Selective hydroxylation of fatty acids offers many opportunities for generating a wide range of pharmaceuticals, flavours, and fragrances from the limited starting materials that are available from biomass . For instance, hydroxylation at each of the 19 C-H bonds in the highly abundant starting material, decanoic acid, would provide 17 unique products that can only be accessed by kinetic control over reaction conditions . The challenge is to find catalysts that can distinguish chemically similar positions so as to selectively modify each of these C-H bonds. Biocatalytic methods offer the potential for exquisite control over the position of hydroxylation, but despite considerable efforts, only a limited number of effective biocatalysts for selective fatty acid hydroxylation have been identified to date. Most of these biocatalysts are from the superfamily of cytochrome P450 monooxygenases (P450s, CYP family) and have been largely limited to terminal or subterminal hydroxylases (Fig. ) . Many different P450 families hydroxylate fatty acids , e.g., CYP2 4 , CYP4 2 , CYP52A 5 , CYP102 , CYP116 9 , CYP147G 10 , CYP152A , and CYP153A . Despite the potential of these enzymes for use in organic synthesis, difficulties with recombinant, heterologous expression, and low stability have limited their implementation. In addition, the identification and development of new biocatalysts is time-consuming; intensive screening of large numbers of natural and synthetic sequences is typically needed to identify a very small number of viable biocatalysts. Efforts to identify novel P450 biocatalysts from metagenomic databases have yielded very few P450s that are capable of selective mid-chain hydroxylation , although much of the metagenomic sequence space remains unstudied, identifying forms that have the necessary specificity and kinetic selectivity is challenging. Directed evolution and rational protein design has improved the activity and selectivity of some terminal fatty acid hydroxylases, e.g., CYP102A1 (P450-BM3) and altered the regioselectivity of others, e.g., CYP152A (P450-Bsβ) , but engineering P450s, like metagenome mining, is timeconsuming, and both labour-and resource-intensive, due to the need to screen large numbers of potential biocatalysts to identify one with the desired properties.