Diatom-derived carbohydrates as factors affecting bacterial community composition in estuarine sediments

Abstract

Microphytobenthic biofilms in estuaries, dominated by epipelic diatoms, are sites of high primary productivity. These diatoms exude large quantities of extracellular polymeric substances (EPS) comprising polysaccharides and glycoproteins, providing a substantial pool of organic carbon available to heterotrophs within the sediment. In this study, sediment slurry microcosms were enriched with either colloidal carbohydrates or colloidal EPS (cEPS) or left unamended. Over 10 days, the fate of these carbohydrates and changes in beta-glucosidase activity were monitored. Terminal restriction fragment length polymorphism (T-RFLP), DNA sequencing, and quantitative PCR (Q-PCR) analysis of 16S rRNA sequences were used to determine whether sediment bacterial communities exhibited compositional shifts in response to the different available carbon sources. Initial heterotrophic activity led to reductions in carbohydrate concentrations in all three microcosms from day 0 to day 2, with some increases in beta-glucosidase activity. During this period, treatment-specific shifts in bacterial community composition were not observed. However, by days 4 and 10, the bacterial community in the cEPS-enriched sediment diverged from those in colloid-enriched and unamended sediments, with Q-PCR analysis showing elevated bacterial numbers in the cEPS-enriched sediment at day 4. Community shifts were attributed to changes in cEPS concentrations and increased beta-glucosidase activity. T-RFLP and sequencing analyses suggested that this shift was not due to a total community response but rather to large increases in the relative abundance of members of the gamma-proteobacteria, particularly Acinetobacter-related bacteria. These experiments suggest that taxon- and substrate-specific responses within the bacterial community are involved in the degradation of diatom-derived extracellular carbohydrates.

FIG. 1.

Changes in mean concentrations (± the standard error) of LMW carbohydrate and cEPS (colloidal EPS)-carbohydrate extracts in sediment slurry microcosm experiments. (A) Control slurries, (B) colloidal enrichments, and (C) cEPS enrichments over a 10-day time course; (D and E) control (D) and poisoned (E) slurries over a 4-day time course; (F) β-glucosidase activity in control and poisoned slurries.

FIG. 2.

Relationship between concentration of HB carbohydrates and the MUF substrate release rate due to β-glucosidase activity. (A to C) Colloidal enrichments (A), cEPS enrichments (B), and MUF release rate (n = 20) and cEPS gain/loss in all treatments (n = 20 per each treatment) (C). Microcosms were sampled at days 0, 2, 4, and 10 (day 0 [D0], D2, D4, and D10, respectively). The results of product-moment correlation analyses are shown (*, P < 0.05; ***, P < 0.001).

FIG. 3.

T-RFLP fingerprints of the total bacterial communities in sediment slurry microcosms. AluI digestion of PCR amplified 16S rRNA genes (5′ T-RFs, black lines, 3′ T-RFs, gray lines). Microcosms: S, no-enrichment sediment control; C, colloidal enrichment; E, cEPS enrichment sediments sampled at days 0 (D0) and 4. T-RFs that are important contributors toward the separation of the three communities at day 4 are indicated (see also Table 2).

FIG. 4.

MDS plots showing changes in the composition of the total and active bacterial communities in sediment slurry microcosms as determined from a Bray-Curtis similarity matrix with data from AluI and CfoI T-RFLP profiles. (A and B) Total community (PCR-amplified 16S rRNA genes) (A) and active community (RT-PCR-amplified 16S rRNA) (B). Microcosms as indicated, sampled at days 0, 2, 4, and 10; n = 3 for each sediment at each time point. Clusters are indicated with Roman numerals.

FIG. 5.

Neighbor-joining tree of cloned RT-PCR-amplified 16S rRNA sequences from sediment microcosms at day 4. Clone designations: C, colloidal-; E, cEPS-enriched sediments. Scale bar indicates the genetic distance between sequences. Percent bootstrap values (1,000 replicates) are indicated.

FIG. 6.

Variation in 16S rRNA gene numbers g of sediment⁻¹ in slurry microcosms as assessed by Q-PCR. Microcosms: S, no-enrichment sediment control; C, colloidal enrichment; E, cEPS enrichment sampled at days 0, 2, 4, and 10. Gene numbers were derived from a standard curve with r² = 0.995, a y intercept of 39.63%, PCR efficiency (E) of 106%, and a no-template control C_T value of 33.73 ± 1.26.

FIG. 7.

Identification of biochemical variables that were most significant in determining the clustering of total (A) and active (B) bacterial community compositions in sediment microcosms, as determined by BIO-ENV analysis. Principle components analysis show clustering (indicated by Roman numerals) based on biochemical variables in microcosms at days 0, 2, 4, and 10. Vectors indicate biochemical variables important in clustering. Euclidean distances are shown.