Bioinformatic approaches to screening the molecular framework underlying local dendritic mRNA translation

Learning and memory systems within the brain are believed to be the result of molecular events that occur at the synapse. These molecular events control synaptic efficacy – the modulation of the underlying molecular architecture of the synapse to influence the strength or weakness of connections between pre- and postsynaptic neurons. Deficits in any of these molecular processes results in neuronal dysfunction. The Mammalian/Mechanistic Target of Rapamycin Complex (mTORC1) is a protein complex within the brain composed of the serine/threonine kinase mTOR and other interacting proteins. Dysregulation of mTOR disrupts the many processes under its control such as local dendritic translation at the synapse. Since mTOR is at the core of many important signaling pathways, aberrant mTOR activity results in neuronal disease. The network of interactions between these molecular components is vast, forming an interconnected system that is dynamic and directed. In order to better understand the mechanistic nature of these interactions, the application of high-throughput technologies must be employed. Here we utilize multiple bioinformatics approaches combined with high-throughput technologies to clarify the role of mTOR in local dendritic translation. Using mass spectrometry, we provide the first evidence that mTOR bidirectionally controls the expression of over 700 proteins in the cortex, many of which are known to be associated with diseases in which mTOR is overactive (Chapter 2). Our investigations reveal a novel role PARK7 in tuberous sclerosis complex. Furthermore, we use and develop multiple bioinformatics tools to further delineate the nature of the RNA-binding properties of PARK7 and alternative avenues for drug discovery (Chapter 3). Finally, we provide evidence that the Fragile-X Mental Retardation protein sequesters a population of mRNAs involved in trans-synaptic signaling that mTOR translates to remodel the synapse, providing a mechanistic basis for the action of rapidly-acting antidepressants (Chapter 4). Collectively, our work stresses the importance of applying high-throughput technologies to answer long-standing questions in the field of local dendritic translation. Our findings provide new avenues of investigation and research to better understand neuronal disease and synaptic plasticityNeuroscienc

A computational model of behavioral adaptation to solve the credit assignment problem

The adaptive fitness of an organism in its ecological niche is highly reliant upon its ability to associate an environmental or internal stimulus with a behavior response through reinforcement. This simple but powerful observation has been successfully applied in a number of contexts within computational neuroscience and reinforcement learning to model both human and animal behaviors. However, a critical challenge faced by these models is the credit assignment problem which asks how past behavior comes to be associated with a delayed reinforcement signal. In this paper we reformulate the credit assignment problem to ask how past stimuli come to be linked to adaptive behavioral responses in the context of a simple neuronal circuit. We propose a biologically plausible variant of a spiking neural network which can model a wide variety of behavioral, learning, and evolutionary phenomena. Our model suggests one fundamental mechanism, potentially in use in the brains of both simple and complex organisms, that would allow it to associate a behavior with an adaptive response. We present results that showcase the model's versatility and biological plausibility in a number of tasks related to classical and operant conditioning including behavioral chaining. We then provide further simulations to demonstrate how adaptive behaviors such as reflexes and simple category detection may have evolved using our model. Our results indicate the potential for further modifications and extensions of our model to replicate more sophisticated and biologically plausible behavioral, learning, and intelligence phenomena found throughout the animal kingdom.Comment: 18 pages, 9 figure

Serverless Federated Learning with flwr-serverless

Federated learning is becoming increasingly relevant and popular as we witness a surge in data collection and storage of personally identifiable information. Alongside these developments there have been many proposals from governments around the world to provide more protections for individuals' data and a heightened interest in data privacy measures. As deep learning continues to become more relevant in new and existing domains, it is vital to develop strategies like federated learning that can effectively train data from different sources, such as edge devices, without compromising security and privacy. Recently, the Flower (\texttt{Flwr}) Python package was introduced to provide a scalable, flexible, and easy-to-use framework for implementing federated learning. However, to date, Flower is only able to run synchronous federated learning which can be costly and time-consuming to run because the process is bottlenecked by client-side training jobs that are slow or fragile. Here, we introduce \texttt{flwr-serverless}, a wrapper around the Flower package that extends its functionality to allow for both synchronous and asynchronous federated learning with minimal modification to Flower's design paradigm. Furthermore, our approach to federated learning allows the process to run without a central server, which increases the domains of application and accessibility of its use. This paper presents the design details and usage of this approach through a series of experiments that were conducted using public datasets. Overall, we believe that our approach decreases the time and cost to run federated training and provides an easier way to implement and experiment with federated learning systems.Comment: Technical report for an open source machine learning python packag

HSP90-CDC37 Functions as a Chaperone for the Oncogenic FGFR3-TACC3 Fusion

The FGFR3-TACC3 (F3-T3) fusion gene was discovered as an oncogenic molecule in glioblastoma and bladder cancers, and has subsequently been found in many cancer types. Notably, F3-T3 was found to be highly expressed in both untreated and matched recurrence glioblastoma under the concurrent radiotherapy and temozolomide (TMZ) treatment, suggesting that targeting F3-T3 is a valid strategy for treatment. Here, we show that the F3-T3 protein is a client of heat shock protein 90 (HSP90), forming a ternary complex with the cell division cycle 37 (CDC37). Deprivation of HSP90 or CDC37 disrupts the formation of the ternary complex, which destabilizes glycosylated F3-T3, and thereby suppresses F3-T3 oncogenic activity. Gliomas harboring F3-T3 are resistant to TMZ chemotherapy. HSP90 inhibitors sensitized F3-T3 glioma cells to TMZ via the inhibition of F3-T3 activation and potentiated TMZ-induced DNA damage. These results demonstrate that F3-T3 oncogenic function is dependent on the HSP90 chaperone system and suggests a new clinical option for targeting this genetic aberration in cancer

Role of FMRP in rapid antidepressant effects and synapse regulation

AbstractRapid antidepressants are novel treatments for major depressive disorder (MDD) and work by blocking N-methyl-aspartate receptors (NMDAR), which, in turn, activate the protein synthesis pathway regulated by mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Our recent work demonstrates that the RNA-binding protein Fragile X Mental Retardation Protein (FMRP) is downregulated in dendrites upon treatment with a rapid antidepressant. Here, we show that the behavioral effects of the rapid antidepressant Ro-25-6981 require FMRP expression, and treatment promotes differential mRNA binding to FMRP in an mTORC1-dependent manner. Further, these mRNAs are identified to regulate transsynaptic signaling. Using a novel technique, we show that synapse formation underlying the behavioral effects of Ro-25-6981 requires GABABR-mediated mTORC1 activity in WT animals. Finally, we demonstrate that in an animal model that lacks FMRP expression and has clinical relevance for Fragile X Syndrome (FXS), GABABR activity is detrimental to the effects of Ro-25-6981. These effects are rescued with the combined therapy of blocking GABABRs and NMDARs, indicating that rapid antidepressants alone may not be an effective treatment for people with comorbid FXS and MDD.</jats:p

Role of FMRP in rapid antidepressant effects and synapse regulation

AbstractRapid antidepressants are novel treatments for major depressive disorder (MDD) and work by blocking N-methyl-D-aspartate receptors (NMDARs), which, in turn, activate the protein synthesis pathway regulated by mechanistic/mammalian target of rapamycin complex 1 (mTORC1). Our recent work demonstrates that the RNA-binding protein Fragile X Mental Retardation Protein (FMRP) is downregulated in dendrites upon treatment with a rapid antidepressant. Here, we show that the behavioral effects of the rapid antidepressant Ro-25-6981 require FMRP expression, and treatment promotes differential mRNA binding to FMRP in an mTORC1-dependent manner. Further, these mRNAs are identified to regulate transsynaptic signaling. Using a novel technique, we show that synapse formation underlying the behavioral effects of Ro-25-6981 requires GABABR-mediated mTORC1 activity in WT animals. Finally, we demonstrate that in an animal model that lacks FMRP expression and has clinical relevance for Fragile X Syndrome (FXS), GABABR activity is detrimental to the effects of Ro-25-6981. These effects are rescued with the combined therapy of blocking GABABRs and NMDARs, indicating that rapid antidepressants alone may not be an effective treatment for people with comorbid FXS and MDD.</jats:p

Aberrant DJ-1 expression underlies L-type calcium channel hypoactivity in tuberous sclerosis complex and Alzheimer’s disease

AbstractL-type voltage-dependent Ca2+ channels (L-VDCC) integrate synaptic signals to facilitate a plethora of cellular mechanisms. L-VDCC dysfunction is implicated in several neurological and psychiatric diseases. Despite their importance, signals upstream of L-VDCC activity that regulate their channel density, however, are poorly defined. In disease models with overactive mammalian target of rapamycin complex 1 (mTORC1) signaling (or mTORopathies), including tuberous sclerosis (TS) and Alzheimer’s disease (AD), we report a novel mechanism downstream of mTORC1 signaling that results in a deficit in dendritic L-VDCC activity. Deficits in L-VDCC activity are associated with increased expression of the mTORC1-regulated RNA-binding protein DJ-1. DJ-1 binds the mRNA coding the auxiliary Ca2+ channel subunit α2δ2 responsible for shuttling L-VDCC to the membrane and represses its expression. Moreover, this novel DJ-1/α2δ2/L-VDCC pathway is disrupted in human AD and preclinical models of AD and TS. Our discovery that DJ-1 directs L-VDCC activity and L-VDCC-associated protein α2δ2 at the synapse suggests that DJ-1/α2δ2/L-VDCC is a common, fundamental pathway disrupted in TS and AD that can be targeted in clinical mTORopathies.Significance StatementMany neurological disorders share symptoms, despite disparity among diseases. Treatments are prescribed based on diagnosis rather than individual symptoms. While only treating symptoms may obscure the disease, mechanism-based drug development allows the two approaches to converge. Hub proteins, those that coordinate the expression of proteins that mediate specific cellular functions, may be dysregulated across a broad range of disorders. Herein, we show that the RNA-binding protein DJ-1 controls the activity of L-type voltage-dependent calcium channels (L-VDCC), via the expression of its auxiliary subunit alpha2delta2 (α2δ2). Importantly, we demonstrate that this novel DJ-1/α2δ2/L-VDCC pathway is commonly disrupted among neurological disorders, namely Alzheimer’s disease (AD) and Tuberous Sclerosis (TS). Collectively, these data rationalize mechanism-based drug therapy to treat disease.</jats:sec