In Lewy body diseases-including Parkinson's disease, without or with dementia, dementia with Lewy bodies, and Alzheimer's disease with Lewy body co-pathology 1 -α-synuclein (α-Syn) aggregates in neurons as Lewy bodies and Lewy neurites 2 . By contrast, in multiple system atrophy α-Syn accumulates mainly in oligodendrocytes as glial cytoplasmic inclusions (GCIs) 3 . Here we report that pathological α-Syn in GCIs and Lewy bodies (GCI-α-Syn and LB-α-Syn, respectively) is conformationally and biologically distinct. GCI-α-Syn forms structures that are more compact and it is about 1,000-fold more potent than LB-α-Syn in seeding α-Syn aggregation, consistent with the highly aggressive nature of multiple system atrophy. GCI-α-Syn and LB-α-Syn show no cell-type preference in seeding α-Syn pathology, which raises the question of why they demonstrate different cell-type distributions in Lewy body disease versus multiple system atrophy. We found that oligodendrocytes but not neurons transform misfolded α-Syn into a GCI-like strain, highlighting the fact that distinct α-Syn strains are generated by different intracellular milieus. Moreover, GCI-α-Syn maintains its high seeding activity when propagated in neurons. Thus, α-Syn strains are determined by both misfolded seeds and intracellular environments.
Pubmed ID: 29743672 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Privately held company that develops and produces antibodies, ELISA kits, ChIP kits, proteomic kits, and other related reagents used to study cell signaling pathways that impact human health.
View all literature mentionsNEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
View all literature mentions