Abstract
BackgroundSoil and sediment microorganisms are highly phylogenetically diverse but are currently largely under-represented in public molecular databases. Their functional characterization by means of metaproteomics is usually performed using metagenomic sequences acquired for the same sample. However, such hugely diverse metagenomic datasets are difficult to assemble; in parallel, theoretical proteomes from isolates available in generic databases are of high quality. Both these factors advocate for the use of theoretical proteomes in metaproteomics interpretation pipelines. Here, we examined a number of database construction strategies with a view to increasing the outputs of metaproteomics studies performed on soil samples.ResultsThe number of peptide-spectrum matches was found to be of comparable magnitude when using public or sample-specific metagenomics-derived databases. However, numbers were significantly increased when a combination of both types of information was used in a two-step cascaded search. Our data also indicate that the functional annotation of the metaproteomics dataset can be maximized by using a combination of both types of databases.ConclusionsA two-step strategy combining sample-specific metagenome database and public databases such as the non-redundant NCBI database and a massive soil gene catalog allows maximizing the metaproteomic interpretation both in terms of ratio of assigned spectra and retrieval of function-derived information.4F9sWsX3PjS31f5TKAyCkGVideo abstract
Highlights
Soil and sediment microorganisms are highly phylogenetically diverse but are currently largely underrepresented in public molecular databases
Benchmarking databases created from sample-specific metagenomics data Different databases built from metagenomics data acquired on a sediment sample were evaluated for metaproteomics based on the number of Peptide-to-spectrum matches (PSMs) as main criterion
A soil core was collected from the Seine River floodplain at the Bouafles site (France) located downstream of Paris
Summary
Soil and sediment microorganisms are highly phylogenetically diverse but are currently largely underrepresented in public molecular databases Their functional characterization by means of metaproteomics is usually performed using metagenomic sequences acquired for the same sample. Such hugely diverse metagenomic datasets are difficult to assemble; in parallel, theoretical proteomes from isolates available in generic databases are of high quality. Soils are open systems exposed to highly variable environmental parameters such as Jouffret et al Microbiome (2021) 9:195 extraction, metaproteomics methods must be developed to suit each soil type [32, 63] Despite these difficulties, several pioneering studies have been performed on soils extracted from forests [40, 74], arid environments [7], agricultural areas [39, 50], permafrost [27], and from mining drainage [53]. Sediments — deposited material arising from weathering, erosion, and transport processes — contain complex microbial ecosystems [19, 64]
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