To determine the significance of differences between clonal libraries of environmental rRNA gene sequences, differences between homologous coverage curves, C X (D), and heterologous coverage curves, C XY (D), were calculated by a Cramér-von Mises-type statistic and compared by a Monte Carlo test procedure. This method successfully distinguished rRNA gene sequence libraries from soil and bioreactors and correctly failed to find differences between libraries of the same composition.The sequencing of 16S rRNA genes from clone libraries of DNAs from environmental samples has led to a wealth of information concerning prokaryotic diversity. However, in addition to methodological problems in producing libraries representative of the environmental sample (for a review, see reference 8), this approach is also limited by the difficulty in comparing libraries and determining if they are significantly different.This problem can be addressed quantitatively by application of the formula for coverage as described by Good (4). Let X be a collection of sequences, such as a library of 16S rRNA genes. Define the "homologous" coverage of X (or C X ) by a sample from X to be C X ϭ 1 Ϫ (N X /n), where N X is the number of unique sequences in the sample (i.e., sequences without a replicate) and n is the total number of sequences. In practice, the definition of N X depends upon the criteria used to define uniqueness. For instance, McCaig et al. (6) considered sequences without a homolog of Ն97% similarity to be unique. Other authors have used Ն99% sequence similarity as the criterion. In principle, uniqueness can be defined at any level of sequence similarity or evolutionary distance (D) and a "homologous coverage curve," or C X (D), can be generated by plotting C X versus D (Fig. 1). The coverage curve then describes how well the sample represents the entire library X at various levels of relatedness. Typically, coverage might be low at high levels of relatedness (low values of D), indicating that only a small fraction of the sequences representing unique species are, in fact, sampled. In contrast, coverage might be much higher at low levels of relatedness, indicating that representatives of most of the deep phylogenetic groups present in X are found in the sample.While C X is the "homologous coverage" of X by a sample of X, it is also possible to calculate a "heterologous coverage" of X (or C XY ) by a sample Y from another collection of sequences by the following formula: (D)] to be similar. Thus, a test for differences between these coverage curves is also a test for differences between X and Y. To determine if the coverage curves C X (D) and C XY (D) are significantly different, the distance between the two curves are first calculated by using the Cramér-von Mises test statistic (7):where D increases in increments of 0.01. If X ϭ Y, then ⌬C XY should not be significantly different than a ⌬C calculated after randomly shuffling sequences between the two samples, X and Y. Typically, the sequences are randomly shuffled a large number...

The massive influx of crude oil into the Gulf of Mexico during the Deepwater Horizon (DWH) disaster triggered dramatic microbial community shifts in surface oil slick and deep plume waters. Previous work had shown several taxa, notably DWH Oceanospirillales, Cycloclasticus and Colwellia, were found to be enriched in these waters based on their dominance in conventional clone and pyrosequencing libraries and were thought to have had a significant role in the degradation of the oil. However, this type of community analysis data failed to provide direct evidence on the functional properties, such as hydrocarbon degradation of organisms. Using DNA-based stable-isotope probing with uniformly 13 C-labelled hydrocarbons, we identified several aliphatic (Alcanivorax, Marinobacter)-and polycyclic aromatic hydrocarbon (Alteromonas, Cycloclasticus, Colwellia)-degrading bacteria. We also isolated several strains (Alcanivorax, Alteromonas, Cycloclasticus, Halomonas, Marinobacter and Pseudoalteromonas) with demonstrable hydrocarbon-degrading qualities from surface slick and plume water samples collected during the active phase of the spill. Some of these organisms accounted for the majority of sequence reads representing their respective taxa in a pyrosequencing data set constructed from the same and additional water column samples. Hitherto, Alcanivorax was not identified in any of the previous water column studies analysing the microbial response to the spill and we discuss its failure to respond to the oil. Collectively, our data provide unequivocal evidence on the hydrocarbondegrading qualities for some of the dominant taxa enriched in surface and plume waters during the DWH oil spill, and a more complete understanding of their role in the fate of the oil.

The microbial populations in no-till agricultural soil and casts of the earthworm Lumbricus rubellus were examined by culturing and molecular methods. Clone libraries of the 16S rRNA genes were prepared from DNA isolated directly from the soil and earthworm casts. Although no single phylum dominated the soil library of 95 clones, the largest numbers of clones were from Acidobacteria (14%), Cytophagales (13%), Chloroflexi (8%), and ␥-Proteobacteria (8%). While the cast clone library of 102 clones was similar to the soil library, the abundances of several taxa were different. Representatives of the Pseudomonas genus as well as the Actinobacteria and Firmicutes increased in number, and one group of unclassified organisms found in the soil library was absent in the cast library. Likewise, soil and cast archaeal 16S rRNA gene libraries were similar, although the abundances of some groups were different. Two hundred and thirty aerobic bacteria were also isolated on general heterotrophic media from casts, burrows, and soil. The cast isolates were both phenotypically and genotypically different from the soil isolates. The cast isolates were more likely to reduce nitrate, grow on acetate and Casamino Acids, and utilize fewer sugars than the soil isolates. On the basis of their ribotypes, the cast isolates were dominated by Aeromonas spp. (28%), which were not found in the soil isolates, and other ␥-Proteobacteria (49%). In contrast, the soil isolates were mostly Actinobacteria (53%), Firmicutes (16%), and ␥-Proteobacteria (19%). Isolates obtained from the sides of earthworm burrows were not different from the soil isolates. Diversity indices for the collections of isolates as well as rRNA gene libraries indicated that the species richness and evenness were decreased in the casts from their levels in the soil. These results were consistent with a model where a large portion of the microbial population in soil passes through the gastrointestinal tract of the earthworm unchanged while representatives of some phyla increase in abundance.

[ 13 C 6 ]salicylate, [U-13 C]naphthalene, and [U-13 C]phenanthrene were synthesized and separately added to slurry from a bench-scale, aerobic bioreactor used to treat soil contaminated with polycyclic aromatic hydrocarbons. Incubations were performed for either 2 days (salicylate, naphthalene) or 7 days (naphthalene, phenanthrene). Total DNA was extracted from the incubations, the "heavy" and "light" DNA were separated, and the bacterial populations associated with the heavy fractions were examined by denaturing gradient gel electrophoresis (DGGE) and 16S rRNA gene clone libraries. Unlabeled DNA from Escherichia coli K-12 was added to each sample as an internal indicator of separation efficiency. While E. coli was not detected in most analyses of heavy DNA, a low number of E. coli sequences was recovered in the clone libraries associated with the heavy DNA fraction of [ 13 C]phenanthrene incubations. The number of E. coli clones recovered proved useful in determining the relative amount of light DNA contamination of the heavy fraction in that sample. Salicylate-and naphthalene-degrading communities displayed similar DGGE profiles and their clone libraries were composed primarily of sequences belonging to the Pseudomonas and Ralstonia genera. In contrast, heavy DNA from the phenanthrene incubations displayed a markedly different DGGE profile and was composed primarily of sequences related to the Acidovorax genus. There was little difference in the DGGE profiles and types of sequences recovered from 2-and 7-day incubations with naphthalene, so secondary utilization of the 13 C during the incubation did not appear to be an issue in this experiment.

Uncultivated bacteria associated with the degradation of pyrene in a bioreactor treating soil contaminated with polycyclic aromatic hydrocarbons (PAH) were identified by DNA-based stable-isotope probing (SIP) and quantified by real-time quantitative PCR. Most of the 16S rRNA gene sequences recovered from (13)C-enriched DNA fractions clustered phylogenetically within three separate groups of beta- and gamma-Proteobacteria unassociated with described genera and were designated "Pyrene Groups 1, 2 and 3". One recovered sequence was associated with the Sphingomonas genus. Pyrene Groups 1 and 3 were present in very low numbers in the bioreactor but represented 75% and 7%, respectively, of the sequences recovered from 16S rRNA gene clone libraries constructed from (13)C-enriched DNA. In a parallel time-course incubation with unlabelled pyrene, there was between a 2- and 4-order-of-magnitude increase in the abundance of 16S rRNA genes from Pyrene groups 1 and 3 and from targeted Sphingomonas spp. over a 10 day incubation. Sequences from Pyrene Group 2 were 11% of the SIP clone libraries but accounted for 14% of the total bacterial 16S rRNA genes in the bioreactor community. However, the abundance of this group did not increase significantly in response to pyrene disappearance. These data indicate that the primary pyrene degraders in the bioreactor were uncultivated, low-abundance beta- and gamma-Proteobacteria not previously associated with pyrene degradation.