Single-cell RNA sequencing for traumatic spinal cord injury

Mutual regulation of microglia and astrocytes after Gas6 inhibits spinal cord injury

JOURNAL/nrgr/04.03/01300535-202502000-00032/figure1/v/2024-05-28T214302Z/r/image-tiff Invasive inflammation and excessive scar formation are the main reasons for the difficulty in repairing nervous tissue after spinal cord injury. Microglia and astrocytes play key roles in the spinal cord injury micro-environment and share a close interaction. However, the mechanisms involved remain unclear. In this study, we found that after spinal cord injury, resting microglia (M0) were polarized into pro-inflammatory phenotypes (MG1 and MG3), while resting astrocytes were polarized into reactive and scar-forming phenotypes. The expression of growth arrest-specific 6 (Gas6) and its receptor Axl were significantly down-regulated in microglia and astrocytes after spinal cord injury. In vitro experiments showed that Gas6 had negative effects on the polarization of reactive astrocytes and pro-inflammatory microglia, and even inhibited the cross-regulation between them. We further demonstrated that Gas6 can inhibit the polarization of reactive astrocytes by suppressing the activation of the Yes-associated protein signaling pathway. This, in turn, inhibited the polarization of pro-inflammatory microglia by suppressing the activation of the nuclear factor-κB/p65 and Janus kinase/signal transducer and activator of transcription signaling pathways. In vivo experiments showed that Gas6 inhibited the polarization of pro-inflammatory microglia and reactive astrocytes in the injured spinal cord, thereby promoting tissue repair and motor function recovery. Overall, Gas6 may play a role in the treatment of spinal cord injury. It can inhibit the inflammatory pathway of microglia and polarization of astrocytes, attenuate the interaction between microglia and astrocytes in the inflammatory microenvironment, and thereby alleviate local inflammation and reduce scar formation in the spinal cord.

ScnML models single-cell transcriptome to predict spinal cord neuronal cell status

Injuries to the spinal cord nervous system often result in permanent loss of sensory, motor, and autonomic functions. Accurately identifying the cellular state of spinal cord nerves is extremely important and could facilitate the development of new therapeutic and rehabilitative strategies. Existing experimental techniques for identifying the development of spinal cord nerves are both labor-intensive and costly. In this study, we developed a machine learning predictor, ScnML, for predicting subpopulations of spinal cord nerve cells as well as identifying marker genes. The prediction performance of ScnML was evaluated on the training dataset with an accuracy of 94.33%. Based on XGBoost, ScnML on the test dataset achieved 94.08% 94.24%, 94.26%, and 94.24% accuracies with precision, recall, and F1-measure scores, respectively. Importantly, ScnML identified new significant genes through model interpretation and biological landscape analysis. ScnML can be a powerful tool for predicting the status of spinal cord neuronal cells, revealing potential specific biomarkers quickly and efficiently, and providing crucial insights for precision medicine and rehabilitation recovery.

Traumatic Human Spinal Cord Injury: Are Single Treatments Enough to Solve the Problem?

Traumatic spinal cord injury (SCI) results in partial or complete motor deficits, such as paraplegia, tetraplegia, and sphincter control, as well as sensory disturbances and autonomic dysregulation such as arterial hypotension, lack of sweating, and alterations in skin lability. All this has a strong psychological impact on the affected person and his/her family, as well as costs to healthcare institutions with an economic burden in the short, medium, and long terms. Despite at least forty years of experimental animal studies and several clinical trials with different therapeutic strategies, effective therapy is not universally accepted. Most of the published works on acute and chronic injury use a single treatment, such as medication, trophic factor, transplant of a cell type, and so on, to block some secondary injury mechanisms or promote some mechanisms of structural/functional restoration. However, despite significant results in experimental models, the outcome is a moderate improvement in muscle strength, sensation, or eventually in sphincter control, which has been considered non-significant in human clinical trials. Here we present a brief compilation of successful individual treatments that have been applied to secondary mechanisms of action. These studies show limited neuroprotective or neurorestorative approaches in animal models and clinical trials. Thus, the few benefits achieved so far represent a rationale to further explore other strategies that seek better structural and functional restoration of the injured spinal cord.

Advance and Application of Single-cell Transcriptomics in Auditory Research

Hearing loss and deafness, as a worldwide disability disease, have been troubling human beings. However, the auditory organ of the inner ear is highly heterogeneous and has a very limited number of cells, which are largely uncharacterized in depth. Recently, with the development and utilization of single-cell RNA sequencing (scRNA-seq), researchers have been able to unveil the complex and sophisticated biological mechanisms of various types of cells in the auditory organ at the single-cell level and address the challenges of cellular heterogeneity that are not resolved through by conventional bulk RNA sequencing (bulk RNA-seq). Herein, we reviewed the application of scRNA-seq technology in auditory research, with the aim of providing a reference for the development of auditory organs, the pathogenesis of hearing loss, and regenerative therapy. Prospects about spatial transcriptomic scRNA-seq, single-cell based genome, and Live-seq technology will also be discussed.

Tackling the glial scar in spinal cord regeneration: new discoveries and future directions

Axonal regeneration and functional recovery are poor after spinal cord injury (SCI), typified by the formation of an injury scar. While this scar was traditionally believed to be primarily responsible for axonal regeneration failure, current knowledge takes a more holistic approach that considers the intrinsic growth capacity of axons. Targeting the SCI scar has also not reproducibly yielded nearly the same efficacy in animal models compared to these neuron-directed approaches. These results suggest that the major reason behind central nervous system (CNS) regeneration failure is not the injury scar but a failure to stimulate axon growth adequately. These findings raise questions about whether targeting neuroinflammation and glial scarring still constitute viable translational avenues. We provide a comprehensive review of the dual role of neuroinflammation and scarring after SCI and how future research can produce therapeutic strategies targeting the hurdles to axonal regeneration posed by these processes without compromising neuroprotection.

Reactive astrogliosis in the era of single-cell transcriptomics

Reactive astrogliosis is a reaction of astrocytes to disturbed homeostasis in the central nervous system (CNS), accompanied by changes in astrocyte numbers, morphology, and function. Reactive astrocytes are important in the onset and progression of many neuropathologies, such as neurotrauma, stroke, and neurodegenerative diseases. Single-cell transcriptomics has revealed remarkable heterogeneity of reactive astrocytes, indicating their multifaceted functions in a whole spectrum of neuropathologies, with important temporal and spatial resolution, both in the brain and in the spinal cord. Interestingly, transcriptomic signatures of reactive astrocytes partially overlap between neurological diseases, suggesting shared and unique gene expression patterns in response to individual neuropathologies. In the era of single-cell transcriptomics, the number of new datasets steeply increases, and they often benefit from comparisons and integration with previously published work. Here, we provide an overview of reactive astrocyte populations defined by single-cell or single-nucleus transcriptomics across multiple neuropathologies, attempting to facilitate the search for relevant reference points and to improve the interpretability of new datasets containing cells with signatures of reactive astrocytes.