Probes for INS

Neuropathic pain resulting from nerve injury can become persistent and difficult to treat but the molecular signaling responsible for its development remains poorly described. Here, we identify the neuronal stress sensor dual leucine zipper kinase (DLK; Map3k12) as a key molecule controlling the maladaptive pathways that lead to pain following injury. Genetic or pharmacological inhibition of DLK reduces mechanical hypersensitivity in a mouse model of neuropathic pain. Furthermore, DLK inhibition also prevents the spinal cord microgliosis that results from nerve injury and arises distant from the injury site. These striking phenotypes result from the control by DLK of a transcriptional program in somatosensory neurons regulating the expression of numerous genes implicated in pain pathogenesis, including the immune gene Csf1. Thus, activation of DLK is an early event, or even the master regulator, controlling a wide variety of pathways downstream of nerve injury that ultimately lead to chronic pain.

Striatal locally projecting neurons, or interneurons, act on nearby circuits and shape functional output to the rest of the basal ganglia. We performed single-cell RNA sequencing of striatal cells enriching for interneurons. We find seven discrete interneuron types, six of which are GABAergic. In addition to providing specific markers for the populations previously described, including those expressing Sst/Npy, Th, Npy without Sst, and Chat, we identify two small populations of cells expressing Cck with or without Vip. Surprisingly, the Pvalb-expressing cells do not constitute a discrete cluster but rather are part of a larger group of cells expressing Pthlh with a spatial gradient of Pvalb expression. Using PatchSeq, we show that Pthlh cells exhibit a continuum of electrophysiological properties correlated with expression of Pvalb. Furthermore, we find significant molecular differences that correlate with differences in electrophysiological properties between Pvalb-expressing cells of the striatum and those of the cortex.

To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease.