Emanuel Schmid

Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions

Leaf-litter decomposition is a central process in carbon cycling; however, our knowledge about the microbial regulation of this process is still scarce. Metaproteomics allows us to link the abundance and activity of enzymes during nutrient cycling to their phylogenetic origin based on proteins, the ‘active building blocks’ in the system. Moreover, we employed metaproteomics to investigate the influence of environmental factors and nutrients on the decomposer structure and function during beech litter decomposition. Litter was collected at forest sites in Austria with different litter nutrient content. Proteins were analyzed by 1-D-SDS-PAGE followed by liquid-chromatography and tandem mass-spectrometry. Mass spectra were assigned to phylogenetic and functional groups by a newly developed bioinformatics workflow, assignments being validated by complementary approaches. We provide evidence that the litter nutrient content and the stoichiometry of C:N:P affect the decomposer community structure and activity. Fungi were found to be the main producers of extracellular hydrolytic enzymes, with no bacterial hydrolases being detected by our metaproteomics approach. Detailed investigation of microbial succession suggests that it is influenced by litter nutrient content. Microbial activity was stimulated at higher litter nutrient contents via a higher abundance and activity of extracellular enzymes.

Structure and function of the symbiosis partners of the lung lichen (Lobaria pulmonaria L. Hoffm.) analyzed by metaproteomics

Environmental proteomics, also referred to as metaproteomics, is an emerging technology to study the structure and function of microbial communities. Here, we applied semi‐quantitative label‐free proteomics using one‐dimensional gel electrophoresis combined with LC‐MS/MS and normalized spectral counting together with fluorescence in situ hybridization and confocal laser scanning microscopy to characterize the metaproteome of the lung lichen symbiosis Lobaria pulmonaria. In addition to the myco‐ and photobiont, L. pulmonaria harbors proteins from a highly diverse prokaryotic community, which is dominated by Proteobacteria and including also Archaea. While fungal proteins are most dominant (75.4% of all assigned spectra), about the same amount of spectra were assigned to prokaryotic proteins (10%) and to the green algal photobiont (9%). While the latter proteins were found to be mainly associated with energy and carbohydrate metabolism, a major proportion of fungal and bacterial proteins appeared to be involved in PTMs and protein turnover and other diverse functions.

Proteome analysis of fungal and bacterial involvement in leaf litter decomposition.

Fungi and bacteria are key players in the decomposition of leaf litter, but their individual contributions to the process and their interactions are still poorly known. We combined semi‐quantitative proteome analyses (1‐D PAGE‐LC‐MS/MS) with qualitative and quantitative analyses of extracellular degradative enzyme activities to unravel the respective roles of a fungus and a bacterium during litter decomposition. Two model organisms, a mesophilic Gram‐negative bacterium (Pectobacterium carotovorum) and an ascomycete (Aspergillus nidulans), were grown in both, pure culture and co‐culture on minimal medium containing either glucose or beech leaf litter as sole carbon source. P. carotovorum grew best in co‐culture with the fungus, whereas growth of A. nidulans was significantly reduced when the bacterium was present. This observation suggests that P. carotovorum has only limited capabilities to degrade leaf litter and profits from the degradation products of A. nidulans at the expense of fungal growth. In accordance with this interpretation, our proteome analysis revealed that most of the extracellular biodegradative enzymes (i.e. proteases, pectinases, and cellulases) in the cultures with beech litter were expressed by the fungus, the bacterium producing only low levels of pectinases.

enviPath – The environmental contaminant biotransformation pathway resource

The University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS) has been a unique resource covering microbial biotransformation pathways of primarily xenobiotic chemicals for over 15 years. This paper introduces the successor system, enviPath (The Environmental Contaminant Biotransformation Pathway Resource), which is a complete redesign and reimplementation of UM-BBD/PPS. enviPath uses the database from the UM-BBD/PPS as a basis, extends the use of this database, and allows users to include their own data to support multiple use cases. Relative reasoning is supported for the refinement of predictions and to allow its extensions in terms of previously published, but not implemented machine learning models. User access is simplified by providing a REST API that simplifies the inclusion of enviPath into existing workflows. An RDF database is used to enable simple integration with other databases. enviPath is publicly available at https://envipath.org with free and open access to its core data.

iPortal: the swiss grid proteomics portal: Requirements and new features based on experience and usability considerations

Development of workflow and data management systems are challenging because of the need to provide a service for users with varying degrees of expertise from novices to experts with more knowledge than the developers. We have received feedback from users and developers on the functionality and usability of the Swiss Grid Proteomics Portal, now called iPortal, during its first year of operation. Monitoring and interaction with the production system under heavy use have provided further information on how to improve efficiency and stability. In a second, highly upgraded version of iPortal, we have introduced several new concepts based on this feedback. In this paper, we detail the requirements and the improvements we have made, and also give an outlook on future directions. Copyright

The SysteMHC Atlas project

Abstract Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.