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The potential effects of microplastic particle exposure on environmental organisms has sparked intense research activities. Various studies have been conducted, however on a limited set of mostly pristine polymer materials. In parallel to the ongoing research activities, it is discussed to include non-natural polymers into the registration process under REACH. Currently, non-natural polymers are exempted from registration, based on the general assumption of being non-hazardous due to their high molecular weight. In addition, the extensive number of polymers exceeding the registration capacities was mentioned as a reason for exemption. Hence, relevant polymers requiring a registration shall be selected according to specific criteria that help to identify those with a concern for hazardous effects. In the line of these developments we here present the results of a systematic ecotoxicity testing of 16 microplastic particles of different polymer composition, part of which are micronized polymer powders used in 3D printing (intentionally produced primary microplastic, losing particle shape by the 3D printing). All polymer materials were systematically varied and extensively characterised with regard to their properties (e.g. particle size, cross-linking, molar mass distribution, end groups, reactivity). Most of the polymers exerted toxicity in 48 h acute Daphnia magna immobilisation assay and 72 h chronic Raphidocelis subcapitata growth inhibition assay, except one PA and one HDPE material showing toxicity in D. magna, and one HDPE material showing toxicity in green algae. From these results we conclude that none of the microplastic particles studied here, independent of their polymer properties, give raise to concern for hazardous effects.

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The immense diversity and constant development of nanomaterials (NMs) increase the need for facilitated risk assessment, which requires knowledge of the modes of action (MoAs) of NMs. This necessitates a comprehensive data basis, which can be obtained using omics. Furthermore, the establishment of suitable in vitro test systems is essential to follow the 3R concept and to cope with the high number of NMs.In the present study, we aimed to compare NM effects in vitro and in vivo using a multi-omics approach. We applied an integrated data analysis strategy based on proteomics and metabolomics to four silica NMs and one titanium dioxide-based NM. For the in vitro investigations, rat alveolar epithelial cells (RLE-6TN) and rat alveolar macrophages (NR8383) were treated with different doses of NMs, and the results were compared with the effects on rat lungs after short-term inhalations and instillations.Since reactive oxygen species (ROS) production has been described as a critical biological effect of NMs, we focused on different levels of oxidative stress. Thus, we found opposite changes in proteins and metabolites related to the production of reduced glutathione in alveolar epithelial cells and alveolar macrophages, demonstrating that the MoAs of NMs depend on the model system used. Interestingly, in vivo, pathways related to inflammation were more affected than oxidative stress responses. Hence, the assignment of the observed effects to levels of oxidative stress was also different in vitro and in vivo.However, the overall classification of “active” and “passive” NMs was consistent in vitro and in vivo, suggesting that both cell lines tested are suitable for the assessment of NM toxicity. In summary, the results presented here highlight the need to carefully review model systems to decipher the extent to which they can replace in vivo assays.

The project nanoGRAVUR (BMBF, 2015–2018) developed a framework for grouping of nanomaterials. Different groups may result for each of the three distinct perspectives of occupational, consumer and environmental safety. The properties, methods and descriptors are harmonised between the three perspectives and are based on: Tier 1 intrinsic physico-chemical properties (what they are) or GHS classification of the non-nano-form (human tox, ecotox, physical hazards); Tier 2 extrinsic physico-chemical properties, release from nano-enabled products, in vitro assays with cells (where they go; what they do); Tier 3 case-specific tests, potentially in vivo studies to substantiate the similarity within groups or application-specific exposure testing. Amongst all properties, dissolution and transformation are least modulated by different nanoforms within one substance, whereas dustiness, dispersion stability, abiotic and especially in vitro surface reactivity vary more often between different nanoforms. The methods developed or selected by nanoGRAVUR fill several gaps highlighted in the ProSafe reviews, and are useful to implement (i) the concept of nanoforms of the European Chemicals Agency (ECHA) and (ii) the concept of discrete forms of the United States Environmental Protection Agency (EPA). One cannot assess the significance of a dissimilarity, if the dynamic range of that property is unknown. Benchmark materials span dynamic ranges that enable us to establish bands, often with order-of-magnitude ranges. In 34 case studies we observed high biological similarity within each substance when we compared different (nano)forms of SiO2, BaSO4, kaolin, CeO2, ZnO, organic pigments, especially when we compared forms that are all untreated on the surface. In contrast, different Fe2O3 or TiO2 (nano)forms differ more significantly. The same nanoforms were also integrated in nano-enabled products (NEPs) for automotive coatings, clinker-reduced cements, cosmetic sunscreen, and lightweight

Nanoenabled products (NEPs) have numerous outdoor uses in construction, transportation or consumer scenarios, and there is evidence that their fragments are released in the environment at low rates. We hypothesized that the lower surface availability of NEPs fragment reduced their environmental effects with respect to pristine nanomaterials. This hypothesis was explored by testing fragments generated by intentional micronisation (“the SUN approach”; Nowack et al. Meeting the Needs for Released Nanomaterials Required for Further Testing: The SUN Approach. The NEPs were composed of four matrices (epoxy, polyolefin, polyoxymethylene, and cement) with up to 5% content of three nanomaterials (carbon nanotubes, iron oxide, and organic pigment). Regardless of the type of nanomaterial or matrix used, it was observed that nanomaterials were only partially exposed at the NEP fragment surface, indicating that mostly the intrinsic and extrinsic properties of the matrix drove the NEP fragment toxicity. Ecotoxicity in multiple assays was done covering relevant media from terrestrial to aquatic, including sewage treatment plant (biological activity), soil worms (Enchytraeus crypticus), and fish (zebrafish embryo and larvae and trout cell lines). We designed the studies to explore the possible modulation of ecotoxicity by nanomaterial additives in plastics/polymer/cement, finding none. The results support NEPs grouping by the matrix material regarding ecotoxicological effect during the use phase. Furthermore, control results on nanomaterial-free polymer fragments representing microplastic had no significant adverse effects up to the highest concentration tested.

Lung lining fluid is the first biological barrier nanoparticles (NPs) encounter during inhalation. As previous inhalation studies revealed considerable differences between surface functionalized NPs with respect to deposition and toxicity, our aim was to investigate the influence of lipid and/or protein binding on these processes. Thus, we analyzed a set of surface functionalized NPs including different SiO2 and ZrO2 in pure phospholipids, CuroSurfTM and purified native porcine pulmonary surfactant (nS). Lipid binding was surprisingly low for pure phospholipids and only few NPs attracted a minimal lipid corona. Additional presence of hydrophobic surfactant protein (SP) B in CuroSurfTM promoted lipid binding to NPs functionalized with Amino or PEG residues. The presence of the hydrophilic SP A in nS facilitated lipid binding to all NPs. In line with this the degree of lipid and protein affinities for different surface functionalized SiO2 NPs in nS followed the same order (SiO2 Phosphate ∼ unmodified SiO2 < SiO2 PEG < SiO2 Amino NPs). Agglomeration and biomolecule interaction of NPs in nS was mainly influenced by surface charge and hydrophobicity. Toxicological differences as observed in short-term inhalation studies (STIS) were mainly influenced by the core composition and/or surface reactivity of NPs. However, agglomeration in lipid media and lipid/protein affinity appeared to play a modulatory role on short-term inhalation toxicity. For instance, lipophilic NPs like ZrO2, which are interacting with nS to a higher extent, exhibited a far higher lung burden than their hydrophilic counterparts, which deserves further attention to predict or model effects of respirable NPs.

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.