C57BL/6 inbred mice have been widely used as research models; however, widespread demand has led to the creation of several B6 substrains with markedly different phenotypes. In this study, we report that two substrains of C57BL/6 mice, C57BL/6J (B6J) and C57BL/6NCrl (B6C), separated over 50 years ago at two different breeding facilities differ significantly in alcohol consumption and alcohol preference. The genomes of these two substrains are estimated to differ by only 1–2% of all gene loci, providing a unique opportunity to extract particular expression signatures between these substrains that are associated with quantifiable behavioral differences. Expression profiling of the cortex and striatum, hippocampus, cerebellum and the ventral brain region from alcohol‐naïve B6C and B6J mice showed intervals on three chromosomes that are enriched in clusters of coregulated transcripts significantly divergent between the substrains. Additional analysis identified two genomic regions containing putative copy number differences between the substrains. One such region on chromosome 14 contained an estimated 3n copy number in the B6J genome compared with B6C. Within this interval, a gene of unknown function, D14Ertd449e, was found to be both associated with alcohol preference and vary in copy number across several inbred strain lineages. H2afz, Psen1, Wdfy1 and Clu were also identified as candidate genes that may be involved in influencing alcohol consumption.

Background Use of in silico bioinformatics analyses has led to important leads in the complex nature of alcoholism at the genomic, epigenomic, and proteomic level, but has not previously been successfully translated to the development of effective pharmacotherapies. In this study, a bioinformatics approach led to the discovery of neuroimmune pathways as an age-specific druggable target. Minocycline, a neuroimmune modulator, reduced high ethanol drinking in adult, but not adolescent, mice as predicted a priori. Methods Age and sex-divergent effects in alcohol consumption were quantified in FVB/NJ × C57BL/6J F1 mice given access to 20% alcohol using a 4 hr/day, 4-day Drinking-In-Dark (DID) paradigm. In silico bioinformatics pathway over-representation analysis for age-specific effects of alcohol in brain was performed using gene expression data collected in control and DID-treated, adolescent and adult, male mice. Minocycline (50 mg/kg i.p., once daily) or saline alone was tested for an effect on ethanol intake in the F1 and C57BL/6J (B6) mice across both age and gender groups. Effects of minocycline on the pharmacokinetic properties of alcohol were evaluated by comparing the rates of ethanol elimination between the saline and minocycline treated F1 and B6 mice. Results Age and gender differences in DID consumption were identified. Only males showed a clear developmental increase difference in drinking over time. In silico analyses revealed neuroimmune-related pathways as significantly over-represented in adult, but not adolescent, male mice. As predicted, minocycline treatment reduced drinking in adult, but not adolescent, mice. The age effect was present for both genders, and in both the F1 and B6 mice. Minocycline had no effect on the pharmacokinetic elimination of ethanol. Conclusions Our results are a proof of concept that bioinformatics analysis of brain gene expression can lead to the generation of new hypotheses and a positive translational outcome for individualized pharmacotherapeutic treatment of high alcohol consumption.

Changes in renal procollagen mRNA levels were measured shortly after the induction of streptozotocin induced diabetes in the rat. "Medullary" procollagen alpha 1(IV) levels seven days after diabetes induction was significantly higher in untreated diabetic rats (DM, N = 12; 244 +/- 57% of the mean control value), than in diabetic rats receiving small doses of insulin insufficient to achieve euglycemia (NPH, N = 10; 87 +/- 12%) and in diluent injected nondiabetic control rats (C, N = 15; 100 +/- 12%; P less than 0.01, DM vs. C and DM vs. NPH). "Medullary" procollagen alpha 1(I) mRNA levels were numerically increased in DM to a lesser degree (141 +/- 5%, ANOVA not significant) compared to C (100 +/- 13%), and this small increment was further normalized by insulin treatment (NPH, 120 +/- 11%). A trend for increased beta-actin mRNA levels in DM did not reach significance (P greater than 0.05). Increases in "medullary" procollagen mRNA levels did not correlate with kidney weight, glomerular tuft volume, creatinine clearance, food intake, or body weight gain, and occurred when renal morphology was normal by light microscopy. Statistically significant but weak correlations were noted between the serum glucose levels and "medullary" procollagen alpha 1(IV) mRNA levels (r = 0.43, P less than 0.05). In addition, weak correlations were noted between glycosuria and "medullary" procollagen alpha 1(I) levels (r = 0.38, P less than 0.05). In situ hybridization studies localized the increased procollagen alpha 1(IV) mRNA levels predominantly in the DM group primarily in the deep cortex and medullary outer stripe of proximal tubules. Glomerular procollagen alpha 1(IV), alpha 1(I), alpha 1(III) and beta-actin mRNA levels were not increased in untreated diabetic rats 7 or 28 days after diabetes induction. Thus, tubular procollagen alpha 1(IV) mRNA levels increased prior to any measurable change in glomerular levels and were ameliorated by insulin administration.

Recent studies in both human and experimental chronic renal disease suggest that there is a linkage between glomerular hypertrophy and glomerulosclerosis. To further define these relationships, we studied the changes in glomerular hypertrophy, procollagen alpha 1(IV) mRNA levels and glomerulosclerosis in rats undergoing 1 2/3 nephrectomy (Nx) or sham nephrectomy (SNx). Glomerular hypertrophy, measured biochemically by RNA/DNA and protein/DNA ratios, was significantly increased in Nx compared to SNx two days after subtotal renal ablation (RNA/DNA: Nx = 133 +/- 8%, SNx = 100 +/- 3% of the mean control value, P < 0.01; protein/DNA: Nx = 164 +/- 22%, SNx = 100 +/- 10%, P < 0.05) and remained elevated after 7 and 15 days (RNA/DNA: seven days Nx = 155 +/- 3%, SNx = 100 +/- 13%, P < 0.01; 15 days Nx = 303 +/- 21%, SNx = 100 +/- 24%, P < 0.001; protein/DNA: seven days Nx = 228 +/- 57%, SNx = 100 +/- 18%, P < 0.05; 15 days Nx = 341 +/- 23%, SNx = 100 +/- 18%, P < 0.01). Light microscopic measures of glomerular tuft volume (GTV) were too insensitive to detect glomerular enlargement until 15 days postoperatively, but GTV measured ultrastructurally demonstrated a 20% increment in Nx compared to SNx as early as two days postoperatively (P < 0.01). The latter increment in GTV was due exclusively to glomerular visceral epithelial cell (GVEC) expansion. Glomerular procollagen alpha 1(IV) mRNA levels were significantly elevated only 15 days after nephrectomy (Nx = 265 +/- 58% of the mean control value, SNx = 100 +/- 12%, P < 0.05; corrected for beta-actin mRNA levels). As this time, exuberant mesangial expansion measured ultrastructurally contributed to a 1.6 +/- 0.1-fold increase in GTV (P < 10(-5)), and to a relative decrement in the GVEC contribution to glomerular cells plus matrix (P < 0.01). Segmental sclerosis was observed only 15 days postoperatively in Nx (Nx = 1.3 +/- 0.4% of glomeruli evaluated, SNx = 0.0%, P < 0.05), and there was a strong correlation between the prevalence of segmental sclerosis and the procollagen alpha 1(IV) mRNA levels in Nx at 15 days (r = 0.93, P < 0.01). There was no significant correlation between the RNA/DNA and protein/DNA ratios and procollagen alpha 1(IV) mRNA levels. Thus, glomerular regions responded differentially to subtotal nephrectomy. Early epithelial cell expansion was followed by later mesangial expansion. Glomerular procollagen alpha 1(IV) mRNA levels were elevated only during the second (mesangial) phase of glomerular hypertrophy, when it correlated with glomerulosclerosis, but not during the initial (epithelial) phase, a pattern consistent with a mesangial origin of the procollagen alpha 1(IV) mRNA.