Mitochondrial complex I activity in microglia sustains neuroinflammation.

Sustained smouldering, or low-grade activation, of myeloid cells is a common hallmark of several chronic neurological diseases, including multiple sclerosis1. Distinct metabolic and mitochondrial features guide the activation and the diverse functional states of myeloid cells2. However, how these metabolic features act to perpetuate inflammation of the central nervous system is unclear. Here, using a multiomics approach, we identify a molecular signature that sustains the activation of microglia through mitochondrial complex I activity driving reverse electron transport and the production of reactive oxygen species. Mechanistically, blocking complex I in pro-inflammatory microglia protects the central nervous system against neurotoxic damage and improves functional outcomes in an animal disease model in vivo. Complex I activity in microglia is a potential therapeutic target to foster neuroprotection in chronic inflammatory disorders of the central nervous system3.

Genetic determinants of micronucleus formation in vivo.

Genomic instability arising from defective responses to DNA damage1 or mitotic chromosomal imbalances2 can lead to the sequestration of DNA in aberrant extranuclear structures called micronuclei (MN). Although MN are a hallmark of ageing and diseases associated with genomic instability, the catalogue of genetic players that regulate the generation of MN remains to be determined. Here we analyse 997 mouse mutant lines, revealing 145 genes whose loss significantly increases (n = 71) or decreases (n = 74) MN formation, including many genes whose orthologues are linked to human disease. We found that mice null for Dscc1, which showed the most significant increase in MN, also displayed a range of phenotypes characteristic of patients with cohesinopathy disorders. After validating the DSCC1-associated MN instability phenotype in human cells, we used genome-wide CRISPR-Cas9 screening to define synthetic lethal and synthetic rescue interactors. We found that the loss of SIRT1 can rescue phenotypes associated with DSCC1 loss in a manner paralleling restoration of protein acetylation of SMC3. Our study reveals factors involved in maintaining genomic stability and shows how this information can be used to identify mechanisms that are relevant to human disease biology1.

Use of passive samplers in pollution monitoring: a numerical approach for marinas.

Triolein-containing semipermeable membrane devices (SPMDs) and butyl rubber (BR) based sorbents were employed as passive samplers in 14 coastal stations of Turkey including shipyards and marinas to characterize time-integrated levels of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) and their relationship to potential pollution sources. Passive samplers of SPMDs and BR sorbents were deployed for 30days in the spring of 2012. The maximum concentrations of total PAH and PCB compounds sequestered by SPMDs were 3338 ng g(-1) SPMD and 4247 pg g(-1) SPMD. (END)-I and DDT-related compounds were dominant OCP compounds for most of the sites in passive samplers. Total PAH concentrations in SPMDs were found 1.2 to 8 times higher than the concentrations in BRs. However, BR sorbents were able to sample some PAHs which could not be sampled by SPMDs. The concentrations of PCBs and OCPs in BRs were similar or higher than SPMDs. SPMD-data were used to estimate the average ambient water concentrations of the contaminants. Two existing theoretical approaches have been used to derive the concentrations of hydrophobic pollutants in the ambient waters. The results were found very similar and range from 7318 to 183864 pg L(-1) for PAHs, from 2 to 186 pg L(-1) for PCBs, and from 98 to 848 pg L(-1) for OCPs. Furthermore, a simple numerical model was designed to estimate the boat-related water concentrations in marinas by using the seawater data supplied by SPMDs. The model was mainly built on the water concentration and the capacities of a particular marina and then applied to two sites in the second marina. A good correlation was found between the model outputs and SPMD-water data.