Nature neuroscience最新文献

Multiple sclerosis (MS) is an inflammatory disease of the central nervous system characterized by myelin loss and progressive neurodegeneration. To understand MS lesion initiation and progression, we generate spatial gene expression maps of white matter (WM) and grey matter (GM) MS lesions. In different MS lesion types, we detect domains characterized by a distinct gene signature, including an identifiable rim around active WM lesions. Expression changes in astrocyte-specific, oligodendrocyte-specific and microglia-specific gene sets characterize the active lesion rims. Furthermore, we identify three WM lesion progression trajectories, predicting how normal-appearing WM can develop into WM active or mixed active–inactive lesions. Our data shed light on the dynamic progression of MS lesions.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. Inflammation is gradually compartmentalized and restricted to specific tissue niches such as the lesion rim. However, the precise cell type composition of such niches, their interactions and changes between chronic active and inactive stages are incompletely understood. We used single-nucleus and spatial transcriptomics from subcortical MS and corresponding control tissues to map cell types and associated pathways to lesion and nonlesion areas. We identified niches such as perivascular spaces, the inflamed lesion rim or the lesion core that are associated with the glial scar and a cilia-forming astrocyte subtype. Focusing on the inflamed rim of chronic active lesions, we uncovered cell–cell communication events between myeloid, endothelial and glial cell types. Our results provide insight into the cellular composition, multicellular programs and intercellular communication in tissue niches along the conversion from a homeostatic to a dysfunctional state underlying lesion progression in MS.

The versatility of somatosensation arises from heterogeneous dorsal root ganglion (DRG) neurons. However, soma transcriptomes of individual human (h)DRG neurons—critical information to decipher their functions—are lacking due to technical difficulties. In this study, we isolated somata from individual hDRG neurons and conducted deep RNA sequencing (RNA-seq) to detect, on average, over 9,000 unique genes per neuron, and we identified 16 neuronal types. These results were corroborated and validated by spatial transcriptomics and RNAscope in situ hybridization. Cross-species analyses revealed divergence among potential pain-sensing neurons and the likely existence of human-specific neuronal types. Molecular-profile-informed microneurography recordings revealed temperature-sensing properties across human sensory afferent types. In summary, by employing single-soma deep RNA-seq and spatial transcriptomics, we generated an hDRG neuron atlas, which provides insights into human somatosensory physiology and serves as a foundation for translational work.

The role of the motor cortex in executing motor sequences is widely debated, with studies supporting disparate views. Here we probe the degree to which the motor cortex’s engagement depends on task demands, specifically whether its role differs for highly practiced, or ‘automatic’, sequences versus flexible sequences informed by external cues. To test this, we trained rats to generate three-element motor sequences either by overtraining them on a single sequence or by having them follow instructive visual cues. Lesioning motor cortex showed that it is necessary for flexible cue-driven motor sequences but dispensable for single automatic behaviors trained in isolation. However, when an automatic motor sequence was practiced alongside the flexible task, it became motor cortex dependent, suggesting that an automatic motor sequence fails to consolidate subcortically when the same sequence is produced also in a flexible context. A simple neural network model recapitulated these results and offered a circuit-level explanation. Our results critically delineate the role of the motor cortex in motor sequence execution, describing the conditions under which it is engaged and the functions it fulfills, thus reconciling seemingly conflicting views about motor cortex’s role in motor sequence generation.