Synthetic statistical approach reveals a high degree of richness of microbial eukaryotes in an anoxic water column

Abstract

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.

FIG. 1.

Inverse Gaussian-mixed Poisson and mixture-of-two-geometrics frequency count distributions fitted to 97% OTU data. The inverse Gaussian-mixed Poisson distribution was calculated as follows: (1) where j = 0, 1, and so forth, t₁ = 0.3431, and t₂ = 0.7959. The mixture-of-two-geometrics distribution was calculated as follows: (2) where j = 0, 1, and so forth, t₁ = 0.3672, t₂ = 7.2341, and t₃ = 0.8220. (A) Frequency count distribution fitted to frequency data. (B) Fitted frequency count distribution extended to zero.

FIG. 2.

Mixture-of-two-exponentials (geometrics) model fitted to full (τ = 133) and partial (τ = 31) OTU data, with difference between curves (OTU defined as rRNA gene sequence clusters at a cutoff level of 99% sequence similarity). The abscissa is truncated at 31.