Unravelling cell type-specific responses to Parkinson's Disease at single cell resolution.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder. The pathological hallmark of PD is loss of dopaminergic neurons and the presence of aggregated α-synuclein, primarily in the substantia nigra pars compacta (SNpc) of the midbrain. However, the molecular mechanisms that underlie the pathology in different cell types is not currently understood. Here, we present a single nucleus transcriptome analysis of human post-mortem SNpc obtained from 15 sporadic Parkinson's Disease (PD) cases and 14 Controls. Our dataset comprises ∼84K nuclei, representing all major cell types of the brain, allowing us to obtain a transcriptome-level characterization of these cell types. Importantly, we identify multiple subpopulations for each cell type and describe specific gene sets that provide insights into the differing roles of these subpopulations. Our findings reveal a significant decrease in neuronal cells in PD samples, accompanied by an increase in glial cells and T cells. Subpopulation analyses demonstrate a significant depletion of tyrosine hydroxylase (TH) enriched astrocyte, microglia and oligodendrocyte populations in PD samples, as well as TH enriched neurons, which are also depleted. Moreover, marker gene analysis of the depleted subpopulations identified 28 overlapping genes, including those associated with dopamine metabolism (e.g., ALDH1A1, SLC6A3 & SLC18A2). Overall, our study provides a valuable resource for understanding the molecular mechanisms involved in dopaminergic neuron degeneration and glial responses in PD, highlighting the existence of novel subpopulations and cell type-specific gene sets.

Molecular and cognitive signatures of ageing partially restored through synthetic delivery of IL2 to the brain.

Cognitive decline is a common pathological outcome during aging, with an ill-defined molecular and cellular basis. In recent years, the concept of inflammaging, defined as a low-grade inflammation increasing with age, has emerged. Infiltrating T cells accumulate in the brain with age and may contribute to the amplification of inflammatory cascades and disruptions to the neurogenic niche observed with age. Recently, a small resident population of regulatory T cells has been identified in the brain, and the capacity of IL2-mediated expansion of this population to counter neuroinflammatory disease has been demonstrated. Here, we test a brain-specific IL2 delivery system for the prevention of neurological decline in aging mice. We identify the molecular hallmarks of aging in the brain glial compartments and identify partial restoration of this signature through IL2 treatment. At a behavioral level, brain IL2 delivery prevented the age-induced defect in spatial learning, without improving the general decline in motor skill or arousal. These results identify immune modulation as a potential path to preserving cognitive function for healthy aging.

Astrocyte layers in the mammalian cerebral cortex revealed by a single-cell in situ transcriptomic map.

Although the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells show distinct layering. In the present study, we developed a high-content pipeline, the large-area spatial transcriptomic (LaST) map, which can quantify single-cell gene expression in situ. Screening 46 candidate genes for astrocyte diversity across the mouse cortex, we identified superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from those of neurons. Astrocyte layer features, established in the early postnatal cortex, mostly persisted in adult mouse and human cortex. Single-cell RNA sequencing and spatial reconstruction analysis further confirmed the presence of astrocyte layers in the adult cortex. Satb2 and Reeler mutations that shifted neuronal post-mitotic development were sufficient to alter glial layering, indicating an instructive role for neuronal cues. Finally, astrocyte layer patterns diverged between mouse cortical regions. These findings indicate that excitatory neurons and astrocytes are organized into distinct lineage-associated laminae.

No Longer Underappreciated: The Emerging Concept of Astrocyte Heterogeneity in Neuroscience.

Astrocytes are ubiquitous in the central nervous system (CNS). These cells possess thousands of individual processes, which extend out into the neuropil, interacting with neurons, other glia and blood vessels. Paralleling the wide diversity of their interactions, astrocytes have been reported to play key roles in supporting CNS structure, metabolism, blood-brain-barrier formation and control of vascular blood flow, axon guidance, synapse formation and modulation of synaptic transmission. Traditionally, astrocytes have been studied as a homogenous group of cells. However, recent studies have uncovered a surprising degree of heterogeneity in their development and function, in both the healthy and diseased brain. A better understanding of astrocyte heterogeneity is urgently needed to understand normal brain function, as well as the role of astrocytes in response to injury and disease.

Identification of region-specific astrocyte subtypes at single cell resolution.

Astrocytes, a major cell type found throughout the central nervous system, have general roles in the modulation of synapse formation and synaptic transmission, blood-brain barrier formation, and regulation of blood flow, as well as metabolic support of other brain resident cells. Crucially, emerging evidence shows specific adaptations and astrocyte-encoded functions in regions, such as the spinal cord and cerebellum. To investigate the true extent of astrocyte molecular diversity across forebrain regions, we used single-cell RNA sequencing. Our analysis identifies five transcriptomically distinct astrocyte subtypes in adult mouse cortex and hippocampus. Validation of our data in situ reveals distinct spatial positioning of defined subtypes, reflecting the distribution of morphologically and physiologically distinct astrocyte populations. Our findings are evidence for specialized astrocyte subtypes between and within brain regions. The data are available through an online database (https://holt-sc.glialab.org/), providing a resource on which to base explorations of local astrocyte diversity and function in the brain.

Kinetic Modelling of Competition and Depletion of Shared miRNAs by Competing Endogenous RNAs.

Non-coding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting, e.g., the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.

Translating ceRNA Susceptibilities into Correlation Functions.

Competition to bind microRNAs induces an effective positive cross talk between their targets, which are therefore known as "competing endogenous RNAs" (ceRNAs). Although such an effect is known to play a significant role in specific situations, estimating its strength from data and experimentally in physiological conditions appears to be far from simple. Here, we show that the susceptibility of ceRNAs to different types of perturbations affecting their competitors (and hence their tendency to cross talk) can be encoded in quantities as intuitive and as simple to measure as correlation functions. This scenario is confirmed by extensive numerical simulations and validated by re-analyzing phosphatase and tensin homolog's cross-talk pattern from The Cancer Genome Atlas breast cancer database. These results clarify the links between different quantities used to estimate the intensity of ceRNA cross talk and provide, to our knowledge, new keys to analyze transcriptional data sets and effectively probe ceRNA networks in silico.

ceRNA crosstalk stabilizes protein expression and affects the correlation pattern of interacting proteins.

Gene expression is a noisy process and several mechanisms, both transcriptional and post-transcriptional, can stabilize protein levels in cells. Much work has focused on the role of miRNAs, showing in particular that miRNA-mediated regulation can buffer expression noise for lowly expressed genes. Here, using in silico simulations and mathematical modeling, we demonstrate that miRNAs can exert a much broader influence on protein levels by orchestrating competition-induced crosstalk between mRNAs. Most notably, we find that miRNA-mediated cross-talk (i) can stabilize protein levels across the full range of gene expression rates, and (ii) modifies the correlation pattern of co-regulated interacting proteins, changing the sign of correlations from negative to positive. The latter feature may constitute a potentially robust signature of the existence of RNA crosstalk induced by endogenous competition for miRNAs in standard cellular conditions.

Probing the Limits to MicroRNA-Mediated Control of Gene Expression.

According to the 'ceRNA hypothesis', microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying significant potential implications for a variety of biological processes. Here, inspired by recent work providing a quantitative description of small regulatory elements as information-conveying channels, we characterize the effectiveness of miRNA-mediated regulation in terms of the optimal information flow achievable between modulator (transcription factors) and target nodes (long RNAs). Our findings show that, while a sufficiently large degree of target derepression is needed to activate miRNA-mediated transmission, (a) in case of differential mechanisms of complex processing and/or transcriptional capabilities, regulation by a post-transcriptional miRNA-channel can outperform that achieved through direct transcriptional control; moreover, (b) in the presence of large populations of weakly interacting miRNA molecules the extra noise coming from titration disappears, allowing the miRNA-channel to process information as effectively as the direct channel. These observations establish the limits of miRNA-mediated post-transcriptional cross-talk and suggest that, besides providing a degree of noise buffering, this type of control may be effectively employed in cells both as a failsafe mechanism and as a preferential fine tuner of gene expression, pointing to the specific situations in which each of these functionalities is maximized.

Different fitnesses for in vivo and in vitro evolutions due to the finite generation-time effect.

We consider the finite generation-time effect in virus evolution models, introducing differential equations with delay. The suggested approach more adequately describes the evolution in case of growing populations than the popular models of population genetics, especially for the viruses with large number of offspring during one life cycle. Now the mean fitness, as a coefficient for exponential population growth, could not be defined via instant characteristics of the model. For the constant population size the finite generation-time does not affect mean fitness in the steady state. The growing virus population is characterized by different fitness than the population with a constant size.