Martin Taubert

Protein-based stable isotope probing

We describe a stable isotope probing (SIP) technique that was developed to link microbe-specific metabolic function to phylogenetic information. Carbon (13C)- or nitrogen (15N)-labeled substrates (typically with >98% heavy label) were used in cultivation experiments and the heavy isotope incorporation into proteins (protein-SIP) on growth was determined. The amount of incorporation provides a measure for assimilation of a substrate, and the sequence information from peptide analysis obtained by mass spectrometry delivers phylogenetic information about the microorganisms responsible for the metabolism of the particular substrate. In this article, we provide guidelines for incubating microbial cultures with labeled substrates and a protocol for protein-SIP. The protocol guides readers through the proteomics pipeline, including protein extraction, gel-free and gel-based protein separation, the subsequent mass spectrometric analysis of peptides and the calculation of the incorporation of stable isotopes into peptides. Extraction of proteins and the mass fingerprint measurements of unlabeled and labeled fractions can be performed in 2–3 d.

Protein-SIP enables time-resolved analysis of the carbon flux in a sulfate-reducing, benzene-degrading microbial consortium

Benzene is a major contaminant in various environments, but the mechanisms behind its biodegradation under strictly anoxic conditions are not yet entirely clear. Here we analyzed a benzene-degrading, sulfate-reducing enrichment culture originating from a benzene-contaminated aquifer by a metagenome-based functional metaproteomic approach, using protein-based stable isotope probing (protein-SIP). The time-resolved, quantitative analysis of carbon fluxes within the community supplied with either 13C-labeled benzene or 13C-labeled carbonate yielded different functional groups of organisms, with their peptides showing specific time dependencies of 13C relative isotope abundance indicating different carbon utilization. Through a detailed analysis of the mass spectrometric (MS) data, it was possible to quantify the utilization of the initial carbon source and the metabolic intermediates. The functional groups were affiliated to Clostridiales, Deltaproteobacteria and Bacteroidetes/Chlorobi. The Clostridiales-related organisms were involved in benzene degradation, putatively by fermentation, and additionally used significant amounts of carbonate as a carbon source. The other groups of organisms were found to perform diverse functions, with Deltaproteobacteria degrading fermentation products and Bacteroidetes/Chlorobi being putative scavengers feeding on dead cells. A functional classification of identified proteins supported this allocation and gave further insights into the metabolic pathways and the interactions between the community members. This example shows how protein-SIP can be applied to obtain temporal and phylogenetic information about functional interdependencies within microbial communities.

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes (13C, 15N, 36S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Protein-based stable isotope probing (protein-SIP) in functional metaproteomics

The community phenotype as the sum of molecular functions of organisms living in consortia strongly depends on interactions within these communities. Therefore, the analyses of the most significant molecules in terms of the phenotype, the proteins, have to be performed on samples without disrupting the meta-species environment. Due to the increasing genomic information, proteins provide insights into a potential molecular function and the phylogenetic structure of the community. Unfortunately, the lists of identified proteins are often based first on the technical capacity of the used methods or instruments, and second on the interpretation of them by the assignment of molecular functions to proteins in databases. Especially in non-model organisms the functions of many proteins are often not known and an increasing number of studies indicate a significant amount of uncertainty. To decrease the dependency on assumptions and to enable functional insights by metaproteome approaches, the metabolic labeling from an isotopically labeled substrate can be used. Since the metabolites deriving from the substrate are very rarely species-specific, the incorporation of the stable isotope into proteins can be used as a surrogate marker for metabolic activity. The degree of incorporation can be determined accurately on the peptide level by mass spectrometry; additionally, the peptide sequence provides information on the metabolic active species. Thereby, protein-stable isotope probing (protein-SIP) adds functional information to metaproteome approaches. The classical metaproteome approaches will be reviewed with an emphasis on their attempts towards functional interpretation. The gain from functional insights into metaproteomics by using metabolic labeling of stable isotopes of carbon, nitrogen, and sulfur is reviewed with a focus on the techniques of measurement, calculation of incorporation and data processing.

XoxF encoding an alternative methanol dehydrogenase is widespread in coastal marine environments

The xoxF gene, encoding a pyrroloquinoline quinone-dependent methanol dehydrogenase, is found in all known proteobacterial methylotrophs. In several newly discovered methylotrophs, XoxF is the active methanol dehydrogenase, catalysing the oxidation of methanol to formaldehyde. Apart from that, its potential role in methylotrophy and carbon cycling is unknown. So far, the diversity of xoxF in the environment has received little attention. We designed PCR primer sets targeting clades of the xoxF gene, and used 454 pyrosequencing of PCR amplicons obtained from the DNA of four coastal marine environments for a unique assessment of the diversity of xoxF in these habitats. Phylogenetic analysis of the data obtained revealed a high diversity of xoxF genes from two of the investigated clades, and substantial differences in sequence composition between environments. Sequences were classified as being related to a wide range of both methylotrophs and non-methylotrophs from Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria. The most prominent sequences detected were related to the family Rhodobacteraceae, the genus Methylotenera and the OM43 clade of Methylophilales, and are thus related to organisms that employ XoxF for methanol oxidation. Furthermore, our analyses revealed a high degree of so far undescribed sequences, suggesting a high number of unknown bacterial species in these habitats.

Time resolved protein-based stable isotope probing (Protein-SIP) analysis allows quantification of induced proteins in substrate shift experiments

The detection of induced proteins after introduction of specific substrates in culture is of high interest for a comparative description of organisms growing under different conditions. In this study, protein‐based stable isotope probing (Protein‐SIP) is used for a fast and reliable detection of newly synthesized proteins in a substrate shift experiment. Therefore, Pseudomonas putida ML2 cells precultured on 12C‐acetate and 12C‐benzene, respectively, were incubated with 13C‐benzene as a stable‐isotope‐labeled substrate. Protein samples from early to stationary growth phase were separated by one‐dimensional gel electrophoresis (1‐DE), subsequently tryptically digested, and analyzed by UPLC Orbitrap MS/MS measurements. Identified peptides from proteins involved in aerobic benzene degradation as well as from housekeeping proteins were chosen to calculate the labeling ratio (proportion of labeled protein to total protein) at different time points. A comparison of parameters from a nonlinear regression analysis of the calculated data enabled a clear differentiation between induced and constitutively expressed proteins. Thus, Protein‐SIP has proven to be a valuable tool for quantitative analysis of induced proteins in substrate shift experiments.

Comparison of methods for simultaneous identification of bacterial species and determination of metabolic activity by protein-based stable isotope probing (Protein-SIP) experiments.

We developed a concept for analysing carbon and nitrogen fluxes in microbial communities by employing protein-based stable isotope probing (Protein-SIP) in metabolic labelling experiments with stable isotope labelled substrates. For identification of microbial species intact protein profiling (IPP) can be used, whereas the assessment of their metabolic activity is achieved by shotgun mass mapping (SMM). Microbial cultures were grown on substrates containing (13)C or (15)N. For identification of species we tested both the IPP and the SMM approaches. Mass spectra (MALDI-MS) were taken from mixtures of either intact proteins or peptides from tryptic digestion for generating species-specific peak patterns. In the case of SMM, the fragmentation of peptides was additionally used to obtain sequence information for species identification. Mass spectra of peptide sequences allow calculation of the amount of (13)C or (15)N incorporation within peptides for determining metabolic activity of the specific species. The comparison of IPP and SMM revealed a higher robustness of species identification by SMM. In addition, the assessment of incorporation levels of (13)C and (15)N into peptides by SMM revealed a lower uncertainty (0.5-0.8 atom %) compared to IPP (6.4-8.9 atom %). The determination of metabolic activity and function of individual species by Protein-SIP can help to analyse carbon and nitrogen fluxes within microbial communities.

Decarboxylating and Nondecarboxylating Glutaryl-Coenzyme A Dehydrogenases in the Aromatic Metabolism of Obligately Anaerobic Bacteria

In anaerobic bacteria using aromatic growth substrates, glutaryl-coenzyme A (CoA) dehydrogenases (GDHs) are involved in the catabolism of the central intermediate benzoyl-CoA to three acetyl-CoAs and CO(2). In this work, we studied GDHs from the strictly anaerobic, aromatic compound-degrading organisms Geobacter metallireducens (GDH(Geo)) (Fe[III] reducing) and Desulfococcus multivorans (GDH(Des)) (sulfate reducing). GDH(Geo) was purified from cells grown on benzoate and after the heterologous expression of the benzoate-induced bamM gene. The gene coding for GDH(Des) was identified after screening of a cosmid gene library. Reverse transcription-PCR revealed that its expression was induced by benzoate; the product was heterologously expressed and isolated. Both wild-type and recombinant GDH(Geo) catalyzed the oxidative decarboxylation of glutaryl-CoA to crotonyl-CoA at similar rates. In contrast, recombinant GDH(Des) catalyzed only the dehydrogenation to glutaconyl-CoA. The latter compound was decarboxylated subsequently to crotonyl-CoA by the addition of membrane extracts from cells grown on benzoate in the presence of 20 mM NaCl. All GDH enzymes were purified as homotetramers of a 43- to 44-kDa subunit and contained 0.6 to 0.7 flavin adenine dinucleotides (FADs)/monomer. The kinetic properties for glutaryl-CoA conversion were as follows: for GDH(Geo), the K(m) was 30 +/- 2 microM and the V(max) was 3.2 +/- 0.2 micromol min(-1) mg(-1), and for GDH(Des), the K(m) was 52 +/- 5 microM and the V(max) was 11 +/- 1 micromol min(-1) mg(-1). GDH(Des) but not GDH(Geo) was inhibited by glutaconyl-CoA. Highly conserved amino acid residues that were proposed to be specifically involved in the decarboxylation of the intermediate glutaconyl-CoA were identified in GDH(Geo) but are missing in GDH(Des). The differential use of energy-yielding/energy-demanding enzymatic processes in anaerobic bacteria that degrade aromatic compounds is discussed in view of phylogenetic relationships and constraints of overall energy metabolism.

Combining metagenomics with metaproteomics and stable isotope probing reveals metabolic pathways used by a naturally occurring marine methylotroph

A variety of culture-independent techniques have been developed that can be used in conjunction with culture-dependent physiological and metabolic studies of key microbial organisms in order to better understand how the activity of natural populations influences and regulates all major biogeochemical cycles. In this study, we combined deoxyribonucleic acid-stable isotope probing (DNA-SIP) with metagenomics and metaproteomics to characterize an uncultivated marine methylotroph that actively incorporated carbon from (13) C-labeled methanol into biomass. By metagenomic sequencing of the heavy DNA, we retrieved virtually the whole genome of this bacterium and determined its metabolic potential. Through protein-stable isotope probing, the RuMP cycle was established as the main carbon assimilation pathway, and the classical methanol dehydrogenase-encoding gene mxaF, as well as three out of four identified xoxF homologues were found to be expressed. This proof-of-concept study is the first in which the culture-independent techniques of DNA-SIP and protein-SIP have been used to characterize the metabolism of a naturally occurring Methylophaga-like bacterium in the marine environment (i.e. Methylophaga thiooxydans L4) and thus provides a powerful approach to access the genome and proteome of uncultivated microbes involved in key processes in the environment.

MetaProSIP: Automated Inference of Stable Isotope Incorporation Rates in Proteins for Functional Metaproteomics

We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and complexity of mass spectrometric data in protein-SIP experiments pose new challenges for data analysis. Together with a flexible experimental setup, the novel bioinformatics tool MetaProSIP offers an automated high-throughput solution for a wide range of (13)C or (15)N protein-SIP experiments with special emphasis on the analysis of metaproteomic experiments where differential labeling of organisms can occur. The information calculated in MetaProSIP includes the determination of multiple relative isotopic abundances, the labeling ratio between old and new synthesized proteins, and the shape of the isotopic distribution. These parameters define the metabolic capacities and dynamics within the investigated microbial culture. MetaProSIP features a high degree of reproducibility, reliability, and quality control reporting. The ability to embed into the OpenMS framework allows for flexible construction of custom-tailored workflows. Software and documentation are available under an open-source license at www.openms.de/MetaProSIP.