Evolutionary Divergence of Phosphorylation to Regulate Interactive Protein Networks in Lower and Higher Species

LRRK2 kinase activity is necessary for development and regeneration in Nematostella vectensis

Background

The starlet sea anemone, Nematostella vectensis, is an emerging model organism with a high regenerative capacity, which was recently found to possess an orthologue to the human LRRK2 gene (nvLRRK2). The leucine rich repeat kinase 2 (LRRK2) gene, when mutated, is the most common cause of inherited Parkinson's Disease (PD). Its protein product (LRRK2) has implications in a variety of cellular processes, however, the full function of LRRK2 is not well established. Current research is focusing on understanding the function of LRRK2, including both its physiological role as well as its pathobiological underpinnings.

Methods

We used bioinformatics to determine the cross-species conservation of LRRK2, then applied drugs targeting the kinase activity of LRRK2 to examine its function in development, homeostasis and regeneration in Nematostella vectensis.

Results

An in-silico characterization and phylogenetic analysis of nvLRRK2 comparing it to human LRRK2 highlighted key conserved motifs and residues. In vivo analyses inhibiting the kinase function of this enzyme demonstrated a role of nvLRRK2 in development and regeneration of N. vectensis. These findings implicate a developmental role of LRRK2 in Nematostella, adding to the expanding knowledge of its physiological function.

Conclusions

Our work introduces a new model organism with which to study LRRK biology. We show a necessity for LRRK2 in development and regeneration. Given the short generation time, genetic trackability and in vivo imaging capabilities, this work introduces Nematostella vectensis as a new model in which to study genes linked to neurodegenerative diseases such as Parkinson's.

A network embedding approach to identify active modules in biological interaction networks

The identification of condition-specific gene sets from transcriptomic experiments is important to reveal regulatory and signaling mechanisms associated with a given cellular response. Statistical methods of differential expression analysis, designed to assess individual gene variations, have trouble highlighting modules of small varying genes whose interaction is essential to characterize phenotypic changes. To identify these highly informative gene modules, several methods have been proposed in recent years, but they have many limitations that make them of little use to biologists. Here, we propose an efficient method for identifying these active modules that operates on a data embedding combining gene expressions and interaction data. Applications carried out on real datasets show that our method can identify new groups of genes of high interest corresponding to functions not revealed by traditional approaches. Software is available at https://github.com/claudepasquier/amine.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.