Autism is a disorder of dispersed brain networks rather than a problem localized to an individual brain area. Human brain imaging studies provide evidence for abnormal long-range connectivity and a lack of coordinated activity between key nodes of dispersed brain networks. These findings lead to the hypothesis that autism spectrum disorders (ASDs) result from long range hypo-connectivity and local hyper-connectivity(Menon 2013). However, because of technical challenges in quantitatively applying classical anatomical methods to investigate long-range connectivity in multiple pathways, the extent to which synaptic connectivity in rodent ASD models is consistent with this hypothesis remains unclear.
High-throughput quantitative brain-wide analysis of structural changes in long-range connections has recently become feasible using an approach that goes with the acronym MAPSeq (Multiplex Analysis of Projections by Sequencing)(Kebschull et al. 2016). MAPSeq relies on tagging individual neurons with a unique molecular identifier, a barcode RNA, that is transported to the neuron’s axon terminals. Quantifying the levels of barcode RNA in areas of interest reveals the targets of the labelled neurons and the strength of projections. In one experiment, the individual projection profile of thousands of neurons can be investigated, making MAPSeq an unprecedented tool for high-throughput, high-resolution assessment of brain-wide connectivity.
We can envision a number of ways in which structural connectophies could manifest in ASD. For example, axons might be misrouted to abnormal targets. Alternatively, axonal branching en route to targets or at the target site might be disrupted. Distinguishing between these and other models would greatly help understand the mechanistic basis of ASDs. These problems are well suited to MAPseq approaches, but would be difficult and unfeasibly time consuming to address using current functional imaging or anatomical labeling techniques.
In this project we will apply MAPseq to investigate connectopathies in rodent models of ASD in a quantitative manner. Our goal is to identify communication pathways with altered structural connectivity from key nodes of memory, attention and social behaviour networks (Entorhinal cortex, Posterior parietal area PPA and amygdala AMY). We will focus on a well characterized mouse model of autism spectrum disorders associated with Fmr1 gene. Structural changes in afferent inputs to visual areas were reported in FMRP-/y mice suggesting a systemic connectivity problem, but the precise nature of these deficits is unclear and the issue has otherwise received very little attention.
Our study is novel in that not only it will establish long-range connectivity patterns of single cells originating from the selected areas but also the data obtained will directly test long range hypo-connectivity hypotheses and will reveal the nature of specific connectivity deficits involved.
Practical lab experience in the Surmeli Lab:
-Tissue preparation and imaging using confocal or light sheet microscopy for 2D and 3D imaging
-Rodent brain surgery
-Genetically modified viral intervention approaches.
-Light sheet microscopy, 3D imaging of axon tracts.
Analytical lab experience in the Surmeli and Hennig Labs:
-Analysis of axonal tracts in 3D using currently available computational tools available and in development for light sheet microscopy images.
-Implementation of statistical modelling tools for processing of deep sequencing data (MAPSeq)
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow. http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit: http://www.ed.ac.uk/usher/precision-medicine
1. Kebschull, Justus M., Pedro Garcia da Silva, Ashlan P. Reid, Ian D. Peikon, Dinu F. Albeanu, and Anthony M. Zador. 2016. “High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.” Neuron 91 (5): 975–87.
2. Menon, Vinod. 2013. “Developmental Pathways to Functional Brain Networks: Emerging Principles.” Trends in Cognitive Sciences 17 (12): 627–40.