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Metaproteomics enables the investigation of the protein repertoire expressed by complex microbial communities. However, to unleash its full potential, refinements in bioinformatic approaches for data analysis are still needed. In this context, sequence databases selection represents a major challenge. This work assessed the impact of different databases in metaproteomic investigations by using a mock microbial mixture including nine diverse bacterial and eukaryotic species, which was subjected to shotgun metaproteomic analysis. Then, both the microbial mixture and the single microorganisms were subjected to next generation sequencing to obtain experimental metagenomic- and genomic-derived databases, which were used along with public databases (namely, NCBI, UniProtKB/SwissProt and UniProtKB/TrEMBL, parsed at different taxonomic levels) to analyze the metaproteomic dataset. First, a quantitative comparison in terms of number and overlap of peptide identifications was carried out among all databases. As a result, only 35% of peptides were common to all database classes; moreover, genus/species-specific databases provided up to 17% more identifications compared to databases with generic taxonomy, while the metagenomic database enabled a slight increment in respect to public databases. Then, database behavior in terms of false discovery rate and peptide degeneracy was critically evaluated. Public databases with generic taxonomy exhibited a markedly different trend compared to the counterparts. Finally, the reliability of taxonomic attribution according to the lowest common ancestor approach (using MEGAN and Unipept software) was assessed. The level of misassignments varied among the different databases, and specific thresholds based on the number of taxon-specific peptides were established to minimize false positives. This study confirms that database selection has a significant impact in metaproteomics, and provides critical indications for improving depth and reliability of metaproteomic results. Specifically, the use of iterative searches and of suitable filters for taxonomic assignments is proposed with the aim of increasing coverage and trustworthiness of metaproteomic data.

This work presents a comparative evaluation of several detergent-based sample preparation workflows for the MS-based analysis of bacterial proteomes, performed using the model organism Escherichia coli. Initially, RapiGest- and SDS-based buffers were compared for their protein extraction efficiency and quality of the MS data generated. As a result, SDS performed best in terms of total protein yields and overall number of MS identifications, mainly due to a higher efficiency in extracting high molecular weight (MW) and membrane proteins, while RapiGest led to an enrichment in periplasmic and fimbrial proteins. Then, SDS extracts underwent five different MS sample preparation workflows, including: detergent removal by spin columns followed by in-solution digestion (SC), protein precipitation followed by in-solution digestion in ammonium bicarbonate or urea buffer, filter-aided sample preparation (FASP), and 1DE separation followed by in-gel digestion. On the whole, about 1000 proteins were identified upon LC-MS/MS analysis of all preparations (>1100 with the SC workflow), with FASP producing more identified peptides and a higher mean sequence coverage. Each protocol exhibited specific behaviors in terms of MW, hydrophobicity, and subcellular localization distribution of the identified proteins; a comparative assessment of the different outputs is presented., (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Bouin's solution has been used for over a century as a common fixative in several pathology laboratories worldwide. Therefore, a considerable number of Bouin-fixed paraffin-embedded (BFPE) tumor samples of various origin are available in hospital repositories as a powerful information mine for clinical investigations. To date, however, such archived tissues have not been subjected to a systematic study aimed to evaluate their potential use in proteomics. In this report, we investigated whether archival BFPE tissue specimens could be exploited for proteomic studies, upon application of protein extraction and proteomic analysis methods previously optimized for formalin-fixed samples. As a result, gastric BFPE protein extracts exhibited poor suitability for 2D-PAGE analysis, whereas over 300 unique proteins could be successfully detected when extracts were subjected to SDS-PAGE followed by LC-MS/MS (GeLC-MS/MS). Among these, several known markers for gastric cancer and normal gastric functionality were identified, indicative of biological and clinical significance of proteomic data mined from BFPE tissues. A quantitative and qualitative comparison of FFPE and BFPE tissue proteomes was also performed, and results are reported. In conclusion, we demonstrated that BFPE specimens can be analyzed by means of a proteomic approach such as GeLC-MS/MS. Although considerable molecular biases and technical constraints exist, BFPE tissue archives can be fruitfully exploited for gathering proteomic data from particularly precious samples., (© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)