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...

Prevalence, antibiotic susceptibility, and genetic diversity were determined for Escherichia coli O157:H7 isolated over 11 months from four beef cattle feedlots in southwest Kansas. From the fecal pat (17,050) and environmental (7,134) samples collected, 57 isolates of E. coli O157:H7 were identified by use of bacterial culture and latex agglutination (C/LA). PCR showed that 26 isolates were eaeA gene positive. Escherichia coli O157:H7 was identified in at least one of the four feedlots in 14 of the 16 collections by C/LA and in 9 of 16 collections by PCR, but consecutive positive collections at a single feedlot were rare. Overall prevalence in fecal pat samples was low (0.26% by C/LA, and 0.08% by PCR). No detectable differences in prevalence or antibiotic resistance were found between isolates collected from home pens and those from hospital pens, where antibiotic use is high. Resistant isolates were found for six of the eight antibiotics that could be used to treat E. coli infections in food animals, but few isolates were multidrug resistant. The high diversity of isolates as measured by random amplification of polymorphic DNA and other characteristics indicates that the majority of isolates were unique and did not persist at a feedlot, but probably originated from incoming cattle. The most surprising finding was the low frequency of virulence markers among E. coli isolates identified initially by C/LA as E. coli O157:H7. These results demonstrate that better ways of screening and confirming E. coli O157:H7 isolates are required for accurate determination of prevalence.

Stable isotope probing (SIP) has been used to track nutrient flows in microbial communities, but existing protein-based SIP methods capable of quantifying the degree of label incorporation into peptides and proteins have been demonstrated only by targeting usually less than 100 proteins per sample. Our method automatically (i) identifies the sequence of and (ii) quantifies the degree of heavy atom enrichment for thousands of proteins from microbial community proteome samples. These features make our method suitable for comparing isotopic differences between closely related protein sequences, and for detecting labeling patterns in low-abundance proteins or proteins derived from rare community members. The proteomic SIP method was validated using proteome samples of known stable isotope incorporation levels at 0.4%, ∼50%, and ∼98%. The method was then used to monitor incorporation of 15N into established and regrowing microbial biofilms. The results indicate organism-specific migration patterns from established communities into regrowing communities and provide insights into metabolism during biofilm formation. The proteomic SIP method can be extended to many systems to track fluxes of 13C or 15N in microbial communities.

Bacterial contamination is common in commercially available raw meat diets, suggesting that there is a risk of foodborne illness in dogs fed these diets as well possible risk for humans associated with the dogs or their environments.

S. enterica infections and environmental contamination were common at this facility. A portion of the Salmonella strains detected on the premises was likely introduced via raw meat that was the primary dietary constituent. Some strains appeared to be widely disseminated in the population. Feeding meat that had not been cooked properly, particularly meat classified as unfit for human consumption, likely contributed to the infections in these dogs.

Objective-To evaluate antimicrobial susceptibility of commensal Escherichia coli strains isolated from the feces of horses and investigate relationships with hospitalization and antimicrobial drug (AMD) administration. Design-Observational study. Animals-68 hospitalized horses that had been treated with AMDs for at least 3 days (HOSP-AMD group), 63 hospitalized horses that had not received AMDs for at least 4 days (HOSP-NOAMD group), and 85 healthy horses that had not been hospitalized or treated with AMDs (community group). Procedures-Fecal samples were submitted for bacterial culture, and up to 3 E coli colonies were recovered from each sample. Antimicrobial susceptibility of 724 isolates was evaluated. Prevalence of resistance was compared among groups by use of log-linear modeling. Results-For 12 of the 15 AMDs evaluated, prevalence of antimicrobial resistance differed significantly among groups, with prevalence being highest among isolates from the HOSP-AMD group and lowest among isolates from the community group. Isolates recovered from the HOSP-AMD and HOSP-NOAMD groups were also significantly more likely to be resistant to multiple AMDs. Resistance to sulfamethoxazole and resistance to trimethoprim-sulfamethoxazole were most common, followed by resistance to gentamicin and resistance to tetracycline. Use of a potentiated sulfonamide, aminoglycosides, cephalosporins, or metronidazole was positively associated with resistance to 1 or more AMDs, but use of penicillins was not associated with increased risk of resistance to AMDs. Conclusion and Clinical Relevance-Results suggest that both hospitalization and AMD administration were associated with prevalence of antimicrobial resistance among E coli strains isolated from the feces of horses.