Abstract
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.
Highlights
Microglia are the resident immune cells in the brain and are essential for the phagocytosis of pathogens and apoptotic cells as well as for modulating adaptive immune responses (Aloisi, 2001; Prinz and Priller, 2014; Colonna and Butovsky, 2017; Wolf et al, 2017)
Microglia in the peri-infarct area were more circular than microglia in the contralateral cortex, whereas the ramification index revealed that microglia in the contralateral cortex were more ramified than in the peri-infarct area
We aimed to develop an algorithm for fully automated analysis of microglial cells using the same exploratory dataset as for the manual analysis shown above
Summary
Microglia are the resident immune cells in the brain and are essential for the phagocytosis of pathogens and apoptotic cells as well as for modulating adaptive immune responses (Aloisi, 2001; Prinz and Priller, 2014; Colonna and Butovsky, 2017; Wolf et al, 2017). Automated Morphological Analysis of Microglia associated molecular patterns (DAMPs) (Colonna and Butovsky, 2017). In this state, microglia were previously described as “resting.” more recent studies demonstrate them to be highly dynamic and should rather be perceived as “surveilling” microglia (Tremblay et al, 2011). Blood-borne immune cells can infiltrate into the ischemic brain, promote post-ischemic inflammation and increase the release of pro-inflammatory cytokines (Gelderblom et al, 2009; Tremblay et al, 2011; Prinz and Priller, 2017). Surveilling microglia react to the inflammatory milieu and become “activated” within minutes after ischemia onset, which is characterized by an increased release of proor anti-inflammatory cytokines, a change in surface molecule expression, and a morphological transformation from ramified into amoeboid microglia (Kriz, 2006; Kettenmann et al, 2011; Tremblay et al, 2011; Kawabori and Yenari, 2015; Wolf et al, 2017)
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