Commensal gut bacteria impact the host immune system and can influence disease processes in several organs, including the brain. However, it remains unclear whether the microbiota has an impact on the outcome of acute brain injury. Here we show that antibiotic-induced alterations in the intestinal flora reduces ischemic brain injury in mice, an effect transmissible by fecal transplants. Intestinal dysbiosis alters immune homeostasis in the small intestine leading to an increase in regulatory T cells and a reduction in IL-17+ γδ T cells, through altered dendritic cell activity. Dysbiosis suppresses trafficking of effector T cells from the gut to the leptomeninges after stroke. Interleukin-10 (IL-10) and IL-17 are required for the neuroprotection afforded by intestinal dysbiosis. The findings reveal a previously unrecognized gut-brain axis and the impact of the intestinal flora and meningeal IL-17+ γδ T cells on ischemic injury.

Analysis of entire transparent rodent bodies after clearing could provide holistic biological information in health and disease, but reliable imaging and quantification of fluorescent protein signals deep inside the tissues remained a challenge. Here, we developed vDISCO, a pressure driven, nanobody based whole-body immunolabeling technology to enhance the signal of fluorescent proteins by up to two orders of magnitude. This allowed us to image and quantify subcellular details through bones, skin and highly autofluorescent tissues of intact transparent mice. For the first time, we visualized whole-body neuronal projections in adult mice. We assessed CNS trauma effects in the whole-body and found degeneration of peripheral nerve terminals in the torso. Furthermore, vDISCO revealed short vascular connections between skull marrow and brain meninges, which were filled with immune cells upon stroke. Thus, our new approach enables unbiased comprehensive studies of the interactions between the nervous system and the rest of the body.

Recovery after stroke is a multicellular process encompassing neurons, resident immune cells, and brain-invading cells. Stroke alters the gut microbiome, which in turn has considerable impact on stroke outcome. However, the mechanisms underlying gut-brain interaction and implications for long-term recovery are largely elusive. Here, we tested the hypothesis that short-chain fatty acids (SCFAs), key bioactive microbial metabolites, are the missing link along the gut-brain axis and might be able to modulate recovery after experimental stroke. SCFA supplementation in the drinking water of male mice significantly improved recovery of affected limb motor function. Using in vivo wide-field calcium imaging, we observed that SCFAs induced altered contralesional cortex connectivity. This was associated with SCFA-dependent changes in spine and synapse densities. RNA sequencing of the forebrain cortex indicated a potential involvement of microglial cells in contributing to the structural and functional remodeling. Further analyses confirmed a substantial impact of SCFAs on microglial activation, which depended on the recruitment of T cells to the infarcted brain. Our findings identified that microbiota-derived SCFAs modulate poststroke recovery via effects on systemic and brain resident immune cells.

Microglia are the resident immune cells of the brain and react quickly to changes in their environment with transcriptional regulation and morphological changes. Brain tissue injury such as ischemic stroke induces a local inflammatory response encompassing microglial activation. The change in activation status of a microglia is reflected in its gradual morphological transformation from a highly ramified into a less ramified or amoeboid cell shape. For this reason, the morphological changes of microglia are widely utilized to quantify microglial activation and studying their involvement in virtually all brain diseases. However, the currently available methods, which are mainly based on manual rating of immunofluorescent microscopic images, are often inaccurate, rater biased, and highly time consuming. To address these issues, we created a fully automated image analysis tool, which enables the analysis of microglia morphology from a confocal Z-stack and providing up to 59 morphological features. We developed the algorithm on an exploratory dataset of microglial cells from a stroke mouse model and validated the findings on an independent data set. In both datasets, we could demonstrate the ability of the algorithm to sensitively discriminate between the microglia morphology in the peri-infarct and the contralateral, unaffected cortex. Dimensionality reduction by principal component analysis allowed to generate a highly sensitive compound score for microglial shape analysis. Finally, we tested for concordance of results between the novel automated analysis tool and the conventional manual analysis and found a high degree of correlation. In conclusion, our novel method for the fully automatized analysis of microglia morphology shows excellent accuracy and time efficacy compared to traditional analysis methods. This tool, which we make openly available, could find application to study microglia morphology using fluorescence imaging in a wide range of brain disease models.