Cell morphology as a quantifier for functional states of resident tissue macrophages

Resident tissue macrophages (RTMs) are essential for maintaining homeostasis in a physiological tissue state. They monitor interstitial fluids, contain acute damage while actively preventing inflammation, and remove dead cells and debris. All these cellular functions are accompanied by characteristic changes in cell morphology, the expression of which can provide information about the functional status of the cells. What is currently known about morphological patterns and dynamic behavior of macrophages is derived primarily from experimental ex vivo cell cultures. However, how macrophages operate in living organisms is in many ways fundamentally different from how they do in a cell culture system. In this work, we employed an intravital imaging platform to generate dynamic data from peritoneal RTMs in vivo in mice under various conditions induced either chemically or physically. Using this data, we built an image processing pipeline and defined a set of human-interpretable cell size and shape features which allowed us to quantify RTM morphodynamics over time. We used those features to quantitatively differentiate cells in various functional states - when macrophages are activated, for instance, or when they “shut down” due to detrimental changes in the environment. The qualitative morphology changes associated with these functional states could be inferred directly from the quantitative measurements. Finally we used the set of cell morphology features monitoring the health of RTMs to improve a setup for explanted tissues. Thus, the proposed method is a versatile tool to provide insights into the dynamic behavior of bona fide macrophages in vivo and helps distinguish between physiological and pathological cell states. Author summary Mammalian tissues are constantly subjected to various stresses - due to pathogens, cell death and molecular waste products - which have to be resolved properly to prevent unwanted inflammatory processes and thus maintain tissue homeostasis. To find such incidents, resident tissue macrophages (RTMs) in vivo display constant sampling behavior which is accompanied by dynamic changes to their morphology. These changes of cellular features are not yet fully understood and were even not yet quantified for RTMs in living organisms. To fill this knowledge gap, we have used an intravital imaging platform to generate time-lapse images of RTMs over time in the peritoneal serosa of a living mouse. Subsequently we have built a custom image processing pipeline to assess the morphology and dynamics of the cells. We could use these measurements to recover the qualitative cell morphology changes over time and even differentiate cells in distinct physiological and pathological states. Thus this analysis lays the basis to the further development of a mathematical model or RTM sampling dynamics or may even be the first step to diagnose macrophages in disease contexts. ### Competing Interest Statement The authors have declared no competing interest.