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Nature Studies Examine Epigenetic Modifications in Parkinson's Disease, Bacterial Gene Expression Patterns

An epigenomic analysis of neurons from Parkinson's disease patients reveals that the loss of TET2, a master regulator of cytosine modification status, can help protect the brain from the effects of the disease. In the study, which appears in Nature Neuroscience, Van Andel Institute scientists performed a genome-wide analysis of DNA methylation and hydroxymethylation at enhancers in neurons from Parkinson's disease patients and controls. They find a widespread increase in cytosine modifications at enhancers in Parkinson's patients, in part due to elevated levels of hydroxymethylation, as well as epigenetic and transcriptional upregulation of TET2. Notably, the researchers find that inactivating TET2 in aged mice fully prevents nigral dopaminergic neuronal loss induced by previous inflammation, as well as attenuates transcriptional immune responses to an inflammatory trigger. Based on these findings, TET2 reduction in Parkinson's disease patients may represent a new therapeutic intervention that could dampen neuroinflammatory responses and protect against neurodegeneration, the authors write.

Using an improved single-cell RNA sequencing protocol, a group of investigators from the Helmholtz-Center for Infection Research has generated insights into the growth-dependent gene expression patterns of the bacteria Salmonella and Pseudomonas. As reported in Nature Microbiology, the scientists used poly(A)-independent multiple annealing and dC-tailing-based quantitative single-cell RNA-seq to overcome the technical barriers that traditionally impede its use in bacteria. With this approach, they captured the growth-dependent gene expression patterns in the individual bacteria across all RNA classes and genomic regions. "Our work here should pave the way for gene-activity profiling in complex ecological microbial niches, such as the microbiome at the level of its many different single bacteria, and to monitor the drug susceptibility of pathogens based on RNA signatures from clinical samples," the researchers write.