Exploring chemical space in non-targeted analysis: a proposed ChemSpace tool.

Non-targeted analysis (NTA) using high-resolution mass spectrometry allows scientists to detect and identify a broad range of compounds in diverse matrices for monitoring exposure and toxicological evaluation without a priori chemical knowledge. NTA methods present an opportunity to describe the constituents of a sample across a multidimensional swath of chemical properties, referred to as "chemical space." Understanding and communicating which region of chemical space is extractable and detectable by an NTA workflow, however, remains challenging and non-standardized. For example, many sample processing and data analysis steps influence the types of chemicals that can be detected and identified. Accordingly, it is challenging to assess whether analyte non-detection in an NTA study indicates true absence in a sample (above a detection limit) or is a false negative driven by workflow limitations. Here, we describe the need for accessible approaches that enable chemical space mapping in NTA studies, propose a tool to address this need, and highlight the different ways in which it could be implemented in NTA workflows. We identify a suite of existing predictive and analytical tools that can be used in combination to generate scores that describe the likelihood a compound will be detected and identified by a given NTA workflow based on the predicted chemical space of that workflow. Higher scores correspond to a higher likelihood of compound detection and identification in a given workflow (based on sample extraction, data acquisition, and data analysis parameters). Lower scores indicate a lower probability of detection, even if the compound is truly present in the samples of interest. Understanding the constraints of NTA workflows can be useful for stakeholders when results from NTA studies are used in real-world applications and for NTA researchers working to improve their workflow performance. The hypothetical ChemSpaceTool suggested herein could be used in both a prospective and retrospective sense. Prospectively, the tool can be used to further curate screening libraries and set identification thresholds. Retrospectively, false detections can be filtered by the plausibility of the compound identification by the selected NTA method, increasing the confidence of unknown identifications. Lastly, this work highlights the chemometric needs to make such a tool robust and usable across a wide range of NTA disciplines and invites others who are working on various models to participate in the development of the ChemSpaceTool. Ultimately, the development of a chemical space mapping tool strives to enable further standardization of NTA by improving method transparency and communication around false detection rates, thus allowing for more direct method comparisons between studies and improved reproducibility. This, in turn, is expected to promote further widespread applications of NTA beyond research-oriented settings.

Large outbreak of Jimsonweed (Datura stramonium) poisoning due to consumption of contaminated humanitarian relief food: Uganda, March-April 2019.

BACKGROUND: Jimsonweed (Datura stramonium) contains toxic alkaloids that cause gastrointestinal and central nervous system symptoms when ingested. This can be lethal at high doses. The plant may grow together with leguminous crops, mixing with them during harvesting. On 13 March 2019, more than 200 case-patients were admitted to multiple health centres for acute gastrointestinal and neurologic symptoms. We investigated to determine the cause and magnitude of the outbreak and recommended evidence-based control and prevention measures. METHODS: We defined a suspected case as sudden onset of confusion, dizziness, convulsions, hallucinations, diarrhoea, or vomiting with no other medically plausible explanations in a resident of Napak or Amudat District from 1 March-30 April 2019. We reviewed medical records and canvassed all villages of the eight affected subcounties to identify cases. In a retrospective cohort study conducted in 17 villages that reported the earliest cases, we interviewed 211 residents about dietary history during 11-15 March. We used modified Poisson regression to assess suspected food exposures. Food samples underwent chemical (heavy metals, chemical contaminants, and toxins), proteomic, DNA, and microbiological testing in one national and three international laboratories. RESULTS: We identified 293 suspected cases; five (1.7%) died. Symptoms included confusion (62%), dizziness (38%), diarrhoea (22%), nausea/vomiting (18%), convulsions (12%), and hallucinations (8%). The outbreak started on 12 March, 2-12 h after Batch X of fortified corn-soy blend (CSB +) was distributed. In the retrospective cohort study, 66% of 134 persons who ate CSB + , compared with 2.2% of 75 who did not developed illness (RRadj = 22, 95% CI = 6.0-81). Samples of Batch X distributed 11-15 March contained 14 tropane alkaloids, including atropine (25-50 ppm) and scopolamine (1-10 ppm). Proteins of Solanaceae seeds and Jimsonweed DNA were identified. No other significant laboratory findings were observed. CONCLUSION: This was the largest documented outbreak caused by food contamination with tropane alkaloids. Implicated food was immediately withdrawn. Routine food safety and quality checks could prevent future outbreaks.

An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

Nontargeted Analysis Study Reporting Tool: A Framework to Improve Research Transparency and Reproducibility.

Non-targeted analysis (NTA) workflows using mass spectrometry are gaining popularity in many disciplines, but universally accepted reporting standards are nonexistent. Current guidance addresses limited elements of NTA reporting-most notably, identification confidence-and is insufficient to ensure scientific transparency and reproducibility given the complexity of these methods. This lack of reporting standards hinders researchers' development of thorough study protocols and reviewers' ability to efficiently assess grant and manuscript submissions. To overcome these challenges, we developed the NTA Study Reporting Tool (SRT), an easy-to-use, interdisciplinary framework for comprehensive NTA methods and results reporting. Eleven NTA practitioners reviewed eight published articles covering environmental, food, and health-based exposomic applications with the SRT. Overall, our analysis demonstrated that the SRT provides a valid structure to guide study design and manuscript writing, as well as to evaluate NTA reporting quality. Scores self-assigned by authors fell within the range of peer-reviewer scores, indicating that SRT use for self-evaluation will strengthen reporting practices. The results also highlighted NTA reporting areas that need immediate improvement, such as analytical sequence and quality assurance/quality control information. Although scores intentionally do not correspond to data/results quality, widespread implementation of the SRT could improve study design and standardize reporting practices, ultimately leading to broader use and acceptance of NTA data.

Strategies for data reduction in non-targeted screening analysis: The impact of sample variability for food safety applications.

While analytical methods targeting specific compounds are critical for food safety, analytes excluded from the targeted list will not be identified. Non-targeted analyses (NTA) using LC/HR-MS complement these approaches by producing information-rich data sets where molecular formula can be generated for each detected compound; however, data mining can be labor intensive. Thus, we examined different NTA approaches to reduce the number of compounds needing further investigation, without relying on a suspect list or MS/MS database, both in single ingredient foods (i.e., oats) and more complex, oat-containing samples. We investigated inherent sample variability and utilized this information to build in-house databases for removing food compounds from sample data. While food databases were useful for data reduction, differential analysis was the most promising approach for single ingredient foods because it substantially reduced the number of features while retaining spiked QC compounds; however, a combination of approaches was necessary with greater sample complexity.

A Proposed Quality Control Standard Mixture and Its Uses for Evaluating Nontargeted and Suspect Screening LC/HR-MS Method Performance.

Nontargeted (NTA) and suspect screening analyses (SSA) aim to detect and identify unknown compounds of interest from a given sample. The complexity and diversity of NTA and SSA methodologies necessitate the use of a comprehensive quality control standard mixture to determine if methods are fit for purpose, but to our knowledge, such a standard has not been developed that can be used by multiple disciplines, nor is one readily available. This work describes the development and analysis of a proposed nontargeted standard/quality control mixture for NTA and SSA applications using liquid chromatography/electrospray ionization-high resolution-mass spectrometry. Considerations in its development included achieving diversity of compounds with respect to elemental composition, molecular weight, retention time, and ionization in positive and/or negative ion modes, which resulted in the inclusion of 89 compounds. The utility of the standard mixture was applied on our own NTA and SSA workflows where sample preparation efficiency and potential sources of error due to instrumental and data processing methods were evaluated. Some areas in need of improvement were identified, such as hydrophilic compound detection and molecular formula generation for compounds containing fluorine. However, our overall methodology was found to be fit for purpose and we were able to establish thresholds to increase reliability and throughput of reported results.

Optimized chemical coverage and data quality for non-targeted screening applications using liquid chromatography/high-resolution mass spectrometry.

Non-targeted small molecule screening methods are used to analyze samples for potential compounds of interest without focusing on specific molecular species. There is great interest in these methods for metabolomic, environmental, forensic, and food safety applications, among others, to determine compounds that are responsible for a particular disease state or the presence of a harmful compound. In order for non-targeted analyses to become standardized and routine, best practices for sample preparation, data collection, and data analysis must be determined. This work focuses on optimizing specific aspects of a non-targeted workflow that utilizes high-resolution mass spectrometry using an Orbitrap instrument coupled to liquid chromatography. Sample preparation, liquid chromatography gradient length, and mass spectrometry resolving power and ionization modes were investigated to determine optimal conditions for detecting and extracting compounds from the data that cover broad molecular and polarity ranges. Infant rice cereal, orange juice, and yogurt with spiked standards were analyzed; food is inherently challenging to analyze due in part to sample complexity and diversity. Of the conditions tested, optimal conditions included a generic sample extraction using acetonitrile, water, and formic acid, a 25 min chromatographic gradient, collecting data in both positive and negative ion modes, and using 70 k resolving power. There are of course tradeoffs associated with each of these options that will be described in detail so that the appropriate conditions can be chosen for the desired application.

Platinum nanoparticles: an avenue for enhancing the release of nitric oxide from S-nitroso-N-acetylpenicillamine and S-nitrosoglutathione.

Nitric oxide (NO) is an endogenous bioregulator with established roles in diverse fields. The difficulty in the modulation of NO release is still a significant obstacle to achieving successful clinical applications. We report herein our initial work using electron spin resonance (ESR) spectroscopy to detect NO generated from S-nitroso-N-acetylpenicillamine (SNAP) and S-nitrosoglutathione (GSNO) donors catalyzed by platinum nanoparticles (Pt NPs, 3 nm) under physiological conditions. With ESR spectroscopy coupled with spin trapping and spin labeling techniques, we identified that Pt NPs can significantly promote the generation of NO from SNAP and GSNO under physiological conditions. A classic NO colorimetric detection kit was also employed to verify that Pt NPs truly triggered the release of NO from its donors. Pt NPs can act as promising delivery vehicles for on-demand NO delivery based on time and dosage. These results, along with the detection of the resulting disulfide product, were confirmed with mass spectrometry. In addition, cellular experiments provided a convincing demonstration that the triggered release of NO from its donors by Pt NPs is efficient in killing human cancer cells in vitro. The catalytic mechanism was elucidated by X-ray photo-electron spectroscopy (XPS) and ultra-high performance liquid chromatography/high-resolution mass spectrometry (UHPLC-HRMS), which suggested that Pt-S bond formation occurs in the solution of Pt NPs and NO donors. Identification of Pt NPs capable of generating NO from S-nitrosothiols (RSNOs) is an important step in harnessing NO for investigations into its clinical applications and therapies.

Nontargeted Screening of Food Matrices: Development of a Chemometric Software Strategy To Identify Unknowns in Liquid Chromatography-Mass Spectrometry Data.

The ability to identify contaminants or adulterants in diverse, complex sample matrixes is necessary in food safety. Thus, nontargeted screening approaches must be implemented to detect and identify unexpected, unknown hazardous compounds that may be present. Molecular formulas can be generated for detected compounds from high-resolution mass spectrometry data, but analysis can be lengthy when thousands of compounds are detected in a single sample. Efficient data mining methods to analyze these complex data sets are necessary given the inherent chemical diversity and variability of food matrixes. The aim of this work is to determine necessary requirements to successfully apply data analysis strategies to distinguish suspect and control samples. Infant formula and orange juice samples were analyzed with one lot of each matrix containing varying concentrations of a four compound mixture to represent a suspect sample set. Small molecular differences were parsed from the data, where analytes as low as 10 ppb were revealed. This was accomplished, in part, by analyzing a quality control standard, matrix spiked with an analytical standard mixture, technical replicates, a representative number of sample lots, and blanks within the sample sequence; this enabled the development of a data analysis workflow and ensured that the employed method is sufficient for mining relevant molecular features from the data.

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.

Suspected Palytoxin Inhalation Exposures Associated with Zoanthid Corals in Aquarium Shops and Homes - Alaska, 2012-2014.

On August 12, 2014, an Anchorage hospital notified the Alaska Section of Epidemiology (SOE) that a middle-aged male resident of Anchorage (patient A) had arrived in the emergency department with possible palytoxin exposure. Patient A complained of a bitter metallic taste, fever, weakness, cough, and muscle pain 7-8 hours after introduction of live zoanthid coral into his home aquarium. Palytoxin, a potent toxin known to produce the reported effects, is contained in zoanthid marine corals.

Identification and Structural Characterization of Naturally-Occurring Broad-Spectrum Cyclic Antibiotics Isolated from Paenibacillus.

The rise of antimicrobial resistance necessitates the discovery and/or production of novel antibiotics. Isolated strains of Paenibacillus alvei were previously shown to exhibit antimicrobial activity against a number of pathogens, such as E. coli, Salmonella, and methicillin-resistant Staphylococcus aureus (MRSA). The responsible antimicrobial compounds were isolated from these Paenibacillus strains and a combination of low and high resolution mass spectrometry with multiple-stage tandem mass spectrometry was used for identification. A group of closely related cyclic lipopeptides was identified, differing primarily by fatty acid chain length and one of two possible amino acid substitutions. Variation in the fatty acid length resulted in mass differences of 14 Da and yielded groups of related MS(n) spectra. Despite the inherent complexity of MS/MS spectra of cyclic compounds, straightforward analysis of these spectra was accomplished by determining differences in complementary product ion series between compounds that differ in molecular weight by 14 Da. The primary peptide sequence assignment was confirmed through genome mining; the combination of these analytical tools represents a workflow that can be used for the identification of complex antibiotics. The compounds also share amino acid sequence similarity to a previously identified broad-spectrum antibiotic isolated from Paenibacillus. The presence of such a wide distribution of related compounds produced by the same organism represents a novel class of broad-spectrum antibiotic compounds.

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.

Storage and uptake of D-serine into astrocytic synaptic-like vesicles specify gliotransmission.

Glial cells are increasingly recognized as active players that profoundly influence neuronal synaptic transmission by specialized signaling pathways. In particular, astrocytes have been shown recently to release small molecules, such as the amino acids l-glutamate and d-serine as "gliotransmitters," which directly control the efficacy of adjacent synapses. However, it is still controversial whether gliotransmitters are released from a cytosolic pool or by Ca(2+)-dependent exocytosis from secretory vesicles, i.e., by a mechanism similar to the release of synaptic vesicles in synapses. Here we report that rat cortical astrocytes contain storage vesicles that display morphological and biochemical features similar to neuronal synaptic vesicles. These vesicles share some, but not all, membrane proteins with synaptic vesicles, including the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) synaptobrevin 2, and contain both l-glutamate and d-serine. Furthermore, they show uptake of l-glutamate and d-serine that is driven by a proton electrochemical gradient. d-Serine uptake is associated with vesicle acidification and is dependent on chloride. Whereas l-serine is not transported, serine racemase, the synthesizing enzyme for d-serine, is anchored to the membrane of the vesicles, allowing local generation of d-serine. Finally, we reveal a previously unexpected mutual vesicular synergy between d-serine and l-glutamate filling in glia vesicles. We conclude that astrocytes contain vesicles capable of storing and releasing d-serine, l-glutamate, and most likely other neuromodulators in an activity-dependent manner.

Combining small-volume metabolomic and transcriptomic approaches for assessing brain chemistry.

The integration of disparate data types provides a more complete picture of complex biological systems. Here we combine small-volume metabolomic and transcriptomic platforms to determine subtle chemical changes and to link metabolites and genes to biochemical pathways. Capillary electrophoresis-mass spectrometry (CE-MS) and whole-genome gene expression arrays, aided by integrative pathway analysis, were utilized to survey metabolomic/transcriptomic hippocampal neurochemistry. We measured changes in individual hippocampi from the mast cell mutant mouse strain, C57BL/6 Kit(W-sh/W-sh). These mice have a naturally occurring mutation in the white spotting locus that causes reduced c-Kit receptor expression and an inability of mast cells to differentiate from their hematopoietic progenitors. Compared with their littermates, the mast cell-deficient mice have profound deficits in spatial learning, memory, and neurogenesis. A total of 18 distinct metabolites were identified in the hippocampus that discriminated between the C57BL/6 Kit(W-sh/W-sh) and control mice. The combined analysis of metabolite and gene expression changes revealed a number of altered pathways. Importantly, results from both platforms indicated that multiple pathways are impacted, including amino acid metabolism, increasing the confidence in each approach. Because the CE-MS and expression profiling are both amenable to small-volume analysis, this integrated analysis is applicable to a range of volume-limited biological systems.

Single-cell metabolomics: changes in the metabolome of freshly isolated and cultured neurons.

Metabolites are involved in a diverse range of intracellular processes, including a cell's response to a changing extracellular environment. Using single-cell capillary electrophoresis coupled to electrospray ionization mass spectrometry, we investigated how placing individual identified neurons in culture affects their metabolic profile. First, glycerol-based cell stabilization was evaluated using metacerebral neurons from Aplysia californica; the measurement error was reduced from ∼24% relative standard deviation to ∼6% for glycerol-stabilized cells compared to those isolated without glycerol stabilization. In order to determine the changes induced by culturing, 14 freshly isolated and 11 overnight-cultured neurons of two metabolically distinct cell types from A. californica, the B1 and B2 buccal neurons, were characterized. Of the more than 300 distinctive cell-related signals detected, 35 compounds were selected for their known biological roles and compared among each measured cell. Unsupervised multivariate and statistical analysis revealed robust metabolic differences between these two identified neuron types. We then compared the changes induced by overnight culturing; metabolite concentrations were distinct for 26 compounds in the cultured B1 cells. In contrast, culturing had less influence on the metabolic profile of the B2 neurons, with only five compounds changing significantly. As a result of these culturing-induced changes, the metabolic composition of the B1 neurons became indistinguishable from the cultured B2 cells. This observation suggests that the two cell types differentially regulate their in vivo or in vitro metabolomes in response to a changing environment.

Peptidomic analyses of mouse astrocytic cell lines and rat primary cultured astrocytes.

Astrocytes play an active role in the modulation of synaptic transmission by releasing cell-cell signaling molecules in response to various stimuli that evoke a Ca2+ increase. We expand on recent studies of astrocyte intracellular and secreted proteins by examining the astrocyte peptidome in mouse astrocytic cell lines and rat primary cultured astrocytes, as well as those peptides secreted from mouse astrocytic cell lines in response to Ca2+-dependent stimulations. We identified 57 peptides derived from 24 proteins with LC-MS/MS and CE-MS/MS in the astrocytes. Among the secreted peptides, four peptides derived from elongation factor 1, macrophage migration inhibitory factor, peroxiredoxin-5, and galectin-1 were putatively identified by mass-matching to peptides confirmed to be found in astrocytes. Other peptides in the secretion study were mass-matched to those found in prior peptidomics analyses on mouse brain tissue. Complex peptide profiles were observed after stimulation, suggesting that astrocytes are actively involved in peptide secretion. Twenty-six peptides were observed in multiple stimulation experiments but not in controls and thus appear to be released in a Ca2+-dependent manner. These results can be used in future investigations to better understand stimulus-dependent mechanisms of astrocyte peptide secretion.

Metabolic differentiation of neuronal phenotypes by single-cell capillary electrophoresis-electrospray ionization-mass spectrometry.

Single-cell mass spectrometry (MS) is a rapidly emerging field in metabolic investigations. The inherent chemical complexity of most biological samples poses analytical challenges when using MS platforms to measure sample content without prior chemical separation. Here, a single-cell capillary electrophoresis (CE) system was coupled with electrospray ionization (ESI) MS to enable the simultaneous measurement of a vast array of endogenous compounds in over 50 identified and isolated large neurons from the Aplysia californica central nervous system. More than 300 distinct ion signals (m/z values) were detected from a single neuron in the positive ion mode, 140 of which were selected for chemometric data analysis. Metabolic features were evaluated among six different neuron types (B1, B2, left pleural 1 (LPl1), metacerebral cell (MCC), R2, and R15) chosen for their various physiological functions. The results indicated chemical similarities among some neuron types (B1 to B2 and LPl1 to R2) and distinctive features for others (MCC and R15 cells). The quantitative nature of the MS platform allowed the comparison of metabolite levels for specific neurons. The CE-ESI-MS approach for examination of individual nanoliter-volume cells as described herein is readily adaptable to other volume-limited samples.