The Lacunocanalicular Network is Denser in C57BL/6 Compared to BALB/c Mice.

Abstract

The lacunocanalicular network (LCN) is an intricate arrangement of cavities (lacunae) and channels (canaliculi), which permeates the mineralized bone matrix. In its porosity, the LCN accommodates the cell network of osteocytes. These two nested networks are attributed a variety of essential functions including transport, signaling, and mechanosensitivity due to load-induced fluid flow through the LCN. For a more quantitative assessment of the networks' function, the three-dimensional architecture has to be known. For this reason, we aimed (i) to quantitatively characterize spatial heterogeneities of the LCN in whole mouse tibial cross-sections of BALB/c mice and (ii) to analyze differences in LCN architecture by comparison with another commonly used inbred mouse strain, the C57BL/6 mouse. Both tibiae of five BALB/c mice (female, 26-week-old) were stained using rhodamine 6G and whole tibiae cross-sections were imaged using confocal laser scanning microscopy. Using image analysis, the LCN was quantified in terms of density and connectivity and lacunar parameters, such as lacunar degree, volume, and shape. In the same tibial cross-sections, the calcium content was measured using quantitative backscattered electron imaging (qBEI). A structural analysis of the LCN properties showed that spatially denser parts of the LCN are mainly due to a higher density of branching points in the network. While a high intra-individual variability of network density was detected within the cortex, the inter-individual variability between different mice was low. In comparison to C57BL/6J mice, BALB/c mice showed a distinct lower canalicular density. This reduced network was already detectable on a local network level with fewer canaliculi emanating from lacunae. Spatial correlation with qBEI images demonstrated that bone modeling resulted in disruptions in the network architecture. The spatial heterogeneity and differences in density of the LCN likely affects the fluid flow within the network and therefore bone's mechanoresponse to loading.