Steven Finkbeiner - US grants

DESCRIPTION (provided by applicant): This consortium aims to capitalize on an unprecedented "grand" opportunity to develop a novel and powerful model of Huntington's disease (HD), a fatal neurodegenerative condition with no current treatment. Skin cells from patients with HD can be reprogrammed to pluripotency and then differentiated into specific neuronal and glial cell types, permitting investigation of the effects of the genetic lesion in the susceptible human cell types. We hypothesize that the genetic changes that cause HD lead to specific alterations in neuronal function- perhaps even survival-that will give important clues as to the mechanism and progression of disease. Altered cellular phenotypes will also serve as the foundation for translational research and drug development. Stimulus funding will bring together a highly focused group that (i) has a strong track record of innovative HD research and of working together, (ii) is poised to engage in cutting-edge research with recently generated induced pluripotent stem (iPS) cells derived from HD patients and is committed to broad distribution of findings, protocols and iPS lines, (iii) can capitalize on this stimulus funding through further grant applications and collaborative studies, and (iv) is partnered with CHDI, an HD foundation with dedicated HD stem cell and translational/drug discovery programs. This infusion of funds will accelerate the coordinated analysis of iPS lines and leverage the complementary, synergistic skill sets that will move the field forward more rapidly than would be possible by any group alone. The proposed studies will provide an entirely novel genetically accurate model to test new drugs in the fight against this disease, a unique resource that will benefit the entire HD community. PUBLIC HEALTH RELEVANCE: We hypothesize that the genetic changes that cause Huntington's disease lead to specific alterations in neuronal function-perhaps even survival-that, in turn, give important clues as to the mechanism of disease and its progression and offer a potential basis for small molecule screening assays. Our studies will provide a more authentic way to study the consequences of the HD mutation in human target cells. They represent a unique and timely opportunity to enhance the investigation of disease mechanisms and will generate a validated resource freely available to the HD community to further accelerate HD research toward a successful treatment.

Administration Component The Administrative Core is responsible for setting the overall direction of the NeuroLINCS center and for ensuring that the resources and components of the Center are optimally utilized. The successful development and evolution of the NeuroLINCS center requires strong interactions between the leaders and co-leaders of each Component and of the center as a whole. Hence, the NeuroLINCS Administrative Component plays a vital role in facilitating these interactions. Moreover, the Administrative Component and its personnel provide the necessary administrative and fiscal oversight to ensure that the NeuroLINCS center is run efficiently. The NeuroLINCS center involves 5 principal sites with defined responsibilities of growing, differentiating and generating new induced pluripotent stem cell lines (iPSCs), performing data generation assays on human brain cells made from iPSCs in response to perturbagens, performing basic analyses and developing cell signatures through integrated data analysis .methods, and establish community interactions. An integrated and highly collaborative group of investigators with expertise in stem cell biology, IPS cells, quantitative molecular phenotyping (omics and single cell imaging) and bioinformatics will work closely together to generate significant and highly predictive cell signatures. The PIs of the NeuroLINCS center are Steven Finkbeiner (Gladstone), Ernest Frankel (MIT), Jeffrey Rothstein (JHU), Clive Svendsen (Cedars) and Leslie Thompson (UCI), who will serve as leaders and co-leaders of components. Each Component has identified co-investigators/collaborators/consultants appropriate for the planned scientific investigations. Component leaders and co-leaders will also be active participants in NeuroLINCS consortium working groups as they are developed to address specific issues. Results of the genetic, proteomic and other characterization conducted by consortium labs will provide important feedback for further enhancement of induction and differentiation protocols and related methodologies and it is anticipated that this collaborative and iterative approach will lead to the broadest success for the study. An Evaluation Program within the NeuroLINCS is in place to determine if the programs supported are meeting the needs of the research community, are efficiently managed, and demonstrably effective and annual objectives and milestones.

This project is directed at developing a novel technology, robotic microscopy (RM), to "bridge multiple spatial, temporal, and organizational scales to provide fundamental insights into the emergent properties of neural circuitry that ultimately lead to behavior and cognition." There are two primary benefits of the proposed studies. First, the experiments will result in the development of an RM instrument that can monitor the molecular dynamics of individual neurons in slices of living brain tissue over weeks at a time. Second, the experiments will use RM to study for the first time how learning and memory change the fundamental properties of specific neurons in situ to enhance synaptic plasticity, providing new insights into the mechanisms involved in learning and memory. In the past, RM was used to study neurons in culture. The primary activity in the proposed studies will be to validate the utility of RM to monitor neuronal dynamics in brain slices that maintain their natural physiological connectivity and architecture. Other benefits will be access of the scientific community to a technology that can examine the biochemistry of neurons and other cell types longitudinally and the development of new instrumentation that can be used in academic courses that teach students, postdoctoral fellows and research scientists novel imaging approaches to study brain circuits.

The problem to be addressed is whether RM can be used to study neurons expressing the Arc gene in situ in hippocampal brain slices. Arc is important for long-term memory consolidation and synaptic plasticity, and its activity is greatly enhanced in specific neuron populations by stimuli that affect learning. The methods to be employed will involve the use of novel Arc genetic probes and transgenic mice to determine if RM can identify selective Arc-expressing neurons activated in brain slices by long-term potentiation (LTP) and long-term depression (LTD) or in brain in vivo during learning and memory consolidation. The goals of the studies will be to determine if different Arc neuronal circuits mediate LTP and LTD, and if the same Arc expressing neurons activated in vivo in the brain during learning can be monitored by RM in situ in brain slices. The scope of the studies will determine if RM can identify and study different Arc neuronal circuits activated in vitro and in vivo by different forms of learning and memory consolidation.

Community Interactions & Outreach Component The NeuroLINCS Community project will plan to provide resources and tools for a broad user base of basic and clinical scientists. It has a structure to facilitate access to the various genetic and proteomic data sets, the signatures created, and the analysis tools. It is designed to be directed to researchers at the bench, clinicians developing biological disease readouts and those in computational roles. It will incorporate an assessment to demonstrate the utility of the generated resources, methodologies, and analytical tools to LINCS and non-LINCS scientific community. Importantly, it will develop and implement a plan to bring in external collaborators who may have data sets that bear on the development of cell signatures. There is an extensive plan to develop workshops, tutorials, and symposia in conjunction with the use of innovative online technologies for disseminating information to target the major LINCS goals. Finally it will develop bidirectional links with the neuroscience clinical and basic community through a series of collaborations with large National clinical data and tissue-based networks.

Data Analysis & Signature Generation Component Our goal is to generate cellular signatures of human neurons in response to perturbagens. Our studies will focus on human neurons, generated from induced pluripotent stem cells (iPSCs) (i-neurons) obtained from both healthy people and patients with neurodegenerative diseases. The cellular signature will be a composite picture of the molecular properties of a neuron that distinguish the state and determine the behavior of the cell. We will generate three classes of cellular signatures. The first will be static signatures based on quantitative molecular phenotyping involving OMIC analysis of the i-neurons. Analysis of the static signatures will highlight critical signaling pathways that distinguish a cellular response to a perturbagen. The second type of signature will be dynamic signatures generated with a novel high throughput, single cell longitudinal analysis system. Robotic Microscopy (RM). RM will be able to pinpoint critical times in the life of i-neurons as their physiology change in response to perturbagens. Analysis of dynamic signatures will guide selection of time points that will be investigated more in depth with methods that generate static signatures. In turn, elements of these static signatures will be perturbed genetically and analyzed by RM to elucidate the epistatic relationship of the components of a signature and to develop explicit multivariate predictive descriptions of cellular responses to perturbations. The third type of signature will emerge from an integration of the individual signatures using clustering methods and machine learning algorithms. The technology to analyze the data of the cellular signatures will be compatible with those produced at other sites in the LINCS network. A major innovation of our program is the implementation of novel data analysis platforms that will produce signatures that will have greater predictive value of a cell's biology than standard technologies. We will integrate Data Analysis and Data Generation, creating feedback loops to allow the cellular signatures that we generate to influence subsequent data generation. In turn, the use of machine learning algorithms in collaboration with Google will allow us to iteratively refine our signatures to make them more predictive in identifying cause and effect relationships from the cellular signatures.

Data Generation Component We propose three broad experimental aims based around the type of assay, perturbagens and technologies being applied that will overlap across the years. The first will use iPSCs from three disease states (non affected, SMA and ALS) in which we have shown specific phenotypes. We will use an iterative approach by first screening for a number of perturbagens of interest to the broad neuroscience community using cost effective assays including simple cell death models and a highly novel imaging analysis system. The second parallel effort will be to use the same iPSC lines but in this case test a set of known cell modifiers (Glutamate, ER stressor and SOD1 ASO) as perturbagens and perform massive parallel quantitative molecular phenotyping (QMP) to generate robust signatures and to define the responses of motor neuron cultures to these perturbagens. We will then perform QMP on neurons, astrocytes and oligodendrocytes from disease and control cells and in response to the same perturbations as above to elucidate signatures across broadly relevant neural cell types. This data will be compared to motor neuron cultures (where expected disease signature will be) with non motor neuron cultures (where no or a more restricted disease signature is expected) to resolve the question of cell type specificity. We will also generate new iPS lines from post mortem human patient tissues to allow clinical pathological signatures to be incorporated into the LINCS data, providing a unique resource to both the SMA and ALS scientific community and to researchers interested in larger questions relating to the CNS. The third is to bring in disease iPS lines from Huntington's and Parkinson's subjects (from the respective NIH consortia and in coordination with various foundations - see letters of support. Overall) and test the specificity of signatures seen in the motor neuron diseases with other neurodegenerative conditions (both disease and response to perturbagens). All of these studies will be done in close association with the data analysis component community section (being responsive to the needs of the community). Given the speed of discovery in iPSC and new molecule generation, we also aim to be flexible in our design to allow incorporation of breakthrough technologies or drugs should they arise.

DESCRIPTION (provided by applicant): There is a critical need to define the state and predict the behavior of human brain cells in health and disease. The number of different cell types in the CNS remains undefined, and despite a demographically ordained wave of neurodegenerative diseases, not a single disease-modifying therapy exists. Our knowledge of the CNS and the foundation for intervening rationally in disease would be dramatically advanced by generating quantitative molecular phenotypes essentially cell signatures of human neurons, astrocytes and oligodendrocytes from healthy people and from patients with motor neuron disease, Huntington's disease, and Parkinson's disease. The CNS is so unique that studying non-neuronal cells does not provide much assistance. Despite this desperate need, the inaccessibility of human brain cells meant studying them would have been impossible until the recent discovery of cellular reprogramming and induced pluripotent stem cell technology. Here we propose to form the NeuroLINCS consortium to accomplish these goals. We have handpicked the team to bring in critical expertise in iPSC technology, disease modeling, transcriptomics, epigenomics, metabolomics, whole genome sequencing, proteomics, high content, high throughput longitudinal single cell analysis, other cell-based assays, bioinformatics, statistics and computational biology. In addition, we are collaborating with Google to bring in special expertise in machine learning and the integration of signatures across platforms into highly predictive models of responses to perturbagens. Together, we expect to develop cell signatures of an array of human brain cell types under different conditions that should be broadly applicable to the LINCs community. We also anticipate generating innovative software tools and approaches that will make the signature generating process cheaper, faster, and more reliable. Besides the unique combination of expertise represented within NeuroLINCS, another distinguishing feature is the long track record that its members have of collaborating with each other. That collaborative spirit will be expressed in NeuroLINCS through its significant and multifaceted community outreach programs. These will involve specific and detailed plans to make the data and tools that NeuroLINCS generates available to the community, to interact with other LINCS sites, and to prepare for DCIC and the prospect of disseminating knowledge and resources at scale.