encyclopedia of metagenomics || metagenomics potential for bioremediation

Metagenomics Potential for Bioremediation

Terrence H. Bella,b, Charles W. Greerb and Etienne Yergeaub*aDepartment of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, QC, CanadabNational Research Council Canada, Montreal, QC, Canada

Synonyms

Metagenomics of polluted substrates/environments

Definition

Bioremediation refers to the detoxification of environments through the activities of living organ-isms. In many environments, microorganisms are the main agents of bioremediation, as they adapttheir existing biochemical pathways to the degradation or conversion of pollutants. Human inter-vention can often improve the ability of microorganisms to rapidly remediate contaminants, but howtreatments affect species diversity and gene allocation in complex microbial communities is not wellcharacterized. The metagenome of a contaminated environment includes all DNA contained withinit; however, a variety of screening methods can be used in bioremediation studies to simplify thecollection and analysis of targeted genomic information.

Introduction

Pollution is a ubiquitous global concern, as many natural and synthetic compounds have beenintroduced into environments in which they are posing hazards to the health of humans andecosystems. Bioremediation is the degradation, conversion, or stabilization of these compoundsby organisms, generally performed by microorganisms and plants. When the organisms that arenative to a contaminated site effectively remove contaminants without intervention, the toxicity atthe site may simply be monitored as the pollutant is reduced or converted to a less toxic form. Inmany cases, however, intervention can increase the rate of bioremediation. The addition of stimu-lating amendments on site (e.g., nutrients, organic matter) and the relocation of contaminatedmaterial to off-site treatment facilities are the most common approaches to encouraging remediation.

Often it is microorganisms that play the most significant role in bioremediation. High-resolutiongenetic information is required to understand how contaminants and treatments affect the complexmicrobial communities that exist in natural environments. Some taxonomic groups have been linkedto the presence of various pollutants, but many of the taxa and enzymes that can potentiallyparticipate in bioremediation remain unknown. Thousands of microbial species may exist ina single gram of soil, so when pollutants are similar in composition to compounds that occurnaturally in the environment, a large number of species are able to compete to use the pollutant asa source of carbon, nutrients, or energy. At the other extreme, when the introduced pollutant is

*Email: [email protected]

Encyclopedia of MetagenomicsDOI 10.1007/978-1-4614-6418-1_123-4# Springer Science+Business Media New York 2012

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http://dx.doi.org/SpringerLink:ChapterTarget

complex or synthetic in origin, there may be no local strains that are immediately capable ofmetabolizing it or reducing its toxicity.

A number of bioremediating microorganisms have been isolated from contaminated sites, but it isnow generally understood that the information obtained from these isolates is insufficient tounderstand the workings of complex microbial communities. More complete genetic informationfrom natural environments is required to understand how contamination affects microbial commu-nities on the whole, and whether there is the potential for further optimization of bioremediation. Thelarge-scale, culture-independent studies that are required to meet this end are now possible with theadvent of new high-throughput sequencing technologies.

Aspirations for Metagenomics in Bioremediation

Understanding the differences between a contaminated environment and its uncontaminated equiv-alent is a major topic of study in bioremediation research, as it can help in determining how much ofthe natural function of the system has been altered by contamination. Metagenomic data can provideinformation about taxonomic and enzymatic diversity both pre- and post-contamination, which willallow the mining of potentially active genes and organisms. Accumulating metagenomes froma variety of contaminated and uncontaminated equivalent environments will make it possible to linkchanges in contaminant composition and concentration to specific genes and taxa. In addition, suchstudies will answer questions about the microbial ecology of the contaminated system, specificallyhow microorganisms respond to the disturbance created by the contaminant. Adjustments ofnutrients, carbon sources, pH, temperature, oxygen, and water content are frequently parts oftreatment scenarios applied to contaminated sites, so metagenomic studies of bioremediation willalso provide information on how microbial communities respond to changes in a variety ofenvironmental factors. To date, only a handful of such studies have been conducted (Table 1).

Types of Metagenomic Studies Used in Bioremediation

Strictly speaking, metagenomics involves the entirety of genetic information contained withina sample. More efficient sequencing now makes it possible to produce this data, but the effortrequired to thoroughly analyze such huge datasets is a limiting step in metagenomic studies. Evenwhen full metagenomes are sequenced, analysis of the data will often focus on specific genes ofinterest. There is also a trade-off between the number of samples analyzed and the depth ofsequencing possible. While it is tempting to completely sequence and annotate single samples, itis difficult to know how representative this sample is of an entire environment or in the case ofcomposite samples, the variability that exists within the environment.

As a compromise, many studies of contaminated sites have used what has been referred to asgene-targeted metagenomics (Iwai et al. 2010), in which specific gene regions are amplified and thensequenced using high-throughput technologies. This has been used in bioremediation studies to lookat specific functional genes (Bell et al. 2011; Iwai et al. 2010) as well as 16S rRNA gene diversity(e.g., Bell et al. 2011; Gihring et al. 2011). The limitations of gene-targeted metagenomics are that(1) genetic information that is not immediately of interest cannot be explored in the future, (2) novelgenes that cannot be amplified by the selected primers are excluded from the analysis, and(3) information about the relative occurrence of the targeted genes within the sample will be lost.


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Table 1 Studies that have used metagenomics to study microbial populations in contaminated substrates

Substrate Contaminant TreatmentGene groupsexamined Key finding

Sequencingtype References

Whole genome sequencing

Groundwater Heavymetals,nitrate,organicsolvents

None 16S rRNA,metabolism,stress response

Significant loss ofspecies and metabolicdiversity followingmore than 50 years ofcontamination

PRISM3730capillaryDNAsequencer

Hemmeet al. 2010

Soil Diesel Monoammoniumphosphate andaeration

16S rRNA,alkyl grouphydroxylases,extradioldioxygenase,intradioldioxygenase,gentisate/homogentisatedioxygenase

Shift fromGammaproteobacteriato Alphaproteobacteriaand Actinobacteriaafter 1 year ofremediation

Roche/454GS FLXTitanium

Yergeauet al. 2012

Gene-targeted sequencing

Soil JP-8 jet fuel Monoammoniumphosphate

16S rRNA, alkB Alphaproteobacteria incontaminated soilswere more effective atincorporating addednitrogen than wereother bacterial taxa

Roche/454GS FLXTitanium

Bellet al. 2011

Rhizospheresoil

PCB None Toluene/biphenyldioxygenases

Unexpected genediversity, including25 novel clusters

Roche/454FLX

Iwaiet al. 2010

Subsurfacesediment

Uranium (VI) Ethanol injection 16S rRNA Identified indicatortaxa specific to varioushydrochemicalconditions and thosethat responded totreatment

Roche/454FLX

Cardenaset al. 2010

Mangrovesediment

MF380heavy fuel oil

None 16S rRNA Wide diversity in bothcontaminated anduncontaminatedsediment, withindicator taxa detectedfor each

Roche/454FLX

dos Santoset al. 2011

Groundwater Uranium,sulfate,nitrate

Emulsifiedvegetable oil

16S rRNA Very narrow group ofmicroorganisms thatwere stimulated by thetreatment and/orinvolved inremediation

Roche/454FLX

Gihringet al. 2011

Liquidmedia

Syntheticaromaticalkanoicacids

Added individualalkanoic acids

16S rRNA Microbial communitywas unique to thecontaminant added,which varied in alkylside branching

Roche/454 Johnsonet al. 2011

(continued)


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Several recent reports have incorporated some type of metagenomics into the study of themicroorganisms living in contaminated environments. Since the labor required to process data isbeginning to outweigh the cost of sequencing as the limiting step in metagenomic analyses, a varietyof screening methods have been used in bioremediation studies to optimize the output of information(Fig. 1). The various approaches to metagenomics that have been taken in bioremediation researchare outlined below.

Multiplexed 16S rRNA Gene SequencingBecause of its potential to quickly assign taxonomy to large numbers of microorganisms, 16S rRNAgene sequencing has gone through several waves of popularity in microbial ecology. Comparisonsof the 16S rRNA gene profiles of environmental samples have taken off again with the advent ofhigh-throughput sequencing (Tringe and Hugenholtz 2008) and are currently more popular than anyother type of metagenomic study. One reason is that a large number of 16S rRNA gene entries existin NCBI and EMBL, as do curated 16S rRNA gene databases such as the Ribosomal DatabaseProject (http://rdp.cme.msu.edu/) and Green Genes (http://greengenes.lbl.gov/). As a result, profilesof community diversity can be conducted with only a cursory understanding of bioinformatics.While early techniques such as T-RFLP and DGGE gave some indication of the variation betweensamples, they only described small portions of microbial communities. Even clone library studiesrarely sampled more than a few hundred clones, whereas multiplexed next-generation sequencingeasily provides several thousand sequences per sample.

Since studies into bioremediation generally aim to identify effective pathways for converting ortolerating contaminants, how relevant is taxonomy? There is still debate surrounding how muchfunctional redundancy exists between microbial species and how prevalent horizontal gene transfer(HGT) is within microbial communities, yet a recent metagenomic study shows that distinctbacterial species likely do exist (Caro-Quintero and Konstantinidis 2012). A number of 16SrRNA gene surveys have been conducted in contaminated environments and have been used toassess how microbial communities vary in relation to uncontaminated reference environments orhow a community changes in a contaminated environment over time. In several of these studies, 16SrRNA gene-targeted metagenomics has identified indicator species that are specific to certaincontaminants and environmental conditions (Cardenas et al. 2010; dos Santos et al. 2011). Similarmultiplexed studies may be used to identify indicator species across multiple environments at similar

Table 1 (continued)

Substrate Contaminant TreatmentGene groupsexamined Key finding

Sequencingtype References

Functional screening

Soil Aliphatic andaromatichydrocarbons

Air sparging Extradioldioxygenase

High diversity ofextradiol dioxygenasegenes in contaminatedsoil; one extradioldioxygenase genefound per 3.6 Mb ofDNA

ABI PRISM3100GeneticAnalyzer

Brennerovaet al. 2009

Activatedsludge

Variousaromaticcompounds

None Extradioldioxygenase

Identified novelarrangements of theextradiol dioxygenasedegradation pathwayon plasmid-like DNA

ABI 3730xlDNAAnalyzer

Suenagaet al. 2009


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http://rdp.cme.msu.edu/

http://greengenes.lbl.gov/

stages of contamination, and these indicator species could theoretically be used to assess the state ofother contaminated sites.

The major advantage of the high-throughput sequencing approach when compared with earlier16S rRNA gene profiling techniques is the depth of coverage. In mangrove sediment contaminatedwith heavy fuel, little change was seen at the phylum level following contamination, while largeshifts were observed at finer taxonomic levels (dos Santos et al. 2011), an effect that may not havebeen visible using coarser profiling methods. Similarly, 16S rRNA gene pyrosequencing showed

Fig. 1 Methods for integrating metagenomics into bioremediation studies


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that a very narrow group of taxa were stimulated by emulsified oil injection in a uranium-contaminated aquifer (Gihring et al. 2011). With less sequencing coverage, it would be impossibleto determine whether these were the only taxa stimulated or simply the most dominant members ofthe community.

Multiplexed Functional Gene SequencingIn many bioremediation studies, specific catabolic, reducing, or oxidizing genes are the subjects ofinterest. In such cases, it may be desirable to simply amplify and sequence these targeted genes. Aswith 16S rRNA gene sequencing, many samples can be processed by multiplex sequencing fora limited cost. Degenerate primers have been used to amplify alkane monooxygenase genes fromhydrocarbon-contaminated Arctic soil, and sequencing showed that those related to Alphaproteo-bacteria responded most positively to amendment with monoammonium phosphate (Bellet al. 2011). Amplicons were also obtained from a PCB-contaminated soil using degenerate primerstargeting toluene/biphenyl dioxygenase genes, and sequencing identified a variety of noveldioxygenase gene clusters (Iwai et al. 2010). In terms of gene discovery, the major drawback ofthis approach is that gene identification depends on novel genes having significant homology at theprimer-targeted regions. Even when the targeted genes are known, the chosen primers will bias therelative gene abundance within each sample. Amplicon size must also be considered, since manysequencing technologies have a maximum read length, although with time, this is becoming less ofa concern.

Functional ScreeningSince bioremediation is generally focused on which microbial communities most effectivelydegrade pollutants, it can potentially be straightforward to functionally screen for samples ofinterest. A study of contaminated Arctic soils compared the hydrocarbon-degrading efficiency ofvarious soils in response to different in situ and ex situ treatments, with degradation occurringsignificantly more effectively in one location. Subsequently, a metagenomic analysis was conductedthroughout a year-long time course on the soil that most rapidly degraded the contaminatinghydrocarbons, along with an uncontaminated reference soil (Yergeau et al. 2012). Metagenomicstudies that are conducted in vitro also involve an aspect of selection, as only microorganisms thatare capable of growing in mixed culture prevail. Mixed culture studies are common, as they oftenevaluate the potential for bioremediation in treatment facilities. Metagenomics is starting to beapplied to such studies, as in one case in which it was determined that the amount of branching insynthetic aromatic alkanoic acids led to vastly different microbial communities (Johnsonet al. 2011).

Prescreening of DNA can also be conducted on large genomic fragments that are contained withinplasmids, such as fosmids or cosmids. By transforming these vectors into hosts such as E. coli, theDNA fragment can be screened for the ability to mineralize or tolerate a specific contaminant. Thisstrategy permits the identification of genes that are involved in the catabolism of particularpollutants, or that permit host survival, provided the essential pathway can be contained ina single DNA fragment and can be expressed in the host. Sequencing is also more targeted usingthis approach, as the sequencing of housekeeping and rRNA genes is limited.

To search for genes capable of degrading catechol, metagenomic DNA from a hydrocarbon-contaminated soil was fragmented, cloned into fosmid vectors, transformed into E. coli, and platedwith catechol as a carbon substrate. A high diversity of extradiol dioxygenase genes was observed,as well as a surprisingly high density of one extradiol dioxygenase per 3.6 Mb of DNA screened(Brennerova et al. 2009). A similar approach identified novel extradiol dioxygenase genes, as well as


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previously unknown arrangements of catechol-degrading pathways (Suenaga et al. 2009). Thedrawbacks of this approach are that the entire genetic pathway must be contained within a singleplasmid; that the host may be unable to survive in the presence of any toxic gene products, meaningthat not all relevant genes will necessarily be identified; and that some genes may not be expressed ifthe chosen host is not closely related to the organism from which the DNA fragment originated.

Full Metagenome AnalysisFull metagenomic sequencing, when possible, provides the greatest amount of information. Withthis approach, any number of post hoc analyses can be conducted on a dataset. While much of thegenetic information obtained from a given environment may lack appropriate comparators inexisting gene banks, collecting full metagenomic information will allow future researchers theopportunity to analyze the dataset. At the moment, a number of database projects are ongoing inan attempt to collect and annotate metagenomic data, including some from contaminated sites (e.g.,http://www.hydrocarbonmetagenomics.com/).

To date, only a handful of complete metagenomic studies have been conducted in contaminatedenvironments. While 16S rRNA gene studies are useful in determining the relative microbialdiversity of environments, the metabolic potential of a microbial community may not be strictlylinked to its taxonomic profile. Thus, full metagenomic studies can be used to assess how diversityrelates to functional potential. A metagenomic study of a diesel-contaminated Arctic soil showedthat a shift in 16S rRNA gene sequences from Gammaproteobacteria to Alphaproteobacteria andActinobacteria mostly correlated with a shift in hydroxylases and dioxygenases that were affiliatedwith those same organisms (Yergeau et al. 2012), demonstrating that, in this case, there wassignificance to taxonomic affiliation. Similarly, most of the functional genes (stress response,metal resistance, etc.) identified in the metagenome of a heavy metal-contaminated groundwatercommunity were traced to Gammaproteobacteria, the group that also dominated the 16S rRNA geneprofile (Hemme et al. 2010).

Full metagenomes can also provide information on the relative abundance of genes of interest.PCR-based approaches introduce a primer bias prior to sequencing, whereas strict metagenomicanalysis permits a more direct quantitative comparison. Within the contaminated groundwatermetagenome, stress-response genes, such as those involved in DNA repair and heavy metalresistance, were more abundantly represented than would be expected in an uncontaminatedcommunity (Hemme et al. 2010). Most hydrocarbon-degrading genes were high in abundance inthe contaminated Arctic soil metagenomes when compared with the uncontaminated reference soil,but extradiol aromatic ring-cleavage dioxygenase sequences decreased after a year of treatment,while other dioxygenases increased in abundance, and alkane hydroxylases remained constantthroughout treatment (Yergeau et al. 2012). Caution should be exercised when using preparatorytechniques such as whole genome amplification, since the quantitation of genes can be affected(Yergeau et al. 2010). Although the amount of DNA required for metagenomic sequencing isdecreasing, whole genome amplification may still be necessary in very low biomass systems, ascan be found in some highly contaminated environments.

Information Lacking from Bioremediation Literature

Genes Involved in BioremediationKey pathways involved in the bioremediation of major contaminants are known, but many novelenzymes and pathways are still being discovered. The lack of sequence conservation in some key


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http://www.hydrocarbonmetagenomics.com/

gene families has made it difficult to determine their true diversity using PCR-based methods. In thecase of genes that code for enzymes that are involved in normal forms of metabolism or otherhousekeeping functions within the cell, this diversity may be extensive. Metagenomic studies acrosscontaminated environments will help correlate gene groups with contaminants, and this may identifyroles for pathways that had previously been considered unimportant in the conversion or tolerance ofcontaminants.

Microbial species that are not directly involved in bioremediation can also represent a sizeableproportion of a contaminated community. Soils contaminated with hydrocarbons have still providedhomes for populations of nitrifying bacteria (Deni and Penninckx 1999) and cyanobacteria (Yergeauet al. 2012), while the stimulation of the microbial reductive chlorination of PCE and TCE by addingorganic products tends to promote many microorganisms that are not involved in remediation(Strycharz et al. 2008). In addition, microorganisms that function in various nutrient cycles (e.g.,nitrogen fixers) may be important to the functioning of the overall community. To date, it is not reallyknown how much these other species affect functioning in contaminated environments or howbioremediation is affected if some processes are disrupted.

Extent of Horizontal Gene TransferIt can be difficult to determine the taxonomic affiliation of plasmid-borne DNA, and certain keygenes involved in bioremediation, such as naphthalene dioxygenases and alkane monooxygenases(Whyte et al. 1997), have been found on plasmids. Mobile genetic elements are known to becommon in at least some natural environments, but it is not known how significant a role HGTplays in the adaptation of microbial communities to contamination.

In metagenomic studies, genes can be compared with the background DNA of the communitymetagenome, which can help in identifying the prevalence of HGT. Bioinformatic analysis ofa metagenome under long-term contamination showed that roughly 12 transposons were presentper Mb of DNA, which was similar to reference strains of Xanthomonas, the dominant communitymember. In addition, large differences in % G+C and codon bias between putatively transposedgenes suggested a very recent origin for acetone carboxylases, mercuric resistance operons, andczcD divalent cation transporters (Hemme et al. 2010). The persistence of HGT after 50 years ofcontinued contaminant stress suggests that it may be very important to the survival of microorgan-isms in a contaminated environment.

Horizontal gene transfer was also suspected when a mismatch between the number of cytochromeP450 genes affiliated with Rhodococcus and the relative abundance of Actinobacteria was observedin the metagenome of diesel-contaminated Arctic soils (Yergeau et al. 2012). A number of the genesdetected in this study can be plasmid-borne, so this may be a common response. Futuremetagenomic analyses pre- and post-contamination may show how quickly this process can shapethe genetic structure of microbial communities. If HGT is determined to be a major force shapingnewly contaminated environments, the metagenomic screening of mobile elements alone may beanother method of eliminating large amounts of housekeeping and redundant genetic information.

QuantitationAs mentioned, metagenomes that have not been modified by processes such as whole genomeamplification may permit actual quantification of gene abundances. Whereas techniques such asqPCR and PCR-based diversity studies are subject to amplification biases, the metagenome repre-sents all of the genetic information that could be extracted from a sample. Most previous attempts toquantify microbial allocation of gene resources to important processes in contaminated sites haverelied heavily on PCR methods.


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Some early metagenomic studies have already shown the potential of quantitation. The relativegenomic allocation to the degradation of various components of jet fuel, a complex contaminant,was observed in a contaminated soil community. It was also observed that known hydrocarbon-degrading genes represented a disproportionate amount of the total metagenome (Brennerovaet al. 2009). An overabundance of genes conferring resistance to heavy metals, nitrate, and organicsolvents was observed in a heavy metal-contaminated aquifer (Hemme et al. 2010). Semiquantita-tive approaches have also been used to determine relative shifts in species abundance and nitrogenincorporation in contaminated environments (Bell et al. 2011; Cardenas et al. 2010), and futurestudies using full metagenome analysis would permit actual quantification.

The Future of Metagenomics in Bioremediation

Technologies that facilitate metagenomic research are advancing quickly, and many studies that hadpreviously been outside the realm of consideration are becoming possible. Companies such asPacBio and Nanopore are producing sequencers that will allowKb reads of DNA, which will make itpossible to assemble continuous genomes in mixed communities. Even with current technologiesthis is becoming feasible, as the entire draft genome of a novel permafrost methanogen wasassembled by end-to-end linking of 113 bp paired-end reads that were produced in a metagenomicstudy using Illumina GAII technology (Mackelprang et al. 2011).

The combination of various high-throughput techniques will enable comprehensive studies ofmicrobial communities and shed light on the links between species diversity, gene density, geneexpression, protein production, and chemical transformation in contaminated environments. Stableisotope probing (SIP) is a technique that involves adding heavy isotope-labeled compounds toa substrate and allowing microorganisms to consume it and incorporate the labeled atoms intocellular components such as DNA, RNA, and phospholipids. In the case of DNA-SIP, all DNA froma treated sample is extracted and then centrifuged in CsCl gradients to separate the “heavy” (labeled)from the “light” (unlabeled) DNA. This technique has great potential in terms of identifyingfunctionally active microbes, specifically those involved in contaminant breakdown, and a recentreview describes the potential power of combining SIP with metagenomics (Chen and Murrell2010). SIP-metagenomic analyses of contaminated substrates allow the genes and species thatactively respond to pollutants to be separated from the huge amount of background geneticinformation that may remain from the initial, uncontaminated soil. The link between taxonomicaffiliation and community function is already being explored through the combination of SIP andhigh-throughput sequencing (Bell et al. 2011), while advances in RNA-SIP will providea comprehensive picture of how the addition of substrates, whether contaminants or amendments,directly affects transcription. At the moment, the CsCl gradients that are required to separate labeledand unlabeled nucleic acids are extremely cumbersome and limit the number of samples that can beprocessed within a given study.

However, a novel proteomic-SIP technique, using 2-dimensional liquid chromatography-tandemmass spectrometry (2D-LC-MS/MS), was able to examine the isotopic ratios of roughly 100,000spectra while simultaneously searching a database of 31,966 protein sequences in under 24 h (Panet al. 2011). The computing power required to conduct the analysis was enormous, but as with allhigh-throughput processing, this can be expected to change rapidly with time. The potential forapplying the proteomic-SIP technique in bioremediation studies is enormous, as even small numbersof proteins produced by rare microorganisms can be tracked (Pan et al. 2011). This will be especiallyuseful in examining bioremediation pathways that involve syntrophic interactions, or those involved


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in the processing of slowly degraded contaminants, in which nutrient flux and subsequent proteinproduction are bound to be low.

In contaminated environments, metagenomics has been used to compare polluted substrates withuncontaminated reference substrates (e.g., Yergeau et al. 2012) and has also been used to directlymeasure species composition within the same matrix before and after contamination (dos Santoset al. 2011). These types of comparative studies are geared at understanding what genetic informa-tion distinguishes a contaminated environment from similar pristine systems. One of the next majorefforts in metagenomics is likely to be the identification of a core microbiome (Shade andHandelsman 2012). In other words, what genes and species are common across an environmentand across multiple environments. With a more comprehensive idea of what core microbiomes exist,environments may be aligned by their conserved regions, much as sequences are now, and the truevariability between environments can then be assessed. In the context of bioremediation, it will beimportant to understand whether there are critical genes and organisms that must respond positivelyto the introduction of a contaminant in order to achieve successful remediation. Genes promotedoutside of this common core must then be the result of other environmental or stochastic processes.

Many current genomic studies focus on snapshots of genetic information in environmentalsamples, but the high growth rate of microorganisms means that many microbial communities areundergoing constant and rapid evolution. This suggests that longer-term metagenomic studiesshould be a focal point of future research. The metagenomic study by Hemme et al. (2010)ofmetal-contaminated groundwater showed that 50 years of pollutant stress had reduced species andmetabolic diversity to a minimal level of complexity. While all necessary metabolic pathways werefound, more than ten times fewer OTUs, with a similar loss in metabolic complexity, were presentthan were observed at an adjacent background site. Monitoring how evolution selects genes incontaminated environments over the long term will undoubtedly assist in the understanding andtreatment of chronically contaminated sites, although the interpretation of large amounts of data willfirst require a solution to the human-processing bottleneck.

Summary

A variety of metagenomic approaches are available to bioremediation researchers. The choice oftechnique will depend heavily on the question that is being asked, as well as the resources that areavailable. While full metagenomic studies provide the greatest amount of data per sample, surveyingfor indicator species or gene diversity across a wide range of samples may be more appropriate inmany cases. These methods may change quickly as technology continues to improve, but ultimately,the best approaches will be those that answer questions about how to most efficiently improve thebioremediation of contaminated sites.

References

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Brennerova MV, Josefiova J, Brenner V, et al. Metagenomics reveals diversity and abundance ofmeta-cleavage pathways in microbial communities from soil highly contaminated with jet fuelunder air-sparging bioremediation. Environ Microbiol. 2009;11:2216–27.


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Cardenas E,WuWM, LeighMB, et al. Significant association between sulfate-reducing bacteria anduranium-reducing microbial communities as revealed by a combined massively parallelsequencing-indicator species approach. Appl Environ Microb. 2010;76:6778–86.

Caro-Quintero A, Konstantinidis KT. Bacterial species may exist, metagenomics reveal. EnvironMicrobiol. 2012;14:347–55.

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Deni J, Penninckx MJ. Nitrification and autotrophic nitrifying bacteria in a hydrocarbon-pollutedsoil. Appl Environ Microb. 1999;65:4008–13.

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Hemme CL, Deng Y, Gentry TJ, et al. Metagenomic insights into evolution of a heavy metal-contaminated groundwater microbial community. ISME J. 2010;4:660–72.

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Johnson RJ, Smith BE, Sutton PA, et al. Microbial biodegradation of aromatic alkanoic naphthenicacids is affected by the degree of alkyl side chain branching. ISME J. 2011;5:486–96.

Mackelprang R, Waldrop MP, DeAngelis KM, et al. Metagenomic analysis of a permafrost micro-bial community reveals a rapid response to thaw. Nature. 2011;480:368–71.

Pan CL, Fischer CR, Hyatt D, et al. Quantitative tracking of isotope flows in proteomes of microbialcommunities. Mol Cell Proteomics. 2011; 10:M110.006049.

Shade A, Handelsman J. Beyond the Venn diagram: the hunt for a core microbiome. EnvironMicrobiol. 2012;14:4–12.

Strycharz SM, Woodard TL, Johnson JP, et al. Graphite electrode as a sole electron donor forreductive dechlorination of tetrachlorethene by Geobacter lovleyi. Appl Environ Microb.2008;74:5943–7.

Suenaga H, Koyama Y, Miyakoshi M, et al. Novel organization of aromatic degradation pathwaygenes in a microbial community as revealed by metagenomic analysis. ISME J. 2009;3:1335–48.

Tringe SG, Hugenholtz P. A renaissance for the pioneering 16S rRNA gene. Curr Opin Microbiol.2008;11:442–6.

Whyte LG, Bourbonnière L, Greer CW. Biodegradation of petroleum hydrocarbons bypsychrotrophic Pseudomonas strains possessing both alkane (alk) and naphthalene (nah) cata-bolic pathways. Appl Environ Microb. 1997;63:3719–23.

Yergeau E, Hogues H, Whyte LG, et al. The functional potential of high Arctic permafrost revealedby metagenomic sequencing, qPCR and microarray analyses. ISME J. 2010;4:1206–14.

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