway-, or network-oriented computational frameworks may be used to place mass spectrometry data into biological context. Despite this progress, the dynamic range of protein expression remains a significant hurdle, and impedes comprehensive proteome analysis. Methods designed to enrich specific protein classes have emerged as an effective means to characterize enzymes or other catalytically active proteins that are otherwise difficult to detect in typical discovery mode proteomics experiments. Collectively, these approaches will facilitate identification of biomarkers and pathways relevant to diagnosis and treatment of human disease.