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Subramaniam, S.

Publications and source records attributed to Subramaniam, S..

2 recordsLinked to original sources

Dedifferentiation orchestrated through remodeling of the chromatin landscape defines PSEN1 mutation-induced Alzheimer's Disease

Early-Onset Familial Alzheimers Disease (EOFAD) is a dominantly inherited neurodegenerative disorder elicited by mutations in the PSEN1, PSEN2, and APP genes1. Hallmark pathological changes and symptoms observed, namely the accumulation of misfolded Amyloid-{beta} (A{beta}) in plaques and Tau aggregates in neurofibrillary tangles associated with memory loss and cognitive decline, are understood to be temporally accelerated manifestations of the more common sporadic Late-Onset Alzheimers Disease. The complete penetrance of EOFAD-causing mutations has allowed for experimental models which have proven integral to the overall understanding of AD2. However, the failure of pathology-targeting therapeutic development suggests that the formation of plaques and tangles may be symptomatic and not describe the etiology of the disease3,4. Here, we use an integrative, multi-omics approach and systems-level analysis in hiPSC-derived neurons to generate a mechanistic disease model for EOFAD. Using patient-specific cells from donors harboring mutations in PSEN1 differentiated into neurons, we characterize the disease-related gene expression and chromatin accessibility changes by RNA- Seq, ATAC-Seq, and histone methylation ChIP-Seq. We show that the defining disease-causing mechanism of EOFAD is dedifferentiation, primarily through the REST-mediated repression of neuronal lineage specification gene programs and the activation of non-specific germ layer precursor gene programs concomitant with modifications in chromatin accessibility. These gene signature profiles and changes in chromatin topology illustrate that EOFAD neurons traverse the chromatin landscape from an ectodermal origin to a mixed germ lineage state. Further, a reanalysis of existing transcriptomic data from PSEN1 patient brain samples demonstrates that the mechanisms identified in our experimental system recapitulate EOFAD in the human brain. Our results comprise a disease model which describes the mechanisms culminating in dedifferentiation that precede amyloid and tau pathology formation and engender neurodegeneration.

neuroscience

Automated methods for 3D Segmentation of Focused Ion Beam-Scanning Electron Microscopic Images

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) is an imaging approach that enables analysis of the 3D architecture of cells and tissues at resolutions that are 1-2 orders of magnitude higher than that possible with light microscopy. The slow speeds of data collection and analysis are two critical problems that limit more extensive use of FIB-SEM technology. Here, we present a robust method that enables rapid, large-scale acquisition of data from tissue specimens, combined with an approach for automated data segmentation using machine learning, which dramatically increases the speed of image analysis. We demonstrate the feasibility of these methods through the 3D analysis of human muscle tissue by showing that our process results in an improvement in speed of up to three orders of magnitude as compared to manual approaches for data segmentation. All programs and scripts we use are open source and are immediately available for use by others.\n\nImpact StatementThe high-throughput, easy-to-use and versatile segmentation pipeline described in our manuscript will enable rapid, large-scale statistical analysis of sub-cellular structures in tissues.

cell biology