Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative.
- MeSH
- hmotnostní spektrometrie přístrojové vybavení metody normy MeSH
- konformace proteinů MeSH
- lidé MeSH
- mapování interakce mezi proteiny metody MeSH
- mezinárodní spolupráce MeSH
- proteiny ultrastruktura MeSH
- proteomika přístrojové vybavení metody normy MeSH
- reagencia zkříženě vázaná chemie MeSH
- reprodukovatelnost výsledků MeSH
- směrnice jako téma MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- kongresy MeSH
- práce podpořená grantem MeSH
Stable isotope probing (SIP) approaches are a suitable tool to identify active organisms in bacterial communities, but adding isotopically labeled substrate can alter both the structure and the functionality of the community. Here, we validated and demonstrated a substrate-independent protein-SIP protocol using isotopically labeled water that captures the entire microbial activity of a community. We found that 18O yielded a higher incorporation rate into peptides and thus comprised a higher sensitivity. We then applied the method to an in vitro model of a human distal gut microbial ecosystem grown in two medium formulations, to evaluate changes in microbial activity between a high-fiber and high-protein diet. We showed that only little changes are seen in the community structure but the functionality varied between the diets. In conclusion, our approach can detect species-specific metabolic activity in complex bacterial communities and more specifically to quantify the amount of amino acid synthesis. Heavy water makes possible to analyze the activity of bacterial communities for which adding an isotopically labeled energy and nutrient sources is not easily feasible. SIGNIFICANCE: Heavy stable isotopes allow for the detection of active key players in complex ecosystems where many organisms are thought to be dormant. Opposed to the labelling with energy or nutrient sources, heavy water could be a suitable replacement to trace activity, which has been shown for DNA and RNA. Here we validate, quantify and compare the incorporation of heavy water either labeled with deuterium or 18‑oxygen into proteins of Escherichia coli K12 and of an in vitro model of a human gut microbial ecosystem. The significance of our research is in providing a freely available pipeline to analyze the incorporation of deuterium and 18‑oxygen into proteins together with the validation of the applicability of tracing heavy water as a proxy for activity. Our approach unveils the relative functional contribution of microbiota in complex ecosystems, which will improve our understanding of both animal- and environment-associated microbiomes and in vitro models.
- MeSH
- izotopové značení MeSH
- izotopy uhlíku analýza MeSH
- lidé MeSH
- mikrobiota * MeSH
- oxid deuteria MeSH
- proteiny * MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.
- Publikační typ
- časopisecké články MeSH
The similarity search in theoretical mass spectra generated from protein sequence databases is a widely accepted approach for identification of peptides from query mass spectra produced by shotgun proteomics. Growing protein sequence databases and noisy query spectra demand database indexing techniques and better similarity measures for the comparison of theoretical spectra against query spectra. We employ a modification of previously proposed parameterized Hausdorff distance for comparisons of mass spectra. The new distance outperforms the original distance, the angle distance and state-of-the-art peptide identification tools OMSSA and X!Tandem in the number of identified peptides even though the q-value is only 0.001. When a precursor mass filter is used as a database indexing technique, our method outperforms OMSSA in the speed of search. When variable modifications are not searched, the search time is similar to X!Tandem. We show that the precursor mass filter is an efficient database indexing technique for high-accuracy data even though many variable modifications are being searched. We demonstrate that the number of identified peptides is bigger when variable modifications are searched separately by more search runs of a peptide identification engine. Otherwise, the false discovery rates are affected by mixing unmodified and modified spectra together resulting in a lower number of identified peptides. Our method is implemented in the freely available application SimTandem which can be used in the framework TOPP based on OpenMS.
