BackgroundThe quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.ResultsWith our years of experience in manually curating genomes for the Joint Genome Institute, we developed a new gene prediction algorithm called Prodigal (PROkaryotic DYnamic programming Gene-finding ALgorithm). With Prodigal, we focused specifically on the three goals of improved gene structure prediction, improved translation initiation site recognition, and reduced false positives. We compared the results of Prodigal to existing gene-finding methods to demonstrate that it met each of these objectives.ConclusionWe built a fast, lightweight, open source gene prediction program called Prodigal http://compbio.ornl.gov/prodigal/. Prodigal achieved good results compared to existing methods, and we believe it will be a valuable asset to automated microbial annotation pipelines.

The Prodigal software is freely available under the General Public License from http://code.google.com/p/prodigal/.

Metagenomics has provided access to genomes of as yet uncultivated microorganisms in natural environments, yet there are gaps in our knowledge-particularly for Archaea-that occur at relatively low abundance and in extreme environments. Ultrasmall cells (<500 nm in diameter) from lineages without cultivated representatives that branch near the crenarchaeal/euryarchaeal divide have been detected in a variety of acidic ecosystems. We reconstructed composite, near-complete ∼1-Mb genomes for three lineages, referred to as ARMAN (archaeal Richmond Mine acidophilic nanoorganisms), from environmental samples and a biofilm filtrate. Genes of two lineages are among the smallest yet described, enabling a 10% higher coding density than found genomes of the same size, and there are noncontiguous genes. No biological function could be inferred for up to 45% of genes and no more than 63% of the predicted proteins could be assigned to a revised set of archaeal clusters of orthologous groups. Some core metabolic genes are more common in Crenarchaeota than Euryarchaeota, up to 21% of genes have the highest sequence identity to bacterial genes, and 12 belong to clusters of orthologous groups that were previously exclusive to bacteria. A small subset of 3D cryo-electron tomographic reconstructions clearly show penetration of the ARMAN cell wall and cytoplasmic membranes by protuberances extended from cells of the archaeal order Thermoplasmatales. Interspecies interactions, the presence of a unique internal tubular organelle [Comolli, et al. (2009) (1)]. Many datasets provide fragmentary glimpses into genetic diversity (2-4) and a few have reported near-complete genomic sequences for uncultivated organisms (5-8). In most cases where extensive reconstruction has been possible, insights have been restricted to relatively dominant members. Furthermore, it has been difficult to use genomic information to infer the nature of interorganism interactions, although these are likely to be very important aspects of microbial community functioning. The need for topological and organizational information to place genomic data in context motivates the combination of cultivation-independent genomics and 3D cryogenic transmission electron microscope-based ultrastructural analyses of microbial communities.Despite the importance of cellular interactions (symbiosis and parasitism), most of what we know about microorganismal associations is from cultivation-based studies (9-11). However, sequencing of the genomes of several endosymbiotic and parasitic Bacteria has revealed reduction in gene and genome sizes, reflecting evolved dependence of the endosymbiont or parasite on its host (12, 13). The ultrasmall archaeal parasite Nanoarchaeum equitans has only 552 genes and requires a connection to its archaeal host, Ignicoccus hopstialis, to survive (10). Recently, it was shown that this interaction involves contact between outer membranes (14). Given the vast diversity of microbial life (15), it is likely that other unusual relationships critical to surviva...