Introduction  Human microbiota-associated (HMA) models are used to allow in vivo studies of the human gut microbiome and its effects on host physiology. In particular, alterations in early life microbiota have been linked to allergy development during childhood. In this study, we investigated how pools of human microbiota collected from infants with different allergy risk, thrive in mice and their offspring, as well as how they influence the host metabolome.

Method  We used a two-generation HMA mouse model in which dams were colonized with human feces from three groups of infants (n = 19, samples collected during the first 8 weeks of life). In two of the groups, all infants had a strong hereditary risk for allergic disease (n = 12), but only 6 of them developed allergy before 2 years of age. In the third group, which was used as a control, none of the infants had allergic heredity or developed allergy (n = 7). Microbiota trajectories were followed from inoculation to mouse offspring, and metabolic profiles were monitored in several intestinal organs as well as in the serum of the murine offspring.

Results  The human microbiota adapted to the murine host but still presented distinct compositional features, reflecting the original inoculated samples. These microbial differences were mirrored in the mouse offspring metabolome, with group-associated patterns in sphingolipids, acylcarnitines and tryptophan metabolites. Furthermore, the metabolic profiles of the mouse offspring aligned with those observed in fecal water preparations from the corresponding human infant fecal samples.

Conclusion  Our findings highlight the significant impact of early-life microbiota on the host metabolome and show that our two-generation HMA model is suitable for studying microbiota‒metabolome relationships relevant to humans. The differences in microbiota‒metabolome correlations between individuals who develop or do not develop allergic disease suggest that an allergic predisposition might be more multifaceted than previously believed.

Our understanding of the environmental behavior, bioaccumulation and concentrations of chlorinated paraffins (CPs) and Dechloranes (Dec) in the Arctic environment is still limited, particularly in freshwater ecosystems. In this descriptive study, short chain (SCCPs) and medium chain (MCCPs) CPs, Dechlorane Plus (DP) and analogues, and polychlorinated biphenyls (PCBs) were measured in sediments, benthic organisms, three-spined stickleback (Gasterosteus aculeatus), Arctic char (Salvelinus alpinus) and brown trout (Salmo trutta) in two Sub-Arctic lakes in Northern Norway. Takvannet (TA) is a remote lake, with no known local sources for organic contaminants, while Storvannet (ST) is situated in a populated area. SCCPs and MCCPs were detected in all sediment samples from ST with concentration of 42.26–115.29 ng/g dw and 66.18–136.69 ng/g dw for SCCPs and MCCPs, respectively. Only SCCPs were detected in TA sediments (0.4–5.28 ng/g dw). In biota samples, sticklebacks and benthic organisms showed the highest concentrations of CPs, while concentrations were low or below detection limits in both char and trout. The congener group patterns observed in both lakes showed SCCP profiles dominated by higher chlorinated congener groups while the MCCPs showed consistency in their profiles, with C₁₄ being the most prevalent carbon chain length. Anti- and syn-DP isomers were detected in all sediment, benthic and stickleback samples with higher concentrations in ST than in TA. However, they were only present in a few char and trout samples from ST. Dec 601 and 604 were below detection limits in all samples in both lakes. Dec 603 was detected only in ST sediments, sticklebacks and 2 trout samples, while Dec 602 was the only DP analogue found in all samples from both lakes. While there were clear differences in sediment concentrations of DP and Dec 602 between ST and TA, differences between lakes decreased with increasing δ¹⁵N. This pattern was similar to the PCB behavior, suggesting the lake characteristics in ST are playing an important role in the lack of biomagnification of pollutants in this lake. Our results suggest that ST receives pollutants from local sources in addition to atmospheric transport.

Ion mobility-mass spectrometry (IM-MS) has become increasingly popular with the rapid expansion of available techniques and instrumentation. To enable accuracy, standardization, and repeatability of IM-MS measurements, the community requires reliable and well-defined reference materials for calibration and tuning of the equipment. To address this need, synthetic dendrimers of high chemical and structural purity were tested on three ion mobility platforms as potential calibrants. First, synthesized dendrimers were characterized by drift tube ion mobility (DTIMS), using an Agilent 6560 IM-qTOF-MS to assess their drift tube collision cross section (^DTCCS) values. Then, assessment of obtained CCS values on trapped ion mobility (TIMS) and traveling wave ion mobility (TWIMS) ion mobility platforms were compared to those found by DTIMS. Across all three systems, dendrimers were found to have high potential for m/z and ion mobility calibration in the CCS range of 160–1700 Ų. To further validate their use as calibrants, drift tube calculated CCS values for dendrimers were utilized to calibrate calculations of CCS for known standards including Agilent Tuning mix, the CCS Major mix from Waters, and SPLASH LIPIDOMIX. Additionally, structures of sodiated dendrimers were computated along with theoretical CCS values which showed good agreement with the experimental CCS values. On the basis of the results presented, we recommend the use of dendrimers as alternatives and/or complementary compounds to commonly used calibrants for ion mobility platforms.

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico–predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS² spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS² spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.

The highly chlorinated chemical Dechlorane Plus (DP) was introduced as a replacement flame retardant for Mirex, which is banned through the Stockholm Convention (SC) for its toxicity (T), environmental persistence (P), potential for bioaccumulation (B) and long-range environmental transport potential (LRETP). Currently, Dechlorane Plus is under consideration for listing under the Stockholm Convention and by the European Chemical Agency as it is suspected to also have potential for P, B, T and LRET. Knowledge of atmospheric concentrations of chemicals in background regions is vital to understand their persistence and long-range atmospheric transport but such knowledge is still limited for Dechlorane Plus. Also, knowledge on environmental occurrence of the less described Dechlorane Related Compounds (DRCs), with similar properties and uses as Dechlorane Plus, is limited. Hence, the main objective of this study was to carry out a spatial mapping of atmospheric concentrations of Dechlorane Plus and Dechlorane Related Compounds at background sites in Europe. Polyurethane foam passive air samplers were deployed at 99 sites across 33 European countries for 3 months in summer 2016 and analyzed for dechloranes. The study showed that syn- and anti-DP are present across the European continent (<MDL-2.6 pg/m³ and <MDL-12.3 pg/m³, respectively), including parts of the Arctic. This supports that these compounds have potential for long-range atmospheric transport to remote regions. The highest concentrations of Dechlorane Plus were observed in central continental Europe, with anti-DP fractions close to the commercial mixture of Dechlorane Plus. The only detected Dechlorane Related Compounds was Dechlorane-602, which was found in 27% of the samples (<MDL-0.33 pg/m³). The measured concentrations and spatial patterns of Dechlorane Plus and Dechlorane-602 in air across Europe indicate the influence of primary sources of these compounds on background concentrations in European air. Future air monitoring efforts targeting dechloranes is needed in both background and source areas, including consistent temporal trends.

Concentration data on POPs in air is necessary to assess the effectiveness of international regulations aiming to reduce the emissions of persistent organic pollutants (POPs) into the environment. POPs in European background air are continuously monitored using active- and passive air sampling techniques at a limited number of atmospheric monitoring stations. As a result of the low spatial resolution of such continuous monitoring, there is limited understanding of the main sources controlling the atmospheric burdens of POPs across Europe. The key objectives of this study were to measure the spatial and temporal variability of concentrations of POPs in background air with a high spatial resolution (n = 101) across 33 countries within Europe, and to use observations and models in concert to assess if the measured concentrations are mainly governed by secondary emissions or continuing primary emissions. Hexachlorobenzene (HCB) was not only the POP detected in highest concentrations (median: 67 pg/m³), but also the only POP that had significantly increased over the last decade. HCB was also the only POP that was positively correlated to latitude. For the other targeted POPs, the highest concentrations were observed in the southern part of Europe, and a declining temporal trend was observed. Spatial differences in temporal changes were observed. For example, γ-HCH (hexachlorocyclohexane) had the largest decrease in the south of Europe, while α-HCH had declined the most in central-east Europe. High occurrence of degradation products of the organochlorine pesticides and isomeric ratios indicated past usage. Model predictions of PCB-153 (2,2^’,4,4^’,5,5^’-hexachlorobiphenyl) by the Global EMEP Multi-media Modelling System suggest that secondary emissions are more important than primary emissions in controlling atmospheric burdens, and that the relative importance of primary emissions are more influential in southern Europe compared to northern Europe. Our study highlights the major advantages of combining high spatial resolution observations with mechanistic modelling approaches to provide insights on the relative importance of primary- and secondary emission sources in Europe. Such knowledge is considered vital for policy makers aiming to assess the potential for further emission reduction strategies of legacy POPs.

Hydroxylated PCBs are an important class of metabolites of the widely distributed environmental contaminants polychlorinated biphenyls (PCBs). However, the absence of authentic standards is often a limitation when subject to detection, identification, and quantification. Recently, new strategies to quantify compounds detected with non-targeted LC/ESI/HRMS based on predicted ionization efficiency values have emerged. Here, we evaluate the impact of chemical space coverage and sample matrix on the accuracy of ionization efficiency-based quantification. We show that extending the chemical space of interest is crucial in improving the performance of quantification. Therefore, we extend the ionization efficiency-based quantification approach to hydroxylated PCBs in serum samples with a retraining approach that involves 14 OH-PCBs and validate it with an additional four OH-PCBs. The predicted and measured ionization efficiency values of the OH-PCBs agreed within the mean error of 2.1 × and enabled quantification with the mean error of 4.4 × or better. We observed that the error mostly arose from the ionization efficiency predictions and the impact of matrix effects was of less importance, varying from 37 to 165%. The results show that there is potential for predictive machine learning models for quantification even in very complex matrices such as serum. Further, retraining the already developed models provides a timely and cost-effective solution for extending the chemical space of the application area.

Organic contaminants (polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), and chlorinated paraffins (CPs)) and heavy metals and metalloids (Ag, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, Zn) were analysed in surface soil samples from the Agbogbloshie e-waste processing and dumping site in Accra (Ghana). In order to identify which of the pollutants are likely to be linked specifically to handling of e-waste, samples were also collected from the Kingtom general waste site in Freetown (Sierra Leone). The results were compared using principal component analyses (PCA). PBDE congeners found in technical octa-BDE mixtures, highly chlorinated PCBs and several heavy metals (Cu, Pb, Ni, Cd, Ag and Hg) showed elevated concentrations in the soils that are likely due to contamination by e-waste. PCAs associated those compounds with pyrogenic PAHs, suggesting that burning of e-waste, a common practice to isolate valuable metals, may cause this contamination. Moreover, other contamination pathways, especially incorporation of waste fragments into the soil, also appeared to play an important role in determining concentrations of some of the pollutants in the soil. Concentrations of several of these compounds were extremely high (especially PBDEs, heavy metals and SCCPs) and in some cases exceeded action guideline levels for soil. This indicates that exposure to these contaminants via the soil alone is potentially harmful to the recyclers and their families living on waste sites. Many organic contaminants and other exposure pathways such as inhalation are not yet included in such guidelines but may also be significant, given that deposition from the air following waste burning was identified as a major pollutant source.