Publications by authors named "Dirk Benndorf"

57 Publications

Indicative Marker Microbiome Structures Deduced from the Taxonomic Inventory of 67 Full-Scale Anaerobic Digesters of 49 Agricultural Biogas Plants.

Microorganisms 2021 Jul 7;9(7). Epub 2021 Jul 7.

Department Bioengineering, Leibniz Institute for Agricultural Engineering and Bioeconomy, Max-Eyth-Allee 100, 14469 Potsdam, Germany.

There are almost 9500 biogas plants in Germany, which are predominantly operated with energy crops and residues from livestock husbandry over the last two decades. In the future, biogas plants must be enabled to use a much broader range of input materials in a flexible and demand-oriented manner. Hence, the microbial communities will be exposed to frequently varying process conditions, while an overall stable process must be ensured. To accompany this transition, there is the need to better understand how biogas microbiomes respond to management measures and how these responses affect the process efficiency. Therefore, 67 microbiomes originating from 49 agricultural, full-scale biogas plants were taxonomically investigated by 16S rRNA gene amplicon sequencing. These microbiomes were separated into three distinct clusters and one group of outliers, which are characterized by a specific distribution of 253 indicative taxa and their relative abundances. These indicative taxa seem to be adapted to specific process conditions which result from a different biogas plant operation. Based on these results, it seems to be possible to deduce/assess the general process condition of a biogas digester based solely on the microbiome structure, in particular on the distribution of specific indicative taxa, and without knowing the corresponding operational and chemical process parameters. Perspectively, this could allow the development of detection systems and advanced process models considering the microbial diversity.
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http://dx.doi.org/10.3390/microorganisms9071457DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307424PMC
July 2021

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles.

Water Res 2021 Sep 10;202:117422. Epub 2021 Jul 10.

Center for Microbial Ecology and Technology (CMET), Ghent University, Coupure Links 653, B-9000, Gent, Belgium.

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.
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http://dx.doi.org/10.1016/j.watres.2021.117422DOI Listing
September 2021

smORFer: a modular algorithm to detect small ORFs in prokaryotes.

Nucleic Acids Res 2021 Sep;49(15):e89

Inst. Biochemistry and Molecular Biology, Department of Chemistry, University of Hamburg, 20146 Hamburg, Germany.

Emerging evidence places small proteins (≤50 amino acids) more centrally in physiological processes. Yet, their functional identification and the systematic genome annotation of their cognate small open-reading frames (smORFs) remains challenging both experimentally and computationally. Ribosome profiling or Ribo-Seq (that is a deep sequencing of ribosome-protected fragments) enables detecting of actively translated open-reading frames (ORFs) and empirical annotation of coding sequences (CDSs) using the in-register translation pattern that is characteristic for genuinely translating ribosomes. Multiple identifiers of ORFs that use the 3-nt periodicity in Ribo-Seq data sets have been successful in eukaryotic smORF annotation. They have difficulties evaluating prokaryotic genomes due to the unique architecture (e.g. polycistronic messages, overlapping ORFs, leaderless translation, non-canonical initiation etc.). Here, we present a new algorithm, smORFer, which performs with high accuracy in prokaryotic organisms in detecting putative smORFs. The unique feature of smORFer is that it uses an integrated approach and considers structural features of the genetic sequence along with in-frame translation and uses Fourier transform to convert these parameters into a measurable score to faithfully select smORFs. The algorithm is executed in a modular way, and dependent on the data available for a particular organism, different modules can be selected for smORF search.
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http://dx.doi.org/10.1093/nar/gkab477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421149PMC
September 2021

Fecal Metaproteomics Reveals Reduced Gut Inflammation and Changed Microbial Metabolism Following Lifestyle-Induced Weight Loss.

Biomolecules 2021 05 12;11(5). Epub 2021 May 12.

Bioprocess Engineering, Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany.

Gut microbiota-mediated inflammation promotes obesity-associated low-grade inflammation, which represents a hallmark of metabolic syndrome. To investigate if lifestyle-induced weight loss (WL) may modulate the gut microbiome composition and its interaction with the host on a functional level, we analyzed the fecal metaproteome of 33 individuals with metabolic syndrome in a longitudinal study before and after lifestyle-induced WL in a well-defined cohort. The 6-month WL intervention resulted in reduced BMI (-13.7%), improved insulin sensitivity (HOMA-IR, -46.1%), and reduced levels of circulating hsCRP (-39.9%), indicating metabolic syndrome reversal. The metaprotein spectra revealed a decrease of human proteins associated with gut inflammation. Taxonomic analysis revealed only minor changes in the bacterial composition with an increase of the families Desulfovibrionaceae, Leptospiraceae, Syntrophomonadaceae, Thermotogaceae and Verrucomicrobiaceae. Yet we detected an increased abundance of microbial metaprotein spectra that suggest an enhanced hydrolysis of complex carbohydrates. Hence, lifestyle-induced WL was associated with reduced gut inflammation and functional changes of human and microbial enzymes for carbohydrate hydrolysis while the taxonomic composition of the gut microbiome remained almost stable. The metaproteomics workflow has proven to be a suitable method for monitoring inflammatory changes in the fecal metaproteome.
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http://dx.doi.org/10.3390/biom11050726DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150863PMC
May 2021

Tracking changes in adaptation to suspension growth for MDCK cells: cell growth correlates with levels of metabolites, enzymes and proteins.

Appl Microbiol Biotechnol 2021 Mar 13;105(5):1861-1874. Epub 2021 Feb 13.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.

Adaptations of animal cells to growth in suspension culture concern in particular viral vaccine production, where very specific aspects of virus-host cell interaction need to be taken into account to achieve high cell specific yields and overall process productivity. So far, the complexity of alterations on the metabolism, enzyme, and proteome level required for adaptation is only poorly understood. In this study, for the first time, we combined several complex analytical approaches with the aim to track cellular changes on different levels and to unravel interconnections and correlations. Therefore, a Madin-Darby canine kidney (MDCK) suspension cell line, adapted earlier to growth in suspension, was cultivated in a 1-L bioreactor. Cell concentrations and cell volumes, extracellular metabolite concentrations, and intracellular enzyme activities were determined. The experimental data set was used as the input for a segregated growth model that was already applied to describe the growth dynamics of the parental adherent cell line. In addition, the cellular proteome was analyzed by liquid chromatography coupled to tandem mass spectrometry using a label-free protein quantification method to unravel altered cellular processes for the suspension and the adherent cell line. Four regulatory mechanisms were identified as a response of the adaptation of adherent MDCK cells to growth in suspension. These regulatory mechanisms were linked to the proteins caveolin, cadherin-1, and pirin. Combining cell, metabolite, enzyme, and protein measurements with mathematical modeling generated a more holistic view on cellular processes involved in the adaptation of an adherent cell line to suspension growth. KEY POINTS: • Less and more efficient glucose utilization for suspension cell growth • Concerted alteration of metabolic enzyme activity and protein expression • Protein candidates to interfere glycolytic activity in MDCK cells.
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http://dx.doi.org/10.1007/s00253-021-11150-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907048PMC
March 2021

The structure and function of soil archaea across biomes.

J Proteomics 2021 04 11;237:104147. Epub 2021 Feb 11.

CEBAS-CSIC, Campus Universitario de Espinardo, Murcia E-30100, Spain.

We lack a predictive understanding of the environmental drivers determining the structure and function of archaeal communities as well as the proteome associated with these important soil organisms. Here, we characterized the structure (by 16S rRNA gene sequencing) and function (by metaproteomics) of archaea from 32 soil samples across terrestrial ecosystems with contrasting climate and vegetation types. Our multi-"omics" approach unveiled that genes from Nitrosophaerales and Thermoplasmata dominated soils collected from four continents, and that archaea comprise 2.3 ± 0.3% of microbial proteins in these soils. Aridity positively correlated with the proportion of Nitrosophaerales genes and the number of archaeal proteins. The interaction of climate x vegetation shaped the functional profile of the archaeal community. Our study provides novel insights into the structure and function of soil archaea across climates, and highlights that these communities may be influenced by increasing global aridity.
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http://dx.doi.org/10.1016/j.jprot.2021.104147DOI Listing
April 2021

The Role of ING2-E5A in Mesophilic Biogas Reactor Systems as Deduced from Multiomics Analyses.

Microorganisms 2020 Dec 17;8(12). Epub 2020 Dec 17.

Center for Biotechnology (CeBiTec), Genome Research of Industrial Microorganisms, Bielefeld University, Universitätsstr. 27, 33615 Bielefeld, Germany.

Members of the genera and were speculated to represent indicators reflecting process instability within anaerobic digestion (AD) microbiomes. Therefore, ING2-E5A was isolated from a biogas reactor sample and sequenced on the PacBio and Illumina MiSeq sequencers. Phylogenetic classification positioned the strain ING2-E5A in close proximity to and species (family Dysgonomonadaceae). ING2-E5A encodes a number of genes for glycosyl-hydrolyses (GH) which are organized in Polysaccharide Utilization Loci (PUL) comprising tandem CD-like genes for a TonB-dependent outer-membrane transporter and a cell surface glycan-binding protein. Different GHs encoded in PUL are involved in pectin degradation, reflecting a pronounced specialization of the ING2-E5A PUL systems regarding the decomposition of this polysaccharide. Genes encoding enzymes participating in amino acids fermentation were also identified. Fragment recruitments with the ING2-E5A genome as a template and publicly available metagenomes of AD microbiomes revealed that species are present in 146 out of 257 datasets supporting their importance in AD microbiomes. Metatranscriptome analyses of AD microbiomes uncovered active sugar and amino acid fermentation pathways for species. Likewise, screening of metaproteome datasets demonstrated expression of the PUL-specific component SusC providing further evidence that PUL play a central role for the lifestyle of species.
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http://dx.doi.org/10.3390/microorganisms8122024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768429PMC
December 2020

OP7, a novel influenza A virus defective interfering particle: production, purification, and animal experiments demonstrating antiviral potential.

Appl Microbiol Biotechnol 2021 Jan 4;105(1):129-146. Epub 2020 Dec 4.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.

The novel influenza A virus (IAV) defective interfering particle "OP7" inhibits IAV replication in a co-infection and was previously suggested as a promising antiviral agent. Here, we report a batch-mode cell culture-based production process for OP7. In the present study, a seed virus containing standard virus (STV) and OP7 was used. The yield of OP7 strongly depended on the production multiplicity of infection. To inactivate infectious STV in the OP7 material, which may cause harm in a potential application, UV irradiation was used. The efficacy of OP7 in this material was preserved, as shown by an in vitro interference assay. Next, steric exclusion chromatography was used to purify and to concentrate (~ 13-fold) the UV-treated material. Finally, administration of produced OP7 material in mice did not show any toxic effects. Furthermore, all mice infected with a lethal dose of IAV survived the infection upon OP7 co-treatment. Thus, the feasibility of a production workflow for OP7 and its potential for antiviral treatment was demonstrated. KEY POINTS: • OP7 efficacy strongly depended on the multiplicity of infection used for production • Purification by steric exclusion chromatography increased OP7 efficacy • OP7-treated mice were protected against a lethal infection with IAV.
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http://dx.doi.org/10.1007/s00253-020-11029-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778630PMC
January 2021

A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane.

Nat Protoc 2020 10 28;15(10):3212-3239. Epub 2020 Aug 28.

Department of Infectious Diseases, Robert Koch Institute, Wernigerode, Germany.

Metaproteomics, the study of the collective protein composition of multi-organism systems, provides deep insights into the biodiversity of microbial communities and the complex functional interplay between microbes and their hosts or environment. Thus, metaproteomics has become an indispensable tool in various fields such as microbiology and related medical applications. The computational challenges in the analysis of corresponding datasets differ from those of pure-culture proteomics, e.g., due to the higher complexity of the samples and the larger reference databases demanding specific computing pipelines. Corresponding data analyses usually consist of numerous manual steps that must be closely synchronized. With MetaProteomeAnalyzer and Prophane, we have established two open-source software solutions specifically developed and optimized for metaproteomics. Among other features, peptide-spectrum matching is improved by combining different search engines and, compared to similar tools, metaproteome annotation benefits from the most comprehensive set of available databases (such as NCBI, UniProt, EggNOG, PFAM, and CAZy). The workflow described in this protocol combines both tools and leads the user through the entire data analysis process, including protein database creation, database search, protein grouping and annotation, and results visualization. To the best of our knowledge, this protocol presents the most comprehensive, detailed and flexible guide to metaproteomics data analysis to date. While beginners are provided with robust, easy-to-use, state-of-the-art data analysis in a reasonable time (a few hours, depending on, among other factors, the protein database size and the number of identified peptides and inferred proteins), advanced users benefit from the flexibility and adaptability of the workflow.
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http://dx.doi.org/10.1038/s41596-020-0368-7DOI Listing
October 2020

Impact of feeding and stirring regimes on the internal stratification of microbial communities in the fermenter of anaerobic digestion plants.

Bioresour Technol 2020 Oct 13;314:123679. Epub 2020 Jun 13.

Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstraße 1, 39106 Magdeburg, Germany. Electronic address:

In anaerobic digestion plants (ADs), homogenization of the feed, fermenter content and microbial communities is crucial for efficient and robust biogas production. However, mixing also requires a significant amount of energy. For an 850 m agricultural AD equipped with eight sampling ports, we investigated whether different feeding and stirring regimes enable a sufficient homogenization of the microbial community using metaproteomics and terminal restriction fragment length polymorphism (TRFLP) analysis. Systematic comparison of samples taken at the top and the bottom as well as at the rim and the center of the AD using scatter plots and students t-test revealed only a small number of differences in metaproteins, taxonomies and biological processes. Obviously, the applied stirring and feeding conditions were sufficient to largely homogenize the content of the AD.
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http://dx.doi.org/10.1016/j.biortech.2020.123679DOI Listing
October 2020

Connecting MetaProteomeAnalyzer and PeptideShaker to Unipept for Seamless End-to-End Metaproteomics Data Analysis.

J Proteome Res 2020 08 11;19(8):3562-3566. Epub 2020 Jun 11.

Bioinformatics Unit (MF 1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Nordufer 20, 13353 Berlin, Germany.

Although metaproteomics, the study of the collective proteome of microbial communities, has become increasingly powerful and popular over the past few years, the field has lagged behind on the availability of user-friendly, end-to-end pipelines for data analysis. We therefore describe the connection from two commonly used metaproteomics data processing tools in the field, MetaProteomeAnalyzer and PeptideShaker, to Unipept for downstream analysis. Through these connections, direct end-to-end pipelines are built from database searching to taxonomic and functional annotation.
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http://dx.doi.org/10.1021/acs.jproteome.0c00136DOI Listing
August 2020

Substrate-Dependent Fermentation of Bamboo in Giant Panda Gut Microbiomes: Leaf Primarily to Ethanol and Pith to Lactate.

Front Microbiol 2020 31;11:530. Epub 2020 Mar 31.

Center for Microbial Ecology and Technology, University of Ghent, Ghent, Belgium.

The giant panda is known worldwide for having successfully moved to a diet almost exclusively based on bamboo. Provided that no lignocellulose-degrading enzyme was detected in panda's genome, bamboo digestion is believed to depend on its gut microbiome. However, pandas retain the digestive system of a carnivore, with retention times of maximum 12 h. Cultivation of their unique gut microbiome under controlled laboratory conditions may be a valid tool to understand giant pandas' dietary habits, and provide valuable insights about what component of lignocellulose may be metabolized. Here, we collected gut microbiomes from fresh fecal samples of a giant panda (either entirely green or yellow stools) and supplied them with green leaves or yellow pith (i.e., the peeled stem). Microbial community composition was substrate dependent, and resulted in markedly different fermentation profiles, with yellow pith fermented to lactate and green leaves to lactate, acetate and ethanol, the latter to strikingly high concentrations (∼3%, v:v, within 3.5 h). Microbial metaproteins pointed to hemicellulose rather than cellulose degradation. The alpha-amylase from the giant panda (E.C. 3.2.1.1) was the predominant identified metaprotein, particularly in reactors inoculated with pellets derived from fecal samples (up to 60%). Gut microbiomes assemblage was most prominently impacted by the change in substrate (either leaf or pith). Removal of soluble organics from inocula to force lignocellulose degradation significantly enriched (in green leaf) and / (in yellow pith). Overall, different substrates (either leaf or pith) markedly shaped gut microbiome assemblies and fermentation profiles. The biochemical profile of fermentation products may be an underestimated factor contributing to explain the peculiar dietary behavior of giant pandas, and should be implemented in large scale studies together with short-term lab-scale cultivation of gut microbiomes.
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http://dx.doi.org/10.3389/fmicb.2020.00530DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145396PMC
March 2020

The Impact of , and Mutations on Growth, Gene Expression and Protein Acetylation in K-12.

Front Microbiol 2020 21;11:233. Epub 2020 Feb 21.

Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.

Acetate is a characteristic by-product of K-12 growing in batch cultures with glucose, both under aerobic as well as anaerobic conditions. While the reason underlying aerobic acetate production is still under discussion, during anaerobic growth acetate production is important for ATP generation by substrate level phosphorylation. Under both conditions, acetate is produced by a pathway consisting of the enzyme phosphate acetyltransferase (Pta) producing acetyl-phosphate from acetyl-coenzyme A, and of the enzyme acetate kinase (AckA) producing acetate from acetyl-phosphate, a reaction that is coupled to the production of ATP. Mutants in the AckA-Pta pathway differ from each other in the potential to produce and accumulate acetyl-phosphate. In the publication at hand, we investigated different mutants in the acetate pathway, both under aerobic as well as anaerobic conditions. While under aerobic conditions only small changes in growth rate were observed, all acetate mutants showed severe reduction in growth rate and changes in the by-product pattern during anaerobic growth. The AckA mutant showed the most severe growth defect. The glucose uptake rate and the ATP concentration were strongly reduced in this strain. This mutant exhibited also changes in gene expression. In this strain, the operon was significantly upregulated under anaerobic conditions hinting to the production of acetoacetate. During anaerobic growth, protein acetylation increased significantly in the mutant. Acetylation of several enzymes of glycolysis and central metabolism, of aspartate carbamoyl transferase, methionine synthase, catalase and of proteins involved in translation was increased. Supplementation of methionine and uracil eliminated the additional growth defect of the mutant. The data show that anaerobic, fermentative growth of mutants in the AckA-Pta pathway is reduced but still possible. Growth reduction can be explained by the lack of an important ATP generating pathway of mixed acid fermentation. An deletion mutant is more severely impaired than or deletion mutants. This is most probably due to the production of acetyl-P in the mutant, leading to increased protein acetylation.
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http://dx.doi.org/10.3389/fmicb.2020.00233DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7047895PMC
February 2020

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer.

Front Microbiol 2019 16;10:1883. Epub 2019 Aug 16.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.
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http://dx.doi.org/10.3389/fmicb.2019.01883DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707425PMC
August 2019

Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity.

Front Microbiol 2019 17;10:1095. Epub 2019 May 17.

Department of Environmental Microbiology, UFZ - Helmholtz Centre for Environmental Research, Leipzig, Germany.

The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species' metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques.
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http://dx.doi.org/10.3389/fmicb.2019.01095DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533897PMC
May 2019

RedCom: A strategy for reduced metabolic modeling of complex microbial communities and its application for analyzing experimental datasets from anaerobic digestion.

PLoS Comput Biol 2019 02 1;15(2):e1006759. Epub 2019 Feb 1.

Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.

Constraint-based modeling (CBM) is increasingly used to analyze the metabolism of complex microbial communities involved in ecology, biomedicine, and various biotechnological processes. While CBM is an established framework for studying the metabolism of single species with linear stoichiometric models, CBM of communities with balanced growth is more complicated, not only due to the larger size of the multi-species metabolic network but also because of the bilinear nature of the resulting community models. Moreover, the solution space of these community models often contains biologically unrealistic solutions, which, even with model linearization and under application of certain objective functions, cannot easily be excluded. Here we present RedCom, a new approach to build reduced community models in which the metabolisms of the participating organisms are represented by net conversions computed from the respective single-species networks. By discarding (single-species) net conversions that violate a minimality criterion in the exchange fluxes, it is ensured that unrealistic solutions in the community model are excluded where a species altruistically synthesizes large amounts of byproducts (instead of biomass) to fulfill the requirements of other species. We employed the RedCom approach for modeling communities of up to nine organisms involved in typical degradation steps of anaerobic digestion in biogas plants. Compared to full (bilinear and linearized) community models, we found that the reduced community models obtained with RedCom are not only much smaller but allow, also in the largest model with nine species, extensive calculations required to fully characterize the solution space and to reveal key properties of communities with maximum methane yield and production rates. Furthermore, the predictive power of the reduced community models is significantly larger because they predict much smaller ranges of feasible community compositions and exchange fluxes still being consistent with measurements obtained from enrichment cultures. For an enrichment culture for growth on ethanol, we also used metaproteomic data to further constrain the solution space of the community models. Both model and proteomic data indicated a dominance of acetoclastic methanogens (Methanosarcinales) and Desulfovibrionales being the least abundant group in this microbial community.
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http://dx.doi.org/10.1371/journal.pcbi.1006759DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373973PMC
February 2019

A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures.

Mol Ecol Resour 2019 Mar;19(2):439-455

Functional Environmental Microbiology, School of Natural Sciences, National University of Ireland Galway, Galway, Ireland.

The soil microbiome is inherently complex with high biological diversity, and spatial heterogeneity typically occurring on the submillimetre scale. To study the microbial ecology of soils, and other microbiomes, biomolecules, that is, nucleic acids and proteins, must be efficiently and reliably co-recovered from the same biological samples. Commercial kits are currently available for the co-extraction of DNA, RNA and proteins but none has been developed for soil samples. We present a new protocol drawing on existing phenol-chloroform-based methods for nucleic acids co-extraction but incorporating targeted precipitation of proteins from the phenol phase. The protocol is cost-effective and robust, and easily implemented using reagents commonly available in laboratories. The method is estimated to be eight times cheaper than using disparate commercial kits for the isolation of DNA and/or RNA, and proteins, from soil. The method is effective, providing good quality biomolecules from a diverse range of soil types, with clay contents varying from 9.5% to 35.1%, which we successfully used for downstream, high-throughput gene sequencing and metaproteomics. Additionally, we demonstrate that the protocol can also be easily implemented for biomolecule co-extraction from other complex microbiome samples, including cattle slurry and microbial communities recovered from anaerobic bioreactors, as well as from Gram-positive and Gram-negative pure cultures.
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http://dx.doi.org/10.1111/1755-0998.12979DOI Listing
March 2019

Reduced TCA cycle rates at high hydrostatic pressure hinder hydrocarbon degradation and obligate oil degraders in natural, deep-sea microbial communities.

ISME J 2019 04 12;13(4):1004-1018. Epub 2018 Dec 12.

Center for Microbial Ecology and Technology (CMET), Gent University, Coupure Links 653, Gent, B 9000, Belgium.

Petroleum hydrocarbons reach the deep-sea following natural and anthropogenic factors. The process by which they enter deep-sea microbial food webs and impact the biogeochemical cycling of carbon and other elements is unclear. Hydrostatic pressure (HP) is a distinctive parameter of the deep sea, although rarely investigated. Whether HP alone affects the assembly and activity of oil-degrading communities remains to be resolved. Here we have demonstrated that hydrocarbon degradation in deep-sea microbial communities is lower at native HP (10 MPa, about 1000 m below sea surface level) than at ambient pressure. In long-term enrichments, increased HP selectively inhibited obligate hydrocarbon-degraders and downregulated the expression of beta-oxidation-related proteins (i.e., the main hydrocarbon-degradation pathway) resulting in low cell growth and CO production. Short-term experiments with HP-adapted synthetic communities confirmed this data, revealing a HP-dependent accumulation of citrate and dihydroxyacetone. Citrate accumulation suggests rates of aerobic oxidation of fatty acids in the TCA cycle were reduced. Dihydroxyacetone is connected to citrate through glycerol metabolism and glycolysis, both upregulated with increased HP. High degradation rates by obligate hydrocarbon-degraders may thus be unfavourable at increased HP, explaining their selective suppression. Through lab-scale cultivation, the present study is the first to highlight a link between impaired cell metabolism and microbial community assembly in hydrocarbon degradation at high HP. Overall, this data indicate that hydrocarbons fate differs substantially in surface waters as compared to deep-sea environments, with in situ low temperature and limited nutrients availability expected to further prolong hydrocarbons persistence at deep sea.
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http://dx.doi.org/10.1038/s41396-018-0324-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6461773PMC
April 2019

SDS-PAGE fractionation to increase metaproteomic insight into the taxonomic and functional composition of microbial communities for biogas plant samples.

Eng Life Sci 2018 Jul 8;18(7):498-509. Epub 2018 Jul 8.

Bioprocess Engineering Otto von Guericke University Magdeburg Germany.

Metaproteomics represent an important tool for the taxonomic and functional investigation of microbial communities in humans, environment, and technical applications. Due to the high complexity of the microbial communities, protein, and peptide fractionation is applied to improve the characterization of taxonomic and functional composition of microbial communities. In order to target scientific questions regarding taxonomic and functional composition adequately, a tradeoff between the number of fractions analyzed and the required depth of information has to be found. Two samples of a biogas plant were analyzed by either single LC-MS/MS measurement (1D) or LC-MS/MS measurements of fractions obtained after SDS-PAGE (2D) separation. Fractionation with SDS-PAGE increased the number of identified spectra by 273%, the number of peptides by 95%, and the number of metaproteins by 59%. Rarefaction plots of species and metaproteins against identified spectra showed that 2D separation was sufficient to identify most microbial families but not all metaproteins. More reliable quantitative comparison could be achieved with 2D. 1D separation enabled high-throughput analysis of samples, however, depth in functional descriptions and reliability of quantification were lost. Nevertheless, the proteotyping of multiple samples was still possible. 2D separations provided more reliable quantitative data combined with a deeper insight into the taxonomic and functional composition of the microbial communities. Regarding taxonomic and functional composition, metaproteomics based on 2D is just the tip of an iceberg.
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http://dx.doi.org/10.1002/elsc.201800062DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6999349PMC
July 2018

MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go.

Anal Chem 2018 01 19;90(1):685-689. Epub 2017 Dec 19.

Bioinformatics Unit (MF 1), Department for Methods Development and Research Infrastructure, Robert Koch Institute , 13353 Berlin, Germany.

Metaproteomics, the mass spectrometry-based analysis of proteins from multispecies samples faces severe challenges concerning data analysis and results interpretation. To overcome these shortcomings, we here introduce the MetaProteomeAnalyzer (MPA) Portable software. In contrast to the original server-based MPA application, this newly developed tool no longer requires computational expertise for installation and is now independent of any relational database system. In addition, MPA Portable now supports state-of-the-art database search engines and a convenient command line interface for high-performance data processing tasks. While search engine results can easily be combined to increase the protein identification yield, an additional two-step workflow is implemented to provide sufficient analysis resolution for further postprocessing steps, such as protein grouping as well as taxonomic and functional annotation. Our new application has been developed with a focus on intuitive usability, adherence to data standards, and adaptation to Web-based workflow platforms. The open source software package can be found at https://github.com/compomics/meta-proteome-analyzer .
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http://dx.doi.org/10.1021/acs.analchem.7b03544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5757220PMC
January 2018

FMNH-dependent monooxygenases initiate catabolism of sulfonamides in Microbacterium sp. strain BR1 subsisting on sulfonamide antibiotics.

Sci Rep 2017 Nov 17;7(1):15783. Epub 2017 Nov 17.

Institute for Ecopreneurship, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.

We report a cluster of genes encoding two monooxygenases (SadA and SadB) and one FMN reductase (SadC) that enable Microbacterium sp. strain BR1 and other Actinomycetes to inactivate sulfonamide antibiotics. Our results show that SadA and SadC are responsible for the initial attack of sulfonamide molecules resulting in the release of 4-aminophenol. The latter is further transformed into 1,2,4-trihydroxybenzene by SadB and SadC prior to mineralization and concomitant production of biomass. As the degradation products lack antibiotic activity, the presence of SadA will result in an alleviated bacteriostatic effect of sulfonamides. In addition to the relief from antibiotic stress this bacterium gains access to an additional carbon source when this gene cluster is expressed. As degradation of sulfonamides was also observed when Microbacterium sp. strain BR1 was grown on artificial urine medium, colonization with such strains may impede common sulfonamide treatment during co-infections with pathogens of the urinary tract. This case of biodegradation exemplifies the evolving catabolic capacity of bacteria, given that sulfonamide bacteriostatic are purely of synthetic origin. The wide distribution of this cluster in Actinomycetes and the presence of traA encoding a relaxase in its vicinity suggest that this cluster is mobile and that is rather alarming.
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http://dx.doi.org/10.1038/s41598-017-16132-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5693940PMC
November 2017

Challenges and perspectives of metaproteomic data analysis.

J Biotechnol 2017 Nov 27;261:24-36. Epub 2017 Jun 27.

Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstraße 1, 39106, Magdeburg, Germany. Electronic address:

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.
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http://dx.doi.org/10.1016/j.jbiotec.2017.06.1201DOI Listing
November 2017

Metaproteomics Applied to Activated Sludge for Industrial Wastewater Treatment Revealed a Dominant Methylotrophic Metabolism of Hyphomicrobium zavarzinii.

Microb Ecol 2016 07 18;72(1):9-13. Epub 2016 Apr 18.

Water Research Institute, Viale F. De Blasio 5, 70132, Bari, Italy.

In biological wastewater treatments, microbial populations of the so-called activated sludge work together in the abatement of pollutants. In this work, the metabolic behavior of the biomass of a lab-scale plant treating industrial pharmaceutical wastewater was investigated through a metaproteomic approach. The complete treatment process included a membrane biological reactor (MBR) coupled with an advanced oxidation process (AOP) for partial breakdown of non-biodegradable molecules. Proteins from biomass samples collected pre- and post-AOP application were investigated by two-dimensional gel electrophoresis (2DE), mass spectrometry (MS), and finally identified by database search. Results showed that most proteins remained constant between pre- and post-AOP. Methanol dehydrogenase (MDH) belonging to Hyphomicrobium zavarzinii appeared as the most constantly expressed protein in the studied consortium. Other identified proteins belonging to Hyphomicrobium spp. revealed a predominant methylotrophic metabolism, and H. zavarzinii appeared as a key actor in the studied microbial community.
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http://dx.doi.org/10.1007/s00248-016-0769-xDOI Listing
July 2016

Predicting compositions of microbial communities from stoichiometric models with applications for the biogas process.

Biotechnol Biofuels 2016 22;9:17. Epub 2016 Jan 22.

Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany.

Background: Microbial communities are ubiquitous in nature and play a major role in ecology, medicine, and various industrial processes. In this study, we used stoichiometric metabolic modeling to investigate a community of three species, Desulfovibrio vulgaris, Methanococcus maripaludis, and Methanosarcina barkeri, which are involved in acetogenesis and methanogenesis in anaerobic digestion for biogas production.

Results: We first constructed and validated stoichiometric models of the core metabolism of the three species which were then assembled to community models. The community was simulated by applying the previously described concept of balanced growth demanding that all organisms of the community grow with equal specific growth rate. For predicting community compositions, we propose a novel hierarchical optimization approach: first, similar to other studies, a maximization of the specific community growth rate is performed which, however, often leads to a wide range of optimal community compositions. In a secondary optimization, we therefore also demand that all organisms must grow with maximum biomass yield (optimal substrate usage) reducing the range of predicted optimal community compositions. Simulating two-species as well as three-species communities of the three representative organisms, we gained several important insights. First, using our new optimization approach we obtained predictions on optimal community compositions for different substrates which agree well with measured data. Second, we found that the ATP maintenance coefficient influences significantly the predicted community composition, especially for small growth rates. Third, we observed that maximum methane production rates are reached under high-specific community growth rates and if at least one of the organisms converts its substrate(s) with suboptimal biomass yield. On the other hand, the maximum methane yield is obtained at low community growth rates and, again, when one of the organisms converts its substrates suboptimally and thus wastes energy. Finally, simulations in the three-species community clarify exchangeability and essentiality of the methanogens in case of alternative substrate usage and competition scenarios.

Conclusions: In summary, our study presents new methods for stoichiometric modeling of microbial communities in general and provides valuable insights in interdependencies of bacterial species involved in the biogas process.
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http://dx.doi.org/10.1186/s13068-016-0429-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724120PMC
January 2016

Comparison of Influenza Virus Particle Purification Using Magnetic Sulfated Cellulose Particles with an Established Centrifugation Method for Analytics.

Anal Chem 2015 Nov 14;87(21):10708-11. Epub 2015 Oct 14.

Max Planck Institute for Dynamics of Complex Technical Systems , Sandtorstrasse 1, 39106 Magdeburg, Germany.

A method for the purification of influenza virus particles using novel magnetic sulfated cellulose particles is presented and compared to an established centrifugation method for analytics. Therefore, purified influenza A virus particles from adherent and suspension MDCK host cell lines were characterized on the protein level with mass spectrometry to compare the viral and residual host cell proteins. Both methods allowed one to identify all 10 influenza A virus proteins, including low-abundance proteins like the matrix protein 2 and nonstructural protein 1, with a similar impurity level of host cell proteins. Compared to the centrifugation method, use of the novel magnetic sulfated cellulose particles reduced the influenza A virus particle purification time from 3.5 h to 30 min before mass spectrometry analysis.
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http://dx.doi.org/10.1021/acs.analchem.5b02681DOI Listing
November 2015

Metaproteomics of activated sludge from a wastewater treatment plant - a pilot study.

Proteomics 2015 Oct 20;15(20):3596-601. Epub 2015 Aug 20.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.

In this study, the impact of protein fractionation techniques prior to LC/MS analysis was investigated on activated sludge samples derived at winter and summer condition from a full-scale wastewater treatment plant (WWTP). For reduction of the sample complexity, different fractionation techniques including RP-LC (1D-approach), SDS-PAGE and RP-LC (2D-approach) as well as RP-LC, SDS-PAGE and liquid IEF (3D-approach) were carried out before subsequent ion trap MS analysis. The derived spectra were identified by MASCOT search using a combination of the public UniProtKB/Swiss-Prot protein database and metagenome data from a WWTP. The results showed a significant increase of identified spectra, enabled by applying IEF and SDS-PAGE to the proteomic workflow. Based on meta-proteins, a core metaproteome and a corresponding taxonomic profile of the wastewater activated sludge were described. Functional aspects were analyzed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway library by plotting KEGG Orthology identifiers (KO numbers) of protein hits into pathway maps of the central carbon (map01200) and nitrogen metabolism (map00910). Using the 3D-approach, most proteins involved in glycolysis and citrate cycle and nearly all proteins of the nitrogen removal were identified, qualifying this approach as most promising for future studies. All MS data have been deposited in the ProteomeXchange with identifier PXD001547 (http://proteomecentral.proteomexchange.org/dataset/PXD001547).
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http://dx.doi.org/10.1002/pmic.201400559DOI Listing
October 2015

Fractionation of biogas plant sludge material improves metaproteomic characterization to investigate metabolic activity of microbial communities.

Proteomics 2015 Oct 12;15(20):3585-9. Epub 2015 Aug 12.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany.

With the development of high resolving mass spectrometers, metaproteomics evolved as a powerful tool to elucidate metabolic activity of microbial communities derived from full-scale biogas plants. Due to the vast complexity of these microbiomes, application of suitable fractionation methods are indispensable, but often turn out to be time and cost intense, depending on the method used for protein separation. In this study, centrifugal fractionation has been applied for fractionation of two biogas sludge samples to analyze proteins extracted from (i) crude fibers, (ii) suspended microorganisms, and (iii) secreted proteins in the supernatant using a gel-based approach followed by LC-MS/MS identification. This fast and easy method turned out to be beneficial to both the quality of SDS-PAGE and the identification of peptides and proteins compared to untreated samples. Additionally, a high functional metabolic pathway coverage was achieved by combining protein hits found exclusively in distinct fractions. Sample preparation using centrifugal fractionation influenced significantly the number and the types of proteins identified in the microbial metaproteomes. Thereby, comparing results from different proteomic or genomic studies, the impact of sample preparation should be considered. All MS data have been deposited in the ProteomeXchange with identifier PXD001508 (http://proteomecentral.proteomexchange.org/dataset/PXD001508).
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http://dx.doi.org/10.1002/pmic.201400557DOI Listing
October 2015

Community shifts in a well-operating agricultural biogas plant: how process variations are handled by the microbiome.

Appl Microbiol Biotechnol 2015 Sep 22;99(18):7791-803. Epub 2015 May 22.

Department Bioengineering, Leibniz-Institute for Agricultural Engineering Potsdam-Bornim e.V. (ATB), Max-Eyth-Allee 100, 14469, Potsdam, Germany,

This study provides a comprehensive, long-term microbiological study of a continuously operated, mesophilic, agricultural biogas plant fed with whole-crop silages of maize and rye, cattle manure and cattle slurry. The microbial community structure was accessed by high-throughput 16S rRNA gene amplicon sequencing. For the characterisation of the microbial dynamics, the community profiling method terminal restriction fragment length polymorphism (TRFLP) in combination with a cloning-sequencing approach as well as a LC-MS/MS approach for protein identification were applied. Our results revealed that the anaerobic digestion is a highly sensitive process: small variations in the process performance induce fluctuations in the microbial community composition and activity. In this context, it could be proven that certain microbial species were better adapted to changing process condition such as temperature (interspecies competition) and that there is a physiological compensation between different microorganisms so that the reactor efficiency was not adversely affected despite of structural and functional changes within the microbial community.
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http://dx.doi.org/10.1007/s00253-015-6627-9DOI Listing
September 2015

Monitoring changes in proteome during stepwise adaptation of a MDCK cell line from adherence to growth in suspension.

Vaccine 2015 Aug 16;33(35):4269-80. Epub 2015 Apr 16.

Otto von Guericke University, Bioprocess Engineering, Universitätsplatz 2, 39106 Magdeburg, Germany; Max Planck Institute for Dynamics of Complex Technical Systems, Bioprocess Engineering, Sandtorstraße 1, 39106 Magdeburg, Germany. Electronic address:

Adaptation of continuous cell lines to growth in suspension in a chemically defined medium has significant advantages for design and optimization in manufacturing of biologicals. In this work, changes in the protein expression level during a step-wise adaptation of an adherent Madin Darby canine kidney (MDCK) cell line to suspension growth were analyzed. Therefore, three cell line adaptations were performed independently. Two adaptations were monitored closely to characterize short term changes in protein expression levels after serum deprivation. In addition, initial stages of suspension growth were analyzed for both adaptations. The third adaptation involved MDCK suspension cells (MDCKSUS2) grown over an extended time period to achieve robust growth characteristics. Here, cells of the final stage of adaptation were compared with their parental cell line (MDCKADH). A combination of two dimensional differential gel electrophoresis for relative protein quantification and tandem mass spectrometry for protein identification enabled insights into cellular physiology. The two closely monitored cell line adaptations followed different routes regarding specific changes in protein expression but resulted in similar proteome profiles at the initial stages of suspension growth analyzed. Compared to the MDCKADH cells more than 90% of all changes in the protein expression level were identified after serum deprivation and were related to cytoskeletal structure, genetic information processing and cellular metabolism. Myosin proteins, involved in cellular detachment by actin-myosin contractile mechanisms were also differentially expressed. Interestingly, for both of the two adaptations, proteins linked for tumorigenicity, like lactoylglutathione lyase and sulfotransferase 1A1 were differentially expressed. In contrast, none of these proteins were differentially expressed for the MDCKSUS2 cell line. Overall, proteomic monitoring allowed identification of key proteins involved in adaptation from adherent to suspension growth. In addition, identified proteins related to tumorigenicity may represent markers to support cell clone selection at early stages of industrial cell line development.
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http://dx.doi.org/10.1016/j.vaccine.2015.02.077DOI Listing
August 2015

Metaproteomics of complex microbial communities in biogas plants.

Microb Biotechnol 2015 Sep 15;8(5):749-63. Epub 2015 Apr 15.

Bioprocess Engineering, Otto von Guericke University Magdeburg, Universitätsplatz 2, Magdeburg, 39106, Germany.

Production of biogas from agricultural biomass or organic wastes is an important source of renewable energy. Although thousands of biogas plants (BGPs) are operating in Germany, there is still a significant potential to improve yields, e.g. from fibrous substrates. In addition, process stability should be optimized. Besides evaluating technical measures, improving our understanding of microbial communities involved into the biogas process is considered as key issue to achieve both goals. Microscopic and genetic approaches to analyse community composition provide valuable experimental data, but fail to detect presence of enzymes and overall metabolic activity of microbial communities. Therefore, metaproteomics can significantly contribute to elucidate critical steps in the conversion of biomass to methane as it delivers combined functional and phylogenetic data. Although metaproteomics analyses are challenged by sample impurities, sample complexity and redundant protein identification, and are still limited by the availability of genome sequences, recent studies have shown promising results. In the following, the workflow and potential pitfalls for metaproteomics of samples from full-scale BGP are discussed. In addition, the value of metaproteomics to contribute to the further advancement of microbial ecology is evaluated. Finally, synergistic effects expected when metaproteomics is combined with advanced imaging techniques, metagenomics, metatranscriptomics and metabolomics are addressed.
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http://dx.doi.org/10.1111/1751-7915.12276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4554464PMC
September 2015
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