Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract

Background: Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium.

Results: Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments.

Conclusions: This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

Keywords: Defined community; Metaproteomics; Microbial consortia; PTMs; Reductionist approach; Rhizospheric microbiome.

Fig. 1

Schematic diagram of study design. Microbial members were selected based on phyla level abundance and tax diversity from natural P. deltoides (Pd) rhizosphere communities. These members were inoculated together and diluted 1:10 after 48 hours for 15 passages. Samples were analyzed by high-resolution metaproteomics to understand the community size and structure, molecular mechanisms underpinning microbial behavior and functions, and post-translational regulations. Created with BioRender.com

Fig. 2

Assessment of microbial population size. (A) Microbial community composition from cell pellets using metaproteomics was estimated by total protein count for each community passaged in defined media MOPS + glucose (MOPS) or complex (R2A) media. There was a total of 15 passages per medium and 3 biological replicates per passage. Individual colors in the stacked bar charts represent each microbial member. (B) Cellular estimates of organism relative abundance plotted against extracellular estimates of organism abundance for each passage for MOPS (black circles) and R2A (red circles). Each circle represents the averaged abundance across replicates for a single passage. Proteome depth (number of proteins identified) is plotted for each microbe per sample measured in the defined microbial community passaged across (C) defined MOPS + glucose (black) and (D) complex R2A (red) media

Fig. 3

Metaproteomics analysis of Pseudomonas sp. GM17 functional behavior during community assembly. (A) Overlap of proteins identified between both media. Each node represents a unique protein accession, and the color indicates whether the relative protein abundance changed significantly based on ANOVA in one (yellow) or both media (red) or not significant in either (grey). Figure generated using DiVenn 2.0. (B) Relative protein abundance for the GacS sensor histidine kinase and the GacA response regulator in MOPS (black) or R2A media (red). Error bars represent standard error for each set of biological triplicates. (C) Heatmap (one-way clustering using ward method) illustration for 18 antibiotic and secondary metabolite gene clusters predicted by antiSMASH v5.0. Color gradient represents the percentage of proteins identified for a given gene cluster. (D). Heatmap (one-way clustering using ward method) illustration of relative protein abundances for proteins encoded by the 18 antibiotic and secondary metabolite gene clusters. Color gradient represents a standardized score calculated per protein and white represents proteins that were not quantified in a particular medium

Fig. 4

Metaproteomics analysis of Pantoea sp. YR343 functional behavior during community assembly. (A) Relative abundance of Pantoea organism abundance in MOPS and R2A media based on metaproteomics data. (B) Relative abundance across R2A passages for geranylgeranyl pyrophosphate synthase and phytoene desaturase, two key proteins involve in carotenoid biosynthesis. Error bars represent standard error for each set of biological triplicates. The dashed arrow in the flow diagram represents multiple steps in biosynthesis. (C) Heatmap of relative protein abundance for proteins involved in aerobic/anaerobic respiration and motility. (D) Relative abundances for proteins associated with defense responses to antagonist behaviors. Error bars represent standard error for each set of biological triplicates

Fig. 5

Metaproteomics analysis of Bacillus sp. BC15 functional behavior during community assembly. (A) Developmental stages of sporulation in Bacillus sp BC15. Under environmental stress or nutrient limited condition, Bacillus undergoes endospore formation which is accomplished across multiple stages of morphogenesis. Relative abundance of the proteins identified (B) across all stages and (C) free spores. Abundance shown are the average of three biological replicates. The color gradient represents the abundance in Log2 scale. (D)Proteome-wide relative abundance distribution of spore-related proteins compared to all other proteins. (E) The pie chart shows the enriched biological processes (p-value<0.05) of “all other” proteins. Gene ontology enrichment analysis was done using ClueGO

Fig. 6

Dynamic regulation of methylation modification in lysine (K) residue of EF-Tu in nutrient-deprived organisms. Percentage abundances of K-methylated modified and unmodified peptides in the Elongation factor Tu proteins of (A) Pantoea sp. YR343 and (B) Rhizobium sp. CF142 in R2A media. (C) Multiple sequence alignment was performed for all Elongation Factor Tu proteins identified by metaproteomics in this study. The lysine amino acid position where the modification occurs in this study is highlighted with a red arrow. Unlike other organisms, Bacillus sp. BC15 and Sphingobium sp. AP49 have an arginine (R) residue at this position and no methylation modifications were observed for these protein sequences. For reference, the Elongation factor TU sequence of E. coli (strain K12) was added for comparison