Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles

MAPLE: A Microbiome Analysis Pipeline Enabling Optimal Peptide Search and Comparative Taxonomic and Functional Analysis

Metaproteomics by mass spectrometry (MS) is a powerful approach to profile a large number of proteins expressed by all organisms in a highly complex biological or ecological sample, which is able to provide a direct and quantitative assessment of the functional makeup of a microbiota. The human gastrointestinal microbiota has been found playing important roles in human physiology and health, and metaproteomics has been shown to shed light on multiple novel associations between microbiota and diseases. MS-powered proteomics generally relies on genome data to define search space. However, metaproteomics, which simultaneously analyzes all proteins from hundreds to thousands of species, faces significant challenges regarding database search and interpretation of results. To overcome these obstacles, we have developed a user-friendly microbiome analysis pipeline (MAPLE, freely downloadable at http://maple.rx.umaryland.edu/), which is able to define an optimal search space by inferring proteomes specific to samples following the principle of parsimony. MAPLE facilitates highly comparable or better peptide identification compared to a sample-specific metagenome-guided search. In addition, we implemented an automated peptide-centric enrichment analysis function in MAPLE to address issues of traditional protein-centric comparison, enabling straightforward and comprehensive comparison of taxonomic and functional makeup between microbiota.

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota

Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

Adaptation of Carbon Source Utilization Patterns of Geobacter metallireducens During Sessile Growth

There are two main strategies known how microorganisms regulate substrate utilization: specialization on one preferred substrate at high concentrations in batch cultures or simultaneous utilization of many substrates at low concentrations in chemostats. However, it remains unclear how microorganisms utilize substrates at low concentrations in the subsurface: do they focus on a single substrate and exhibit catabolite repression or do they de-repress regulation of all catabolic pathways? Here, we investigated the readiness of Geobacter metallireducens to degrade organic substrates under sessile growth in sediment columns in the presence of a mixed community as a model for aquifers. Three parallel columns were filled with sand and flushed with anoxic medium at a constant inflow (18 ml h-1) of the substrate benzoate (1 mM) with non-limiting nitrate concentrations (30 mM) as electron acceptor. Columns were inoculated with the anaerobic benzoate degrader G. metallireducens. Microbial degradation produced concentration gradients of benzoate toward the column outlet. Metagenomics and label-free metaproteomics were used to detect and quantify the protein expression of G. metallireducens. Bulk benzoate concentrations below 0.2 mM led to increased abundance of catabolic proteins involved in utilization of fermentation products and aromatic compounds including the complete upregulation of the toluene-degrading pathway although toluene was not added to the medium. We propose that under sessile conditions and low substrate concentrations G. metallireducens expresses a specific set of catabolic pathways for preferred substrates, even when these substrates are not present.

Specialized proteomic responses and an ancient photoprotection mechanism sustain marine green algal growth during phosphate limitation

Marine algae perform approximately half of global carbon fixation, but their growth is often limited by the availability of phosphate or other nutrients^1,2. As oceans warm, the area of phosphate-limited surface waters is predicted to increase, resulting in ocean desertification^3,4. Understanding the responses of key eukaryotic phytoplankton to nutrient limitation is therefore critical^5,6. We used advanced photo-bioreactors to investigate how the widespread marine green alga Micromonas commoda grows under transitions from replete nutrients to chronic phosphate limitation and subsequent relief, analysing photosystem changes and broad cellular responses using proteomics, transcriptomics and biophysical measurements. We find that physiological and protein expression responses previously attributed to stress are critical to supporting stable exponential growth when phosphate is limiting. Unexpectedly, the abundance of most proteins involved in light harvesting does not change, but an ancient light-harvesting-related protein, LHCSR, is induced and dissipates damaging excess absorbed light as heat throughout phosphate limitation. Concurrently, a suite of uncharacterized proteins with narrow phylogenetic distributions increase multifold. Notably, of the proteins that exhibit significant changes, 70% are not differentially expressed at the mRNA transcript level, highlighting the importance of post-transcriptional processes in microbial eukaryotes. Nevertheless, transcript-protein pairs with concordant changes were identified that will enable more robust interpretation of eukaryotic phytoplankton responses in the field from metatranscriptomic studies. Our results show that P-limited Micromonas responds quickly to a fresh pulse of phosphate by rapidly increasing replication, and that the protein network associated with this ability is composed of both conserved and phylogenetically recent proteome systems that promote dynamic phosphate homeostasis. That an ancient mechanism for mitigating light stress is central to sustaining growth during extended phosphate limitation highlights the possibility of interactive effects arising from combined stressors under ocean change, which could reduce the efficacy of algal strategies for optimizing marine photosynthesis.

Combined iron and sulfate reduction biostimulation as a novel approach to enhance BTEX and PAH source-zone biodegradation in biodiesel blend-contaminated groundwater

The use of biodiesel as a transportation fuel and its growing mandatory blending percentage in diesel increase the likelihood of contaminating groundwater with diesel/biodiesel blends. A 100L-field experiment with B20 (20% biodiesel and 80% diesel, v/v) was conducted to assess the potential for the combined biostimulation of iron and sulfate reducing bacteria to enhance BTEX and PAH biodegradation in a diesel/biodiesel blend-contaminated groundwater. A B20 field experiment under monitored natural attenuation (MNA) was used as a baseline control. Ammonium acetate and a low-cost and sustainable product recovered from acid mine drainage treatment were used to stimulate iron and sulfate-reducing conditions. As a result, benzene and naphthalene concentrations (maximum concentrations were 28.1μgL^-1 and 10.0μgL^-1, respectively) remained lower than the MNA experiment (maximum concentrations were 974.7μgL^-1 and 121.3μgL^-1, respectively) over the whole experiment. Geochemical changes were chronologically consistent with the temporal change of the predominance of Geobacter and GOUTA19 which might be the key players responsible for the rapid attenuation of benzene and naphthalene. To the best of our knowledge, this is the first field experiment to demonstrate the potential for the combined iron and sulfate biostimulation to enhance B20 source-zone biodegradation.

Metatranscriptomic Analysis Reveals Unexpectedly Diverse Microbial Metabolism in a Biogeochemical Hot Spot in an Alluvial Aquifer

Organic matter deposits in alluvial aquifers have been shown to result in the formation of naturally reduced zones (NRZs), which can modulate aquifer redox status and influence the speciation and mobility of metals, affecting groundwater geochemistry. In this study, we sought to better understand how natural organic matter fuels microbial communities within anoxic biogeochemical hot spots (NRZs) in a shallow alluvial aquifer at the Rifle (CO) site. We conducted a 20-day microcosm experiment in which NRZ sediments, which were enriched in buried woody plant material, served as the sole source of electron donors and microorganisms. The microcosms were constructed and incubated under anaerobic conditions in serum bottles with an initial N₂ headspace and were sampled every 5 days for metagenome and metatranscriptome profiles in combination with biogeochemical measurements. Biogeochemical data indicated that the decomposition of native organic matter occurred in different phases, beginning with mineralization of dissolved organic matter (DOM) to CO₂ during the first week of incubation, followed by a pulse of acetogenesis that dominated carbon flux after 2 weeks. A pulse of methanogenesis co-occurred with acetogenesis, but only accounted for a small fraction of carbon flux. The depletion of DOM over time was strongly correlated with increases in expression of many genes associated with heterotrophy (e.g., amino acid, fatty acid, and carbohydrate metabolism) belonging to a Hydrogenophaga strain that accounted for a relatively large percentage (~8%) of the metatranscriptome. This Hydrogenophaga strain also expressed genes indicative of chemolithoautotrophy, including CO₂ fixation, H₂ oxidation, S-compound oxidation, and denitrification. The pulse of acetogenesis appears to have been collectively catalyzed by a number of different organisms and metabolisms, most prominently pyruvate:ferredoxin oxidoreductase. Unexpected genes were identified among the most highly expressed (>98th percentile) transcripts, including acetone carboxylase and cell-wall-associated hydrolases with unknown substrates (numerous lesser expressed cell-wall-associated hydrolases targeted peptidoglycan). Many of the most highly expressed hydrolases belonged to a Ca. Bathyarchaeota strain and may have been associated with recycling of bacterial biomass. Overall, these results highlight the complex nature of organic matter transformation in NRZs and the microbial metabolic pathways that interact to mediate redox status and elemental cycling.

The impact of sequence database choice on metaproteomic results in gut microbiota studies

BACKGROUND

Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification.

RESULTS

Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields.

CONCLUSIONS

This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources.

Metagenomic applications in environmental monitoring and bioremediation

With the rapid advances in sequencing technology, the cost of sequencing has dramatically dropped and the scale of sequencing projects has increased accordingly. This has provided the opportunity for the routine use of sequencing techniques in the monitoring of environmental microbes. While metagenomic applications have been routinely applied to better understand the ecology and diversity of microbes, their use in environmental monitoring and bioremediation is increasingly common. In this review we seek to provide an overview of some of the metagenomic techniques used in environmental systems biology, addressing their application and limitation. We will also provide several recent examples of the application of metagenomics to bioremediation. We discuss examples where microbial communities have been used to predict the presence and extent of contamination, examples of how metagenomics can be used to characterize the process of natural attenuation by unculturable microbes, as well as examples detailing the use of metagenomics to understand the impact of biostimulation on microbial communities.

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga Micromonas pusilla

Micromonas is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of Micromonas pusilla CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3’ UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga Micromonas.

ConsPred: a rule-based (re-)annotation framework for prokaryotic genomes

MOTIVATION

The rapidly growing number of available prokaryotic genome sequences requires fully automated and high-quality software solutions for their initial and re-annotation. Here we present ConsPred, a prokaryotic genome annotation framework that performs intrinsic gene predictions, homology searches, predictions of non-coding genes as well as CRISPR repeats and integrates all evidence into a consensus annotation. ConsPred achieves comprehensive, high-quality annotations based on rules and priorities, similar to decision-making in manual curation and avoids conflicting predictions. Parameters controlling the annotation process are configurable by the user. ConsPred has been used in the institutions of the authors for longer than 5 years and can easily be extended and adapted to specific needs.

SUMMARY

The ConsPred algorithm for producing a consensus from the varying scores of multiple gene prediction programs approaches manual curation in accuracy. Its rule-based approach for choosing final predictions avoids overriding previous manual curations.

AVAILABILITY AND IMPLEMENTATION

ConsPred is implemented in Java, Perl and Shell and is freely available under the Creative Commons license as a stand-alone in-house pipeline or as an Amazon Machine Image for cloud computing, see https://sourceforge.net/projects/conspred/.

CONTACT

thomas.rattei@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.

Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants

Background

Prasinophytes are widespread marine green algae that are related to plants. Cellular abundance of the prasinophyte Micromonas has reportedly increased in the Arctic due to climate-induced changes. Thus, studies of these unicellular eukaryotes are important for marine ecology and for understanding Viridiplantae evolution and diversification.

Results

We generated evidence-based Micromonas gene models using proteomics and RNA-Seq to improve prasinophyte genomic resources. First, sequences of four chromosomes in the 22 Mb Micromonas pusilla (CCMP1545) genome were finished. Comparison with the finished 21 Mb genome of Micromonas commoda (RCC299; named herein) shows they share ≤8,141 of ~10,000 protein-encoding genes, depending on the analysis method. Unlike RCC299 and other sequenced eukaryotes, CCMP1545 has two abundant repetitive intron types and a high percent (26 %) GC splice donors. Micromonas has more genus-specific protein families (19 %) than other genome sequenced prasinophytes (11 %). Comparative analyses using predicted proteomes from other prasinophytes reveal proteins likely related to scale formation and ancestral photosynthesis. Our studies also indicate that peptidoglycan (PG) biosynthesis enzymes have been lost in multiple independent events in select prasinophytes and plants. However, CCMP1545, polar Micromonas CCMP2099 and prasinophytes from other classes retain the entire PG pathway, like moss and glaucophyte algae. Surprisingly, multiple vascular plants also have the PG pathway, except the Penicillin-Binding Protein, and share a unique bi-domain protein potentially associated with the pathway. Alongside Micromonas experiments using antibiotics that halt bacterial PG biosynthesis, the findings highlight unrecognized phylogenetic complexity in PG-pathway retention and implicate a role in chloroplast structure or division in several extant Viridiplantae lineages.

Conclusions

Extensive differences in gene loss and architecture between related prasinophytes underscore their divergence. PG biosynthesis genes from the cyanobacterial endosymbiont that became the plastid, have been selectively retained in multiple plants and algae, implying a biological function. Our studies provide robust genomic resources for emerging model algae, advancing knowledge of marine phytoplankton and plant evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2585-6) contains supplementary material, which is available to authorized users.

Impact of Organic Carbon Electron Donors on Microbial Community Development under Iron- and Sulfate-Reducing Conditions

Although iron- and sulfate-reducing bacteria in subsurface environments have crucial roles in biogeochemical cycling of C, Fe, and S, how specific electron donors impact the compositional structure and activity of native iron- and/or sulfate-reducing communities is largely unknown. To understand this better, we created bicarbonate-buffered batch systems in duplicate with three different electron donors (acetate, lactate, or glucose) paired with ferrihydrite and sulfate as the electron acceptors and inoculated them with subsurface sediment as the microbial inoculum. Sulfate and ferrihydrite reduction occurred simultaneously and were faster with lactate than with acetate. 16S rRNA-based sequence analysis of the communities over time revealed that Desulfotomaculum was the major driver for sulfate reduction coupled with propionate oxidation in lactate-amended incubations. The reduction of sulfate resulted in sulfide production and subsequent abiotic reduction of ferrihydrite. In contrast, glucose promoted faster reduction of ferrihydrite, but without reduction of sulfate. Interestingly, the glucose-amended incubations led to two different biogeochemical trajectories among replicate bottles that resulted in distinct coloration (white and brown). The two outcomes in geochemical evolution might be due to the stochastic evolution of the microbial communities or subtle differences in the initial composition of the fermenting microbial community and its development via the use of different glucose fermentation pathways available within the community. Synchrotron-based x-ray analysis indicated that siderite and amorphous Fe(II) were formed in the replicate bottles with glucose, while ferrous sulfide and vivianite were formed with lactate or acetate. These data sets reveal that use of different C utilization pathways projects significant changes in microbial community composition over time that uniquely impact both the geochemistry and mineralogy of subsurface environments.

Prediction of microbial phenotypes based on comparative genomics

The accessibility of almost complete genome sequences of uncultivable microbial species from metagenomes necessitates computational methods predicting microbial phenotypes solely based on genomic data. Here we investigate how comparative genomics can be utilized for the prediction of microbial phenotypes. The PICA framework facilitates application and comparison of different machine learning techniques for phenotypic trait prediction. We have improved and extended PICA's support vector machine plug-in and suggest its applicability to large-scale genome databases and incomplete genome sequences.

We have demonstrated the stability of the predictive power for phenotypic traits, not perturbed by the rapid growth of genome databases. A new software tool facilitates the in-depth analysis of phenotype models, which associate expected and unexpected protein functions with particular traits. Most of the traits can be reliably predicted in only 60-70% complete genomes. We have established a new phenotypic model that predicts intracellular microorganisms. Thereby we could demonstrate that also independently evolved phenotypic traits, characterized by genome reduction, can be reliably predicted based on comparative genomics.

Our results suggest that the extended PICA framework can be used to automatically annotate phenotypes in near-complete microbial genome sequences, as generated in large numbers in current metagenomics studies.

Identification of Bacteria Synthesizing Ribosomal RNA in Response to Uranium Addition During Biostimulation at the Rifle, CO Integrated Field Research Site

Understanding which organisms are capable of reducing uranium at historically contaminated sites provides crucial information needed to evaluate treatment options and outcomes. One approach is determination of the bacteria which directly respond to uranium addition. In this study, uranium amendments were made to groundwater samples from a site of ongoing biostimulation with acetate. The active microbes in the planktonic phase were deduced by monitoring ribosomes production via RT-PCR. The results indicated several microorganisms were synthesizing ribosomes in proportion with uranium amendment up to 2 μM. Concentrations of U (VI) >2 μM were generally found to inhibit ribosome synthesis. Two active bacteria responding to uranium addition in the field were close relatives of Desulfobacter postgateii and Geobacter bemidjiensis. Since RNA content often increases with growth rate, our findings suggest it is possible to rapidly elucidate active bacteria responding to the addition of uranium in field samples and provides a more targeted approach to stimulate specific populations to enhance radionuclide reduction in contaminated sites.

Proteomic tools to decipher microbial community structure and functioning

Recent advances in microbial ecology allow studying microorganisms in their environment, without laboratory cultivation, in order to get access to the large uncultivable microbial community. With this aim, environmental proteomics has emerged as an appropriate complementary approach to metagenomics providing information on key players that carry out main metabolic functions and addressing the adaptation capacities of living organisms in situ. In this review, a wide range of proteomic approaches applied to investigate the structure and functioning of microbial communities as well as recent examples of such studies are presented.

Functional environmental proteomics: elucidating the role of a c-type cytochrome abundant during uranium bioremediation

Studies with pure cultures of dissimilatory metal-reducing microorganisms have demonstrated that outer-surface c-type cytochromes are important electron transfer agents for the reduction of metals, but previous environmental proteomic studies have typically not recovered cytochrome sequences from subsurface environments in which metal reduction is important. Gel-separation, heme-staining and mass spectrometry of proteins in groundwater from in situ uranium bioremediation experiments identified a putative c-type cytochrome, designated Geobacter subsurface c-type cytochrome A (GscA), encoded within the genome of strain M18, a Geobacter isolate previously recovered from the site. Homologs of GscA were identified in the genomes of other Geobacter isolates in the phylogenetic cluster known as subsurface clade 1, which predominates in a diversity of Fe(III)-reducing subsurface environments. Most of the gscA sequences recovered from groundwater genomic DNA clustered in a tight phylogenetic group closely related to strain M18. GscA was most abundant in groundwater samples in which Geobacter sp. predominated. Expression of gscA in a strain of Geobacter sulfurreducens that lacked the gene for the c-type cytochrome OmcS, thought to facilitate electron transfer from conductive pili to Fe(III) oxide, restored the capacity for Fe(III) oxide reduction. Atomic force microscopy provided evidence that GscA was associated with the pili. These results demonstrate that a c-type cytochrome with an apparent function similar to that of OmcS is abundant when Geobacter sp. are abundant in the subsurface, providing insight into the mechanisms for the growth of subsurface Geobacter sp. on Fe(III) oxide and suggesting an approach for functional analysis of other Geobacter proteins found in the subsurface.

Changes in protein expression across laboratory and field experiments in Geobacter bemidjiensis

Bacterial extracellular metal respiration, as carried out by members of the genus Geobacter, is of interest for applications including microbial fuel cells and bioremediation. Geobacter bemidjiensis is the major species whose growth is stimulated during groundwater amendment with acetate. We have carried out label-free proteomics studies of G. bemidjiensis grown with acetate as the electron donor and either fumarate, ferric citrate, or one of two hydrous ferric oxide mineral types as electron acceptor. The major class of proteins whose expression changes across these conditions is c-type cytochromes, many of which are known to be involved in extracellular metal reduction in other, better-characterized Geobacter species. Some proteins with multiple homologues in G. bemidjiensis (OmcS, OmcB) had different expression patterns than observed for their G. sulfurreducens homologues under similar growth conditions. We also compared the proteome from our study to a prior proteomics study of biomass recovered from an aquifer in Colorado, where the microbial community was dominated by strains closely related to G. bemidjiensis. We detected an increased number of proteins with functions related to motility and chemotaxis in the Colorado field samples compared to the laboratory samples, suggesting the importance of motility for in situ extracellular metal respiration.

Integrated 'omics analysis for studying the microbial community response to a pH perturbation of a cellulose-degrading bioreactor culture

Integrated 'omics have been used on pure cultures and co-cultures, yet they have not been applied to complex microbial communities to examine questions of perturbation response. In this study, we used integrated 'omics to measure the perturbation response of a cellulose-degrading bioreactor community fed with microcrystalline cellulose (Avicel). We predicted that a pH decrease by addition of a pulse of acid would reduce microbial community diversity and temporarily reduce reactor function in terms of cellulose degradation. However, 16S rDNA gene pyrosequencing results revealed increased alpha diversity in the microbial community after the perturbation, and a persistence of the dominant community members over the duration of the experiment. Proteomics results showed a decrease in activity of proteins associated with Fibrobacter succinogenes 2 days after the perturbation followed by increased protein abundances 6 days after the perturbation. The decrease in cellulolytic activity suggested by the proteomics was confirmed by the accumulation of Avicel in the reactor. Metabolomics showed a pattern similar to that of the proteome, with amino acid production decreasing 2 days after the perturbation and increasing after 6 days. This study demonstrated that community 'omics data provide valuable information about the interactions and function of anaerobic cellulolytic community members after a perturbation.

Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities

Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

Bioinformatic progress and applications in metaproteogenomics for bridging the gap between genomic sequences and metabolic functions in microbial communities

Metaproteomics of microbial communities promises to add functional information to the blueprint of genes derived from metagenomics. Right from its beginning, the achievements and developments in metaproteomics were closely interlinked with metagenomics. In addition, the evaluation, visualization, and interpretation of metaproteome data demanded for the developments in bioinformatics. This review will give an overview about recent strategies to use genomic data either from public databases or organismal specific genomes/metagenomes to increase the number of identified proteins obtained by mass spectrometric measurements. We will review different published metaproteogenomic approaches in respect to the used MS pipeline and to the used protein identification workflow. Furthermore, different approaches of data visualization and strategies for phylogenetic interpretation of metaproteome data are discussed as well as approaches for functional mapping of the results to the investigated biological systems. This information will in the end allow a comprehensive analysis of interactions and 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 ((13)C, (15)N, (36)S) 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.

Metaproteomics: harnessing the power of high performance mass spectrometry to identify the suite of proteins that control metabolic activities in microbial communities

The availability of extensive genome information for many different microbes, including unculturable species in mixed communities from environmental samples, has enabled systems-biology interrogation by providing a means to access genomic, transcriptomic, and proteomic information. To this end, metaproteomics exploits the power of high-performance mass spectrometry for extensive characterization of the complete suite of proteins expressed by a microbial community in an environmental sample.

Insights into the structure and metabolic function of microbes that shape pelagic iron-rich aggregates ("iron snow")

Microbial ferrous iron [Fe(II)] oxidation leads to the formation of iron-rich macroscopic aggregates ("iron snow") at the redoxcline in a stratified lignite mine lake in east-central Germany. We aimed to identify the abundant Fe-oxidizing and Fe-reducing microorganisms likely to be involved in the formation and transformation of iron snow present in the redoxcline in two basins of the lake that differ in their pH values. Nucleic acid- and lipid-stained microbial cells of various morphologies detected by confocal laser scanning microscopy were homogeneously distributed in all iron snow samples. The dominant iron mineral appeared to be schwertmannite, with shorter needles in the northern than in the central basin samples. Total bacterial 16S rRNA gene copies ranged from 5.0 × 10(8) copies g (dry weight)(-1) in the acidic central lake basin (pH 3.3) to 4.0 × 10(10) copies g (dry weight)(-1) in the less acidic (pH 5.9) northern basin. Total RNA-based quantitative PCR assigned up to 61% of metabolically active microbial communities to Fe-oxidizing- and Fe-reducing-related bacteria, indicating that iron metabolism was an important metabolic strategy. Molecular identification of abundant groups suggested that iron snow surfaces were formed by chemoautotrophic iron oxidizers, such as Acidimicrobium, Ferrovum, Acidithiobacillus, Thiobacillus, and Chlorobium, in the redoxcline and were rapidly colonized by heterotrophic iron reducers, such as Acidiphilium, Albidiferax-like, and Geobacter-like groups. Metaproteomics yielded 283 different proteins from northern basin iron snow samples, and protein identification provided a glimpse into some of their in situ metabolic processes, such as primary production (CO2 fixation), respiration, motility, and survival strategies.

Biostimulation induces syntrophic interactions that impact C, S and N cycling in a sediment microbial community

Stimulation of subsurface microorganisms to induce reductive immobilization of metals is a promising approach for bioremediation, yet the overall microbial community response is typically poorly understood. Here we used proteogenomics to test the hypothesis that excess input of acetate activates complex community functioning and syntrophic interactions among autotrophs and heterotrophs. A flow-through sediment column was incubated in a groundwater well of an acetate-amended aquifer and recovered during microbial sulfate reduction. De novo reconstruction of community sequences yielded near-complete genomes of Desulfobacter (Deltaproteobacteria), Sulfurovum- and Sulfurimonas-like Epsilonproteobacteria and Bacteroidetes. Partial genomes were obtained for Clostridiales (Firmicutes) and Desulfuromonadales-like Deltaproteobacteria. The majority of proteins identified by mass spectrometry corresponded to Desulfobacter-like species, and demonstrate the role of this organism in sulfate reduction (Dsr and APS), nitrogen fixation and acetate oxidation to CO2 during amendment. Results indicate less abundant Desulfuromonadales, and possibly Bacteroidetes, also actively contributed to CO2 production via the tricarboxylic acid (TCA) cycle. Proteomic data indicate that sulfide was partially re-oxidized by Epsilonproteobacteria through nitrate-dependent sulfide oxidation (using Nap, Nir, Nos, SQR and Sox), with CO2 fixed using the reverse TCA cycle. We infer that high acetate concentrations, aimed at stimulating anaerobic heterotrophy, led to the co-enrichment of, and carbon fixation in Epsilonproteobacteria. Results give an insight into ecosystem behavior following addition of simple organic carbon to the subsurface, and demonstrate a range of biological processes and community interactions were stimulated.

Persistence of uranium groundwater plumes: contrasting mechanisms at two DOE sites in the groundwater-river interaction zone

We examine subsurface uranium (U) plumes at two U.S. Department of Energy sites that are located near large river systems and are influenced by groundwater-river hydrologic interaction. Following surface excavation of contaminated materials, both sites were projected to naturally flush remnant uranium contamination to levels below regulatory limits (e.g., 30 μg/L or 0.126 μmol/L; U.S. EPA drinking water standard), with 10 years projected for the Hanford 300 Area (Columbia River) and 12 years for the Rifle site (Colorado River). The rate of observed uranium decrease was much lower than expected at both sites. While uncertainty remains, a comparison of current understanding suggests that the two sites have common, but also different mechanisms controlling plume persistence. At the Hanford 300 A, the persistent source is adsorbed U(VI) in the vadose zone that is released to the aquifer during spring water table excursions. The release of U(VI) from the vadose zone and its transport within the oxic, coarse-textured aquifer sediments is dominated by kinetically-limited surface complexation. Modeling implies that annual plume discharge volumes to the Columbia River are small (<one pore volume). At the Rifle site, slow oxidation of naturally reduced, contaminant U(IV) in the saturated zone and a continuous influx of U(VI) from natural, up-gradient sources influence plume persistence. Rate-limited mass transfer and surface complexation also control U(VI) migration velocity in the sub-oxic Rifle groundwater. Flux of U(VI) from the vadose zone at the Rifle site may be locally important, but it is not the dominant process that sustains the plume. A wide range in microbiologic functional diversity exists at both sites. Strains of Geobacter and other metal reducing bacteria are present at low natural abundance that are capable of enzymatic U(VI) reduction in localized zones of accumulated detrital organic carbon or after organic carbon amendment. Major differences between the sites include the geochemical nature of residual, contaminant U; the rates of current kinetic processes (both biotic and abiotic) influencing U(VI) solid-liquid distribution; the presence of detrital organic matter and the resulting spatial heterogeneity in microbially-driven redox properties; and the magnitude of groundwater hydrologic dynamics controlled by river-stage fluctuations, geologic structures, and aquifer hydraulic properties. The comparative analysis of these sites provides important guidance to the characterization, understanding, modeling, and remediation of groundwater contaminant plumes influenced by surface water interaction that are common world-wide.

MultiAlign: a multiple LC-MS analysis tool for targeted omics analysis

Background

MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and chromatographic elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. For example, clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs.

Results

MultiAlign was applied to two large proteomics datasets obtained from liquid chromatography-mass spectrometry analyses of environmental samples. Peptides in the datasets for a microbial community that had a known metagenome were identified by matching mass and elution time features to those in an established reference peptide database. Results compared favorably with those obtained using existing tools such as VIPER, but with the added benefit of being able to trace clusters of peptides across conditions to existing tandem mass spectra. MultiAlign was further applied to detect clusters across experimental samples derived from a reactor biomass community for which no metagenome was available. Several clusters were culled for further analysis to explore changes in the community structure. Lastly, MultiAlign was applied to liquid chromatography-mass spectrometry-based datasets obtained from a previously published study of wild type and mitochondrial fatty acid oxidation enzyme knockdown mutants of human hepatocarcinoma to demonstrate its utility for analyzing metabolomics datasets.

Conclusion

MultiAlign is an efficient software package for finding similar analytes across multiple liquid chromatography-mass spectrometry feature maps, as demonstrated here for both proteomics and metabolomics experiments. The software is particularly useful for proteomic studies where little or no genomic context is known, such as with environmental proteomics.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

Timing the onset of sulfate reduction over multiple subsurface acetate amendments by measurement and modeling of sulfur isotope fractionation

Stable isotope fractionations of sulfur are reported for three consecutive years of acetate-enabled uranium bioremediation at the US Department of Energy's Rifle Integrated Field Research Challenge (IFRC) site. The data show a previously undocumented decrease in the time between acetate addition and the onset of sulfate reducing conditions over subsequent amendments, from 20 days in the 2007 experiment to 4 days in the 2009 experiment. Increased sulfide concentrations were observed at the same time as δ(34)S of sulfate enrichment in the first year, but in subsequent years elevated sulfide was detected up to 15 days after increased δ(34)S of sulfate. A biogeochemical reactive transport model is developed which explicitly incorporates the stable isotopes of sulfur to simulate fractionation during the 2007 and 2008 amendments. A model based on an initially low, uniformly distributed population of sulfate reducing bacteria that grow and become spatially variable with time reproduces measured trends in solute concentration and δ(34)S, capturing the change in onset of sulfate reduction in subsequent years. Our results demonstrate a previously unrecognized hysteretic effect in the spatial distribution of biomass growth during stimulated subsurface bioremediation.

Microbiology and proteomics, getting the best of both worlds!

High-throughput identification of proteins with the latest generation of hybrid high-resolution mass spectrometers is opening new perspectives in microbiology. I present, here, an overview of tandem mass spectrometry technology and bioinformatics for shotgun proteomics that make 2D-PAGE approaches obsolete. Non-labelling quantitative approaches have become more popular than labelling techniques on most proteomic platforms because they are easier to carry out while their quantitative outcome is rather robust. Parameters for recording mass spectrometry data, however, need to be chosen carefully and statistics to assess the confidence of the results should not be neglected. Interestingly, next-generation sequencing methodologies make any microbial model quickly amenable to proteomics, leading to the documentation of a wide range of organisms from diverse environments. Some recent discoveries made using microbial proteomics have challenged some biological dogma, such as: (i) initiation of the translation does not occur predominantly from ATG codons in some microorganisms, (ii) non-canonical initiation codons are used to regulate the production of specific but important proteins and (iii) a gene may code for multiple polypeptide species, heterogeneous in terms of sequences. Microbial diversity and microbial physiology can now be revisited by means of exhaustive comparative proteomic surveys where thousands of proteins are detected and quantified. Proteogenomics, consisting of better annotating of genomes with the help of proteomic evidence, is paving the way for integrated multi-omic approaches in microbiology. Finally, meta-proteomic tools and approaches are emerging for tackling the high complexity of the microbial world as a whole, opening new perspectives for assessing how microbial communities function.

Proteomic analysis of 17β-estradiol degradation by Stenotrophomonas maltophilia

Microbial degradation plays a critical role in determining the environmental fate of steroid hormones, such as 17β-estradiol (E2). The molecular mechanisms governing the microbial transformation of E2 and its primary degradation intermediate, estrone (E1), are largely unknown. The objective of this study was to identify metabolism pathways that might be involved in microbial estrogen degradation. To achieve the objective, Stenotrophomonas maltophilia strain ZL1 was used as a model estrogen degrading bacterium and its protein expression level during E2/E1 degradation was studied using quantitative proteomics. During an E2 degradation experiment, strain ZL1 first converted E2 to E1 stoichiometrically. At 16 h E1 reached its peak concentration, and microbial growth started. At the same time, enzymes involved in certain catabolic and anabolic pathways were most highly expressed compared to the other time points tested. Among those enzymes, the ones involved in protein and lipid biosyntheses were observed to be particularly active. Based on the metabolite information from a previous study and the proteomic data from this study, we hypothesized that S. maltophilia strain ZL1 was able to convert E1 to amino acid tyrosine through ring cleavage on a saturated ring of the E1 molecule and then utilize tyrosine in protein biosynthesis.

Microbial metaproteomics: identifying the repertoire of proteins that microorganisms use to compete and cooperate in complex environmental communities

The availability of genome information for microbial consortia, including unculturable species, from environmental samples has enabled systems-biology interrogation by providing a means to access genomic, transcriptomic, and proteomic information. This provides a unique opportunity to characterize the molecular activities and interactions of these microbial systems at a comprehensive level never before possible. Such information not only provides details about the organizational, functional, and metabolic activities of such systems, but also the untapped reserve of molecular activities that might be invoked and exploited under certain environmental conditions. Since bacteria naturally exist in complex ecosystems, it is imperative to develop and utilize analytical approaches that can provide molecular level details on systems consisting of mixed microbial membership. This is the realm of metaproteomics-the characterization of the complement of proteins expressed by a microbial community in an environmental sample.

High-density PhyloChip profiling of stimulated aquifer microbial communities reveals a complex response to acetate amendment

There is increasing interest in harnessing the functional capacities of indigenous microbial communities to transform and remediate a wide range of environmental contaminants. Information about which community members respond to stimulation can guide the interpretation and development of remediation approaches. To comprehensively determine community membership and abundance patterns among a suite of samples associated with uranium bioremediation experiments, we employed a high-density microarray (PhyloChip). Samples were unstimulated, naturally reducing, or collected during Fe(III) (early) and sulfate reduction (late biostimulation) from an acetate re-amended/amended aquifer in Rifle, Colorado, and from laboratory experiments using field-collected materials. Deep community sampling with PhyloChip identified hundreds-to-thousands of operational taxonomic units (OTUs) present during amendment, and revealed close similarity among highly enriched taxa from drill core and groundwater well-deployed column sediment. Overall, phylogenetic data suggested that stimulated community membership was most affected by a carryover effect between annual stimulation events. Nevertheless, OTUs within the Fe(III)- and sulfate-reducing lineages, Desulfuromonadales and Desulfobacterales, were repeatedly stimulated. Less consistent, co-enriched taxa represented additional lineages associated with Fe(III) and sulfate reduction (e.g. Desulfovibrionales; Syntrophobacterales; Peptococcaceae) and autotrophic sulfur oxidation (Sulfurovum; Campylobacterales). Data implies complex membership among highly stimulated taxa and, by inference, biogeochemical responses to acetate, a nonfermentable substrate.

Key players and team play: anaerobic microbial communities in hydrocarbon-contaminated aquifers

Biodegradation of anthropogenic pollutants in shallow aquifers is an important microbial ecosystem service which is mainly brought about by indigenous anaerobic microorganisms. For the management of contaminated sites, risk assessment and control of natural attenuation, the assessment of in situ biodegradation and the underlying microbial processes is essential. The development of novel molecular methods, "omics" approaches, and high-throughput techniques has revealed new insight into complex microbial communities and their functions in anoxic environmental systems. This review summarizes recent advances in the application of molecular methods to study anaerobic microbial communities in contaminated terrestrial subsurface ecosystems. We focus on current approaches to analyze composition, dynamics, and functional diversity of subsurface communities, to link identity to activity and metabolic function, and to identify the ecophysiological role of not yet cultured microbes and syntrophic consortia. We discuss recent molecular surveys of contaminated sites from an ecological viewpoint regarding degrader ecotypes, abiotic factors shaping anaerobic communities, and biotic interactions underpinning the importance of microbial cooperation for microbial ecosystem services such as contaminant degradation.

Strategies for metagenomic-guided whole-community proteomics of complex microbial environments

Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predictions from environmental metagenomic sequences has been challenging because of the variable overlap between proteomic datasets and corresponding short-read nucleotide sequence data. In this study, we have benchmarked several strategies for increasing microbial peptide spectral matching in metaproteomic datasets using protein predictions generated from matched metagenomic sequences from the same human fecal samples. Additionally, we investigated the impact of mass spectrometry-based filters (high mass accuracy, delta correlation), and de novo peptide sequencing on the number and robustness of peptide-spectrum assignments in these complex datasets. In summary, we find that high mass accuracy peptide measurements searched against non-assembled reads from DNA sequencing of the same samples significantly increased identifiable proteins without sacrificing accuracy.

Variably saturated flow and multicomponent biogeochemical reactive transport modeling of a uranium bioremediation field experiment

Three-dimensional, coupled variably saturated flow and biogeochemical reactive transport modeling of a 2008 in situ uranium bioremediation field experiment is used to better understand the interplay of transport and biogeochemical reactions controlling uranium behavior under pulsed acetate amendment, seasonal water table variation, spatially variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. While the simulation of the 2008 Big Rusty acetate biostimulation field experiment in Rifle, Colorado was generally consistent with behaviors identified in previous field experiments at the Rifle IFRC site, the additional process and property detail provided several new insights. A principal conclusion from this work is that uranium bioreduction is most effective when acetate, in excess of the sulfate-reducing bacteria demand, is available to the metal-reducing bacteria. The inclusion of an initially small population of slow growing sulfate-reducing bacteria identified in proteomic analyses led to an additional source of Fe(II) from the dissolution of Fe(III) minerals promoted by biogenic sulfide. The falling water table during the experiment significantly reduced the saturated thickness of the aquifer and resulted in reactants and products, as well as unmitigated uranium, in the newly unsaturated vadose zone. High permeability sandy gravel structures resulted in locally high flow rates in the vicinity of injection wells that increased acetate dilution. In downgradient locations, these structures created preferential flow paths for acetate delivery that enhanced local zones of TEAP reactivity and subsidiary reactions. Conversely, smaller transport rates associated with the lower permeability lithofacies (e.g., fine) and vadose zone were shown to limit acetate access and reaction. Once accessed by acetate, however, these same zones limited subsequent acetate dilution and provided longer residence times that resulted in higher concentrations of TEAP reaction products when terminal electron donors and acceptors were not limiting. Finally, facies-based porosity and reactive surface area variations were shown to affect aqueous uranium concentration distributions with localized effects of the fine lithofacies having the largest impact on U(VI) surface complexation. The ability to model the comprehensive biogeochemical reaction network, and spatially and temporally variable processes, properties, and conditions controlling uranium behavior during engineered bioremediation in the naturally complex Rifle IFRC subsurface system required a subsurface simulator that could use the large memory and computational performance of a massively parallel computer. In this case, the eSTOMP simulator, operating on 128 processor cores for 12h, was used to simulate the 110-day field experiment and 50 days of post-biostimulation behavior.

Molecular analysis of the metabolic rates of discrete subsurface populations of sulfate reducers

Elucidating the in situ metabolic activity of phylogenetically diverse populations of sulfate-reducing microorganisms that populate anoxic sedimentary environments is key to understanding subsurface ecology. Previous pure culture studies have demonstrated that the transcript abundance of dissimilatory (bi)sulfite reductase genes is correlated with the sulfate-reducing activity of individual cells. To evaluate whether expression of these genes was diagnostic for subsurface communities, dissimilatory (bi)sulfite reductase gene transcript abundance in phylogenetically distinct sulfate-reducing populations was quantified during a field experiment in which acetate was added to uranium-contaminated groundwater. Analysis of dsrAB sequences prior to the addition of acetate indicated that Desulfobacteraceae, Desulfobulbaceae, and Syntrophaceae-related sulfate reducers were the most abundant. Quantifying dsrB transcripts of the individual populations suggested that Desulfobacteraceae initially had higher dsrB transcripts per cell than Desulfobulbaceae or Syntrophaceae populations and that the activity of Desulfobacteraceae increased further when the metabolism of dissimilatory metal reducers competing for the added acetate declined. In contrast, dsrB transcript abundance in Desulfobulbaceae and Syntrophaceae remained relatively constant, suggesting a lack of stimulation by added acetate. The indication of higher sulfate-reducing activity in the Desulfobacteraceae was consistent with the finding that Desulfobacteraceae became the predominant component of the sulfate-reducing community. Discontinuing acetate additions resulted in a decline in dsrB transcript abundance in the Desulfobacteraceae. These results suggest that monitoring transcripts of dissimilatory (bi)sulfite reductase genes in distinct populations of sulfate reducers can provide insight into the relative rates of metabolism of different components of the sulfate-reducing community and their ability to respond to environmental perturbations.

Monitoring the metabolic status of geobacter species in contaminated groundwater by quantifying key metabolic proteins with Geobacter-specific antibodies

Simple and inexpensive methods for assessing the metabolic status and bioremediation activities of subsurface microorganisms are required before bioremediation practitioners will adopt molecular diagnosis of the bioremediation community as a routine practice for guiding the development of bioremediation strategies. Quantifying gene transcripts can diagnose important aspects of microbial physiology during bioremediation but is technically challenging and does not account for the impact of translational modifications on protein abundance. An alternative strategy is to directly quantify the abundance of key proteins that might be diagnostic of physiological state. To evaluate this strategy, an antibody-based quantification approach was developed to investigate subsurface Geobacter communities. The abundance of citrate synthase corresponded with rates of metabolism of Geobacter bemidjiensis in chemostat cultures. During in situ bioremediation of uranium-contaminated groundwater the quantity of Geobacter citrate synthase increased with the addition of acetate to the groundwater and decreased when acetate amendments stopped. The abundance of the nitrogen-fixation protein, NifD, increased as ammonium became less available in the groundwater and then declined when ammonium concentrations increased. In a petroleum-contaminated aquifer, the abundance of BamB, an enzyme subunit involved in the anaerobic degradation of mono-aromatic compounds by Geobacter species, increased in zones in which Geobacter were expected to play an important role in aromatic hydrocarbon degradation. These results suggest that antibody-based detection of key metabolic proteins, which should be readily adaptable to standardized kits, may be a feasible method for diagnosing the metabolic state of microbial communities responsible for bioremediation, aiding in the rational design of bioremediation strategies.

An iterative workflow for mining the human intestinal metaproteome

BACKGROUND

Peptide spectrum matching (PSM) is the standard method in shotgun proteomics data analysis. It relies on the availability of an accurate and complete sample proteome that is used to make interpretation of the spectra feasible. Although this procedure has proven to be effective in many proteomics studies, the approach has limitations when applied on complex samples of microbial communities, such as those found in the human intestinal tract. Metagenome studies have indicated that the human intestinal microbiome contains over 100 times more genes than the human genome and it has been estimated that this ecosystem contains over 5000 bacterial species. The genomes of the vast majority of these species have not yet been sequenced and hence their proteomes remain unknown. To enable data analysis of shotgun proteomics data using PSM, and circumvent the lack of a defined matched metaproteome, an iterative workflow was developed that is based on a synthetic metaproteome and the developing metagenomic databases that are both representative for but not necessarily originating from the sample of interest.

RESULTS

Two human fecal samples for which metagenomic data had been collected, were analyzed for their metaproteome using liquid chromatography-mass spectrometry and used to benchmark the developed iterative workflow to other methods. The results show that the developed method is able to detect over 3,000 peptides per fecal sample from the spectral data by circumventing the lack of a defined proteome without naive translation of matched metagenomes and cross-species peptide identification.

CONCLUSIONS

The developed iterative workflow achieved an approximate two-fold increase in the amount of identified spectra at a false discovery rate of 1% and can be applied in metaproteomic studies of the human intestinal tract or other complex ecosystems.

Geobacter: the microbe electric's physiology, ecology, and practical applications

Geobacter species specialize in making electrical contacts with extracellular electron acceptors and other organisms. This permits Geobacter species to fill important niches in a diversity of anaerobic environments. Geobacter species appear to be the primary agents for coupling the oxidation of organic compounds to the reduction of insoluble Fe(III) and Mn(IV) oxides in many soils and sediments, a process of global biogeochemical significance. Some Geobacter species can anaerobically oxidize aromatic hydrocarbons and play an important role in aromatic hydrocarbon removal from contaminated aquifers. The ability of Geobacter species to reductively precipitate uranium and related contaminants has led to the development of bioremediation strategies for contaminated environments. Geobacter species produce higher current densities than any other known organism in microbial fuel cells and are common colonizers of electrodes harvesting electricity from organic wastes and aquatic sediments. Direct interspecies electron exchange between Geobacter species and syntrophic partners appears to be an important process in anaerobic wastewater digesters. Functional and comparative genomic studies have begun to reveal important aspects of Geobacter physiology and regulation, but much remains unexplored. Quantifying key gene transcripts and proteins of subsurface Geobacter communities has proven to be a powerful approach to diagnose the in situ physiological status of Geobacter species during groundwater bioremediation. The growth and activity of Geobacter species in the subsurface and their biogeochemical impact under different environmental conditions can be predicted with a systems biology approach in which genome-scale metabolic models are coupled with appropriate physical/chemical models. The proficiency of Geobacter species in transferring electrons to insoluble minerals, electrodes, and possibly other microorganisms can be attributed to their unique "microbial nanowires," pili that conduct electrons along their length with metallic-like conductivity. Surprisingly, the abundant c-type cytochromes of Geobacter species do not contribute to this long-range electron transport, but cytochromes are important for making the terminal electrical connections with Fe(III) oxides and electrodes and also function as capacitors, storing charge to permit continued respiration when extracellular electron acceptors are temporarily unavailable. The high conductivity of Geobacter pili and biofilms and the ability of biofilms to function as supercapacitors are novel properties that might contribute to the field of bioelectronics. The study of Geobacter species has revealed a remarkable number of microbial physiological properties that had not previously been described in any microorganism. Further investigation of these environmentally relevant and physiologically unique organisms is warranted.