Non-target evaluation of contaminants in honey bees and pollen samples by gas chromatography time-of-flight mass spectrometry

Toxicity of soil leaching liquor from coking plant in developmental zebrafish embryos/larvae model

The coking industry in China is the largest coke supplier in the world. Contaminated soil in industrial areas poses a serious threat to human and ecosystems. Most of the studies investigated the toxicity of soil from coking plant on soil microorganisms, while the toxic effects of soil leaching liquor on aquatics are limited. In this study, the composition of soil leaching liquor from a coking plant in Taiyuan (TY) was analyzed, and the developmental toxicity on zebrafish was evaluated. The results showed that a total of 91 polycyclic aromatic hydrocarbons were detected in the leaching liquor, followed by phenols and benzene series. The leaching liquor induced developmental impairment in zebrafish larvae, including delayed incubation, deficits in locomotor behavior, vascular and cardiac dysplasia, and impaired neurodevelopment. The results of metabolomics analysis showed that TY soil leaching liquor induced significant metabolic profile disturbances in zebrafish embryos/larvae. The developmental toxicity of the leaching liquor metabolic disorders may be associated with the leaching liquor-induced abnormalities in zebrafish embryonic development. Metabolic pathways were identified by arginine and proline metabolism, phosphotransferase system, starch and sucrose metabolism, steroid biosynthesis, beta-alanine metabolism, and nucleotide metabolism pathways.

Simultaneous analysis of pesticides and mycotoxins in primary processed foods: The case of bee pollen

Primary Processed Foods are a class of food items that are ready for consumption after minimal processing in the supply chain. These products are ubiquitous in our daily diet, but so far a limited number of studies dealt with the optimization of quality control methods to check their content of contaminants. Among primary processed foods, bee pollen is a nutritionally acclaimed food supplement, whose contamination with pesticides and mycotoxins has been largely proven. For this reason, the present study aimed at optimizing for the first time a comprehensive LC-MS/MS method capable of analyzing 282 pesticides and 8 mycotoxins in bee pollen. To obtain a suitable method, two extraction procedures (QuEChERS and Accelerated Solvent Extraction), as well as different chromatographic gradients and columns, were tested. The optimized methodology, comprehending an extraction based on semi-automated QuEChERS, and an analytical method including inert LC column technology, was validated and applied to a sample set of 34 bee pollens. The analyzed samples collectively showed the presence of 41 pesticides and 1 mycotoxin.

Method optimisation for large scope pesticide multiresidue analysis in bee pollen: A pilot monitoring study

Pesticide contamination in emerging foods and supplements is currently a topic of great interest. This study focused on the evaluation of pesticide residues in commercial bee pollen samples to evaluate the risk associated with their consumption. To this end, an automated clean-up method for the pesticide extracts of bee pollen was developed. An LC-MS/MS and a GC-MS/MS method were validated for the analysis of 353 pesticides in 80 bee pollen samples purchased from different countries. The results showed the presence of 77 different pesticide residues in bee pollen, including plant protection chemicals and veterinary treatments. 85 % of the samples were contaminated with pesticides and no relevant differences were found between conventional and organic samples. Pesticide concentrations exceeding the imposed MRL were found in 40 % of the samples, but the risk assessment showed that consumers are not exposed to an unacceptable risk when consuming the evaluated bee pollen.

The main strategies for soil pollution apportionment: A review of the numerical methods

Nowadays, a large number of compounds with different physical and chemical properties have been determined in soil. Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control. Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control. Many efforts have made to develop methods for identifying the sources of soil pollutants. These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods. We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis. The numerical methods, such as spatial geostatistics analysis, receptor models, and machine learning methods are addressed in depth. In most cases, however, the effectiveness of any single approach for source apportionment remains limited. Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution. This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution. This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

The role of the veterinary diagnostic toxicologist in apiary health

Susceptibility of individuals and groups to toxicants depends on complex interactions involving the host, environment, and other exposures. Apiary diagnostic investigation and honey bee health are truly population medicine: the colony is the patient. Here we provide basic information on the application of toxicology to the testing of domestic honey bees, and, in light of recent research, expand on some of the challenges of interpreting analytical chemistry findings as they pertain to hive health. The hive is an efficiently organized system of wax cells used to store brood, honey, and bee bread, and is protected by the bee-procured antimicrobial compound propolis. Toxicants can affect individual workers outside or inside the hive, with disease processes that range from acute to chronic and subclinical to lethal. Toxicants can impact brood and contaminate honey, bee bread, and structural wax. We provide an overview of important natural and synthetic toxicants to which honey bees are exposed; behavioral, husbandry, and external environmental factors influencing exposure; short- and long-term impacts of toxicant exposure on individual bee and colony health; and the convergent impacts of stress, nutrition, infectious disease, and toxicant exposures on colony health. Current and potential future toxicology testing options are included. Common contaminants in apiary products consumed or used by humans (honey, wax, pollen), their sources, and the potential need for product testing are also noted.

Application and prospect of metabolomics-related technologies in food inspection

BACKGROUND

Food inspection covers a broad range of topics, including nutrient analysis, food pollutants, food auxiliary materials, additives, and food sensory identification. The foundation of diverse subjects like food science, nutrition, health research, and the food industry, as well as the desired reference for drafting trade and food legislation, makes food inspection highly significant. Because of their high efficiency, sensitivity, and accuracy, instrumental analysis methods have gradually replaced conventional analytical methods as the primary means of food hygiene inspection.

SCOPE AND APPROACH

Metabolomics-based analysis technology, such as nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), has become a widely used analytics platform. This research provides a bird's eye view of the application and future of metabolomics-related technologies in food inspection.

KEY FINDINGS AND CONCLUSIONS

We have provided a summary of the features and the application range of various metabolomics techniques, the strengths and weaknesses of different metabolomics platforms, and their implementation in specific inspection procedures. These procedures encompass the identification of endogenous metabolites, the detection of exogenous toxins and food additives, analysis of metabolite alterations during processing and storage, as well as the recognition of food adulteration. Despite the widespread utilization and significant contributions of metabolomics-based food inspection technologies, numerous challenges persist as the food industry advances and technology continues to improve. Thus, we anticipate addressing these potential issues in the future.

Hydrocarbons and other risks in a beekeeping area of México: the precautionary principle for prevention and biotechnology for remediation

The Yucatan Peninsula is the most important beekeeping region. However, the presence of hydrocarbons and pesticides violates the human right to a healthy environment twice over; it can affect human beings directly due to its toxicological characteristics, but it also constitutes a risk, not very well dimensioned, regarding the loss of biodiversity of the ecosystem via the impact on pollination. On the other hand, the precautionary principle obliges the authorities to prevent damage to the ecosystem that may be caused by the productive activity of individuals. Although there are studies that separately warn about the decrease of bees in the Yucatan due to industrial activity, this work has the novelty of presenting an intersectoral analysis of the risk that includes the soy industry, the swine industry and the tourist industry. The latter incorporates a new risk not considered until now, which is the presence of hydrocarbons in the ecosystem. Additionally, we can demonstrate that hydrocarbons, such as diesel and gasoline, should be avoided when using no genetically modified organisms (GMOs) in bioreactors. The objective of this work was to propose the precautionary principle around the risks in a beekeeping area and to propose biotechnology without using GMOs.

Wide-Scope Multi-residue analysis of pesticides in beef by gas chromatography coupled with quadrupole Orbitrap mass spectrometry

Increasing pesticide contamination in foods of animal origin has made the wide-scope multi-residue analysis of pesticides an international concern. By using 191 pesticides, this study investigates a sensitive and reliable method for multi-residue analysis of pesticides in beef to determine the extent of the application of this method. The QuEChERS method was employed to extract and purify the pesticides as C18 was utilized as the absorbents. Then, the purified pesticides were analysed using gas chromatography - quadrupole orbitrap mass spectrometry (GC-Q-Orbitrap-MS). The validation test results revealed that this method was satisfactorily sensitive since its screening detection limit (SDL) ranged from 0.2 to 100 µg∙kg^-1. The recovery tests implemented at three spiking levels, namely 100, 200, and 500 µg∙kg^-1, generated the results of 71.95 %-113.97 %, while the intra- and inter-day precisions were 0.27 %-17.94 %, indicating that this method had excellent accuracy and precision.

Development and Validation of a Gas Chromatography-Mass Spectrometry Method for Determining Acaricides in Bee Pollen

Pesticides can be found in beehives for several reasons, including contamination from surrounding crops or for their use by beekeepers, which poses a risk to bee ecosystems and consumers. Therefore, efficient and sensitive methods are needed for determining pesticide residues in bee products. In this study, a new analytical method has been developed and validated to determine seven acaricides (atrazine, chlorpyrifos, chlorfenvinphos, α-endosulfan, bromopropylate, coumaphos, and τ-fluvalinate) in bee pollen using gas chromatography coupled to mass spectrometry. After an optimization study, the best sample treatment was obtained when using a modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) method employing an ethyl acetate and cyclohexane as the extractant mixture, and a mixture of salts for the clean-up step. A chromatographic analysis (<21 min) was performed in an Agilent DB-5MS column, and it was operated under programmed temperature conditions. The method was fully validated in terms of selectivity, limits of detection (0.2–3.1 µg kg−1) and quantification (0.6–9.7 µg kg−1), linearity, matrix effect (<20% in all cases), trueness (recoveries between 80% and 108%), and precision. Finally, the proposed method was applied to analyze commercial bee pollen samples, and some of the target pesticides (chlorfenvinphos, α-endosulfan, coumaphos, and τ-fluvalinate) were detected.

Pesticide Residues and Metabolites in Greek Honey and Pollen: Bees and Human Health Risk Assessment

BACKGROUND

Bees encounter a plethora of environmental contaminants during nectar and pollen collection from plants. Consequently, after their entrance into the beehives, the transfer of numerous pollutants to apicultural products is inevitable.

METHODS

In this context, during the period of 2015-2020, 109 samples of honey, pollen, and beebread were sampled and analyzed for the determination of pesticides and their metabolites. More than 130 analytes were investigated in each sample by applying two validated multiresidue methods (HPLC-ESI-MS/MS and GC-MS/MS).

RESULTS

Until the end of 2020, 40 determinations were reported in honey, resulting in a 26% positive to at least one active substance. The concentrations of pesticides ranged from 1.3 ng/g to 785 ng/g honey. For seven active substances in honey and pollen, maximum residue limits (MRLs) exceedances were observed. Coumaphos, imidacloprid, acetamiprid, amitraz metabolites (DMF and DMPF), and tau-fluvalinate were the predominant compounds detected in honey, while several pyrethroids such as λ-cyhalothrin, cypermethrin, and cyfluthrin were also found. Pollen and beebread, as expected, accumulated a higher number of active substances and metabolites (32 in total), exhibiting almost double the number of detections.

CONCLUSIONS

Although the above findings verify the occurrence of numerous pesticide and metabolite residues in both honey and pollen, the human risk assessment in the majority of the cases does not raise any concerns, and the same applies to bee risk assessment.

Bee Pollen and Bread as a Super-Food: A Comparative Review of Their Metabolome Composition and Quality Assessment in the Context of Best Recovery Conditions

Recently, functional foods have been a subject of great interest in dietetics owing not only to their nutritional value but rather their myriad of health benefits. Moreover, an increase in consumers' demands for such valuable foods warrants the development in not only production but rather tools of quality and nutrient assessment. Bee products, viz., pollen (BP) and bread, are normally harvested from the flowering plants with the aid of bees. BP is further subjected to a fermentation process in bee hives to produce the more valuable and bioavailable BB. Owing to their nutritional and medicinal properties, bee products are considered as an important food supplements rich in macro-, micro-, and phytonutrients. Bee products are rich in carbohydrates, amino acids, vitamins, fatty acids, and minerals in addition to a myriad of phytonutrients such as phenolic compounds, anthocyanins, volatiles, and carotenoids. Moreover, unsaturated fatty acids (USFAs) of improved lipid profile such as linoleic, linolenic, and oleic were identified in BP and BB. This work aims to present a holistic overview of BP and BB in the context of their composition and analysis, and to highlight optimized extraction techniques to maximize their value and future applications in nutraceuticals.

Non-targeted metabolomics of moldy wheat by ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry

Introduction

As one of the staple foods for the world's major populations, the safety of wheat is critical in ensuring people's wellbeing. However, mildew is one of the prevalent safety issues that threatens the quality of wheat during growth, production, and storage. Due to the complex nature of the microbial metabolites, the rapid identification of moldy wheat is challenging.

Methods

In this research, identification of moldy wheat samples was studied using ultra-performance liquid chromatography - quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics. The non-targeted PCA model for identifying moldy wheat from normal wheat was established by using previously established compounds database of authentic wheat samples. The partial least squares-discriminant analysis (PLS-DA) was performed.

Results and discussion

By optimizing the model parameters, correct discrimination of the moldy wheat as low as 5% (w/w) adulteration level could be achieved. Differential biomarkers unique to moldy wheat were also extracted to identify between the moldy and authentic wheat samples. The results demonstrated that the chemical information of wheat combined with the existing PCA model could efficiently discriminate between the constructed moldy wheat samples. The study offered an effective method toward screening wheat safety.

Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.

Fungicides and bees: a review of exposure and risk

Fungicides account for more than 35% of the global pesticide market and their use is predicted to increase in the future. While fungicides are commonly applied during bloom when bees are likely foraging on crops, whether real-world exposure to these chemicals - alone or in combination with other stressors - constitutes a threat to the health of bees is still the subject of great uncertainty. The first step in estimating the risks of exposure to fungicides for bees is to understand how and to what extent bees are exposed to these active ingredients. Here we review the current knowledge that exists about exposure to fungicides that bees experience in the field, and link quantitative data on exposure to acute and chronic risk of lethal endpoints for honey bees (Apis mellifera). From the 702 publications we screened, 76 studies contained quantitative data on residue detections in honey bee matrices, and a further 47 provided qualitative information about exposure for a range of bee taxa through various routes. We compiled data for 90 fungicides and metabolites that have been detected in honey, beebread, pollen, beeswax, and the bodies of honey bees. The risks posed to honey bees by fungicide residues was estimated through the EPA Risk Quotient (RQ) approach. Based on residue concentrations detected in honey and pollen/beebread, none of the reported fungicides exceeded the levels of concern (LOC) set by regulatory agencies for acute risk, while 3 and 12 fungicides exceeded the European Food Safety Authority (EFSA) chronic LOC for honey bees and wild bees, respectively. When considering exposure to all bees, fungicides of most concern include many broad-spectrum systemic fungicides, as well as the widely used broad-spectrum contact fungicide chlorothalonil. In addition to providing a detailed overview of the frequency and extent of fungicide residue detections in the bee environment, we identified important research gaps and suggest future directions to move towards a more comprehensive understanding and mitigation of the risks of exposure to fungicides for bees, including synergistic risks of co-exposure to fungicides and other pesticides or pathogens.

Analysis of Multiclass Pesticide Residues in Tobacco by Gas Chromatography Quadrupole Time-of-Flight Mass Spectrometry Combined with Mini Solid-Phase Extraction

A screening method using gas chromatography quadrupole time-of-flight mass spectrometry (GC-QTOF/MS) combined with mini solid-phase extraction (mini-SPE) was established for the quantification and validation of multiclass pesticide residues in tobacco. The method was quicker and easier, with sample purity higher than that obtained by traditional SPE and dispersed-SPE. Box-Behnken design, an experimental design for response-surface methodology, was used to optimize the variables affecting the target pesticide recovery. Under the optimized conditions, 92% of the pesticides showed satisfactory recoveries of 70%–120% with precision <20% at spiking levels of 50, 250, and 500 ng/g. The limits of detection and quantification for all the analyses were 0.05–29.9 ng/g and 0.20–98.8 ng/g, respectively. In addition, a screening method based on the retention time and a homebuilt high-resolution mass spectrometry database were established. Under the proposed screening parameters and at spiking levels of 50, 100, and 500 ng/g, 76.6%, 94.7%, and 99.0% multiclass pesticide residues were detected, respectively, using the workflow software. The validated method was successfully applied to the analysis of real tobacco samples. Thus, the combination of mini-SPE and GC-QTOF/MS serves as a suitable method for the quantitative analysis and rapid screening of multiclass pesticide residues in tobacco.

Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles

The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL^-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg^-1 and 0.3-2.1 μg kg^-1 in bovine and piscine muscle matrices, respectively.

A global study of pesticides in bees: QuEChERS as a sample preparation methodology for their analysis - Critical review and perspective

To this day, it remains unknown what the cause of decline of honey bee populations is and how to prevent this phenomenon efficiently. Poisonings with pesticides are assumed to be among the main causes for the decline of the honey bee population. Despite the significant progress observed in analytics over recent years, research aimed at improving methods applied in diagnostics of bee poisoning is still in progress. This is no easy task, since determination of the content of trace amounts (often equal to sublethal doses) of a wide range of compounds with diverse physico-chemical properties in honey bee samples with a complex matrix composition poses a serious challenge to modern analytics. This overview is the first to include a comprehensive critical assessment of analytical methods proposed for quantification of pesticides in honey bees over the last decade. Since the QuEChERS method is currently of great significance to ensuring accurate and reliable results of pesticide quantification in honey bees, the present overview focuses on the major aspects of this method, which will provide a comprehensive reference for scientists. The review focuses on the limitations of methods and on potential future prospects. It also contains information on the detection of pesticides in honey bees between 2010 and 2020 and characterizes the pesticide classes which are most toxic to these insects. This is extremely important, not just in the context of understanding the potential adverse impact of pesticides, manifesting as losses in bee colonies; it is also intended to facilitate decision-making in future research related to this difficult yet very important subject.

Pesticides residues and metabolites in honeybees: A Greek overview exploring Varroa and Nosema potential synergies

The aim of this study was to investigate reported cases of honeybee mortality incidents and the potential association to pesticide exposure and to their metabolites. The same honeybee samples were also assessed for Varroa mites, and Nosema microsporidia provoked infections to provide an integrated picture of all observable stressors that may impact bees' survival. Thus, honeybee samples from different areas of Greece (2014-2018) were analyzed for the presence of pesticide residues and metabolites. In this context, an existing LC-ESI-QqQ-MS multiresidue method of analytes of different chemical classes such as neonicotinoids, organophosphates, triazoles, carbamates, was enriched with additional active substances, developed and validated. A complementary GC-EI-QqQ-MS method was also exploited for the same scope covering pyrethroid compounds. Both methods monitored more than 150 active substances and metabolites and presented acceptable linearity over the ranges assayed. The calculated recoveries ranged from 65 to 120% for the three concentration levels, while the precision (RSD%) values ranged between 4 and 15%. Therefore, this approach proved sufficient to act as a monitoring tool for the determination of pesticide residues in cases of suspected honeybee poisoning incidents. From the analysis of 320 samples, the presence of 70 active substances and metabolites was confirmed with concentrations varying from 1.4 ng/g to 166 μg/g. Predominant detections were the acaricide coumaphos, several neonicotinoids exemplified by clothianidin, organophosporous compounds dimethoate and chlorpyrifos, and some pyrethroids. Metabolites of imidacloprid, chlorpyrifos, coumaphos, acetamiprid, fenthion and amitraz were also identified. Concerning Nosema and Varroa they were identified in 27 and 22% of samples examined, respectively, verifying their prevalence and coexistence with pesticides and their metabolites in honeybees.

Overcoming matrix effects in the analysis of pyrethroids in honey by a fully automated direct immersion solid-phase microextraction method using a matrix-compatible fiber

Pyrethroids insecticides may constitute a major hazard to honeybees, leading to colony collapse disorder. However, the determination of pyrethroids in honey has remained a challenging undertaking for analysts to date due to the high complexity of this matrix as well as the MRLs. This paper presents a fully automated method to overcome matrix influences using matrix-compatible overcoated SPME fiber for quantitative analysis of pyrethroids in diluted honey by GC-MS. The developed method was optimized using a multivariate approach providing LOQ values much lower than the stablished MRL (0.10-10 ng/g), while granting satisfactory linearity (R² > 0.998) in a wide linear range of 0.1-2000 ng/g, repeatability with RSDs < 10%, reproducibility RSDs < 20%, and accuracy ranging from 75 to 118% and from 82 to 120 % for inter-day and intra-day assays, respectively by using five replicates. The method herein proposed overcomes challenges presented by complex matrices while minimizing sample handling and the overall complexity of the procedure.

A three-year large scale study on the risk of honey bee colony exposure to blooming sunflowers grown from seeds treated with thiamethoxam and clothianidin neonicotinoids

Despite the restriction of the use of neonicotinoids in the EU, including thiamethoxam and clothianidin, the debate over their risk on honey bees has not been fully settled. This study presents results of a three-year study working with 180 honey bee colonies in ten replicates. Colonies were sorted into three treatments (60 colonies per treatment) exposed to sunflower blooms grown from seeds treated with thiamethoxam, clothianidin and a non-treated control. Each colony was assessed at six moments: one before to exposition to sunflower, two during the exposition (short-time risk), two after exposition (medium-time risk) and one after wintering (long-time risk). The health and development of the colonies were assessed by monitoring adult bee population, brood development, status of the queen, food reserves and survival. No significant difference among treatments when raw data was considered. However, when evolution from initial status of the colony was evaluated, a significant difference was observed from the first week of exposure to sunflower blooms. In this period, the number of adult bees and the amount of brood were slightly lower in the bee hives exposed to neonicotinoids, although such differences disappeared in subsequent evaluations. The concentration of residues in samples of beebread and adult bees was at the level of ng·g^-1. Magnitude of the effect of the treatment factor on the variability of colony health and development related parameters was low. The most important factor was the hive, followed by the replicate and year, and to a lesser extent the initial strength of the colonies.

Invertebrates facing environmental contamination by endocrine disruptors: Novel evidences and recent insights

The crisis of biodiversity we currently experience raises the question of the impact of anthropogenic chemicals on wild life health. Endocrine disruptors are notably incriminated because of their possible effects on development and reproduction, including at very low doses. As commonly recorded in the field, the burden they impose on wild species also concerns invertebrates, with possible specificities linked with the specific physiology of these animals. A better understanding of chemically-mediated endocrine disruption in these species has clearly gained from knowledge accumulated on vertebrate models. But the molecular pathways specific to invertebrates also need to be reckoned, which implies dedicated research efforts to decipher their basic functioning in order to be able to assess its possible disruption. The recent rising of omics technologies opens the way to an intensification of these efforts on both aspects, even in species almost uninvestigated so far.

Determination of polychlorinated biphenyls in honeybee, pollen, and honey samples from urban and semi-urban areas in Turkey

In recent years, honeybees and bee products such as pollen and honey have been used as bioindicators for monitoring environmental pollution. Unfortunately, there are few studies about polychlorinated biphenyl (PCB) concentrations in honeybees and bee products from Turkey. Honeybee and pollen samples were taken between May and September 2017, and honey samples were taken between July and September 2017 at urban and semi-urban areas in Bursa (Turkey). PCB concentrations measured by gas chromatography-microelectron capture detector (GC-μECD) were found to be 135.46 ± 6.53, 81.47 ± 23.52, and 106.35 ± 21.60 ng g^-1 dry weight (dw) for honeybee, pollen, and honey samples in the urban area, respectively; and 126.35 ± 26.54, 67.57 ± 27.34, and 118.88 ± 55.28 ng g^-1 dw for honeybee, pollen, and honey samples in the semi-urban area, respectively. Pearson correlation was made between meteorological parameters and pollutant concentrations. According to the correlation results, a significant relationship was found between the pollen and honey results and the total cloudiness and temperature in the semi-urban area. The coefficient of divergence (COD) and Pearson correlation coefficient (PCC) methods were applied to determine the similarities and differences between the pollutant concentrations and sources of the two areas and the temporal variation. According to these two methods, PCB concentrations and emission sources in honeybee and pollen samples in urban and semi-urban areas were generally different in May and June, and similar in August and September.

Non-targeted study of the thermal degradation of tylosin in honey, water and water:honey mixtures

Tylosin A is a macrolide antibiotic used in beekeeping. The aim of the study was to characterise the behaviour of tylosin A in honey after heating and during storage, and to identify its degradation products using a non-targeted approach. In addition, the possibility of a semi-quantification of tylosin B using tylosin A was assessed as a case study for the semi-quantification of degradation products using the parent compounds. The results showed significant degradation of tylosin A in aqueous solution (~96%) as well as in spiked and incurred honey dissolved in water (~50% and ~29%, respectively) after heating at 100°C for 90 min. However, at a lower heating temperature of 70°C, degradation was only observed in water (~31%). When stored at room temperature (27°C) for one year, tylosin A degraded significantly (~47%) in an incurred honey sample. Tylosin B, the only reported degradation product of tylosin A in honey so far, increased significantly in aqueous solution under all treatments, but it only increased in spiked water-honey mixture after heating at 100°C. Two new degradation products, namely 5-O-mycaminosyltylonolide (OMT) and lactenocin, were tentatively identified in water and spiked honey after heating at 100°C. The results of the present study reinforce the conclusion that relying only on the water model or spiked food matrix is not sufficient to understand the thermal degradation of antibiotics in food matrices. Finally, a semi-quantification of tylosin B with a relative error of 20% in an incurred honey sample was possible using the response factor of tylosin A, its parent compound. The results of this study prove that a semi-quantification using the parent compound to quantify its degradation compound can provide satisfactory results, but this will be analyte-dependent.

The toxic unit approach as a risk indicator in honey bees surveillance programmes: A case of study in Apis mellifera iberiensis

The influence of genetic diversity and exposure to xenobiotics on the prevalence of pathogens was studied within the context of a voluntary epidemiological study in Spanish apiaries of Apis mellifera iberiensis, carried out during the spring season of years 2014 and 2015. As such, the evolutionary lineages of the honey bee colonies were identified, a multiresidue analysis of xenobiotics was carried out in beebread and worker bee samples, and the Toxic Unit (TUm) was estimated for each sampled apiary. The relationship between lineages and the most prevalent pathogens (Nosema ceranae, Varroa destructor, trypanosomatids, Black Queen Cell Virus; and Deformed Wing Virus) was analysed with contingency tables, and the possible relationships between TUm and the prevalence of these pathogens were studied by using a factor analysis. The statistical analysis supported the associations between V. destructor and Deformed Wing Virus (DWV), and between N. ceranae and Black Queen Cell Virus (BQCV), but the association between these pathogens and trypanosomatids was not observed. TUm values varied between 5.5 × 10^-6 and 3.65 × 10^-1. When TUm < 3.35 × 10^-4, it was mainly determined by coumaphos, tau-fluvalinate and/or chlorfenvinphos. At higher values, other insecticides also contributed to TUm, although a clear predominance was not seen up to TUm ≥ 1.83 × 10^-2, when it was mainly defined by acrinathrin, spinosad and/or imidacloprid. The possible cumulative effect from the joint action of xenobiotics was >10% in the 63% of the cases. The prevalence of pathogens did not appear to be influenced by the distribution of evolutionary lineages and, while the prevalence of V. destructor was not found to be determined by TUm, there was a trend towards an increasing prevalence of N. ceranae when TUm ≥ 23 10^-4. This study is an example of using TUm approach beyond the field of the ecotoxicology.

Bioactive Constituents of F. esculentum Bee Pollen and Quantitative Analysis of Samples Collected from Seven Areas by HPLC

Bee pollen contains all the essential amino acids needed by humans. China is the largest producer of bee pollen in the world. In the present study, we identified 11 fatty acids in F. esculentum bee pollen oil by GC-MS analysis, and 16 compounds were isolated from F. esculentum bee pollen by column chromatography and identified. A high-performance liquid chromatography-diode array detector (HPLC-DAD) method was established for the quality control of F. esculentum bee pollen. A validated HPLC-DAD method was successfully applied to the simultaneous characterization and quantification of nine main constituents in seven samples collected from seven different areas in China. The results showed that all standard calibration curves exhibited good linearity (R2 > 0.999) in HPLC-DAD analysis with excellent precision, repeatability and stability. The total amount in the samples from the seven regions ranged from 23.50 to 46.05 mg/g. In addition, seven compounds were studied for their bioactivity using enzymic methods, whereby kaempferol (3) showed high α-glucosidase inhibitory activity (IC50: 80.35 μg/mL), ergosterol peroxide (8) showed high tyrosinase inhibitory activity (IC50: 202.37 μg/mL), and luteolin (1) had strong acetylcholinesterase inhibitory activity (IC50: 476.25 μg/mL). All results indicated that F. esculentum bee pollen could be a nutritious health food.

Optimization of the Data Treatment Steps of a Non-targeted LC-MS-Based Workflow for the Identification of Trace Chemical Residues in Honey

Non-targeted screening (e.g., suspected-target) is emerging as an attractive tool to investigate the occurrence of contaminants in food. The sample preparation and instrument analysis steps are known to influence the identification of analytes with non-targeted workflows, especially for complex matrices. However, for methods based on mass spectrometry, the impact of the post-analysis data treatment (e.g., feature extraction) on the capacity to correctly identify a contaminant at trace level is currently not well understood. The aim of the study was to investigate the influence of seven post-analysis data treatment parameters on the non-targeted identification of trace contaminants in honey using high-performance liquid chromatography coupled to hybrid quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). Seven compounds reported as veterinary drugs for honeybees were applied as model compounds. Among the parameters studied, the expansion window for chromatogram extraction and the average scans included in the spectra influenced significantly the identification process results. The optimized data treatment was applied to the non-targeted screening of veterinary drugs, pesticides, and other contaminants in 55 honey samples as a proof of concept. Among the 43 compounds included in a library of honey-related compounds that was used for screening, eight compounds were tentatively identified in at least one honey sample. The tentative identity of two of these compounds (tylosin A and hydroxymethylfurfural) was further confirmed with analytical standards. Graphical Abstract.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

Exploration of environmental contaminants in honeybees using GC-TOF-MS and GC-Orbitrap-MS

This study reports an analytical approach by gas chromatography and high-resolution mass spectrometry (HRMS) intended to be used for investigation of non-targeted environmental contaminants in honeybees. The approach involves a generic extraction and analysis with two GC-HRMS systems: time-of-flight and Orbitrap analyzers, GC-TOF-MS, and GC-Orbitrap-MS operated in electron-impact ionization (EI) mode. The workflow for screening of non-targeted contaminants consisted of initial peak detection by deconvolution and matching the first-stage mass spectra EI-MS with a nominal mass spectral library. To gain further confidence in the structural characterization of the contaminants under investigation, molecular formula of representative ions (molecular and fragment ions) was provided for those with an accurate mass scoring (error < 5 ppm). This methology was applied for screening environmental contaminants in 75 samples of adult honeybee. This approach has provided the tentative identification of environmental contaminants belonging to different chemical groups, among them, PAHs, phthalates and synthetic musks. Residues of veterinary treatments used in apiculture were also detected in the honeybee samples.

Qualitative analysis of Schizonepeta annua (Pall.) Schischk essential oil by gas chromatography-quadrupole time-of-flight mass spectrometry

In this study, a method for the qualitative analysis of small molecular compounds in Schizonepeta annua (Pall.) Schischk essential oil was established based on gas chromatography-quadrupole time-of-flight mass spectrometry. In addition to an automated search of the NIST library, the identification of oxygenated monoterpenes, phenolic esters, and phenolic compounds was achieved by two additional strategies. One strategy involved comparing the relative errors of accurate masses measured for ions in the experimental spectra with those calculated for fragments identified from the NIST database of candidate matches. The second strategy involved combination of the product ion scans and positive chemical ionisation spectra for structural elucidation. Overall, 95.45% of the total essential oil volatile chemical content of Schizonepeta annua (Pall.) Schischk was identified, with phenolic monoterpenes dominating.

Pesticide residues in honey bees, pollen and beeswax: Assessing beehive exposure

In order to study the distribution of pesticide residues in beekeeping matrices, samples of live in-hive worker honey bees (Apis mellifera), fresh stored pollen and beeswax were collected during 2016-2017 from 45 apiaries located in different landscape contexts in Spain. A total of 133 samples were screened for 63 pesticides or their degradation products to estimate the pesticide exposure to honey bee health through the calculation of the hazard quotient (HQ). The influence of the surrounding environment on the content of pesticides in pollen was assessed by comparing the concentrations of pesticide residues found in apiaries from intensive farming landscapes to those found in apiaries located in mountainous, grassland and urban contexts. Beeswax revealed high levels of miticides used in beekeeping such as coumaphos, chlorfenvinphos, fluvalinate and acrinathrin, which were detected in more than 75% of samples. Pollen was predominantly contaminated by miticides but also by insecticides used in agriculture such as chlorpyrifos and acetamiprid, which showed concentrations significantly higher in apiaries located in intensive farming contexts. Pesticides residues were less frequent and at lower concentrations in live honey bees. Beeswax showed the highest average hazard scores (HQ > 5000) to honey bees. Pollen samples contained the largest number of pesticide residues and relevant hazard (HQ > 50) to bees. Acrinathrin was the most important contributor to the hazard quotient scores in wax and pollen samples. The contributions of the pesticides dimethoate and chlorpyrifos to HQ were considered relevant in samples.

Viability of honeybee colonies exposed to sunflowers grown from seeds treated with the neonicotinoids thiamethoxam and clothianidin

In this study, honeybee colonies were monitored in a field study conducted on sunflowers grown from seeds treated with the systemic neonicotinoids thiamethoxam or clothianidin. This field trial was carried out in different representative growing areas in Spain over a beekeeping season. The health and development of the colonies was assessed by measuring factors that have a significant influence on their strength and overwintering ability. The parameters assessed were: colony strength (adult bees), brood development, amount of pollen and honey stores and presence and status of the queen. The concentration of residues (clothianidin and thiamethoxam) in samples of beebread and in adult bees was at the level of ng.g^-1; in the ranges of 0.10-2.89 ng g^-1 and 0.05-0.12 ng g^-1; 0.10-0.37 ng g^-1 and 0.01-0.05 ng g^-1, respectively. Multivariate models were applied to evaluate the interaction among factors. No significant differences were found between the honeybee colonies of the different treatment groups, either exposed or not to the neonicotinoids. The seasonal development of the colonies was affected by the environmental conditions which, together with the initial strength of the bee colonies and the characteristics of the plots, had a significant effect on the different variables studied.

Analysis and evaluation of (neuro)peptides in honey bees exposed to pesticides in field conditions

During the last years, declines in honey bee colonies are being registered worldwide. Cholinergic pesticides and their extensive use have been correlated to the decline of pollinators and there is evidence that pesticides act as neuroendocrine disruptors affecting the metabolism of neuropeptides. However, there is a big absence of studies with quantitative results correlating the effect of pesticide exposure with changes on neuropeptides insects, and most of them are conducted under laboratory conditions, typically with individual active ingredients. In this study, we present an analytical workflow to evaluate pesticide effects on honey bees through the analysis of (neuro)peptides. The workflow consists of a rapid extraction method and liquid chromatography with triple quadrupole for preselected neuropeptides. For non-target analysis, high resolution mass spectrometry, multivariate analysis and automatic identification of discriminated peptides using a specific software and protein sequence databases. The analytical method was applied to the analysis of target and non-target (neuro)peptides in honey bees with low and high content of a wide range of pesticides to which have been exposed in field conditions. Our findings show that the identification frequency of target neuropeptides decreases significantly in honey bees with high concentration of pesticides (pesticide concentrations ≥ 500 μg kg^-1) in comparison with the honey bees with low content of pesticides (pesticide concentrations ≤ 20 μg kg^-1). Moreover, the principal component analysis in non-target search shows a clear distinction between peptide concentration in honey bees with high level of pesticides and honey bees with low level. The use of high resolution mass spectrometry has allowed the identification of 25 non-redundant peptides responsible for discrimination between the two groups, derived from 18 precursor proteins.