NovoLign: metaproteomics by sequence alignment
peer-reviewed · ISME Communications · 2024
| Date | 2024-01-08 |
| Type | peer-reviewed |
| Venue | ISME Communications |
| Publisher | Oxford University Press (OUP) |
| Contribution | downstream-application |
| DOI | 10.1093/ismeco/ycae121 |
| Citations (OpenAlex) | 9 |
| Venue 2-year citedness | 4.64 |
Abstract
Tremendous advances in mass spectrometric and bioinformatic approaches have expanded proteomics into the field of microbial ecology. The commonly used spectral annotation method for metaproteomics data relies on database searching, which requires sample-specific databases obtained from whole metagenome sequencing experiments. However, creating these databases is complex, time-consuming, and prone to errors, potentially biasing experimental outcomes and conclusions. This asks for alternative approaches that can provide rapid and orthogonal insights into metaproteomics data. Here, we present NovoLign, a de novo metaproteomics pipeline that performs sequence alignment of de novo sequences from complete metaproteomics experiments. The pipeline enables rapid taxonomic profiling of complex communities and evaluates the taxonomic coverage of metaproteomics outcomes obtained from database searches. Furthermore, the NovoLign pipeline supports the creation of reference sequence databases for database searching to ensure comprehensive coverage. We assessed the NovoLign pipeline for taxonomic coverage and false positive annotations using a wide range of in silico and experimental data, including pure reference strains, laboratory enrichment cultures, synthetic communities, and environmental microbial communities. In summary, we present NovoLign, a de novo metaproteomics pipeline that employs large-scale sequence alignment to enable rapid taxonomic profiling, evaluation of database searching outcomes, and the creation of reference sequence databases. The NovoLign pipeline is publicly available via: https://github.com/hbckleikamp/NovoLign.
Methods and tools
- NovoLign: Aligns de novo sequences from whole metaproteomics experiments to give rapid taxonomic profiles and to check the coverage of database search results.
Methods it uses
- PEAKS: Commercial DP-based de novo