Loading-related regulation of gene expression in bone in the contexts of estrogen deficiency, lack of estrogen receptor alpha and disuse

Abstract

Loading-related changes in gene expression in resident cells in the tibia of female mice in the contexts of normality (WT), estrogen deficiency (WT-OVX), absence of estrogen receptor alpha (ERalpha(-/-)) and disuse due to sciatic neurectomy (WT-SN) were established by microarray. Total RNA was extracted from loaded and contra-lateral non-loaded tibiae at selected time points after a single, short period of dynamic loading sufficient to engender an osteogenic response. There were marked changes in the expression of many genes according to context as well as in response to loading within those contexts. In WT mice at 3, 8, 12 and 24 h after loading the expression of 642, 341, 171 and 24 genes, respectively, were differentially regulated compared with contra-lateral bones which were not loaded. Only a few of the genes differentially regulated by loading in the tibiae of WT mice have recognized roles in bone metabolism or have been linked previously to osteogenesis (Opn, Sost, Esr1, Tgfb1, Lrp1, Ostn, Timp, Mmp, Ctgf, Postn and Irs1, BMP and DLX5). The canonical pathways showing the greatest loading-related regulation were those involving pyruvate metabolism, mitochondrial dysfunction, calcium-induced apoptosis, glycolysis/gluconeogenesis, aryl hydrocarbon receptor and oxidative phosphorylation. In the tibiae from WT-OVX, ERalpha(-/-) and WT-SN mice, 440, 439 and 987 genes respectively were differentially regulated by context alone compared to WT. The early response to loading in tibiae of WT-OVX mice involved differential regulation compared to their contra-lateral non-loaded pair of fewer genes than in WT, more down-regulation than up-regulation and a later response. This was shared by WT-SN. In tibiae of ERalpha(-/-) mice, the number of genes differentially regulated by loading was markedly reduced at all time points. These data indicate that in resident bone cells, both basal and loading-related gene expression is substantially modified by context. Many of the genes differentially regulated by the earliest loading-related response were primarily involved in energy metabolism and were not specific to bone.

Fig. 1

Effect of context on gene expression in non-loaded mouse tibia at the  3-h time point. (A) A Venn diagram of the number of differentially expressed genes in tibiae from WT-OVX, ERα^−/− and WT-SN mice backgrounds in comparison to WT mice tibiae. Total RNA was extracted from the non-loaded mouse tibiae at the  3-h time point. The numbers in brackets, beneath the treatment group name, represent the total number of genes differentially regulated in that group in comparison to WT mice tibiae. (B) Canonical pathways most significant to each set of these differentially expressed genes in tibiae from WT-OVX, ERα^−/− and WT-SN mouse backgrounds as analyzed by Ingenuity Pathway Analysis software. The canonical pathways shown are ranked with the most significant pathway heading the list in each context. The significance is based on a Fisher's exact test as described in the methods (⁎p <  0.05, ⁎⁎p <  0.01 and ⁎⁎⁎p <  0.001). The number of genes up- and down-regulated in each canonical pathway within each context are also illustrated.

Fig. 2

Time course of differentially expressed genes in response to loading tibiae in mice according to context. The number of genes differentially up or down-regulated at 3, 8, 12 and 24 h in tibiae from WT, WT-OVX and WT-SN mice and 3, 8 and 24 h in tibiae from ERα^−/− mice after a single period of in vivo loading compared to their contra-lateral, non-loaded controls.

Fig. 3

Heat maps of identified genes differentially expressed by loading according to context (A = WT, B = WT-OVX, C = WT-SN and D = ERα^–/–). Heat map visualization of clusters formed was generated by using CLADIST. Hierarchical clustering analysis was done in Euclidean distance by average linkage method. Genes are colored based on their fold expression level. Red indicates up-regulation while blue indicates down-regulation of genes at each time point after loading. The intensity of the color indicates the level of differential regulation.

Fig. 3

Heat maps of identified genes differentially expressed by loading according to context (A = WT, B = WT-OVX, C = WT-SN and D = ERα^–/–). Heat map visualization of clusters formed was generated by using CLADIST. Hierarchical clustering analysis was done in Euclidean distance by average linkage method. Genes are colored based on their fold expression level. Red indicates up-regulation while blue indicates down-regulation of genes at each time point after loading. The intensity of the color indicates the level of differential regulation.

Fig. 4

The number of genes at each time point, in each context, that are differentially regulated by loading that are common to the loading response in tibiae from WT mice. Loading-induced differentially expressed genes in tibiae from WT-OVX, ERα^−/− and WT-SN mice are separated into those common to (black) and different from (white), those regulated in the tibiae from WT mice at the equivalent time point after loading.

Fig. 5

Comparison of the fold change in regulation of 16 sample genes as assessed by the microarray and quantitative real-time RT-PCR with β-actin as an internal control. Target genes were selected based on interest and fold change in the microarray both in up- and down-regulation according to context or in response to loading in different contexts. Genes differentially expressed by context were selected from WT-OVX mice vs. WT mice tibiae (Itga4, Esr1), ERα^−/− mice vs. WT mice tibiae (Ppargc1a and Strn) and WT-SN mice vs. WT mice tibiae (Ankrd1, Bnip3, Postn and Hist4h4). Genes differentially expressed by loading in WT mice tibiae were selected from 3 h (Ctgf, Postn, Timp and Ttn), 8 h (Bnip3 and Irs1) and 12 h time points (Sost). Genes differentially expressed by loading in WT-OVX mice tibiae were selected from 3 h time point (Irs1⁎ and Sost⁎). Gene differentially expressed by loading in WT-SN mice tibiae was selected from 3 h time point (Myf6). Genes differentially expressed by loading in ERα^−/− mice tibiae were selected from 8 h time point (Ndufa11 and Pkm2).

Fig. 6

Functional analysis of genes differentially expressed by loading in tibiae from WT, WT-OVX, ERα^−/− and WT-SN mice mapped into 1 of 15 functional groups using the Ingenuity Pathway Analysis knowledge data base. The number of “focus” genes in each of these 15 functional categories that were most significantly over-represented (10^− 5 < p > 10^− 2) are shown for all four contexts.

Fig. 7

Canonical pathway analysis of genes differentially regulated by loading mouse tibiae according to context. Canonical pathways that were most significant to the focus genes differentially regulated at the earliest sampling time (3 h) after loading of WT mouse tibiae were constructed using the IPA knowledge data base. Using this set of canonical pathways as a template, focus genes differentially regulated by loading at all sampling points in all four contexts were processed to find the degree to which these pathways were represented in response to loading in each group of mice. A negative log value of 1.3 has only a 5% chance of being generated by chance alone.