Recent advances in 2-dimensional gel electrophoresis technologies, namely the introduction of fluorescent dyes, which allow multiple samples to be co-separated and visualized on one 2-D gel, have increased the utility of this methodology for the discovery of robust protein biomarkers for disease [18–20]. For example, power analysis for 2D-DIGE has demonstrated statistical power of >0.8 for detecting 2-fold changes at p ≤ 0.01 with 4 biological replicates. In our experiment urine samples representing 4 control and 4 age matched infected cattle were run with an internal standard. The internal standard, created by pooling aliquots of all biological samples in the experiment, was run on all gels within the experiment thereby creating an intrinsic link across all gels. Normalization of the internal standard across gels allowed the ratio of relative abundance of the same protein to be compared directly, separating gel-to-gel variation from biological variation. Differences in protein abundance were then determined by comparing the ratio obtained from one fluorescent labelled sample directly with another.
Changes in the amount of a given soluble protein in urine can result from a change in its concentration in the blood plasma, a change in the function of the glomerular filter, an alteration in the proximal tubule scavenging system or a change in local production and excretion. No proteinuria indicating a change in the glomerular filter was observed in response to BSE infection (Additional file 2). In addition, no significant difference (p < 0.01) in the standardized log of abundance for cystatin was observed at any time point when compared to the corresponding control (Additional file 3). Cystatin is a low molecular weight cysteine proteinase inhibitor that is freely filtered by the renal glomeruli and reabsorbed in the proximal tubules. Consequently cystatin serves as an indicator of the health of the proximal tubule scavenging system[23, 24]. The absence of change in cystatin abundance indicated that the proximal tubule scavenging system was unaffected by BSE infection. Together these results suggest that the differential abundances observed in response to BSE infection were likely due to changes in the protein concentration in the blood plasma or a disease associated alteration in local production.
One of the identified classifier proteins that exhibited increased abundance in response to infection was immunoglobulin Gamma-2 chain C region. Increased immunoglobulin has previously been observed in the urine of scrapie infected hamsters and in one report it was speculated that this was the result of a nephritic syndrome [5, 6, 16]. In contrast, the data presented suggests that the increased abundance of immunoglobulin in urine associated with BSE was probably due to a change in immunoglobulin concentration in the blood plasma. Nonetheless, the detection of differential abundance of another immunoglobulin protein in urine by an unbiased screen lends support to the suggestion that immunoglobulin light chain may constitute a surrogate marker for TSE diseases[6, 16].
In addition to immunoglobulin Gamma-2 chain C region and cystatin, the 3 other identified classifier proteins were well known urinary proteins. One was the antimicrobial peptide cathelicidin that is produced in the kidney by the epithelial cells that line the urinary tract. When exposed to bacteria the levels of cathelcidin mRNA are known to rapidly increase, however, even in the absence of microbes the epithelial surface of the urinary tract are continuously bathed with cathelicidin[25, 26]. A second protein was the natriuretic peptide uroguanylin that is produced in the small intestine and kidney. In response to salt loading no increase in circulating uroguanylin is observed indicating that the natriuretic effect of uroguanylin is in part mediated by increased renal production that inhibits tubular resorption of ions from the glomerular filtrate. These characteristics suggested that the decreased abundance of both cathelicidin, observed after 24 mpi, and uroguanylin throughout the experiment were probably the result of decreased renal production and excretion. The precise cause of the decreased production and the possible effects of the altered abundance on prion pathobiology are not known.
The third protein, identified as clusterin, was able to distinguish between infected animals and age matched controls with 100% accuracy throughout the experiment. Clusterin is a multifunctional glycoprotein with nearly ubiquitous tissue distribution. Increased abundance of clusterin in association with TSE diseases has been reported previously and has included increased expression in astrocytes as well as a significant accumulation in cerebrospinal fluid and blood plasma. Thus, increased amounts of circulating clusterin may have caused the increased clusterin abundance observed in the urine of the BSE infected animals. Despite the power of clusterin as a biomarker of BSE in this experiment, the increased clusterin abundance in CSF observed in models of other neurodegenerative diseases, such as Alzheimer's disease, and in response to a variety of renal insults raises doubts as to the specificity of clusterin per se as a biomarker of BSE in cattle [30–34]. However, the specificity of the particular isoform of clusterin observed to best discriminate between BSE infected and control cattle remains to be seen.
EDA analyses also demonstrated that the differential abundance of different subsets of proteins provided accurate measures of disease progression and aging. This was an unexpected result, but the ability to follow disease progression by monitoring the differential abundance of a subset of proteins has potential applications as a prognostic indicator or in the assessment of the therapeutic benefit of potential treatments. Furthermore, while markers of disease progression must be sensitive to changes in disease state and present in easily accessible tissues that permit repeated sampling, they do not require the same high disease specificity as diagnostic markers. The ultimate utility of these markers of disease progression will be determined by their identification and validation as well as their applicability to clinically relevant disease models. Significantly, the markers of disease progression demonstrated very little overlap with those identified as able to track age. This indicates that they were a measure of disease specific progression and that their identification may also provide insight into the pathology of these diseases.
The results demonstrate that in principle it is possible to identify biomarkers of TSE disease by analyzing changes in the urine protein profile provoked by the disease. Extending the present study to larger numbers of cattle and to those of other strains will test the value of the biomarkers identified. Even more promising markers may have been missed due to the bias of 2D-DIGE to the identification of abundant proteins. This shortfall will be addressed in future studies by utilizing a variety of pre-fractionation methods.