In C. elegans, the conserved transcription factor DAF-16/FOXO is a powerful aging regulator, relaying dire conditions into expression of stress resistance and longevity promoting genes. For some of these functions, including low insulin/IGF signaling (IIS), DAF-16 depends on the protein SMK-1/SMEK, but how SMK-1 exerts this role has remained unknown. We show that SMK-1 functions as part of a specific Protein Phosphatase 4 complex (PP4 SMK-1). Loss of PP4 SMK-1 hinders transcriptional initiation at several DAF-16-activated genes, predominantly by impairing RNA polymerase II recruitment to their promoters. Search for the relevant substrate of PP4 SMK-1 by phosphoproteomics identified the conserved transcriptional regulator SPT-5/SUPT5H, whose knockdown phenocopies the loss of PP4 SMK-1. Phosphoregulation of SPT-5 is known to control transcriptional events such as elongation and termination. Here we also show that transcription initiating events are influenced by the phosphorylation status of SPT-5, particularly at DAF-16 target genes where transcriptional initiation appears rate limiting, rendering PP4 SMK-1 crucial for many of DAF-16's physiological roles.
Neurodegenerative diseases may be the cause or the consequence of an acceleration of physiological ageing. Evidence for this concept is lacking due to practical limitations of human studies. Here, we compared the processes of physiological and pathological ageing of individual C. elegans over their lifespan. Using multi-parametric phenotyping, trajectories of ageing can be defined within a phenotypic landscape made of a large set of phenotypical features. Rather than an acceleration of ageing, a model for synucleinopathy showed a divergent trajectory of ageing. The pathological progression in individual animals can be predicted from early phenotypes with high accuracy. Despite of similar lifespans, disease-model worms display an early onset of decline in their phenotypic range of ability. This loss of flexibility provides an index of health valid for physiological and pathological contexts. Finally, we demonstrate the power of multi-parametric dataset to describe ageing, to quantify health and to predict specific health risks.
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