Proteomics of Soil and Sediment: Protein Identification by De Novo Sequencing of Mass Spectra Complements Traditional Database Searching

Abstract:

Proteomics has the potential to elucidate the metabolic pathways and taxa responsible for in situ biogeochemical transformations. However, low rates of protein identification from high resolution mass spectra have been a barrier to the development of proteomics in complex environmental samples. Much of the difficulty lies in the computational challenge of linking mass spectra to their corresponding proteins. Traditional database search methods for matching peptide sequences to mass spectra are often inadequate due to the complexity of environmental proteomes and the large database search space, as we demonstrate with soil and sediment proteomes generated via a range of extraction methods.

One alternative to traditional database searching is de novo sequencing, which identifies peptide sequences without the need for a database. BLAST can then be used to match de novo sequences to similar genetic sequences. Assigning confidence to putative identifications has been one hurdle for the implementation of de novo sequencing. We found that accurate de novo sequences can be screened by quality score and length. Screening criteria are verified by comparing the results of de novo sequencing and traditional database searching for well-characterized proteomes from simple biological systems. The BLAST hits of screened sequences are interrogated for taxonomic and functional information.

We applied de novo sequencing to organic topsoil and marine sediment proteomes. Peak-rich proteomes, which can result from various extraction techniques, yield thousands of high-confidence protein identifications, an improvement over previous proteomic studies of soil and sediment. User-friendly software tools for de novo metaproteomics analysis have been developed. This “De Novo Analysis” Pipeline is also a faster method of data analysis than constructing a tailored sequence database for traditional database searching.