Chemical Identification Research Articles

A Portable and Reusable Database Infrastructure for Mass Spectrometry, and Its Associated Toolkit (The DIMSpec Project).

Nontargeted analysis (NTA) is a rapidly growing field of techniques that includes the identification of unknown chemical analytes in complex mixtures such as environmental, biological, and food matrices. The use of reference mass spectral databases is a key component of most NTA workflows, providing a high level of confidence for chemical identification when analytical standards are not available, yet effective interlaboratory sharing of research grade spectra remains challenging. The Database Infrastructure for Mass Spectrometry (DIMSpec) project focused on the creation of an open-source toolkit supporting storage and sharing of high-resolution mass spectra with attached sample and methodological metadata. As a demonstration of its utility, the DIMSpec toolkit was used to create a database of curated mass spectra for per- and polyfluoroalkyl substances (PFAS) generated from various sources. While the underlying toolkit is agnostic to analytical targets, this initial release (along with the database schema, mass spectral data, and database tools) should enable PFAS researchers to use these data for their own studies, including the identification of novel PFAS in the environment.

Chemical Relationship among Genetically Authenticated Medicinal Species of Genus Angelica

The genus Angelica comprises various species utilized for diverse medicinal purposes, with differences attributed to the varying levels or types of inherent chemical components in each species. This study employed DNA barcode analysis and HPLC analysis to genetically authenticate and chemically classify eight medicinal Angelica species (n = 106) as well as two non-medicinal species (n = 14) that have been misused. Nucleotide sequence analysis of the nuclear internal transcribed spacer (ITS) region revealed differences ranging from 11 to 117 bp, while psbA-trnH showed variances of 3 to 95 bp, respectively. Phylogenetic analysis grouped all samples except Angelica sinensis into the same cluster, with some counterfeits forming separate clusters. Verification using the NCBI database confirmed the feasibility of species identification. For chemical identification, a robust quantitative HPLC analysis method was developed for 46 marker compounds. Subsequently, two A. reflexa-specific and seven A. biserrata-specific marker compounds were identified, alongside non-specific markers. Moreover, chemometric clustering analysis reflecting differences in chemical content between species revealed that most samples formed distinct clusters according to the plant species. However, some samples formed mixed clusters containing different species. These findings offer crucial insights for the standardization and quality control of medicinal Angelica species.

Non-targeted analysis and toxicity prediction for evaluation of photocatalytic membrane distillation removing organic contaminants from hypersaline oil and gas field-produced water

Membrane distillation (MD) has received ample recognition for treating complex wastewater, including hypersaline oil and gas (O&G) produced water (PW). Rigorous water quality assessment is critical in evaluating PW treatment because PW consists of numerous contaminants beyond the targets listed in general discharge and reuse standards. This study evaluated a novel photocatalytic membrane distillation (PMD) process, with and without a UV light source, against a standard vacuum membrane distillation (VMD) process for treating PW, utilizing targeted analyses and a non-targeted chemical identification workflow coupled with toxicity predictions. PMD with UV light resulted in better removals of dissolved organic carbon, ammoniacal nitrogen, and conductivity. Targeted organic analyses identified only trace amounts of acetone and 2-butanone in distillates. According to non-targeted analysis, the number of suspects reduced from 65 in feed to 25–30 across all distillate samples. Certain physicochemical properties of compounds influenced contaminant rejection in different MD configurations. According to preliminary toxicity predictions, VMD, PMD with and without UV distillate samples, respectively contained 21, 22, and 23 suspects associated with critical toxicity concerns. Overall, non-targeted analysis together with toxicity prediction provides a competent supportive tool to assess treatment efficiency and potential impacts on public health and the environment during PW reuse.

Increased Selectivity in Photolytic Activation of Nanoassemblies Compared to Thermal Activation in On-Surface Ullmann Coupling.

On-surface synthesis is a powerful method that has emerged recently to fabricate a large variety of atomically precise nanomaterials on surfaces based on polymerization. It is very successful for thermally activated reactions within the framework of heterogeneous catalysis. As a result, it often lacks selectivity. We propose to use selective activation of specific bonds as a crucial ingredient to synthesize desired molecules with high selectivity. In this approach, thermally nonaccessible products are expected to arise in photolytically activated on-surface reactions with high selectivity. We demonstrate for assembled 2,2'-dibromo biphenyl clusters on Cu(111) that the thermal and photolytic activations yield distinctly different products, combining submolecular resolution of individual product molecules in real-space imaging by scanning tunneling microscopy with chemical identification in X-ray photoelectron spectroscopy and supported by ab initio calculations. The photolytically activated Ullmann coupling of 2,2'-dibromo biphenyl is highly selective, with only one identified product. It starkly contrasts the thermal reaction, which yields various products because alternate pathways are activated at the reaction temperature. Our study extends on-surface synthesis to a directed formation of thermally inaccessible products by direct bond activation. It promises tailored reactions of nanomaterials within the framework of on-surface synthesis based on the photolytic activation of specific bonds.

Automated Structure Discovery for Scanning Tunneling Microscopy.

Scanning tunneling microscopy (STM) with a functionalized tip apex reveals the geometric and electronic structures of a sample within the same experiment. However, the complex nature of the signal makes images difficult to interpret and has so far limited most research to planar samples with a known chemical composition. Here, we present automated structure discovery for STM (ASD-STM), a machine learning tool for predicting the atomic structure directly from an STM image, by building upon successful methods for structure discovery in noncontact atomic force microscopy (nc-AFM). We apply the method on various organic molecules and achieve good accuracy on structure predictions and chemical identification on a qualitative level while highlighting future development requirements for ASD-STM. This method is directly applicable to experimental STM images of organic molecules, making structure discovery available for a wider scanning probe microscopy audience outside of nc-AFM. This work also allows more advanced machine learning methods to be developed for STM structure discovery.

A natural diphenolic glucoside, sonnerphenolic C: Chemical synthesis, structural revision, redox transformation, and identification as an antioxidant

To investigate the redox o-hydroxylation of epirhododendrin (1) with tyrosinase and vitamin C, the possible product, sonnerphenolic C (2), and its epimer, tripodantoside (3), were synthesized for the first time via key steps including glycosylation and epimeric separation. The NMR data of synthetic compounds 2 and 3 were completely consistent with those of natural products 2 and 3, respectively. However, the specific rotation value of synthesized 2 (−15.5, c 1.8 in MeOH) was different from that of the previously reported data (+33.4, c 1.8 in MeOH) of natural product 2. L-Glucoside 5, the enantiomer of 2, was successively prepared through a similar synthetic route using l-glucose as the sugar material. The specific rotation value of 5 was recorded as +18.5 (c 1.8 in MeOH), indicating that the structure of natural product 2 should be revised to that of 5. Additionally, 1 and its epimer rhododendrin (4), were concisely synthesized using the same steps for 2 and 3. The initially proposed redox transformation of 1 to 2 was confirmed by the analysis of the reaction mixture with 1, tyrosinase, and vitamin C. Furthermore, 2 was newly identified in Acer nikoense extract as a natural antioxidant by HPLC and 2,2-diphenyl-1-picrylhydrazyl radical scavenging experiments.

Enhanced Detection of Estrogen-like Compounds by Genetically Engineered Yeast Sensor Strains.

The release of endocrine-disrupting compounds (EDCs) to the environment poses a health hazard to both humans and wildlife. EDCs can activate or inhibit endogenous endocrine functions by binding hormone receptors, leading to potentially adverse effects. Conventional analytical methods can detect EDCs at a high sensitivity and precision, but are blind to the biological activity of the detected compounds. To overcome this limitation, yeast-based bioassays have previously been developed as a pre-screening method, providing an effect-based overview of hormonal-disruptive activity within the sample prior to the application of analytical methods. These yeast biosensors express human endocrine-specific receptors, co-transfected with the relevant response element fused to the specific fluorescent protein reporter gene. We describe several molecular manipulations of the sensor/reporter circuit in a Saccharomyces cerevisiae bioreporter strain that have yielded an enhanced detection of estrogenic-like compounds. Improved responses were displayed both in liquid culture (96-well plate format) as well as in conjunction with sample separation using high-performance thin-layer chromatography (HPTLC). The latter approach allows for an assessment of the biological effect of individual sample components without the need for their chemical identification at the screening stage.

Analysis of aged microplastics: a review

AbstractMicroplastics are emerging contaminants that undergo progressive aging under environmental conditions such as sunlight irradiation, mechanical forces, temperature variations, and the presence of biological organisms. Since aging modifies microplastic properties, such as their own toxicity and the toxicity of trapped pollutants, advanced methods to analyze microplastics are required. Here we review methods to analyze microplastic aging with focus on the aging process, qualitative identification, quantitative characterization, and chemometrics. Qualitative identification is done by mechanical techniques, thermal techniques, e.g., thermal degradation and gas chromatography–mass spectrometry, and spectral techniques, e.g., infrared, Raman, fluorescent, and laser techniques. Quantitative characterization is done by microscopy and mass spectrometry. Microplastic aging results in a series of surface physical changes, biofilm formation, chemical oxidation, thermal alternation, and mechanical deterioration. Changes in mechanical and thermal properties allow to differentiate aged microplastics. Infrared and Raman spectroscopy are rapid and sensitive for chemical identification of microplastics in complex environmental samples. Combining two techniques is preferable for accurate detection and categorization.

Development of Nontargeted Workflow of Occupational Exposure by Infrared Ion Spectroscopy and Silicone Wristbands' Passive Sampling.

A new approach using orthogonal analytical techniques is developed for chemical identification. High resolution mass spectrometry and infrared ion spectroscopy are applied through a 5-level confidence paradigm to demonstrate the effectiveness of nontargeted workflow for the identification of hazardous organophosphates. Triphenyl phosphate is used as a surrogate organophosphate for occupational exposure, and silicone wristbands are used to represent personal samplers. Spectral data of a target compound is combined with spectral data of the sodium adduct and quantum chemical calculations to achieve a confirmed identification. Here, we demonstrate a nontargeted workflow that identifies organophosphate exposure and provides a mechanism for selecting validated methods for quantitative analyses.

Occurrence and abundance of microplastics and plasticizers in landfill leachate from open dumpsites in Sri Lanka

Occurrence and abundance of microplastics and plasticizers in landfill leachate from open dumpsites in Sri Lanka

Underestimated role of hydroxyl radicals for bromate formation in persulfate-based advanced oxidation processes

In persulfate-based advanced oxidation processes (PS-AOPs), sulfate radicals (SO4•-) have been recognized to play more important roles in inducing bromate (BrO3−) formation rather than hydroxyl radicals (HO•) because of the stronger oxidation capacity of the former. However, this study reported an opposite result that HO• indeed dominated the formation of bromate instead of SO4•-. Quenching experiments were coupled with electron paramagnetic resonance (EPR) detection and chemical probe identification to elucidate the contributions of each radical species. The comparison of different thermal activated persulfates (PDS and PMS) demonstrated that the significant higher bromate formation in HEAT/PMS ([BrO3−]/[Br−]0 = 0.8), as compared to HEAT/PDS ([BrO3−]/[Br−]0 = 0.2), was attributable to the higher concentration of HO• radicals in HEAT/PMS. Similarly, the bromate formation in UV/PDS ([BrO3−]/[Br−]0 = 1.0), with a high concentration of HO•, further underscored the dominant role of HO•. As a result, we quantified that HO• and SO4•- radicals accounted 66.7% and 33.3% for bromate formation. This controversial result can be reconciled by considering the critical intermediate, hypobromic acid/hypobromate (HOBr/BrO−), involved in the transformation of Br− to BrO3−. HO• have the chemical preference to induce the formation of HOBr/BrO− intermediates (contributing ∼ 60%) relative to SO4•- radicals (contributing ∼ 40%). This study highlighted the dominant role of HO• in the formation of bromate rather than SO4•- in PS-AOPs and potentially offered novel insights for reducing disinfection byproduct formation by controlling the radical species in AOPs.

Evaluation of microplastic pollution using bee colonies: An exploration of various sampling methodologies

Recent research has highlighted the potential of honeybees and bee products as biological samplers for monitoring xenobiotic pollutants. However, the effectiveness of these biological samplers in tracking microplastics (MPs) has not yet been explored. This study evaluates several methods of sampling MPs, using honeybees, pollen, and a novel in-hive passive sampler named the APITrap. The collected samples were characterized using a stereomicroscopy to count and categorise MPs by morphology, colour, and type. To chemical identification, a micro-Fourier transform-infrared (FTIR) spectroscopy was employed to determine the polymer types. The study was conducted across four consecutive surveillance programmes, in five different apiaries in Denmark. Our findings indicated that APITrap demonstrated better reproducibility, with a lower variation in results of 39%, compared to 111% for honeybee samples and 97% for pollen samples. Furthermore, the use of APITrap has no negative impact on bees and can be easily applied in successive samplings. The average number of MPs detected in the four monitoring studies ranged from 39 to 67 in the APITrap, 6 to 9 in honeybee samples, and 6 to 11 in pollen samples. Fibres were the most frequently found, accounting for an average of 91% of the total MPs detected in the APITrap, and similar values for fragments (5%) and films (4%). The MPs were predominantly coloured black, blue, green and red. Spectroscopy analysis confirmed the presence of up to five different synthetic polymers. Polyethylene terephthalate (PET) was the most common in case of fibres and similarly to polypropylene (PP), polyethylene (PE), polyacrylonitrile (PAN) and polyamide (PA) in non fibrous MPs. This study, based on citizen science and supported by beekeepers, highlights the potential of MPs to accumulate in beehives. It also shows that the APITrap provides a highly reliable and comprehensive approach for sampling in large-scale monitoring studies.

Ag Nanoparticles@Au Nanograting Array as a 3D Flexible and Effective Surface-Enhanced Raman Scattering Substrate.

Surface-enhanced Raman scattering (SERS) is a powerful analytical technique for chemical identification, but it remains a great challenge to realize the large-scale and well-controlled fabrication of sensitive and repeatable SERS substrates. Here, we report a facile strategy to fabricate centimeter-sized periodic Au nanograting (Au-NG) decorated with well-arranged Ag nanoparticles (Ag-NPs) (denoted as Ag-NPs@Au-NG) as a three-dimensional (3D) flexible hybrid SERS substrate with high sensitivity and good reproducibility. The Au-NG patterns with periodic ridges and grooves are fabricated through nanoimprint lithography by employing a low-cost digital versatile disc (DVD) as a master mold, and the Ag-NPs are assembled by a well-controlled interface self-assembly method without any coupling agents. Multiple coupling electromagnetic field effects are created at the nanogaps between the Ag-NPs and Au-NG patterns, leading to high-density and uniform hot spots throughout the substrate. As a result, the Ag-NPs@Au-NG arrays demonstrate an ultrahigh SERS sensitivity as low as 10-13 M for rhodamine 6G with a high average enhancement factor (EF) of 1.85 × 108 and good signal reproducibility. For practical applications, toxic organic pollutants including crystal violet, thiram, and melamine have been successfully detected with high sensitivity at a low detection limit, showing a good perspective in the rapid detection of toxic organic pollutants.

Generation of synthetic FTIR spectra to facilitate chemical identification of microplastics

In a context where learning databases of microplastic FTIR spectra are often incomplete, the objective of our work was to test whether a synthetic data generation method could be relevant to fill the gaps. To this end, synthetic spectra were generated to create new databases. The effectiveness of machine learning from these databases was then tested and compared with previous results. The results showed that the creation of synthetic learning databases could avoid, to a certain extent, the need for learning databases of environmental microplastics FTIR spectra. However, some limitations were encountered, for example, when two different chemical classes had very similar reference spectra or when the intensities of the bands associated with fouling became too intense. The FTIR study of the ageing and fouling of microplastics in the natural environment is one of the identified ways that could further improve this approach.

Effect of microplastics used in agronomic practices on agricultural soil properties and plant functions: Potential contribution to the circular economy of rural areas.

The extensive use of plastic materials and their improper disposal results in high amounts of plastic waste in the environment. Aging of plastics leads to their breakdown into smaller particles, such as microplastics (MPs) and nanoplastics. This research investigates plastics used in agricultural practices as they contribute to MP pollution in agricultural soils. The distribution and characteristics of MPs in agricultural soils were evaluated. In addition, the effect of MPs on soil properties, the relationship between MPs and metals in soil, the effect of MPs on the fate of pesticides in agricultural soils and the influence of MPs on plant growth were analysed, discussing legume, cereal and vegetable crops. Finally, a brief description of the main methods of chemical analysis and identification of MPs is presented. This study will contribute to a better understanding of MPs in agricultural soils and their effect on the soil-plant system. The changes induced by MPs in soil parameters can lead to potential benefits as it is possible to increase the availability of micronutrients and reduce plant uptake of toxic elements. Furthermore, although plastic pollution remains an emerging threat to soil ecosystems, their presence may result in benefits to agricultural soils, highlighting the principles of the circular economy.

Forward-predictive SERS-based chemical taxonomy for untargeted structural elucidation of epimeric cerebrosides

Achieving untargeted chemical identification, isomeric differentiation, and quantification is critical to most scientific and technological problems but remains challenging. Here, we demonstrate an integrated SERS-based chemical taxonomy machine learning framework for untargeted structural elucidation of 11 epimeric cerebrosides, attaining >90% accuracy and robust single epimer and multiplex quantification with <10% errors. First, we utilize 4-mercaptophenylboronic acid to selectively capture the epimers at molecular sites of isomerism to form epimer-specific SERS fingerprints. Corroborating with in-silico experiments, we establish five spectral features, each corresponding to a structural characteristic: (1) presence/absence of epimers, (2) monosaccharide/cerebroside, (3) saturated/unsaturated cerebroside, (4) glucosyl/galactosyl, and (5) GlcCer or GalCer’s carbon chain lengths. Leveraging these insights, we create a fully generalizable framework to identify and quantify cerebrosides at concentrations between 10−4 to 10−10 M and achieve multiplex quantification of binary mixtures containing biomarkers GlcCer24:1, and GalCer24:1 using their untrained spectra in the models.

Chemical characterization, multivariate analysis and comparison of biological activities of different parts of Fraxinus mandshurica.

Fraxinus mandshurica (Oleaceae) is used as a traditional medicinal plant for the treatment of red eyes, menstrual disorders, excessive leucorrhea, chronic bronchitis and psoriasis. To perform chemical characterization of the secondary metabolites of F. mandshurica roots, bark, stems and leaves, 32 samples were collected from eight provinces in this study. A total of 64 chemical components were detected from four different parts of F. mandshurica by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Meanwhile, a total of nine secoiridoids were obtained by natural product chemical extraction, isolation and identification methods. Quantitative analysis by high-performance liquid chromatography-diode array detection-mass spectrometry showed the highest total content of secoiridoids in the bark, which is also consistent with the traditional medicinal parts. The results of methodological validation showed that the correlation coefficient (R2 ) values were all >0.9993, indicating a good linear range of the standard curve, while the relative standard deviations of precision, reproducibility and stability were <3%, and the spiked recoveries ranged from 98.22 to 102.27%, indicating that the experimental method was reliable and stable. In addition, fingerprinting and a heatmap were established to demonstrate the content trends of F. mandshurica more visually from different origins. Multivariate analysis, including principal component analysis and partial least squares discriminant analysis, was performed to determine the chemical characteristics of different parts of F. mandshurica, and six characteristic secoiridoids that could be used to distinguish different origins were screened. Finally, the inhibition of tyrosinase, α-glucosidase, acetylcholinesterase and pancreatic lipase activities by the nine characteristic compounds and extracts from different parts were investigated, and the results showed that they all exhibited different degrees of enzyme activity inhibition and thus have potential applications in whitening and blemish removal, hypoglycemia, anti-Alzheimer's disease and anti-obesity as a new source of natural enzyme activity inhibitors. This study establishes an identification and evaluation method applicable to phytochemistry of different origins, which is a guideline for quality control, origin evaluation and clinical application of traditional medicinal plants. This is also an unprecedented study on the identification of the chemical composition of different parts of F. mandshurica, characteristic compounds and the inhibition of enzyme activity of extracts from different parts.

Unraveling the chemical identification and biological potential of the genus Asparagopsis: a comprehensive review

The genus Asparagopsis has garnered escalating attention in the spheres of marine biology and biotechnology due to its diverse chemical composition and promising biological capabilities. This all-encompassing review is dedicated to conducting an exhaustive inquiry into the chemical identification and biological importance of Asparagopsis species. By meticulously dissecting the array of chemical compounds found in genus Asparagopsis, encompassing polysaccharides, lipids, proteins, sterols, and bromoform. We unveil their potential utility in realms such as biomedicine, biotechnology, and the conservation of the environment. Furthermore, we delve into the bioactive attributes inherent in these compounds, encompassing effects such as antioxidative, antimicrobial, and anti-inflammatory properties, as well as their conceivable role in cancer treatments. Furthermore, this review underscores the environmental pertinence of genus Asparagopsis, particularly its capacity to mitigate climate change through the generation of compounds that alleviate greenhouse gas effects. Additionally, we delve into the economic facets of this genus, spanning from its integration into food additives to its contributions in cosmetics and sustainable agriculture. This comprehensive review furnishes a multi-faceted comprehension of Asparagopsis, illuminating its chemical diversity and biological significance, thereby paving the way for further explorations into its potential contributions across a spectrum of sectors.

Bacillus megaterium: Evaluation of Chemical Nature of Metabolites and Their Antioxidant and Agronomics Properties.

Bacillus megaterium is particularly known for its abundance in soils and its plant growth promotion. To characterize the metabolites excreted by this specie, we performed successive liquid/liquid extractions from bacteria culture medium with different polarity solvents (cyclohexane, dichloromethane, ethyl acetate and butanol) to separate the metabolites in different polarity groups. The extracts were characterized regarding their total phenolic content, the amount of reducing sugar, the concentration of primary amines and proteins, their chromatographic profile by HPLC-DAD-ELSD and their chemical identification by GC-MS. Among the 75 compounds which are produced by the bacteria, 19 identifications were for the first time found as metabolites of B. megaterium and 23 were described for the first time as metabolites in Bacillus genus. The different extracts containing B. megaterium metabolites showed interesting agronomic activity, with a global inhibition of seed germination rates of soya, sunflower, corn and ray grass, but not of corn, compared to culture medium alone. Our results suggest that B. megaterium can produce various metabolites, like butanediol, cyclic dipeptides, fatty acids, and hydrocarbons, with diverse effects and sometimes with opposite effects in order to modulate its response to plant growth and adapt to various environmental effects. These findings provide new insight into bioactive properties of this species for therapeutic uses on plants.

Volatile organic compounds emitted by Megaplatypusmutatus associated fungi: chemical identification and temperature-modulated responses by the ambrosial beetle

BackgroundIn ambrosia and bark beetles–fungi interaction, volatile organic compounds (VOCs) play a central role in mediating various aspects of community dynamics of beetles and/or fungi. These functions include facilitating beetle habitat location, mate identification, and fungal partner differentiation. However, the understanding on this context remains limited, especially in the globally distributed subfamily Platypodinae, which comprises predominantly ambrosia beetles. There is a lack of chemical data on ambrosia fungi from native South American species. This study addresses this gap by characterizing VOCs from twelve fungal species associated with Megaplatypusmutatus and assessing species-specific behavioral responses during dispersal.MethodsFungal VOCs were collected by gas chromatography–mass spectrometry combined with solid-phase microextraction and Y-olfactometry assays of males and females were performed at dispersal stage. Statistical analyses involved: non-metric multidimensional scaling multivariate plot and PermanovaPERMANOVA test, a cluster analysis through unweighted pair group method with Jaccard index, and finally, a chi-square goodness-of-fit test for beetle behavioral assays.ResultsWe identified 72 VOCs from the fungal species isolated from M.mutatus galleries, exocuticle, and gut. The olfactory behavior of M.mutatus demonstrated its capacity to discriminate between volatile profiles, showing a preference for either the fungus or the control source. Our results also enhance the understanding in a chemotaxonomic context and in the behavioral responses of M.mutatus revealing the beetle's remarkable low temperature tolerance and its capability to maintain mobility and orientation toward volatile sources even after zero-degree Celsius exposure.ConclusionThis study presents a comprehensive insight into fungal VOC profiles, emphasizing the sources of isolation within pest associated fungi, as well as its symbiotic species from the Raffaelea genus. In conclusion, our findings suggest that Megaplatypusmutatus exhibits a general aversion to its fungal VOCs symbiont. However, a notable exception arises when the beetles are pre-exposed for 48 h to freezing conditions, highlighting the beetles' ability to withstand freezing conditions as adults and to exhibit altered responses to their fungal associates under these circumstances.