Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

Abstract

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Figure 1

Overview of a protein-SIP experiment studying the carbon flux between heterotrophic (Acidiphilum cryptum) and autotrophic (Acidithiobacillus ferrooxidans) organisms over four sampling points (t1–t4) (Kermer et al., 2012). Labeled galactose is metabolized by A. cryptum to labeled CO₂. In early time points, only a low amount of labeled CO₂ is present and is fixed by the autotrophic strain, leading to a low RIA. In later time points, the metabolic activity of A. cryptum resulted in a strong increase in ¹³CO₂, leading to a higher RIA in A. ferrooxidans. The ¹³C-flux was reconstructed by the changes of the isotopologue patterns (color code, see sampling bar in the figure). Representative mass spectra showing the peptide ion mass distribution of peptide AGGLPAVIGELIR of dihydroxy-acid dehydratase (A. cryptum, gi148259108) and peptide AFDGSSIAGWK of glutamine synthetase, type I (A. ferrooxidans, gi198282766).

Figure 2

Data evaluation of a protein-SIP experiment to detect the carbon flux in an anaerobic benzene-degrading community (Taubert et al., 2012). (a) Protein grouping based on RIA vs LR to define metabolic groups of bacterial organisms obtained by ¹³C benzene metabolisation. Colored data points indicate different metabolic groups: group 1, Clostridiales (orange dots); group 2, Deltaproteobacteria (blue triangles); group 3, Bacteroidetes (green squares). Arrows indicate the chronological development between the RIA and LR. A low variability of the RIA and a strong increase in LR (as shown for group 1) indicates a direct metabolisation of the ¹³C-labeled substrate and a high growth rate. A stronger change of RIA over time indicates an indirect metabolisation (like shown for group 2 and 3). (b) Model of the carbon flux with the bacterial community based on data of the protein-SIP experiment using ¹³C-labeled benzene and ¹³C-labeled carbonate.

Figure 3

Integration of protein-SIP in the toolbox of microbial ecology and the combination of OMICS to reconstruct metabolic networks.