Stable-Isotope Probing Identifies Uncultured Planctomycetes as Primary Degraders of a Complex Heteropolysaccharide in Soil.

The exopolysaccharides (EPSs) produced by some bacteria are potential growth substrates for other bacteria in soil. We used stable-isotope probing (SIP) to identify aerobic soil bacteria that assimilated the cellulose produced by Gluconacetobacter xylinus or the EPS produced by Beijerinckia indica. The latter is a heteropolysaccharide comprised primarily of l-guluronic acid, d-glucose, and d-glycero-d-mannoheptose. (13)C-labeled EPS and (13)C-labeled cellulose were purified from bacterial cultures grown on [(13)C]glucose. Two soils were incubated with these substrates, and bacteria actively assimilating them were identified via pyrosequencing of 16S rRNA genes recovered from (13)C-labeled DNA. Cellulose C was assimilated primarily by soil bacteria closely related (93 to 100% 16S rRNA gene sequence identities) to known cellulose-degrading bacteria. However, B. indica EPS was assimilated primarily by bacteria with low identities (80 to 95%) to known species, particularly by different members of the phylum Planctomycetes. In one incubation, members of the Planctomycetes made up >60% of all reads in the labeled DNA and were only distantly related (<85% identity) to any described species. Although it is impossible with SIP to completely distinguish primary polysaccharide hydrolyzers from bacteria growing on produced oligo- or monosaccharides, the predominance of Planctomycetes suggested that they were primary degraders of EPS. Other bacteria assimilating B. indica EPS included members of the Verrucomicrobia, candidate division OD1, and the Armatimonadetes. The results indicate that some uncultured bacteria in soils may be adapted to using complex heteropolysaccharides for growth and suggest that the use of these substrates may provide a means for culturing new species.

Assessing species biomass contributions in microbial communities via metaproteomics.

Microbial community structure can be analyzed by quantifying cell numbers or by quantifying biomass for individual populations. Methods for quantifying cell numbers are already available (e.g., fluorescence in situ hybridization, 16-S rRNA gene amplicon sequencing), yet high-throughput methods for assessing community structure in terms of biomass are lacking. Here we present metaproteomics-based methods for assessing microbial community structure using protein abundance as a measure for biomass contributions of individual populations. We optimize the accuracy and sensitivity of the method using artificially assembled microbial communities and show that it is less prone to some of the biases found in sequencing-based methods. We apply the method to communities from two different environments, microbial mats from two alkaline soda lakes, and saliva from multiple individuals. We show that assessment of species biomass contributions adds an important dimension to the analysis of microbial community structure.