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BackgroundDue to advances in next generation sequencing technologies and corresponding reductions in cost, it is now attainable to investigate genome-wide gene expression and variants at a patient-level, so as to better understand and anticipate heterogeneous responses to therapy. Consequently, it is feasible to inform personalized drug treatment decisions using personal genomics data. However, these efforts are limited due to a lack of reliable computational approaches for predicting effective drugs for individual patients. The reverse gene set enrichment analysis (i.e., connectivity mapping) approach and its variants have been widely and successfully used for drug prediction. However, the performance of these methods is limited by undefined mechanism of action (MoA) of drugs and reliance on cohorts of patients rather than personalized predictions for individual patients.ResultsIn this study, we have developed and evaluated a computational approach, known as Mechanism and Drug Miner (MD-Miner), using a network-based computational approach to predict effective drugs and reveal potential drug mechanisms of action at the level of signaling pathways. Specifically, the patient-specific signaling network is constructed by integrating known disease associated genes with patient-derived gene expression profiles. In parallel, a drug mechanism of action network is constructed by integrating drug targets and z-score profiles of drug-induced gene expression (pre vs. post-drug treatment). Potentially effective candidate drugs are prioritized according to the number of common genes between the patient-specific dysfunctional signaling network and drug MoA network. We evaluated the MD-Miner method on the PC-3 prostate cancer cell line, and showed that it significantly improved the success rate of discovering effective drugs compared with the random selection, and could provide insight into potential mechanisms of action.ConclusionsThis work provides a signaling network-based drug repositioning approach. Compared with the reverse gene signature based drug repositioning approaches, the proposed method can provide clues of mechanism of action in terms of signaling transduction networks.

Mutations in TDP-43, a RNA-binding protein with multiple functions in RNA metabolism, cause amyotrophic lateral sclerosis (ALS), but it is uncertain how defects in RNA biology trigger motor neuron degeneration. TDP-43 is a major constituent of ribonucleoprotein (RNP) granules, phase separated biomolecular condensates that regulate RNA splicing, mRNA transport, and translation. ALS-associated TDP-43 mutations, most of which are found in the low complexity domain, promote aberrant liquid to solid phase transitions and impair the dynamic liquid-like properties and motility of RNP transport granules in neurons. Here, we perform a comparative analysis of ALS-linked mutations and TDP-43 variants in order to identify critical structural elements, aromatic and charged residues that are key determinants of TDP-43 RNP transport and condensate formation in neurons. We find that A315T and Q343R disease-linked mutations and substitutions of aromatic residues within the α-helical domain and LARKS, show the most severe defects in TDP-43 RNP granule transport and impair both anterograde and retrograde motility. F313L and F313-6L/Y substitutions of one or both phenylalanine residues in LARKS suggest the aromatic rings are important for TDP-43 RNP transport. Similarly, W334F/L substitutions of the tryptophan residue in the α-helical domain, impair TDP-43 RNP motility (W334L) or anterograde transport (W334F). We also show that R293A and R293K mutations, which disrupt the only RGG in the LCD, profoundly reduce long-range, directed transport and net velocity of TDP-43 RNP granules. In the disordered regions flanking the α-helical domain, we find that F283Y, F397Y or Y374F substitutions of conserved GF/G and SYS motifs, also impair anterograde and/or retrograde motility, possibly by altering hydrophobicity. Similarly, ALS-linked mutations in disordered regions distant from the α-helical domain also show anterograde transport deficits, consistent with previous findings, but these mutations are less severe than A315T and Q343R. Overall our findings demonstrate that the conserved α-helical domain, phenylalanine residues within LARKS and RGG motif are key determinants of TDP-43 RNP transport, suggesting they may mediate efficient recruitment of motors and adaptor proteins. These results offer a possible mechanism underlying ALS-linked TDP-43 defects in axonal transport and homeostasis.

Altered RNA metabolism is a common pathogenic mechanism linked to familial and sporadic Amyotrophic lateral sclerosis (ALS). ALS is characterized by mislocalization and aggregation of TDP-43, an RNA-binding protein (RBP) with multiple roles in post-transcriptional RNA processing. Recent studies have identified genetic interactions between TDP-43 and Ataxin-2, a polyglutamine (polyQ) RBP in which intermediate length polyQ expansions confer increased ALS risk. Here, we used live-cell confocal imaging, photobleaching and translation reporter assays to study the localization, transport dynamics and mRNA regulatory functions of TDP-43/Ataxin-2 in rodent primary cortical neurons. We show that Ataxin-2 polyQ expansions aberrantly sequester TDP-43 within ribonucleoprotein (RNP) condensates, and disrupt both its motility along the axon and liquid-like properties. Our data suggest that Ataxin-2 governs motility and translation of neuronal RNP condensates and that Ataxin-2 polyQ expansions fundamentally perturb spatial localization of mRNA and suppress local translation. Overall, these results indicate Ataxin-2 polyQ expansions have detrimental effects on stability, localization, and translation of transcripts critical for axonal and cytoskeletal integrity, particularly important for motor neurons.

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