Long-term monitoring of mercury in young German adults: Time trend analyses from the German Environmental Specimen Bank, 1995-2018.

As highlighted in the Minamata Convention, Mercury (Hg) in its various forms poses a substantial risk to human health and the environment. The health relevance of Hg is also recognized by the European Human Biomonitoring Initiative (HBM4EU), which classifies Hg as a priority substance, since considerable knowledge and data gaps on Hg exposure levels and their changes over time still exist in Europe. The German Environmental Specimen Bank (German ESB) provides valuable policy relevant data and long-term trends of substance exposure on a national level for international comparison and evaluation. In this study we analysed data of the German ESB on Hg exposure of young adults aged 20 to 29 including data on urinary Hg levels from 1995 to 2018 and whole blood Hg levels from 2001 to 2010. Results show a clear decrease in both, about 86% in urine total daily Hg excretion from 1995 (0.76 µg/L) to 2018 (0.11 µg/L) (n = 10,069) and about 57% in blood concentrations of Hg from 2001 (1.76 µg/L) to 2010 (0.77 µg/L) (n = 4085). Over the investigated timeframe only a few values exceeded the toxicologically derived health based guidance value HBM I for blood and urine, with these exceedances decreasing over time in line with the general trend. The factors mostly influencing Hg excretion identified in this study are dental amalgam as well as fish and seafood consumption. Besides other factors (e.g. age and sex), also airborne Hg exposure appears to be a low but evident influencing factor in Germany. Although a considerable decrease in internal Hg exposure is recognized in the last decades, the current low-level exposure may cause adverse health effects especially to vulnerable groups such as pregnant women and children. To further elucidate and evaluate current exposure sources and to reduce human exposure to Hg, continuous environmental and human biomonitoring is needed.

Sea Bass Primary Cultures versus RTgill-W1 Cell Line: Influence of Cell Model on the Sensitivity to Nanoparticles.

Determination of acute toxicity to vertebrates in aquatic environments is mainly performed following OECD test guideline 203, requiring the use of a large number of fish and with mortality as endpoint. This test is also used to determine toxicity of nanomaterials in aquatic environments. Since a replacement method for animal testing in nanotoxicity studies is desirable, the feasibility of fish primary cultures or cell lines as a model for nanotoxicity screenings is investigated here. Dicentrarchus labrax primary cultures and RTgill-W1 cell line were exposed to several concentrations (0.1 to 200 ug/mL) of different nanoparticles (TiO2, polystyrene and silver), and cytotoxicity, metabolic activity and reactive oxygen species formation were investigated after 24 and 48 h of exposure. Protein corona as amount of protein bound, as well as the influence of surface modification (-COOH, -NH2), exposure media (Leibovitz's L15 or seawater), weathering and cell type were the experimental variables included to test their influence on the results of the assays. Data from all scenarios was split based on the significance each experimental variable had in the result of the cytotoxicity tests, in an exploratory approach that allows for better understanding of the determining factors affecting toxicity. Data shows that more variables significantly influenced the outcome of toxicity tests when the primary cultures were exposed to the different nanoparticles. Toxicity tests performed in RTgill-W1 were influenced only by exposure time and nanoparticle concentration. The whole data set was integrated in a biological response index to show the overall impact of nanoparticle exposures.

Pitfalls in HLA Ligandomics-How to Catch a Li(e)gand.

Knowledge about the peptide repertoire presented by human leukocyte antigens (HLA) holds the key to unlock target-specific cancer immunotherapies such as adoptive cell therapies or bispecific T cell engaging receptors. Therefore, comprehensive and accurate characterization of HLA peptidomes by mass spectrometry (immunopeptidomics) across tissues and disease states is essential. With growing numbers of immunopeptidomics datasets and the scope of peptide identification strategies reaching beyond the canonical proteome, the likelihood for erroneous peptide identification as well as false annotation of HLA-independent peptides as HLA ligands is increasing. Such "fake ligands" can lead to selection of nonexistent targets for immunotherapeutic development and need to be recognized as such as early as possible in the preclinical pipeline. Here we present computational and experimental methods that enable the identification of "fake ligands" that might be introduced at different steps of the immunopeptidomics workflow. The statistics presented herein allow discrimination of true HLA ligands from coisolated HLA-independent proteolytic fragments. In addition, we describe necessary steps to ensure system suitability of the chromatographic system. Furthermore, we illustrate an algorithm for detection of source fragmentation events that are introduced by electrospray ionization during mass spectrometry. For confirmation of peptide sequences, we present an experimental pipeline that enables high-throughput sequence verification through similarity of fragmentation pattern and coelution of synthetic isotope-labeled internal standards. Based on these methods, we show the overall high quality of existing datasets but point out limitations and pitfalls critical for individual peptides and how they can be uncovered in order to identify true ligands.

Long-term time trend of lead exposure in young German adults - Evaluation of more than 35 Years of data of the German Environmental Specimen Bank.

Lead is a ubiquitous pollutant with well-known effects on human health. As there is no lower toxicological threshold for lead in blood and since data gaps on lead exposure still exist in many European countries, HBM data on lead is of high importance. To address this, the European Human Biomonitoring Initiative HBM4EU classified lead as a priority substance. The German Environmental Specimen Bank (German ESB) has monitored lead exposure since more than 35 years. Using data from the early 1980s to 2019 we reveal and discuss long-term trends in blood lead levels (BLLs) and current internal exposure of young adults in Germany. BLLs in young adults decreased substantially in the investigated period. As results from the ESB sampling site Muenster demonstrate, the geometric mean of BLLs of young adults decreased from 1981 (78,7 µg/L) to 2019 (10.4 µg/L) by about 87%. Trends in human exposure closely correlate with air lead levels (ALLs) provided by the European Monitoring and Evaluation Programme (EMEP). Hence, the decrease of BLLs largely reflects the drop in air lead pollution. Known associations of sex, smoking, alcohol consumption, and housing situation with BLLs are confirmed with data of the German ESB. Although internal lead exposure in Germany decreased substantially, the situation might be different in other European countries. Since 2010, BLLs of young adults in Germany levelled out at approximately 10 µg/L. The toxicity of lead even at low levels is known to cause adverse health effects especially in children following exposure of the child or the mother during pregnancy. To identify current exposure sources and to minimize future lead exposure, continuous monitoring of lead intake and exposure levels is needed.

Towards Harmonized Biobanking for Biomonitoring: A Comparison of Human Biomonitoring-Related and Clinical Biorepositories.

Human biomonitoring (HBM) depends on high-quality human samples to identify status and trends in exposure and ensure comparability of results. In this context, much effort has been put into the development of standardized processes and quality assurance for sampling and chemical analysis, while effects of sample storage and shipment on sample quality have been less thoroughly addressed. To characterize the currently applied storage and shipment procedures within the consortium of the European Human Biomonitoring Initiative (HBM4EU), which aims at harmonization of HBM in Europe, a requirement analysis based on data from an online survey was conducted. In addition, the online survey was addressed to professionals in clinical biobanking represented by members of the European, Middle Eastern and African Society for Biopreservation and Biobanking (ESBB) to identify the current state-of-the-art in terms of sample storage and shipment. Results of this survey conducted in these two networks were compared to detect processes with potential for optimization and harmonization. In general, many similarities exist in sample storage and shipment procedures applied by ESBB members and HBM4EU partners and many requirements for ensuring sample quality are already met also by HBM4EU partners. Nevertheless, a need for improvement was identified for individual steps in sample storage, shipment, and related data management with potential impact on sample and data quality for HBM purposes. Based on these findings, recommendations for crucial first steps to further strengthen sample quality, and thus foster advancement in HBM on a pan-European level are given.

Trends in characteristics of 24-h urine samples and their relevance for human biomonitoring studies - 20 years of experience in the German Environmental Specimen Bank.

To document trends in human exposure to environmental pollutants, the German Environmental Specimen Bank (ESB) has been routinely collecting and archiving 24-h urine samples from young adults at four sampling sites in Germany on an annual basis. For the purpose of normalizing measured analyte concentrations, urinary creatinine (UC), specific gravity (SG), conductivity (CON), and total urine volume (UVtot) of 24-h urine samples have also been recorded. These parameters are however susceptible to variation over time, as well as within/among participants and normalization against them can thus affect the interpretation of data regarding exposure to environmental pollutants. To evaluate the influence of normalization against these parameters, we first sought to determine variations of these parameters with regard to differences between sexes and trends over time. We analysed data from 8619 urine samples collected from 1997 to 2016. We observed an inverse relation between UVtot and UC, SG, and CON. We also found differences between sexes for UC, SG and CON, but not UVtot. UC, SG, and CON showed significant decreasing trends over time in both sexes. In contrast, a significant increase of over 30% in UVtot, independent of participant age and BMI, was revealed. This increase in UVtot and the concomitant sample dilution is likely to have an impact on measured analyte concentrations in 24-h urine samples. Hence, normalization of urinary concentrations is warranted when interpreting time trends of human exposure. Next, urinary calcium (Ca2+) concentrations of ESB participants were used to demonstrate the effects of normalization against each of the four urine parameters. From 1997 to 2016, measured Ca2+ concentrations showed a statistically significant but scientifically implausible decrease. Normalization of Ca2+ concentrations against UVtot (by calculating the total daily excretion), UC, or CON, but not SG, eliminated this decrease. Consistent with previous work, Ca2+ concentrations in urine and total daily Ca2+ excretion were higher for males than females. Normalization against UC, SG, or CON, however, attenuated this difference. Thus, to avoid misinterpretation in trend analysis and sex-specific excretion in 24-h urine samples, the calculation of the total daily excretion is recommended.

Network-based analysis of omics data: the LEAN method.

Motivation: Most computational approaches for the analysis of omics data in the context of interaction networks have very long running times, provide single or partial, often heuristic, solutions and/or contain user-tuneable parameters. Results: We introduce local enrichment analysis (LEAN) for the identification of dysregulated subnetworks from genome-wide omics datasets. By substituting the common subnetwork model with a simpler local subnetwork model, LEAN allows exact, parameter-free, efficient and exhaustive identification of local subnetworks that are statistically dysregulated, and directly implicates single genes for follow-up experiments.Evaluation on simulated and biological data suggests that LEAN generally detects dysregulated subnetworks better, and reflects biological similarity between experiments more clearly than standard approaches. A strong signal for the local subnetwork around Von Willebrand Factor (VWF), a gene which showed no change on the mRNA level, was identified by LEAN in transcriptome data in the context of the genetic disease Cerebral Cavernous Malformations (CCM). This signal was experimentally found to correspond to an unexpected strong cellular effect on the VWF protein. LEAN can be used to pinpoint statistically significant local subnetworks in any genome-scale dataset. Availability and Implementation: The R-package LEANR implementing LEAN is supplied as supplementary material and available on CRAN ( https://cran.r-project.org ). Contacts: benno@pasteur.fr or tournier-lasserve@univ-paris-diderot.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

Bacterial Internalization, Localization, and Effectors Shape the Epithelial Immune Response during Shigella flexneri Infection.

Intracellular pathogens are differentially sensed by the compartmentalized host immune system. Nevertheless, gene expression studies of infected cells commonly average the immune responses, neglecting the precise pathogen localization. To overcome this limitation, we dissected the transcriptional immune response to Shigella flexneri across different infection stages in bulk and single cells. This identified six distinct transcriptional profiles characterizing the dynamic, multilayered host response in both bystander and infected cells. These profiles were regulated by external and internal danger signals, as well as whether bacteria were membrane bound or cytosolic. We found that bacterial internalization triggers a complex, effector-independent response in bystander cells, possibly to compensate for the undermined host gene expression in infected cells caused by bacterial effectors, particularly OspF. Single-cell analysis revealed an important bacterial strategy to subvert host responses in infected cells, demonstrating that OspF disrupts concomitant gene expression of proinflammatory, apoptosis, and stress pathways within cells. This study points to novel mechanisms through which bacterial internalization, localization, and injected effectors orchestrate immune response transcriptional signatures.

Identification and characterization of an ABA-activated MAP kinase cascade in Arabidopsis thaliana.

Abscisic acid (ABA) is a major phytohormone involved in important stress-related and developmental plant processes. Recent phosphoproteomic analyses revealed a large set of ABA-triggered phosphoproteins as putative mitogen-activated protein kinase (MAPK) targets, although the evidence for MAPKs involved in ABA signalling is still scarce. Here, we identified and reconstituted in vivo a complete ABA-activated MAPK cascade, composed of the MAP3Ks MAP3K17/18, the MAP2K MKK3 and the four C group MAPKs MPK1/2/7/14. In planta, we show that ABA activation of MPK7 is blocked in mkk3-1 and map3k17mapk3k18 plants. Coherently, both mutants exhibit hypersensitivity to ABA and altered expression of a set of ABA-dependent genes. A genetic analysis further reveals that this MAPK cascade is activated by the PYR/PYL/RCAR-SnRK2-PP2C ABA core signalling module through protein synthesis of the MAP3Ks, unveiling an atypical mechanism for MAPK activation in eukaryotes. Our work provides evidence for a role of an ABA-induced MAPK pathway in plant stress signalling.

Identification of additional proteins in differential proteomics using protein interaction networks.

In this study, we developed a novel computational approach based on protein-protein interaction networks to identify a list of proteins that might have remained undetected in differential proteomic profiling experiments. We tested our computational approach on two sets of human smooth muscle cell protein extracts that were affected differently by DNase I treatment. Differential proteomic analysis by saturation DIGE resulted in the identification of 41 human proteins. The application of our approach to these 41 input proteins consisted of four steps: (i) Compilation of a human protein-protein interaction network from public databases; (ii) calculation of interaction scores based on functional similarity; (iii) determination of a set of candidate proteins that are needed to efficiently and confidently connect the 41 input proteins; and (iv) ranking of the resulting 25 candidate proteins. Two of the three highest-ranked proteins, beta-arrestin 1, and beta-arrestin 2, were experimentally tested, revealing that their abundance levels in human smooth muscle cell samples were indeed affected by DNase I treatment. These proteins had not been detected during the experimental proteomic analysis. Our study suggests that our computational approach may represent a simple, universal, and cost-effective means to identify additional proteins that remain elusive for current 2D gel-based proteomic profiling techniques.