Metabolite profiles in non-invasive samples, such as seminal fluid (SF), provide an ideal medium to improve diagnosis and understanding pathogenesis of genitourinary disease. This biofluid is known to exhibit extreme time-dependent metabolite changes (hydrolysis) due to endogenous enzyme action. In our goal to craft an approach to allow home-based sample collection, use of tartrate, a known competitive inhibitor of the primary enzyme (prostatic acid phosphatase), was considered.
We investigated the effect of tartrate and sample temperature on metabolites in SF from 3 volunteers of varying ages and ethnic origins. 1D NOESY spectra were acquired every 3 minutes for 18 hours at both 500 and 900 MHz, with experimental repetition and variation performed to test the effect of tartrate (10 mM) and temperature variation (277K; 298K). 2D spectra were also obtained to assist metabolite identification. Spectral alignment (icoshift) and data reduction (using standard and optimized bucketing methods) were performed prior to multivariate statistical analysis. Principal components analysis, partial least squares and orthogonal projections to latent structures were used to investigate metabolite correlation for different clinical variables.
Initial analysis confirmed previously known time-dependent changes in SF metabolites. Addition of 10 mM tartrate reduced the half-life time of metabolite hydrolysis from 171 mins to over 942 mins at 298K. When the temperature was reduced to 277K, the observed reaction was further slowed, so that less than 5% degradation was present after 500 mins. We will present more detailed findings, including metabolites most affected for any given time period.Our results suggest that the combination of tartrate and sample cooling will provide adequate SF enzyme retardation to allow consistent metabolite levels and more reliable insight into pathologic processes. Furthermore, the use of tartrate doubles as a concentration standard to allow for more accurate metabolite quantification to facilitate further, advanced analysis methods.