Non-random assembly of bacterioplankton communities in the subtropical north pacific ocean

Abstract

The exploration of bacterial diversity in the global ocean has revealed new taxa and previously unrecognized metabolic potential; however, our understanding of what regulates this diversity is limited. Using terminal restriction fragment length polymorphism (T-RFLP) data from bacterial small-subunit ribosomal RNA genes we show that, independent of depth and time, a large fraction of bacterioplankton co-occurrence patterns are non-random in the oligotrophic North Pacific subtropical gyre (NPSG). Pair-wise correlations of all identified operational taxonomic units (OTUs) revealed a high degree of significance, with 6.6% of the pair-wise co-occurrences being negatively correlated and 20.7% of them being positive. The most abundant OTUs, putatively identified as Prochlorococcus, SAR11, and SAR116 bacteria, were among the most correlated OTUs. As expected, bacterial community composition lacked statistically significant patterns of seasonality in the mostly stratified water column except in a few depth horizons of the sunlit surface waters, with higher frequency variations in community structure apparently related to populations associated with the deep chlorophyll maximum. Communities were structured vertically into epipelagic, mesopelagic, and bathypelagic populations. Permutation-based statistical analyses of T-RFLP data and their corresponding metadata revealed a broad range of putative environmental drivers controlling bacterioplankton community composition in the NPSG, including concentrations of inorganic nutrients and phytoplankton pigments. Together, our results suggest that deterministic forces such as environmental filtering and interactions among taxa determine bacterioplankton community patterns, and consequently affect ecosystem functions in the NPSG.

Keywords: 16S rRNA gene; assembly; community; gyre; oligotrophic; time series.

Figure 1

(A) Spearman’s rank correlation coefficients (ρs) from pair-wise correlations of all OTU pairs (n = 78,607), plotted as a frequency histogram using 0.01 intervals. Significant correlations (p < 0.05) are indicated in black. Monte Carlo simulations were used to test if the observed histogram was different from random. Following a permutation procedure where OTUs were randomized within sites, a total of 1000 randomized matrices were created, and pair-wise correlations were performed on each matrix. The maximum and minimum numbers of correlations within each 0.01 interval (from 1 to −1) were determined from all 1000 randomized matrices (hismax and hismin; black lines). (B) Plot of the average relative abundance of each OTU, determined via T-RFLP, against the number of significant pair-wise correlations to other OTUs. Putative identities are indicated for the most abundant OTUs. The dashed line indicates the median number of significant pair-wise correlations.

Figure 2

(A) Depth-specific distribution of oxygen and chlorophyll a concentrations from HOT cruises 165–200 (November 2004 to February 2008). (B) Standardized effective size of C-score (SEScscore), average Bray–Curtis similarity from all pariwise comparisons within a single depth, and Gini coefficients from depth-specific communities. Average Bray–Curtis similarity and Gini coefficients were calculated from T-RFLP-based community structure profiles pooled by depth. SESscore was calculated by adapting the procedure proposed by Gotelli and McCabe (2002), using all time points for a specific depth.

Figure 3

Non-metric multidimensional scaling (NMS) of bacterial community structure based on a T-RFLP analysis of bacterial SSU rRNA genes amplified from bacterioplankton samples collected approximately monthly at Station ALOHA from November 2004 to February 2008 (n = 296; stress-value = 12.1).

Figure 4

Spearman’s rank correlation coefficients (ρs) between depth and the relative abundance of individual OTUs, determined by T-RFLP (number of OTUs = 397), plotted in a frequency histogram using 0.01 intervals. Significant correlations (p < 0.05) are indicated in black. ρs Values indicate the strength of the relationship, with positive values indicating an increase in the relative contribution of an OTU with depth and negative values indicating a decrease.