Schneider T, Schmid E, de Castro Junior JV, Cardinale M, Eberl L, Grube M et al.. Structure and function of the symbiosis partners of the lung lichen (Lobaria pulmonaria L. Hoffm.) analyzed by metaproteomics. Proteomics 11: 2752-2756

University of Zurich, Institute of Plant Biology, Zürich, Switzerland.
Proteomics (Impact Factor: 3.81). 07/2011; 11(13):2752-6. DOI: 10.1002/pmic.201000679
Source: PubMed


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.

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Available from: Massimiliano Cardinale, May 27, 2014
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    • "Orbitrap Fusion MS (Thermo Fisher Scientific, Waltham, MA, USA) coupled to a TriVersa NanoMate (Advion, Ltd., Harlow, UK). 5 mL of the peptide lysates was separated with a Dionex Ultimate 3000 nano- LC system (Dionex/Thermo Fisher Scientific, Idstein, Germany). " PROteomics results Pruning and Homology group ANotation Engine " (PROPHANE, Schneider et al., 2011 "
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    ABSTRACT: A B S T R A C T The long-term effects of deforestation on the soil microbial community and its functionality are largely unknown. In order to assess simultaneously the phylogeny and functionality, we applied phospholipid fatty acid analysis (PLFAs), metaproteomics and enzyme activities in soil samples from a natural area located in Southeast Spain (Caravaca de la Cruz), dominated by Pinus halepensis (F), and an adjacent area deforested 15-years ago (DF). Deforestation induced a long-term loss of bacterial biomass and enzyme activity, but an increase in the bacterial diversity as estimated by metaproteomics. Protein abundances analysis revealed that Proteobacteria was higher in F than DF. In addition, the abundance of cyanobacterial proteins was significantly higher in DF (7.3%) when compared to F (0.9%). Interestingly, cyanobacterial proteins involved in carbon fixation (Ribulose 1,5-bisphosphate carboxylase, phycocyanins and photosystem proteins) were only identified in DF. The data suggest that Cyanobacteria play a critical role in the ecosystem functioning and biotic carbon fixation when soil is deforested in semiarid areas. ã 2015 Published by Elsevier B.V.
    Applied Soil Ecology 09/2015; 93. DOI:10.1016/j.apsoil.2015.04.006 · 2.64 Impact Factor
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    • "Currently, two major ideas are used to address this difficulty: either the analysis is based primarily on unique peptides that are specific for a single organism (Karlsson et al., 2012; Lo et al., 2007; Rooijers et al., 2011) or the phylogenetic resolution is reduced. This can be achieved by limiting the analysis to a set of well-chosen representative species that have no significant overlap (Chourey et al., 2013) or by dynamically allocating results to the lowest common ancestor that allows a distinction (Huson et al., 2007; Jagtap et al., 2012a; Schneider et al., 2011). When disregarding shared peptides and focusing on unique peptides, it is feasible to identify the species present in an organism as long as the coverage is high enough to observe a sufficient number of these peptides with sufficient confidence. "
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    ABSTRACT: Motivation: Metaproteomic analysis allows studying the interplay of organisms or functional groups and has become increasingly popular also for diagnostic purposes. However, difficulties arise owing to the high sequence similarity between related organisms. Further, the state of conservation of proteins between species can be correlated with their expression level, which can lead to significant bias in results and interpretation. These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions.Results: We introduce Pipasic (peptide intensity-weighted proteome abundance similarity correction) as a tool that corrects identification and spectral counting-based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. Pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor, as demonstrated on examples of viral diagnostics and an acid mine drainage dataset.Availability and implementation: Pipasic source code is freely available from RenardB@rki.deSupplementary information: Supplementary data are available at Bioinformatics online
    Bioinformatics 06/2014; 30(12):i149-i156. DOI:10.1093/bioinformatics/btu267 · 4.98 Impact Factor
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    • "Lichens are traditionally considered as mutualistic symbioses of fungi and photoautotrophs (algae or cyanobacteria). Recent microscopic studies revealed high abundances of bacteria in these symbioses, comparable to those of rhizosphere soil and other microbial hot spots (Cardinale et al., 2008; Grube et al., 2009; Schneider et al., 2011). Counting of bacteria in confocal images of FISH-labeled bacteria helped to statistically evaluate the effect of environmental factors on the frequency of main bacterial phyla in different lichen species (Cardinale et al., 2012; this was one of the few cases in which data obtained with confocal microscopy were statistically assessed). "
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