Phenotypic Characterisation:
We have generated phenotype data on nine ENU induced lines (GENA/ 263, GENA/348, GENA/389, IGT/1, IGT/3, IGT/4, IGT6, GENA394 and IGT/10) and in addition the Lepr db/db mice for diabetic complications in the kidney. Phenotypic characterisation included histological analysis of kidney sections measuring extracellular matrix area in the mesangium of glomeruli, plasma glucose and insulin levels and biochemical analysis of urine for glucose, albumin and creatinine. Morphological measurements of kidney and bodyweight have been recorded.
Of the ENU induced lines characterised only GENA/348 (Gck mutant) and IGT/10 exhibited potentially interesting kidney phenotypes. GENA/348 animals showed impaired glucose tolerance which has been shown to be caused by a point mutation in the MODY2 gene, glucokinase. Histological analysis of kidney sections from GENA/348 progeny showed a 20% increase in glomerular mesangial matrix in comparision to age-matched control animals. IGT/10 animals exhibited hyperglycaemia, glycosuria and proteinuria. Preliminary histological analysis of IGT/10 kidney sections showed a 10% increase in glomerular mesangial matrix in comparision to age-matched control animals.
The GENA 348 model is available on request.
The Lepr db/db mouse was further characterized using metabolomic analysis of urine samples (Salek et al. "A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and man" (2007) Physiological Genomics 29: 99-108). This study demonstrated metabolic similarities between all 3 species with responses associated with general metabolic stress and changes in the TCA cycle.
Expression Profiling:
We selected an established severe diabetes mutant to be used for expression profiling experiments. Mice carrying a mutation in the leptin receptor (Lepr db/db) develop diabetes at 4-6 wks of age and become obese. Phenotype data was collected at 4 week intervals and included plasma glucose and insulin measurements, histological analysis of extracellular matrix expansion in the glomerulii of kidneys and glucose and protein levels in the urine. In addition, we collected 24hr urine samples in metabolic cages for both db/db and control animals for more detailed urine analysis (including an estimation of glomerular filtration rate) to correspond with microarray datapoints. An initial expression profiling experiment was performed using the mouse Compugene 7.5k "known" gene oligo arrays which were hybridised with RNA from the kidneys of 8wk, 12wk and 16wk old db/db and control animals. After analysis of this micro array data we were able to generate a list of 50 genes that were differentially expressed in at least two time-points. The identity of each gene is known from the sequence of each oligonucleotide on the array (in the original plan we would have used spotted cDNA arrays however we were able to gain access to larger and more specific oligonucleotide gene probe arrays) and the map position and sequence of all of these genes is known through analysis of the mouse genomic reference sequence and EST databases. This list was further refined by comparative analysis of genes differentially expressed in the GK rat expression profiling experiment (WP5) and published results in the mouse to produce a TOP50 list of candidate genes which would then have 10 to 15 genes chosen from it which would be screened in the 47 EURAGEDIC pools.
During the final year an opportunity arose to use the ~32k Operon oligo array set. Instead of using a second line we decided to increase the time-span of our longitudinal study using the db/db mice so that a more comprehensive analysis of gene expression changes during the critical phase of development of diabetic kidney disease could be achieved (this was more than equivalent to carrying out an experiment on a second line). For this second expression profiling experiment we extended the time-course to include 20 and 24wk animals; the time-points analysed are 4wk, 8wk, 12wk, 16wk, 20wk and 24wks of age.
Preliminary analysis of this microarray data has generated lists of differentially expressed genes that are statistically significantly at each time-point. Further analysis of longitudinal expression patterns is underway using this high quality dataset.
Data has been deposited in ArrayStager and is being further characterised by the EUREGENE consortium. A manuscript is being planned and prepared.