Deciphering the Functioning of Microbial Communities: Shedding Light on the Critical Steps in Metaproteomics

Abstract

Unraveling the complex structure and functioning of microbial communities is essential to accurately predict the impact of perturbations and/or environmental changes. From all molecular tools available today to resolve the dynamics of microbial communities, metaproteomics stands out, allowing the establishment of phenotype-genotype linkages. Despite its rapid development, this technology has faced many technical challenges that still hamper its potential power. How to maximize the number of protein identification, improve quality of protein annotation, and provide reliable ecological interpretation are questions of immediate urgency. In our study, we used a robust metaproteomic workflow combining two protein fractionation approaches (gel-based versus gel-free) and four protein search databases derived from the same metagenome to analyze the same seawater sample. The resulting eight metaproteomes provided different outcomes in terms of (i) total protein numbers, (ii) taxonomic structures, and (iii) protein functions. The characterization and/or representativeness of numerous proteins from ecologically relevant taxa such as Pelagibacterales, Rhodobacterales, and Synechococcales, as well as crucial environmental processes, such as nutrient uptake, nitrogen assimilation, light harvesting, and oxidative stress response, were found to be particularly affected by the methodology. Our results provide clear evidences that the use of different protein search databases significantly alters the biological conclusions in both gel-free and gel-based approaches. Our findings emphasize the importance of diversifying the experimental workflow for a comprehensive metaproteomic study.

Keywords: bioinformatics; mass spectrometry; metagenomics; metaproteomics; microbial ecology.

FIGURE 1

Taxonomic and functional protein annotation. Comparison of the proportion of proteins for which a consensus annotation was found. Bars represent the percentage of annotated proteins versus the total identified proteins depending on methodology.

FIGURE 2

(A) Relative taxonomic composition at order level for each methodology. Values represent the proportion of proteins with identical taxonomy on total identified protein using TAX-DB, NAM-DB, AM-DB, or Comb-DB in both gel-free and gel-based approaches. The number of peptides detected for each protein was used as quantitative value. Taxa displaying a proportion <1% were gathered into “Other” category. (B) Venn diagrams showing the number of common and unique taxa identified at order level.

FIGURE 3

(A) Relative functional composition for each methodology. Values represent the proportion of proteins with identical functional name on total identified protein using TAX-DB, NAM-DB, AM-DB, or Comb-DB in both gel-free and gel-based approaches. The number of peptides detected for each protein was used as quantitative value. Protein isoforms and/or sub-units were grouped under the same function. Functions displaying a proportion <1% were gathered into “Other” category. (B) Venn diagrams showing the number of common and unique protein functions.

FIGURE 4

Heatmaps of the taxonomic (top clusters) and the functional (right clusters) linkages for each methodology. Proteins annotated at both order and functional levels were ranked according to the number of identified peptides. Protein isoforms and/or sub-unit were grouped under the same function. Clusters were determined using complete linkage hierarchical clustering and Euclidean distance metric.

FIGURE 5

Diversity and taxonomic distribution of proteins involved in nutrient transport, nitrogen assimilation, light harvesting, and oxidative stress response for each methodology. Horizontal and vertical bar charts correspond to the total number of peptides detected for a given function (y-axis) or order (x-axis) in all metaproteomes. Protein isoforms and/or sub-unit were grouped under the same function. The lack of symbol in colored boxes means that the protein was observed in both gel-free and gel-based approaches.