All experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of the Indiana University School of Medicine, which is in accordance with National Institutes of Health guidelines for the care and use of laboratory animals. 36 Wild type male C57BL/6 mice were obtained from Jackson Laboratory at 8–12 weeks old (~25–30 g) and were randomly divided into sham saline (SS), mTBI saline (TS), and mTBI propranolol (TP) and sham propranolol (SP) for downstream gene expression analyses. Mice were randomly subdivided into day 1, day 7, and day 30 timepoints with n = 3 for each group at each timepoint. All experiments were performed in accordance with relevant ARRIVE guidelines.

mTBI was inflicted using a technique described recently (Nguyen et al., 2021; Smith et al., 2023). Briefly, mice were anesthetized with 2–4% isoflurane and heads stereotactically fixed with heat-pad support below the abdomen. Closed-head mTBI was produced using a control cortical impact (CCI) device after shaving, cleaning, sanitizing the area, and making a skin incision to expose the skull. After the baseline point of the device was set by lowering the tip to the exposed skull surface and the stage position was set to zero, the impactor was retracted, the impact depth was set, and the impact was made. The approximate center of the impact site was 1 mm posterior to the bregma and 0.5 mm lateral from midline over the right cortical hemisphere. The skull was struck with the impactor tip at a speed of 3 m/s to a depth of 1 mm. Sham injury animals were shaved, cleaned, sanitized, an incision was made to expose the skull, but no impact was performed on the skull. The resulting skin wound was sutured, and animal placed on heating pad until fully recovered. All animals survived the injury without any skull fracture or hemorrhage. The injury paradigm was performed once a week for three weeks for a total of 3 injuries (Figure 1).

Verification of the absence of skull fracture was assayed by changes in intraocular pressure (IOP) using ICARE TONOLAB (Vantaa, Finland) tonometer (Chen et al., 2019) and served as a surrogate measure for internal brain pressure. The IOP measurements were done immediately before and after the injury for up to 30 min (data not shown). Predictably, if the skull calvarium was fractured by the CCI device, an absence of IOP would be present. Alternatively, if there were no changes in IOP, injury to the skull bone was deemed to be insufficient and the animal excluded from the study. No animals were subsequently removed from this study.

Propranolol chloride (Tocris Bioscience, Bristol, United Kingdom) was dissolved in saline (3 mg/mL). Based on the treatment group designation, the drug (10 mg/kg) or saline vehicle was injected intraperitoneally into each mouse immediately following mTBI or sham surgery as previously stated by other studies (Haffner-Luntzer et al., 2019; Loftus et al., 2019). Each mouse was subjected to a total of three of either propranolol or saline injections.

We followed previously described bone marrow protocols to extract bone marrow tissue from the femurs of mice (Marim et al., 2010). Briefly, scissors were used to cut the femur from the pelvis and knee joint. The femur was then placed into an ice cold PBMC culture medium composed of complete RPMI medium (88% RPMI 1640; ThermoFisher), 10% Fetal Bovine Serum (Sigma-Aldrich), 1% Penicillin-Streptomycin (Sigma-Aldrich), and 1% Glutamax (ThermoFisher). Next, a 23G needle attached to a 3 mL syringe filled with ice cold complete RPMI was inserted into the medullary cavity of the femur and the bone marrow was flushed out into a 15 mL tube. The procedure was repeated 2–3 times until the femur diaphysis was white. The resultant tissue was centrifuged at 400xg for 10 min at 4°C, and the supernatant was discarded. Remaining tissue was then resuspended in RBC lysis buffer for 10 min at room temperature, recentrifuged, and resuspended in calcium free PBS. The suspension was again centrifuged at 400xg for 10 min at room temperature, resuspended in complete RPMI medium, and then added to the equal volume of FBS supplemented with 10% DMSO for freezing. The frozen bone marrow was stored in liquid nitrogen at −196°C until future analyses.

mRNA was isolated from each bone marrow sample using the TRIzol reagent (Invitrogen) as described in the manufacturer’s protocol. RNA samples were evaluated by nCounter gene expression analysis technology (NanoString Technologies) and quantified via nCounter Digital Analyzer (NanoString Technologies). The expression of 770 genes (including 14 internal reference genes) was determined using the nCounter Stem Cell Characterization Panel™ (mouse, NanoString, XT-CSO-MSCC-12). To minimize variability among arrays, densitometry values between arrays were normalized using Robust Multichip Average function and further transformed to a log2 scale. Gene expression levels in each sample were normalized against the geometric mean of six housekeeping genes, specifically Cltc, Gapdh, Tpia, Tbp, Pgk1, and Tubb5. A cutoff was introduced at the value of the highest negative control present on the chip. 100 ng of total mRNA was used as input and sample hybridization was performed according to the manufacturer’s instructions. Raw data processing, quality control (QC), and normalization were performed using the nSolver™ 4.0 analysis software. QC and normalization were performed with an imaging QC of >75% field of view registration, binding density QC within 0.1–2.25 range, positive control linearity QC of R2 above 0.95, and positive control limit of detection set as 0.5 fM positive control above 2 standard deviations above the mean of the negative controls. Normalization to housekeeping genes, of which genes below 100 were excluded, and pathway scoring, gene set analysis, differential expression analysis, and cell type profiling were completed using the Advanced Analysis software plugin (version 2.0.115). For each experiment, the fold changes were calculated comparing to their appropriate sham-injured saline treated control at each timepoint. For pathway scoring and differential expression analysis, a value of p of ≤0.05 was applied as cutoffs. For all NanoString analyses at 1 day, 1 week, and 1 month after injury, gene expression measurements for each group were normalized to the sham saline (n = 3) baseline of each timepoint.

Differentially expressed (DE) genes were calculated using fold change by comparing transcript levels between the combined samples within a group of SP, TS, or TP bone marrow and sham saline bone marrow baseline. The results of these multiple t test analyses are summarized in volcano plots, (Tables 1–3), and in Supplementary Data Sheets S1–S6. Data was graphed −log10(value of p) vs. fold change with Bonferroni adjusted p value dotted lines shown to depict varying levels of significance at p < 0.50, p < 0.10, p < 0.05, and p < 0.01. 12 of the most significantly changed genes across the experimental groups and timepoints were chosen for further characterization (Figure 2). These data were generated by NanoString advanced analysis and selected due to high differential expression. Log2 fold changes for these mRNAs were further assessed across the experimental timepoints to determine group dependent changes for these transcripts.

Panel derived transcripts from each sample were grouped into pathways by Nanostring Advanced Analysis software and Scores are displayed on the same scale via a Z-transformation. Mean z score for each group was compared at each timepoint to the sham saline baseline control to understand how pathway scores cluster together and which samples exhibit similar pathway score profiles at each timepoint.

NanoString data normalized to housekeeping gene expression were initially analyzed using the t-test to identify the top 100 significant genes. The Bonferroni correction was applied to derive the adjusted p values with a ≤0.05 with a cut off adjusted p value of ≤0.05. Sham saline data were utilized as baseline for each timepoint. Gene expression changes were reported as log2 fold change. Expression change data were compared using two-way ANOVA (treatment vs. time) test followed by the Šidák multiple comparisons post hoc test (GraphPad Prism 9, La Jolla, California). Pathway score significance was calculated using unpaired t-test, with p < 0.05 being considered significant, and mean values were calculated by averaging pathway Z scores of individual samples within a group at one timepoint (n = 3/group). All data were presented as mean ± S.E.M. The sample size was n = 3 for each tested group.

Figure 1 shows the timeline of the experiments. Three mice per treatment group were used for each post-injury/drug treatment time point in this study (Figure 1). This gave a detailed coverage of acute, subacute and chronic responses of bone marrow tissue to rmTBI in the absence or presence of propranolol treatment.

Mice sacrificed on the day 1 following completion of the 3x injury/drug treatment paradigm showed no significant changes of gene expression in SP treatment group (Figure 3A), whereas the TS treatment group exhibited increased gene expression in branched chain amino acid transaminase (Bcat2), valosin-containing protein (Vcp) and neurolysin (Nln) (Figure 3B; Supplementary Data Sheet S1). The TP treatment group exhibited the greatest change at day 1 as there were 66 genes which displayed decreased expression including Bcat2 (Figure 3C; Supplemetary Data Sheet S2).

Complex biological processes, such as those present in bone marrow tissue involve the coordinated regulation of multiple intracellular signaling pathways controlling gene expression. The signaling pathway changes found in the SP treatment group were limited to an increase in Hedgehog signaling (Table 1). In contrast, the decreases in gene expression observed in both TS and TP bone marrow tissue were accompanied by decreases in signaling pathway scores on the day 1 time point following injury paradigm for all assayed pathways (Table 1, p < 0.05, t test).

Seven days post cessation of the 3x injury/drug treatment paradigm, the SP group exhibited 57 genes which were significantly different when compared with the SS group (Figure 4A, p < 0.05, t test). Of this group, 48 genes exhibited decreased expression and 9 genes showed increase expression (Figure 4A; Supplementary Data Sheet S3). A significant decreased expression for 21 genes in the TS group were evident (Figure 4B; Supplemetary Data Sheet S4). The SP and TS groups at 7 days exhibited similar decreases in Usp7, tfdp2, add1, pp2r5b1, cir1, and cul1. Unlike the day 1 post injury paradigm, TP bone marrow failed to exhibit either increases or decreases in gene expression at 7 days (Figure 4C).

Signaling pathway changes in SP bone marrow tissue exhibited the greatest number of pathway changes (26 of 32) at 7 days post-injury (Table 2). The SP bone marrow tissue displayed decreases in amino acid metabolism, apoptosis, autophagy, cell cycle, cytoskeletal reorganization, epigenetic modifications, glutamine metabolism, hedgehog signaling, notch signaling, senescence and quiescence, and TGFβ signaling (Table 2, p < 0.05, t test). Increases in signaling pathway were also apparent. Significant changes were found in AP1 signaling, ectodermal lineages, endodermal lineage, fatty acid metabolism, glucose metabolism, hippo signaling, hypoxia response, MAPK signaling, mesodermal lineages, mTOR signaling, Na.QZ.ve state, oxidative stress, partially reprogrammed, pluripotency markers, and RhoROCK signaling (Table 2).

TS bone marrow tissue exhibited numerous changes in 15 of 32 signaling pathways (Table 2). These changes were largely reductions in signaling pathways such as, autophagy, cell cycle, cytoskeletal reorganization, epigenetic modifications, glutamine metabolism, hedgehog signaling, HOX gene activation, integrin signaling, JAK–STAT signaling, notch signaling, primed state activation, and senescence and quiescence. Significant increases were found only in three signaling pathways such as amino acid metabolism, AP-1 signaling, and partially reprogramed cells (Table 2, p < 0.05).

Despite a lack of gene expression changes in the TP animal group, we observed significant increases in signaling pathway scores for glutamine metabolism, hedgehog signaling, and JAK–STAT signaling. Increases in signaling pathways were limited to only glutamine metabolism in TP bone marrow when compared to TS bone marrow (Table 2).

We observed significant differential expression of 40 genes in the SP group and 52 genes in the TP group but no changes in gene expression in the TS group at 30-days (Figure 5B) after completion of the injury/drug treatment paradigm. Among the genes which exhibited decreased expression in both treatment conditions of SP and TP were Cul1, Itgb1, Sorbs1, Tsc22d1, E2f4, Brd7, Mark3, Cir1, and Amd1/2 (Figures 5A,C; Supplementary Data Sheets S5, S6). This differential gene expression profiling clearly demonstrates the long-lasting impact of propranolol on bone marrow tissue in both SP and TP animal groups. None of the genes associated with TS met the established criterion for significant change in expression levels.

Characterization of signaling path way changes following the injury/drug treatment paradigm demonstrated significant signaling pathway changes present in SP, TS, and TP bone marrow tissues 30 days after injury. The SP bone marrow tissue exhibited significantly decreased signaling in 25/32 pathways when compared to the SS bone marrow tissue. The pathway score changes for the various groups are summarized in Table 3. TS bone marrow had increased signaling in amino acid metabolism, apoptosis, cell cycle signaling, cytoskeletal reorganization, glucose metabolism, hedgehog signaling, and oxidative stress pathways. Additional signaling changes appeared in the TP bone marrow tissue 30 days following injury, as shown by significant decreases in 24/32 pathways compared to baseline SS tissue. Here, we again observed a high crossover of decreased signaling changes common between SP and TP bone marrow tissues. Signaling pathway changes that differed between SP and TP were limited to an increase in AP-1 signaling. Compared to TS bone marrow tissue, rmTBI bone marrow from TP mice exhibit significant decreases in 24/32 signaling pathways.

Expression of numerous genes were affected by the drug/injury paradigm across the three timepoints (Figure 2; Table 3). SP group changes at day 1 were most evident by decreased gene expression of hmgb1, rock1, hdac6, vegfa, tfdp2, sorbs1, bcat2, camk1, and cul1 when compared to SS treated animal mRNA transcripts. The only gene expression which increased at day 1 was usp7 (p < 0.05, two-way ANOVA, Šidák post hoc). This change was restricted to a comparison between sham saline (SS) bone marrow and not to rmTBI (TS) bone marrow.

Seven days after injury TP mRNA transcripts were increased for hmgb1, usp7, tfdp2, itgb1, sorbs1, and cul1 when compared to TS derived bone marrow mRNA expression levels by two-way ANOVA with Šidák post hoc test. Jak2 was also increased in TP bone marrow when compared to SP bone marrow tissue. Two gene transcripts, hdac6 and vegfa, were decreased in TP bone marrow but only when compared to SP bone marrow. Interestingly, TP genes did not differ from SS derived gene transcripts for the genes we investigated at this timepoint.

Two-way ANOVA testing for the 30-day timepoint displayed genetic changes for several gene transcripts derived from TP animals. We observed increased hmgb1, rock1, hdac6, usp7, vegfa, jak2, tfdp2, itgb1, sorbs1, bcat2, and cul1 compared to the TS-derived bone marrow tissue (Supplementary Data Sheets S5, S6). It is worth noting that some gene expression increases in the TP group were considerably less when the data were compared to SS-derived bone marrow tissue, specifically for itgb1 and cul1 genes. It should be noted however that for the ANOVA analyses of these 12 genes, we detected a significant interaction between our two variables of treatment and time.

We next performed pathway enrichment analysis on genes that exhibited timeline-specific changes (Figures 6A,B). More than 500 genes showed temporal expression changes in TS bone marrow tissue. In contrast, only 122 genes had time-dependent changes in TP, suggesting that propranolol largely blunted gene expression changes. In general, genes involved in cell proliferation, differentiation, and stem cell renewal were enriched in TS bone marrow tissue (FoxO, neurotrophin, cell cycle, pluriopotency, and Hippo signaling pathways). Similar classes of genes were enriched in TP (90 out of 122 genes are shared with TS). Finally, using a linear regression model, we searched for genes that are differentially expressed between TS and TP independently of the TBI timeline. This analysis revealed only modest enrichment of genes that still showed some degrees of time-dependent effects (Figure 6C; highlighted in yellow rectangles as an example).