Carbon nanotubes degraded by neutrophil myeloperoxidase induce less pulmonary inflammation

We have shown previously that single-walled carbon nanotubes can be catalytically biodegraded over several weeks by the plant-derived enzyme, horseradish peroxidase1. However, whether peroxidase intermediates generated inside human cells or biofluids are involved in the biodegradation of carbon nanotubes has not been explored. Here, we show that hypochlorite and reactive radical intermediates of the human neutrophil enzyme myeloperoxidase catalyse the biodegradation of single-walled carbon nanotubes in vitro, in neutrophils and to a lesser degree in macrophages. Molecular modelling suggests that interactions of basic amino acids of the enzyme with the carboxyls on the carbon nanotubes position the nanotubes near the catalytic site. Importantly, the biodegraded nanotubes do not generate an inflammatory response when aspirated into the lungs of mice. Our findings suggest that the extent to which carbon nanotubes are biodegraded may be a major determinant of the scale and severity of the associated inflammatory responses in exposed individuals

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics