Urine is a complex mixture of metabolites of various chemical nature and thus a significant source of biomarkers for human diseases. Short endogenous peptides are amino acid sequences shorter than four which have been frequently described as potential biomarkers, but still represent an analytical challenge due to their wide range of polarity, poor ionization efficiency using electrospray-mass spectrometry (MS) for their determination and the absence of automation in their detection. The aim of the present project will be the development of an analytical methodology for the enrichment, separation and identiffication of short peptides from urine samples in order to tackle the main issues related to the analysis of these compounds. First, an enrichment strategy based on graphitized carbon black tested and developed on a mixture of analytical standard peptides which was representative of the naturally occurring peptides in body fluids. Ultra high performance liquid chromatography separation was carried out using two orthogonal chromatographic strategies, namely reversed phase (RP) C18 and Zic-HILIC columns, in order to maximize the number of identified peptides. A suspect screening approach was chosen for high resolution MS coupling.[3] In particular, a database of all the amino acid combinations for short peptides was compiled and MS/MS fragmentation was only performed on precursor ions matching with those in the database, resulting in a significant boost in sensitivity. Finally, MS/MS spectra were manually matched to spectra generated in silico to confirm the identity and the correct amino acid sequence. The method will be applied to the investigation of short endogenous peptides in human urine from healthy individuals. After the optimization of the methodology,for assessing a specific pathology, eligible participants, including pathological patients will be collected to discover possible new biomarkers related to a specific pathology.
Despite potential of short peptides as biomarkers, their diagnostic and prognostic value is not well characterized as they are generally under investigated due to lack of dedicated analytical workflows.
Although peptidomic studies offer a promising strategy for the discovery of novel cancer biomarkers, they have a number of limitations. LMW proteins are present at relatively low abundance. Also, there is potential for LMW peptides to associate with highly abundant proteins which would inevitably result in a loss of information. Furthermore, a loss of information can occur due to the tendency of highly abundant proteins to suppress the signal of low abundant peptides. This masking effect can be overcome through the enrichment for LMW peptides during sample preparation. Identification of endogenous peptides during analysis is also more complex as the site of enzymatic digestion cannot be specified. Thus, the criteria for peptide identification have to be more stringent than those for proteomic identification.
The advance of this research compared to the recent literature will be in the development of an analytical methodology able to overcome the major drawbacks in analysis of short endogenous peptides. In particular, the three major challenges related to the analysis of short peptides will be overcome by the use of specific and innovative enrichment systems as well as of chromatographic columns. Moreover, an automatized database for the identification of di, tri and tetrapeptides will be built in order to have a comprhensive identification of these compounds. The analytical methodologies will allow to identify a very high number of short peptides useful for further application to the diagnostic field in order to discovery possible biomarker for urinary pathology. Up to date, only medium size peptides have been studied as possible biomarker, therefore the study of short peptides will be a progress in the biomarker discovery.