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.

Diel Rhythms of Marine Picoplanktonic Communities Assessed by Comparative Metaproteomics

“…In situ physicochemical measurement confirmed the oligotrophic environmental conditions in which the studied picoplanktonic communities were sampled (Supplementary Information 1), therefore large volumes of water (60L/sample) were sequentially filtered onto both 0.8 and 0.2µm pore-size filters. A combined protein search database allowed us to maximize the number of protein identification [25]. Protein inference issue, commonly encountered in metaproteomics, was overcome in this study by using taxonomic and functional consensus protein annotation [26].…”

Metaproteomics insights into traditional fermented foods and beverages

“…The typical metaproteomics workflow is shown in Figure 3, including (a) extraction and purification of proteins from TFFB; (b) protein digestion; (c) mass spectrometry (MS) analysis of peptide fragments; (d) protein qualitative and quantitative analysis (Schneider & Riedel, 2010; Tilocca et al., 2020). The qualitative properties of proteins can be retrieved through a non‐assembled metagenome–derived database, an assembled metagenome–derived database, or a taxonomy–built database (Geron, Werner, Wattiez, Lebaron, & Matallana‐Surget, 2019). Metaproteomics can be subdivided into two different types of analysis: descriptive analysis and comparative analysis.…”

“…For example, using a combination of strong cation exchange and reversed‐phase chromatography to achieve 2D separation of the yeast proteome has led to the identification of 1,504 yeast proteins (Peng, Elias, Thoreen, Licklider, & Gygi, 2003). Although it is not as intuitive as 2D electrophoresis, this method allows for a high degree of automation, and can yield more accurate protein information (Geron et al., 2019), thus facilitating the study of metaproteomics and allowing for favorable development prospects.…”

“…Databases are critical in the analysis of sample metaproteome data (Tanca et al., 2016), and the biological conclusions obtained by using different databases for search and analysis differ substantially (Geron et al., 2019). Sample protein databases can be based on protein databases generated from shotgun metagenomics data of a sample, or can be pseudo‐metagenomics databases constructed from proteins obtained from a public database according to the community microbial structure obtained from 16S rRNA (Muth, Renard, & Martens, 2016).…”

Fish Pathology Research and Diagnosis in Aquaculture of Farmed Fish; a Proteomics Perspective

“…Metagenomics and metaproteomics are among the most powerful and emerging high-throughput tools in marine/ocean environments to disclose the genome and proteome, of the associated microbial communities [ 172 , 175 , 176 , 177 ]. These methodologies are still scarce on aquaculture research, although it might be extremely useful in the study of microbial populations inherent to the farmed fish surrounding environment.…”