The dynamics of early-state transcriptional changes and aggregate formation in a Huntington's disease cell model

Abstract

Background: Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a CAG expansion in the Huntingtin (HTT) gene. Proteolytic cleavage of mutant huntingtin (Htt) protein with an expanded polyglutamine (polyQ) stretch results in production of Htt fragments that aggregate and induce impaired ubiquitin proteasome, mitochondrial functioning and transcriptional dysregulation. To understand the time-resolved relationship between aggregate formation and transcriptional changes at early disease stages, we performed temporal transcriptome profiling and quantification of aggregate formation in living cells in an inducible HD cell model. Results: Rat pheochromocytoma (PC12) cells containing a stably integrated, doxycycline-inducible, eGFP-tagged N-terminal human Htt fragment with an expanded polyQ domain were used to analyse gene expression changes at different stages of mutant Htt aggregation. At earliest time points after doxycycline induction no detectable aggregates and few changes in gene expression were observed. Aggregates started to appear at intermediate time points. Aggregate formation and subsequent enlargement of aggregates coincided with a rapid increase in the number of differentially expressed (DE) genes. The increase in number of large aggregates coincided with a decrease in the number of smaller aggregates whereas the transcription profile reverted towards the profile observed before mutant Htt induction. Cluster-based analysis of the 2,176 differentially expressed genes revealed fourteen distinct clusters responding differently over time. Functional enrichment analysis of the two major gene clusters revealed that genes in the up-regulated cluster were mainly involved in metabolic (antioxidant activity and cellular ketone metabolic processes) and genes in the down-regulated cluster in developmental processes, respectively. Promoter-based analysis of the identified gene clusters resulted in identification of a transcription factor network of which several previously have been linked to HD. Conclusions: We demonstrate a time-resolved relationship between Htt aggregation and changes in the transcriptional profile. We identified two major gene clusters showing involvement of (i) mitochondrial dysfunction and (ii) developmental processes implying cellular homeostasis defects. We identified novel and known HD-linked transcription factors and show their interaction with known and predicted regulatory proteins. Our data provide a novel resource for hypothesis building on the role of transcriptional key regulators in early stages of HD and possibly other polyQ-dependent diseases.