Discovery of phosphonic acid natural products by mining the genomes of 10,000 actinomycetes.

Although natural products have been a particularly rich source of human medicines, activity-based screening results in a very high rate of rediscovery of known molecules. Based on the large number of natural product biosynthetic genes in microbial genomes, many have proposed "genome mining" as an alternative approach for discovery efforts; however, this idea has yet to be performed experimentally on a large scale. Here, we demonstrate the feasibility of large-scale, high-throughput genome mining by screening a collection of over 10,000 actinomycetes for the genetic potential to make phosphonic acids, a class of natural products with diverse and useful bioactivities. Genome sequencing identified a diverse collection of phosphonate biosynthetic gene clusters within 278 strains. These clusters were classified into 64 distinct groups, of which 55 are likely to direct the synthesis of unknown compounds. Characterization of strains within five of these groups resulted in the discovery of a new archetypical pathway for phosphonate biosynthesis, the first (to our knowledge) dedicated pathway for H-phosphinates, and 11 previously undescribed phosphonic acid natural products. Among these compounds are argolaphos, a broad-spectrum antibacterial phosphonopeptide composed of aminomethylphosphonate in peptide linkage to a rare amino acid N(5)-hydroxyarginine; valinophos, an N-acetyl l-Val ester of 2,3-dihydroxypropylphosphonate; and phosphonocystoximate, an unusual thiohydroximate-containing molecule representing a new chemotype of sulfur-containing phosphonate natural products. Analysis of the genome sequences from the remaining strains suggests that the majority of the phosphonate biosynthetic repertoire of Actinobacteria has been captured at the gene level. This dereplicated strain collection now provides a reservoir of numerous, as yet undiscovered, phosphonate natural products.

Use of Foodborne Disease Data for HACCP Risk Assessment.

Methodological limitations in the way foodborne disease data are analyzed and reported nationally make it difficult to use it for Hazard Analysis Critical Control Point (HACCP) risk assessment. This warranted the creation of a new system of classification and analysis. Foodborne disease data from reported outbreaks in New York State (NYS) between the years 1980-1991 (1,528 outbreaks involving 31,675 cases) were reviewed to develop two new categories by which foodborne disease vehicles were classified: Method of Preparation and Significant Ingredient. In addition, the current Centers for Disease Control and Prevention (CDC) list of contributing factors was expanded to more accurately reflect common problems encountered in these outbreaks. Data grouped by this method can be more readily used for the hazard analysis, identification of Critical Control Points (CCPs) and establish critical limits steps of the HACCP system. By identifying these features in a system that closely relates to the food preparation practices, corrective action can be taken to reduce or eliminate the occurrence of illness from that particular food. Two dimensional tables of these new data show trends in preparation methods, ingredients and contributing factors that can be used for risk assessment of establishments and their menus. A more detailed table shows agents of concern and likely CCPs associated with specific ingredients for each method of preparation that more accurately links foodborne disease data with HACCP. The presented data illustrates how this new method of analysis can be used to perform HACCP risk assessment. Increased support of foodborne disease surveillance would provide the data needed to make this new system a valuable tool for use in HACCP risk assessment.