Retrobiosynthetic NMR studies with 13C-labeled glucose. Formation of gallic acid in plants and fungi.

The biosynthesis of gallic acid was studied in cultures of the fungus Phycomyces blakesleeanus and in leaves of the tree Rhus typhina. Fungal cultures were grown with [1-13C]glucose or with a mixture of unlabeled glucose and [U-13C6]glucose. Young leaves of R. typhina were kept in an incubation chamber and were supplied with a solution containing a mixture of unlabeled glucose and [U-13C6]glucose via the leaf stem. Isotope distributions in isolated gallic acid and aromatic amino acids were analyzed by one-dimensional 1H and 13C NMR spectroscopy. A quantitative analysis of the complex isotopomer composition of metabolites was obtained by deconvolution of the 13C13C coupling multiplets using numerical simulation methods. This approach required the accurate analysis of heavy isotope chemical shift effects in a variety of different isotopomers and the analysis of long range 13C13C coupling constants. The resulting isotopomer patterns were interpreted using a retrobiosynthetic approach based on a comparison between the isotopomer patterns of gallic acid and tyrosine. The data show that both in the fungus and in the plant all carbon atoms of gallic acid are biosynthetically equivalent to carbon atoms of shikimate. Notably, the carboxylic group of gallic acid is derived from the carboxylic group of an early intermediate of the shikimate pathway and not from the side chain of phenylalanine or tyrosine. It follows that the committed precursor of gallic acid is an intermediate of the shikimate pathway prior to prephenate or arogenate, most probably 5-dehydroshikimate. A formation of gallic acid via phenylalanine, the lignin precursor, caffeic acid, or 3,4, 5-trihydroxycinnamic acid can be ruled out as major pathways in the fungus and in young leaves of R. typhina. The incorporation of uniformly 13C-labeled glucose followed by quantitative NMR analysis of isotopomer patterns is suggested as a general method for biosynthetic studies. As shown by the plant experiment, this approach is also applicable to systems with low incorporation rates.