No abstract

Marine plastic debris is a growing concern that has captured the general public’s attention. While the negative impacts of plastic debris on oceanic macrobiota, including mammals and birds, are well documented, little is known about its influence on smaller marine residents, including microbes that have key roles in ocean biogeochemistry. Our work provides a new perspective on microbial communities inhabiting microplastics that includes its effect on microbial biogeochemical activities and a description of the cross-domain communities inhabiting plastic particles. This study is among the first molecular ecology, plastic debris biota surveys in the North Pacific Subtropical Gyre. It has identified fundamental differences in the functional potential and taxonomic composition of plastic-associated microbes versus planktonic microbes found in the surrounding open-ocean habitat.

We evaluate the substantial amount of information accumulated on bacterial diversity in a variety of environments and address several fundamental questions, focusing on aquatic systems but including other environments to provide a broader context. Bacterial diversity data were extracted from 225 16S rDNA libraries described in published reports, representing a variety of aquatic and non-aquatic environments. Libraries were predominantly composed of rare phylotypes that appeared only once or twice in the library, and the number of phylotypes observed was correlated with library size (implying that few libraries are exhaustive samples of diversity in the source community). Coverage, the estimated proportion of phylotypes in the environment represented in the library, ranged widely but on average was remarkably high and not correlated with library size. Phylotype richness was calculated by methods based on the frequency of occurrence of different phylotypes in 194 libraries that provided appropriate data. For 90% of aquatic-system libraries, and for 79% of non-aquatic libraries, the estimated phylotype richness was 6 200 phylotypes. Nearly all of the larger estimates were in aquatic sediments, digestive systems and soils. However, the approaches used to estimate phylotype richness may yield underestimates when libraries are too small. A procedure is described to provide an objective means of determining when a library is large enough to provide a stable and unbiased estimate of phylotype richness. A total of 56 libraries, including 44 from aquatic systems, were considered 'large enough' to yield stable estimates suitable for comparing richness among environments. Few significant differences in phylotype richness were observed among aquatic environments. For one of two richness estimators, the average phylotype richness was significantly lower in hyperthermal environments than in sediment and bacterioplankton, but no other significant differences among aquatic environments were observed. In general, and with demonstrated exceptions, published studies have captured a large fraction of bacterial diversity in aquatic systems. In most cases, the estimated bacterial diversity is lower than we would have expected, although many estimates should be considered minimum values. We suggest that on local scales, aquatic bacterial diversity is much less than any predictions of their global diversity, and remains a tractable subject for study. The global-scale diversity of aquatic Bacteria, on the other hand, may be beyond present capabilities for effective study.

The phylogenetic diversity of a continental-shelf picoplankton community was examined by analyzing 16s ribosomal RNA (rRNA) genes amplified from environmental DNA with bacterial-specific primers and the polymerase chain reaction (PCR). Picoplankton populations collected from the pycnocline (10 m) over the eastern continental shelf of the United States near Cape Hatteras, North Carolina, served as the source of bulk nucleic acids used in this study. A large proportion of the 169 rDNA clones recovered (33%) were related to plastid 16s r-RNA genes, including plastids from both chromophyte and chlorophyte algae. Most bacterial gene clones (75% of bacterial clones, 50% of the total) were closely related to r-RNA gene lineages that had been discovered previously in clone libraries from opcnocean marine habitats, including the SARI36 cluster (y-Proteobacteria), SAR83, SARll, and SAR116 clusters (all a-Proteobacteria), as well as the marine Gram-positive cluster (high G+C Gram-positive). Most of the remaining bacterial clones recovered were phylogenetically related to the y and /3 subclasses of the Proteobacteria, including an rDNA lineage within the type 1 methylotroph clade of the p subclass. The abundance of plastid rDNAs and the lack of cyanobacterial-related clones, as well as the presence of P-Proteobacteria, are features of this coastal picoplankton gene clone library that distinguish it from similar studies of oligotrophic open-ocean sites. Overall, however, these data indicate that a limited number of as yet uncultured bacterioplankton lineages, related to those previously observed in the open ocean, can account for most cells in this coastal marine bacterioplankton assemblage.

As a necessary step in the study of prokaryotic diversity using 16S rDNA libraries, authors should evaluate how well their libraries represent diversity in the source environment. Phylotype-richness estimates can be used to judge whether a library represents diversity sufficiently for its intended purpose. We have argued that richness estimates are most useful if libraries are first shown to be large enough to yield stable estimates. In this article, we (1) evaluate two potentially suitable, non-parametric richness estimators (S ACE and S Chao1 ), tested against model libraries and libraries drawn from natural prokaryotic communities; (2) evaluate whether stable richness estimates are also unbiased; and (3) examine characteristics of prokaryotic libraries that influence the usefulness of richness estimators. Richness estimates consistently reached a stable asymptotic value for libraries that sampled diversity exhaustively. Stable estimates appear to be unbiased or minimally biased estimates of phylotype richness. The S ACE estimator was often undefined, sometimes overestimated phylotype richness at intermediate sampling efforts, and sometimes stabilized at a larger library size than the S Chao1 estimator. The S Chao1 estimator appears well suited for estimating phylotype richness from prokaryotic 16S rDNA libraries. Libraries judged too small to yield a stable richness estimate typically had a highly uneven frequency distribution of phylotypes, with a preponderance of phylotypes that occurred only once in the library. Libraries considered large enough typically had a more even frequency distribution of phylotypes. A software tool is provided to aid others in assessing whether their libraries are large enough to yield stable phylotype-richness estimates. LIMNOLOGY and OCEANOGRAPHY: METHODScedure gave us greater confidence that the richness estimates and the comparisons based on them were valid.The assessment procedure we applied was rudimentary, and critically important questions remain unanswered. Stable phylotype-richness estimates are not necessarily unbiased estimates, and as Hughes et al. (2001) commented "To test for bias, one needs to know the true richness to compare against the sample estimates. As yet, this comparison is impossible for microbes, because no communities have been exhaustively sampled." Furthermore, the relationship of richness estimators to library size has been examined in several recent studies and by subsampling 16S rDNA libraries, and results have been mixed. Hughes et al. (2001) observed that in several large (128 to 284 clones) prokaryotic libraries, richness estimates based on S Chao1 first increased and then usually stabilized with increasing subsample size and were independent of sample size thereafter. However, S Chao1 estimates did not stabilize for bacteria in a high-productivity aquatic mesocosm, and S ACE did not yield stable estimates for any library. Hill et al. (2003) observed that S Chao1 estimates stabilized with one but not with a second large bacterial libra...

2594 designated SARW1 (Sargasso Sea water column no. 1), GBW1 and GBW2 (Georges Bank water columns no. 1 and 2, respectively), and GBSED1 (Georges Bank sediment no.

Nine strains of marine Proteobacteria were assayed for nucleic acid content during non-steady-state growth to assess whether a species-specific growth rate based on rRNA content is feasible for environmental samples. The large and small ribosomal subunits and genomic DNA were quantified using image analysis. It was found that the maximal intracellular concentration of 16S rRNA during batch growth for the bacteria averaged 155 fg+/-60 (S.D.) per cell for eight of the nine marine bacteria in the exponential phase (with the exception of one strain, Pac 218). The dilution/decay of 16S rRNA/cell was rapid with a return to pre-shift up values within 6-12 h for all strains except Vibrio fisherii. An overall relationship between the RNA:DNA ratio and the specific growth rate for non-steady-state growth for all bacterial strains was not observed as previously described for other Proteobacteria during steady-state growth. However, a predictable relationship between rRNA content and growth rate for many isolates during batch growth was observed. Furthermore, the rapid kinetics of intracellular rRNA levels indicates it will be feasible to assess whether specific bacteria are in steady state or non-steady state in the marine environment. If the condition of steady state is met for a specific Proteobacterial group in an environmental sample, it will be possible to estimate species-specific growth rates by measuring rRNA content.

Nanoplankton and picoplankton abundance and community grazing on picoplankton were deterrnined in surnmer and autumn at several stations in a productive coastal environment (Georges Bank. NW Atlantic Ocean) and in an oligotrophic oceanic ecosystem (Sargasso Sea). Ranges of heterotrophic nanoplankton (HNAN) abundance were 1.2 to 3.6 X 103 ceils rnl-' on Georges Bank, and 2.2 to 6.8 X 10' ceiis ml-' in the Sargasso Sea. Ranges of phototrophic nanoplankton (PNAN) abundance in these ecosystems were 1.9 to 6.0 X 103 and 1.3 to 4.7 X 102, respectively. Mixotrophic nanoplankton (MNAN), operationaiiy defined here as chloroplast-bearing nanoplankton that ingested fluorescent tracers, comprised an average of 12 to 17% of PNAN in surface waters in both environments during August and October. Mixotrophs at specific stations constituted as much as 38% of total PNAN abundance on Georges Bank and 30 % in the Sargasso Sea. Mixotrophs represented up to 39 % of the total phagotrophic nanoplankton abundance (MNAN/[MNAN + HNAN]). Community grazing impact was estimated from the disappearance of fluorescent prey surrogates (fluorescently labeled bacteria, FLB; cyanobacteria, FLC; and <3 pm algae, FLA). Absolute grazing rates (total picoplankton cells removed d-') on Georges Bank exceeded those in the Sargasso Sea due to the greater abundances of predators and prey. However, there was overlap in the specific grazing losses at the 2 sites (ranges = 0.08 to 0.38 d-' in the coastal ocean and 0.05 to 0.24 d-' in the oligotrophic ocean). Rates of bactenvory were in approximate balance with rates of bactenal production (3H-thymidine uptake), but production exceeded bacterivory on Georges Bank during the surnmer cruise. These data are among the first documenting the impact of grazing on picoplankton in these environments, and they are consistent with the prediction that nanoplanktonic protists are major predators of picoplankton. While the proportion of phototrophs that are phagotrophic was highly variable, our study indicates that algal mixotrophy is widespread in the marine environment, occurring in both coastal and oligotrophic sites, and should be considered quantitatively in microbial food web investigations.KEY WORDS: Nanoplankton/picoplankton interactions . Mixotrophy . Bacterivory . Herbivory Microbial food w e b . Flagellates . Cyanobacteria