This work strongly supports the hypothesis that the kinase activity is the primary enzymatic output of LRRK2 and reveals a novel mode of action for RGS proteins independently of their established GAP domain function
Posted On April 24, 2022
This work strongly supports the hypothesis that the kinase activity is the primary enzymatic output of LRRK2 and reveals a novel mode of action for RGS proteins independently of their established GAP domain function. against neuronal toxicity of the most prevalent mutation in mutations in PD patients. INTRODUCTION Mutations in the gene have emerged as the most common genetic determinant of Parkinson’s disease (PD), causing late-onset, familial autosomal dominant PD and accounting for up to 40% of PD cases in certain ethnic populations (1,2). LRRK2-associated PD is clinically and neurochemically indistinguishable from sporadic PD. The most prevalent mutation in LRRK2, G2019S, has also been found in 1C2% of sporadic PD cases (2,3). Animal models demonstrate that the G2019S mutation in LRRK2 can induce degeneration of dopaminergic (DA) neurons, which are the primary target of neurodegeneration in PD (4,5). These findings suggest that LRRK2 plays a pivotal role in the pathogenesis of human PD. LRRK2 is a large, multi-domain protein of 2527 amino acids. It contains two catalytic domains, a kinase domain with highest sequence homology to mitogen-activated protein kinase kinase kinase (MKKK) and receptor-interacting protein (RIP) kinase families and a Ras-of-complex proteins (ROC) GTPase domain, flanked by a C-terminal of ROC (COR) domain (6). LRRK2 can autophosphorylate and phosphorylate generic substrates (e.g. myelin basic protein or LRRKtide) as well as a range of putative substrates such as ArfGAP1, 4E-BP, moesin and -tubulin (7C11). However few, if any, of these putative substrates have been broadly verified by multiple independent groups and validated as authentic physiological substrates of LRRK2 kinase activity (12,13). All six mutations that clearly segregate AX20017 with disease occur in the kinase domain (G2019S and I2020T), Roc GTPase domain (R1441C/G/H) or COR domain (Y1699C) (6). These pathogenic mutations have been shown to affect kinase and GTPase activities to varying degrees: the R1441C/G/H and Y1699C variants impair GTP AX20017 hydrolysis without consistent effects on kinase activity, while the predominant G2019S mutation enhances kinase activity with no effect on GTPase activity (6,14C18). Although the mechanisms remain unclear, these findings suggest that both activities may play a role in mediating neurodegeneration. Indeed, kinase activity is required for the pathogenic effects of the G2019S mutation in primary neurons and in rodents (5,6,17,19). A number of studies have implicated LRRK2 in the regulation of a wide variety of biological processes such as protein translation (20), cytoskeletal processes (9,21), vesicular dynamics (22), response to mitochondrial damage (23) and autophagy (24,25). This complexity of LRRK2 biology has made it extremely difficult to understand the contributions of the kinase and GTPase domains to the function of LRRK2 (26). In particular, the upstream signaling mechanisms that control LRRK2 GTPase and kinase activities and the pathogenic effects of familial mutations remain unknown (26,27). Identifying the signaling proteins that regulate LRRK2 function and toxicity remains a critical outstanding goal for the development of effective therapeutic strategies. In the present study, we used an approach to elucidate the gene regulatory network linked to network based on human PD blood and brain transcriptomes. This work highlights in particular the role of the signaling GTPase-activating protein (GAP) RGS2 as a key regulator of LRRK2 activity, function and neuronal toxicity. RESULTS Elucidation of the regulatory network AX20017 The context AX20017 likelihood of relatedness (CLR) algorithm is designed to analyze state-dependent genome-wide expression data based on the degree of synchrony of transcript levels, using mutual information as a metric for scoring the similarity between expression levels of two transcripts (28). CLR IRF7 identifies the component gene regulatory networks among large numbers of subjects. We employed the CLR algorithm to analyze, in an unbiased manner, a set of 119 publicly available array data sets from the Substantia Nigra pars compacta (SNpc), frontal cortex and whole blood of human PD patients AX20017 and control cases (29,30). Whole blood was included to enhance the input of data from tissues that were not in terminal stages of degeneration. Recent studies support the utility of leukocytes for study of PD by identifying putative PD biomarkers using blood.