the prokaryotes volume 187 || the structure and function of microbial communities

CHAPTER 1.13

The Structure and Function of Microbial Communities

The Structure and Function of Microbial Communities

DAVID A. STAHL, MEREDITH HULLAR AND SEANA DAVIDSON

Introduction

For the greater part of its history, microbiologyhas been a science of the single cell. The cell hasdominated thought and experiment. So much sothat discussion of other forms of organization, ifaddressed at all, was most often the subject ofhallway speculation rather than a serious ques-tion of investigation. It is heartening that withinthe last decade or so the science of microbiologyhas begun to address the dimensions of organi-zation that transcend the single cell. For exam-ple, the study of biofilms as organized systems isnow more acceptable, and several high profilepublications have emerged that examine thephysiological basis of structure and function at amulticellular level of monospecific biofilm com-munities (Fuqua et al., 1994; Fuqua et al., 1996;Hastings and Greenberg, 1999; Whiteley et al.,2001). Although there remains an essentialreductionism to these studies, they have demon-strated the importance of intrapopulation, andpossibly interpopulation, communication sys-tems in controlling the structure and activity ofmulti-species microbial systems.

A decade ago one of the authors contributeda short article to the American Society for Micro-biology (ASM) News (Stahl, 1993), noting a fun-damental variance between microbiology andgeneral biological sciences. Microbiology wasnot built upon a foundation of natural history, forlack of tools to observe and categorize microbesin the field. Morphology was of little utility—thesimple shapes of microorganisms conceal theirremarkable diversity. Culture-based studies pro-vided only a sketchy census of natural diversity,and conventional biochemical tests did not servea phylogenetically based system of classification.It was only through comparative sequencing, firstof proteins and later of nucleic acids, that infer-ences of phylogenetic relationship among micro-organisms could be made (Zuckerkandl andPauling, 1965; Jukes and Cantor, 1969). Today wesee a field transformed by comparative analysesof genes and more recently of completegenomes. The metric provided by a molecularclock introduced an evolutionary perspective

and phylogenetic dimension most forcefullyrepresented by a universal tree of life (Woese,1987; Woese et al., 1990). This single phylogenyrevealed the vast diversity of microbial life,reducing the plants and animals to a peripheralbranch (Fig. 1). This has fueled more generalrecognition that the primary biology of ourplanet is microbial and provided an essentialframework to conduct a census of diversity(Stahl et al., 1984; Olsen et al., 1986; Ward et al.,1990; DeLong et al., 1994; Amann et al., 1995).Within that framework, both cultured and uncul-tured organisms could be related through a com-mon metric based on the sequence divergence ofcommon biopolymers (e.g., DNA encoded RNAand protein components of the cellular transla-tional and transcriptional machinery). As envi-ronmental surveys were initiated, and todaycontinue, microbiologists are confronted with anatural diversity that far exceeds that repre-sented in pure culture, revealing major lines ofdescent (kingdom and phylum level) that werepreviously unrecognized. The astounding impli-cation is that we are only now beginning toexplore significantly the biological diversity ofour planet.

This introduction must include a disclaimer.Although our subject is microbial communitystructure, the accepted unit of community struc-ture, the species, remains poorly conceptualized.Complete genome sequences and expansivemolecular diversity surveys have not providedmuch illumination on the “species problem.”For example, comparative analyses of differ-ent strains of

Escherichia coli

have revealeda remarkable plasticity in genome sequenceamong organisms coherent by traditional pheno-typic criteria (Wren, 2000; Hayashi et al., 2001;Perna, 2001; Pennisi, 2001; Dobrindt et al., 2003).Microbial geneticists were startled by the largefraction of genes of unknown function revealedin the genome sequence of

E. coli

. Each newlysequenced genome contains a similarly high frac-tion of unknowns (20–30%). Nonetheless, clini-cal labs would assign

E. coli

strains differing byas much as 30% to the same species withoutdifficulty. In contrast, strains of other well

Prokaryotes (2006) 1:299–327DOI: 10.1007/0-387-30741-9_13

300 D.A. Stahl, M. Hullar and S. Davidson CHAPTER 1.13

described genera and species are much more uni-form in genome sequence and organization. Forexample, the genome sequence of

Mycobacte-rium bovis

is greater than 99.95% identical to

M.tuberculosis

, having no genes that uniquely dis-tinguish it from

M. tuberculosis

(Garnier et al.,2003). This apparent incongruity illustrates oneof the limitations of characterizing microorgan-isms in populations of clonally derived cells—thepure culture—and of emphasizing selected fea-tures (such as host range or pathogenicity) informal descriptions. Here, we emphasize that thelaboratory culture is not an appropriate contextfor fully appreciating any organism—divorcedfrom a native habitat of which we have littleunderstanding. The high proportion of genes ofunknown function in every completed genome isanother reflection of the pure culture paradigm.The environment is the context in whichgenomes evolved, function, and continue toevolve. It is the only context in which they canbe fully understood.

The habitat in which microbial communitiesreside includes the interplay between bioticand abiotic factors. Microbiologists, again largelybecause of the pure culture paradigm, havetended to emphasize the abiotic features of hab-itat (electron donor, electron acceptor, salinity,temperature, pressure, etc.). These are the stan-dards by which organisms have been defined.However, these factors are in most instancesonly a thin slice of the parameter space definingtheir ecology and evolution. As was long agoexpressed by Darwin, “. . . the most importantof all causes of organic change is one which isalmost independent of altered physical condi-tions, namely, the mutual relation of organismsto organisms. If some of these many speciesbecome modified and improved, others will haveto be improved in a corresponding degree orthey will be exterminated.” Thus, more complete

understanding of any organism must encompassthe features of higher order organization thathave shaped the organism’s evolution and con-temporary “niche.”

A recent retrospective by Moselio Schaechtersuggests that we have so far experienced twogolden ages in microbiology (Schaechter, 2003).The first age followed recognition of microorgan-isms in general terms—as examples of the unityof biochemical processes, as agents of diseaseand spoilage, and the primary engines of bio-geochemical transformations. The technologicaldevelopment that heralded the beginning of thisfirst golden age was the pure culture method.Advances in molecular biology and associatedmethods of genetic analysis introduced the sec-ond golden age. We are now poised at the begin-ning of a third golden age which will develop amore complete understanding of systems oforganization (ecology), their origins, and mech-anisms of change (evolution). This age will befostered not only by the rapid advances intechnology (e.g., high throughput sequencing,proteome and transcriptome analyses, nanotech-nology, and bioinformatics) we now see influenc-ing research in all areas of inquiry where lifeintrudes, but also by the coalescing of disciplinesneeded to address the complexity of systems-level organization. An empirical observation hasbeen that predictions of higher levels of organi-zation in biological systems are not readilyderived from understanding gained at lowerlevels (Mayr, 1982). Thus, at least for biologicalsystems, it is essential that the tools of analysisaccommodate the complexity encountered athigher organizational levels. Advances in tech-nology in concert with disciplinary coalescencewill foster investigations that move far beyondthe study of clonal lines in laboratory culture tostudies of natural systems comprised of diverseinteracting populations. This will continue to be

Fig. 1. Universal phylogenetic tree inrooted form shows the three domains.Branching order and branch lengthsare based upon rRNA sequence com-parisons (Woese et al., 1990). Insettree illustrates elaborations of existingbranches (Pace, 1997) but mainte-nance of the fundamental frameworkdetermined in the earlier phylogeny.

BACTERIA

ARCHAEAEUCARYA

Archaea

Eucarya

Bacteria

Crenarchaeota

Euryarchaeota

macroscopicorganisms

N.R. Pace, 1997C.R. Woese, 1990

protists

CHAPTER 1.13 The Structure and Function of Microbial Communities 301

true and the final section of this chapter isdevoted to limited discussion of the changinglandscape of technology.

Structure and Function of Microbiological Systems

Microbiological systems can be characterized inthree general ways: 1) the historical (consideringsystem origins and evolution), 2) the proximate(characterizing the immediate structure andfunction of a system), and 3) the temporal(addressing the interplay of biotic and abioticelements that shape a system over diel andannual temporal periods). No one way ofcharacterization provides complete understand-ing—all three must be considered. In turn, eachcharacterization must incorporate the differentdimensions of structure and function. Thesedimensions encompass both the biotic (phyloge-netic, evolutionary, and metabolic) and the abi-otic (chemical and physical). We have organizedthis chapter by considering both the differentways microbiological systems are characterizedand the multiple dimensions of structure andfunction that serve characterization.

The Historical System

The Phylogenetic Dimension

The evolution of our planet is intertwined withthe evolutionary history of its microorganisms.Neither the planet nor any one organism is fullyintelligible apart from that ancestry. Today, areasonable representation of the phylogeneticrelationships among all life is available (Woeseet al., 1990; Woese, 2000). The “universal tree,”inferred by comparative sequencing of the smallribosomal subunit rRNA, remains the canonicalstructure (Fig. 1). Although it is recognized thathorizontal gene transfer may have eroded someof the fine detail of structure (Doolittle, 1999),there is an emerging consensus that microorgan-isms display an organismal genealogy and thatmany genes are phylogenetically informative(Ochman et al., 2000; Daubin et al., 2003).

Recognition that a microbial genealogy couldbe inferred from comparative analysis of appro-priate gene homologs (orthologs) had significantimpact on our perspective and understanding ofthe structure and function of microbiological sys-tems. The most immediate impact derived fromrecognition that our census of biological diver-sity was incomplete; the several thousand namedspecies of microorganisms scattered amongthinly branched parts of a tree was not an ade-quate representation of diversification spanning

the greater part of the evolutionary history ofthis planet. Subsequent application of molecularmethods to directly describe environmentalmicrobial diversity has confirmed that thegreater part of biological diversity is microbialand that the greater part of microbial diversityhas yet to be described (Amann, 2000a; DeLongand Pace, 2001; Torsvik et al., 2002a; Torsvik etal., 2002b).

The phylogenetic dimension embodies theconnection between the diversification of liferepresented in the canonical tree and the emer-gence of functional groups (e.g., methanogens,acetogens, sulfate reducers, and nitrifiers) inboth an evolving and contemporary biosphere. Ifmicroorganisms have diversified to fill both gen-eral and specific niches, the record of this diver-sification will be captured by their genealogy.However, there is considerable confusion con-cerning the ability to infer physiology from phy-logenetic affiliation. There are many examples ofclose phylogenetic relationship between organ-isms that have remarkably different physiologi-cal attributes, for example, close relationshipsbetween phototrophs and autotrophs, andbetween autotrophs and heterotrophs (for exam-ples, see Lane et al., 1992). Conversely, there arealso examples of phylogenetically defined groupsthat are remarkably coherent in physiologicalcharacteristics. The

Desulfovibrio

(Devereux etal., 1989; Devereux et al., 1990), methanogenicgroups (Raskin et al., 1994), and nitrifiers (Headet al., 1993; Teske et al., 1994) are notable exam-ples of phylogenetic and physiological coher-ence. Part of this apparent discordance almostcertainly derives from failure to recognize eco-logically significant features. This is a conse-quence of using the pure culture phenotype toinfer environmental activity outside of thecontext of the complex environment andinteractions between organisms of a microbialcommunity. As we develop methods for directobservations of populations within an environ-mental setting, we anticipate that many addi-tional phylogenetically cohesive characters willbe revealed.

A general relationship between habitat andtaxonomic groups has long been recognized.However, molecular tools are refining the char-acterization of that relationship. An early obser-vation of direct correspondence was made in amicrobial mat community in which the depth dis-tribution of different sulfate-reducing popula-tions corresponded with members affiliated withdiscrete phylogenetic clades (Risatti et al., 1994).A similar correspondence between phylogeneticaffiliation and aquatic habitat has been noted.The ubiquitous (SAR11) group, first identifiedby Giovannoni et al. (1990), appears to be exclu-sively marine (Morris et al., 2002). However, the


greater assemblage of organisms to which themarine SAR11 belongs includes more distantlyrelated freshwater representatives (Bahr et al.,1996; Field et al., 1997; Morris et al., 2002).

Prochlorococcus

appears to be an exclusivelymarine assemblage of unicellular cyanobacteria.An early suggestion that genetic variation among

Prochlorococcus

isolates corresponded to differ-ent light adapted populations was subsequentlyconfirmed (Moore et al., 1998). The populationstructure and thus phylogeny of planktonic bac-terial communities are associated with generalfeatures of habitat (marine versus freshwater,and depth-associated changes in physical andchemical variables).

Although a correlation between closelyrelated populations and habitat is not unex-pected, we also ask the more general question—how are the most ancient of evolutionary diver-gences (domain and division level; Hugenholtzet al., 1998) related to the structure and activitiesof contemporary systems? If the emergence anddiversification of a new lineage were primarilyexplained by a key evolutionary innovation, thenretention of that innovation among contempo-rary representatives would serve to characterizethe lineage and the defining evolutionary inno-vation. A few notable examples support this, sug-gesting a centrality of the phylogeneticdimension (Fig. 2). The first example is one ofremarkable biochemical innovation, the inven-

tion of oxygenic photosynthesis. There is goodsupport that this innovation was a consequencein part of horizontal gene transfer between earlyanoxygenic phototrophs, each having distinctphotosystems. The melding of those photosys-tems into a two-photosystem apparatus definedthe emergence of the cyanobacteria (Buttner etal., 1992). This ancestral metabolic innovationdefines all contemporary representatives of thegroup. In contrast, the spirochetes provide anexample of structural innovation. The spiralbody form combined with axial flagella offeredadvantage for moving in viscous environments,and today they are abundant residents in manysuch habitats, including microbial biofilms andmats. A final example of both structural andphysiological innovation is the endospore ofnamed species of

Bacillus

and

Clostridium

. Thebacterial endospore was apparently inventedonly once and likely in large part defines boththe origin and successful radiation of majorGram-positive lineages.

The Evolutionary Dimension

The reflections of past innovations in microbialphylogeny raise immediate questions aboutmechanism and context of innovation. Completegenome sequencing is beginning to reveal thecontribution of horizontal gene transfer as amechanism of biological innovation. However, it

Fig. 2. Evolutionary distance tree of the bac-terial domain shows currently recognized divi-sions and putative (candidate) divisions. Thetree was constructed using the ARB softwarepackage (with the Lane mask and Olsen rate-corrected neighbor-joining options) and asequence database modified for the March,1997, ARB database release.

Thermotogales

Dictyoglomus groupOP6

OP8

OP5OP4

OP1

OP1

1

OP7OP9OP12

OP10OP3

OP2EM

19Aquificales

Thermodesulfobacterium

group

10 changes per siteArchaea, Eucarya

ProteobacteriaSynergistes

Flexistipes

Nitrospira group

Acidobacterium group

chlamydiae

Verrucomicrobiates

Fibrobacter group

spirochetes

Flexibacter group

Bacteroides-Cytophaga

green sulfur bacteriacyanobacteria

low G

+C

gram-positive bacteria

fuso

bact

eria

high

G+C

gra

m-p

ositi

ve b

acte

riaTh

erm

us-D

eino

cocc

us g

roup

Green

non

-sulfu

r bac

-

teria

Coprothermobacter

planctomycetales


is too early to constrain its contribution to majorinnovations in the microbial world since thegenomic data sets are still quite sparse in cover-age of the major prokaryotic lineages. The con-text, or environment, in which innovation isfostered can’t be separated from mechanism. Ifhorizontal gene transfer is an important mecha-nism, then the fodder of innovation (geneticdiversity) will be determined by opportunitiesfor interaction among contributing populations.Microbial mat communities provide a specificexample of this point. Microbial mats are highlyactive, highly compact, and highly diverse micro-bial communities providing ample opportunityfor intimate interactions among geneticallydiverse populations. If some early mat commu-nities were based on anoxygenic photosynthesis,this community would be a plausible context forthe development of oxygenic photosynthesis viahorizontal gene exchange among intimatelyassociated phototrophs. If early mats providedviscous habitats rich in organic substrates pro-duced by phototrophs, this would also have beenan ideal context for the emergence of spiro-chetes. These primarily heterotrophic organismsare adapted to move rapidly in highly viscousenvironments like microbial mats and biofilms.

Novelty can also arise through isolation limit-ing genetic exchange and contributing to geneticdrift and local adaptation. The degree to whichthis phenomenon occurs in bacteria is conten-tious. The prevailing opinion has been that bacte-rial species are cosmopolitan and exhibit aworldwide distribution. Indeed, surveys using the16S rRNA suggest a global distribution of manyspecies that can be poles apart (Fuhrman et al.,1992; Fuhrman, 1993; Giovannoni and Cary,1995; Staley and Gosink, 1999). The adage“Everything is everywhere and nature selects”(Beijerinck, 1913) suggests that geographic barri-ers do not restrict bacterial dispersal. In this view,bacterial distribution is solely determined by theglobal dispersal of pre-adapted populations. Thisview is primarily based on the 16S rRNA genedivergence, which may not be representative ofchanges in other genes that define specific adap-tive traits. The alternative, a biogeography in partdetermined by evolutionary adaptation to thelocal environment, is now receiving some sup-port. Several studies have shown that geographi-cally separated populations sharing identical orvery similar16S rRNA sequences differ at othergenetic loci (Moore et al., 1998; Casamayor et al.,2002; Rocap et al., 2002b). A recent study byWhitaker et al (2003) found that strains of theextremophile

Sulfolobus

clustered geographi-cally rather than by environmental variables thatcharacterized different hot springs. Theirmultilocus analysis revealed that the geneticdistances between populations increased pro-

portionally with geographic distance, suggestingthat dispersal of populations and exchange ofgenetic material between geographically distantgroups was limited. Using the 16S rRNA gene asa marker, Papke et al. (2003) also observedgenetic differences among thermophilic cyano-bacteria from different geographic regions. Theirdistribution patterns were also ascribed to bio-geographic isolation. These and other cumulativedata suggest that global distribution patternsreflect both endemic and cosmopolitan groups.This is also supported by recent studies of purecultures maintained over many generations in thelaboratory, demonstrating the capacity for con-tinued adaptive change within a single clonal lineof descent (Elena and Lenski, 2003).

Although specific examples are limited, avail-able data point clearly to the importance of con-tingency in metabolic innovation and adaptiveradiation of microorganisms. For example, wide-spread dispersal may follow major metabolicinnovations that derive from interspecies hori-zontal gene transfer within a complex commu-nity, whereas adaptive radiation reflected bybiogeographic patterns may arise from morerestrictive mechanisms of genetic change. A lessspeculative discussion of the evolutionarydimension of microbial community structureand function must await more comprehensivedescriptions of natural communities.

The Proximate System

Chemical and Physical Dimensions

A central consideration in discussing the struc-ture of microbial communities concerns theinterplay between physical and biological con-trols of organization. Microorganisms are smalland experience low Reynolds numbers—viscos-ity and diffusion dominate their world ratherthan the mixing and turbulence more familiar tous. Only the fastest and largest bacterium known,

Thiovulum majus

, is able to significantly increasesubstrate availability by generating advectiveflow through the entire colony via coordinatedcommunal organization (slime veil formation)and motility (Fenchel and Glud, 1998; Schulz andJørgensen, 2001; Thar and Fenchel, 2001). Moregenerally, diffusive delivery of nutrient solutes ismore important than advective transport(Purcell, 1977; Blackburn and Fenchel, 1999),and diffusion determines structure at bothmicroscopic and macroscopic scales. At micro-scopic dimensions, a diffusive “sphere” sur-rounds every metabolically active prokaryoticcell such that substrate concentrations onlyapproach that of the bulk solution several celldiameters away from the microbe’s surface.


Microorganisms have developed a variety ofstrategies to enhance nutrient recovery includingthe production of siderophores, exoenzymes,smallness and motility (Button, 1994; Blackburnet al., 1998; Blackburn and Fenchel, 1999).Directed movement along a concentration gradi-ent gives the prokaryotic cell a mechanism tomove towards regions of higher nutrient concen-tration, and by doing so increases the flux ofnutrient through the cell’s diffusive sphere. Arecent publication (Fenchel, 2002) suggests thateven in a turbulent water column, “nutrientmicropatches” derived from cell lysis and excre-tion by protozoa have life spans sufficiently longto increase nutrient availability to bacteria, notto mention the occurrence of particles or marinesnow. The implications for global processes aresignificant; motile bacteria converging tran-siently on microscale nutrient patches act toaccelerate nutrient uptake and secondary pro-duction on a global scale. The ability of microor-ganisms to utilize available substrates in acompetitive manner, and the distribution ofthese substrates, governs the structure of themicrobial communities.

In environments experiencing limited mixing,diffusion and light attenuation contribute to

stable architecture at the macroscopic dimen-sions of millimeters to meters. These systems arelayered both chemically and biologically. Webriefly discuss several types of layered communi-ties common to aquatic habitats, although werecognize there are terrestrial layered communi-ties as well.

SEDIMENTS. Within a sediment, in theabsence of significant advection or bioturbation,mass transport occurs primarily through molec-ular diffusion. Sediments vary in coarseness andporosity, but in general the sediment matrix lim-its or prevents water to advect through it. Gra-dients are formed whenever the production orconsumption of a product or nutrient (reactant)exceeds the diffusion of that product or reactant.Substrate concentration reaches a minimum (aboundary condition) at a depth at which the rateof diffusion from the bulk phase matches theconsumption rate needed to sustain the mini-mum free energy required for maintenance.Under these conditions, substrate-concentrationgradients reach steady state, yielding character-istic profiles (Nealson and Stahl, 1997; Brusseauet al., 1998; Fig. 3). A key variable is the amountof organic substrate received via sedimentationof organic matter derived from primary produc-

Fig. 3. Chemically stratified freshwater sediment from Lake Michigan and chemically stratified water column of the BlackSea. Although the distributions of the chemicals are similar, the scales over which the chemicals are distributed vary fromcentimeters in lake sediment to meters in the Black Sea water column.

Black Sea(Marine Basin)

% max

A B CLake Michigan(freshwater Sediment)

% max

Hot spring Microbial Mat

00

50

100

150

200

50 100

DE

PT

H (

m)

O2

O2 = 300 µM; Mn++ = 5 µM; Fe++

= 300 µM; NO3- = 10 µM; NO2

- =10.1 µM; NH4

+ = 300 µM; SO4= =

25 mM; H2S = 100 µM.

O2 = 300 µM; Mn++ = 25 µM; Fe++ =25 µM; NO3

- = 30 µM; NO2- = 10.3

µM; NH4+ = 120 µM; SO4

= = 300 µM;CH4 = 300 µM.

NO3-

NO2-

NH4+

H2S

Fe++ Mn++

00

5

10

15

20

50 100

DE

PT

H (

cm)

O2NO3

-

NO2-

NH4+

SO4=

CH4

Fe++

Mn++0

1

2

3

DE

PT

H (

mm

)

O2 or H2S, µM

O2 pH

H2S

pH

6 7 8 9

200 400 600 800 1000


tion in the water column or from terrestrial inputor sediment surface photosynthesis in shallowsystems that allow light penetration to the bot-tom. The observed depth-related changes inchemical composition correspond to a progres-sion of thermodynamically predictable redoxchanges. Given a variety of possible respiratorymodes, those that yield the greatest free energyprevail at each depth under steady state condi-tions. This begins near the surface with oxygendepletion and typically ends with the reductionof sulfate (in marine environments) to producesulfide or the reduction of CO

2

(in freshwaterenvironments) to produce methane.

THE WATER COLUMN. The water columnof marine and freshwater systems may alsoexhibit similar depth related chemical structure,most comparably when oxygen depletionextends into the water column. This is observedin small eutrophic lakes and in the permanentlystratified Black Sea (Nealson and Stahl, 1997;Taillefert et al., 2002). In addition to diffusion-controlled structure characteristic of sediments,the water column is divided by changes in den-sity, temperature and light. The attenuation oflight in the world’s oceans provides the most eas-ily resolvable of gradients along which differentbacterial populations distribute. For example,as previously noted, different “ecotypes” of

Prochlorococcus

are adapted to different lightintensities (Moore et al., 1998; West and Scanlon,1999; Rocap et al., 2002). Physiological analyseshave shown that one ecotype is adapted to thehigher light intensities of the upper water col-umn, having a low chlorophyll (Chl)

b/a

2

ratio,and the other (higher Chl

b/a

2

) to life deeper inthe euphotic zone. Genome sequence compari-sons have also pointed to specific adaptive differ-ences (Rocap et al., 2003). For example, theecotype adapted to the lower euphotic zone haslost the photolyase gene which is involved in thelight-driven enzymatic catalysis of DNA damagerepair, presumably because there is little selec-tive advantage to maintain this function underlow light conditions.

Variables other than light also contribute todepth-related structure of oceanic provinces.Unlike the relationship to thermodynamic pref-erence observed in chemically stratified lakesand sediments, the controlling variables in themarine water column have yet to be fullyresolved. For example, the archaeal phylotypescommon in the open ocean vary in depth-relatedabundance patterns (Massana et al., 2000). Stud-ies of the Antarctic Peninsula showed that plank-tonic euryarchaeotes were most abundant insurface waters (Masanna, 1998). Increasingarchaeal abundance with depth (ca. 25% of totalrRNA) was associated with a shift in dominancefrom euryarchaeal to crenarchaeal rRNA (Mas-

sana, 1998). A more recent study at the HawaiiOcean Time-series (HOTS) station examiningthe depth-related abundance of these archaealgroups (pelagic euryarchaeota versus pelagiccrenarchaea) revealed a similar depth-relatedpattern of abundance (Karner et al., 2001).Pelagic creanarchaea comprised a large fractionof total picoplankton below the euphotic zone(

>

150 m), approaching 39% of total DNA-containing picoplankton detected. These groupsare surely physiologically distinct, as suggestedby a time series study in the Santa Barbara Chan-nel that showed the abundance patterns of thesetwo archaeal groups correlated with generalenvironmental variables (Massana et al., 1997).Other abundant marine picoplankton such as theclade defined by

Pelagibacter ubique

(SAR11)and SAR211 and SAR203 marine clusters alsoshow characteristic depth-related abundancepatterns (Giovannoni et al., 1996; Field, 1997;Wright et al., 1997; Morris et al., 2002). Recentsuccess in culturing representatives of the SAR11 cluster suggests that temperature, not light(Rappe et al., 2002; Zengler et al., 2002), may bean important factor in the growth and distribu-tion of members of this assemblage. The soon tobe available genome sequences for these abun-dant marine picoplankton will undoubtedly pro-vide insights into their physiology and likelyprovide some explanatory basis for the patternsof structure observed in the open oceans.

MICROBIAL MATS. Microbial mats areamong the most visibly conspicuous of layeredcommunities (Fig. 4). Built by photosynthetic orchemolithotrophic bacteria, they share featuresof structure similar to sediment and water col-umn communities, in that population distribu-tion is governed by light availability and diffusiveflux of substrates and metabolites. However,

Fig. 4. An example of a layered community from GuerreroNegro Baja California Sur. The colors denote pigments fromdifferent microbial groups. Photograph courtesy of JesseDillon.


mats provide for much closer physical andmetabolic interactions among contributingpopulations. The most abundant and versatilephotosynthetic mat builders today are theoxygen-producing cyanobacteria (Cohen et al.,1989). The most common types of chem-olithotrophic mats are comprised of filamentoussulfur-oxidizing bacteria, generally occurring onsediment surfaces at the interface between gra-dients of reduced sulfur species and the oxidantsoxygen or nitrate (Jørgensen and Revsbech,1983; Jannasch et al., 1989; Sassen et al., 1993).

The cyanobacterial mats are complete micro-bial ecosystems, comprised of primary producers(cyanobacteria) and populations of consumersthat together mediate all key biogeochemicalcycles (Fig. 5). Remarkably, this ecosystem canbe represented by a fragment of microbial matonly several centimeters on a side. Although thisgeneral type of microbial community is thoughtto have existed for over 3.5 billion years (Cohenand Rosenberg, 1989), the evolution of meta-zoan grazers, competition with macrophytes, andchanging oceanic carbonate chemistry triggeredthe decline of the extensive mat communities(represented by stromatolithic fossils) at theend of the Proterozoic (Grotzinger and Knoll,1999). Today’s mats develop conspicuously onlyin aquatic environments where environmentalstress limits or excludes grazing, most commonlyin hypersaline or thermal habitats. These areamong the best studied of microbial communi-ties and have provided a superb context for stud-ies relating structure and function (Cohen andRosenberg, 1989).

Hypersaline cyanobacterial mats are charac-terized by intense oxygen production during theday in the photic surface layer and by highlyactive sulfate reduction throughout the mat.These gradients virtually disappear at nightwhen the entire mat turns anoxic and sulfidic(Revsbech and Jørgensen, 1983; Canfield andDesMarais, 1993). Both molecular and cultiva-tion studies of the oxic surface layer of cyanobac-terial mats have revealed high numbers ofsulfate-reducing bacteria (SRB; Risatti et al.,1994; Teske et al., 1998; Minz et al., 1999a; Minzet al., 1999b). Although SRBs are classical anaer-obes, oxygen supersaturation apparently doesnot interfere with the activity of near surfacepopulations in these mats (Jørgensen andCohen, 1977; Canfield and DesMarais, 1991;Canfield and DesMarais, 1993; Fründ andCohen, 1992; Jørgensen, 1994; Teske et al., 1998).As yet, there is no physiological or ecologicalbasis to explain these unexpected patterns ofdistribution.

The chemolithotrophic

Thioploca

mats on theChilean and Peruvian continental shelf are themost extensive microbial mats on earth (Gal-lardo, 1977; Fossing et al., 1995). Abundant

Thi-oploca

populations residing in the uppercentimeter of these mats participate in an intensesulfur cycle. The high rate of sulfate reduction(up to 1500 nmol · cm

–3

· d

–1

) is balanced by theoxidation of sulfide by

Thioploca

such that sul-fate is not appreciably depleted (Thamdrup andCanfield, 1996; Ferdelman et al., 1997). Thishighly efficient sulfur cycle has been attributedto a close physical association between sulfate-

Fig. 5. The distribution and conversions of oxygen, sulfur, hydrogen and carbon dioxide within a layered cyanobacterial matcommunity.

Day Night

HS

HS

HS

RepresentativeMicrosensor

Measurements

Dep

th B

elow

Sur

face

(m

m)

0

10

Production ofBiomarkers

Organic andMineral

Biomarkers

Mineral Phases

FeS

Mat Surface

S-Gases

fermenters

phototrophicS-bacteria

sulfatereducers

methanogens

BiomarkerGases

aerobicheterotrophs

cyanobacteria

OrganicAcids, H2

O2 O2 CH2O

CO2 CO2

CO2

CH4

CH4

SO42-

O2 O2

O2

Sinter

chemolithotrophicS-bacteria


reducing and sulfur-oxidizing bacteria. Filamen-tous sulfate reducers of the genus

Desulfonema

were observed growing within the

Thioploca

sheaths, suggesting a complete cycle of sulfatereduction and re-oxidation within individual

Thioploca

bundles, representing an example ofsyntrophy (Fukui et al., 1999).

Some mat populations rely on motility to fol-low shifting chemical gradients. Microbes such asthe filamentous microaerophilic sulfide-oxidizingbacterium

Beggiatoa

monitor local chemical andphysical dimensions of habitat, using that sen-sory input to relocate to environments bettersuited to their physiology.

Beggiatoa

in thecyanobacterial mats of Guerrero Negro followthe diel up-and-down movement of the oxygen-sulfide interface closely (Garcia-Pichel et al.,1994). Other organisms have developed a strat-egy to bridge spatially separated resources. Thisis exemplified by the recent discovery that

Thi-oploca

species use large internal vacuoles tostore high concentrations of nitrate for anaerobicrespiration. Much like a scuba diver fills divingtanks with oxygen to dive in an oxygen limitedwater environment,

Thioploca

migrate to thesediment surface, partially emerge from theirsediment-embedded sheaths to partially enterthe water column, and charge internal vacuoleswith high concentrations of nitrate (Hüttel et al.,1996). They then return (“dive”) to the anoxicdepths of the sediment (gliding at a speed of 3–5 mm · h

–1

) to use their stored nitrate for sulfideoxidation (Maier et al., 1990; Fossing et al.,1995).

BIOFILMS. The term “biofilm” is the gener-ally accepted term for microorganisms attachedto a solid surface in a relatively thin film. Biofilmspervade virtually all environments and surfaces,often dominating the microbial activity distrib-uted between the individual planktonic andaggregated habitats (Van Loosdrecht et al.,1990). Characklis and Marshall (1990) have gen-erally defined biofilms as systems displaying thefollowing four features: 1) cells immobilized at asubstratum and frequently embedded in anorganic polymer matrix of microbial origin, 2)a surface accumulation, which is not necessarilyuniform in time or space, 3) a significant fractionof inorganic or abiotic substances held togetherby the biotic matrix, and 4) transport and trans-fer processes are rate limiting and play a muchmore important role than in the suspendedgrowth microbial systems. The fourth character-istic highlights the importance of diffusion andreaction in controlling population structure andassociated metabolic processes. As for the previ-ously described layered communities, gradientsform in response to the balance between micro-bial synthesis and consumption of diffusiblesubstances, creating niches distinct from the

proximal bulk water. Similar to mat communi-ties, natural biofilm systems provide for a spec-trum of stable habitat types. Thus, a biofilmcommunity of thickness less than 1 mm can havea diverse and stable microbial ecology amenableto study. For example, the biofilms produced byoral microbiota colonizing tooth surfaces pro-vide a model system for experimental study andare receiving increasing attention (Kolen-brander, 2000).

The microbial populations colonizing sus-pended particles demonstrate many attributes ofbiofilms. Suspended organic particles, marineand lake “snow,” conspicuous in aquatic habitatsprovide hot spots of nutrients and carbonsources for bacterial growth (Alldredge andSilver, 1988; Byung and Azam, 1988; reviewed inTurner, 2002). High densities of multiple micro-bial populations are embedded in a mucoidextracellular polysaccharide (EPS) matrix, pro-viding opportunity for interaction. Reduced dif-fusion and high activity serve to create localizedconcentration gradients. Depletion of oxygentowards the center of larger aggregates supportsthe coexistence of aerobes and anaerobes(Alldredge and Cohen, 1987), as revealed by thepresence of sulfate-reducing bacteria (DeLonget al., 1993) and possibly nitrogen fixation (Paerland Prufert, 1987). Because microorganisms arethe only biota having the capacity to utilize thedilute carbon and energy in many aquatic habi-tats, the colonization and transformation ofthese particles by microorganisms represents animportant portion of secondary production andmay play an important role in food web energet-ics, atmospheric CO

2

exchange, and flux ofnutrients to the deep-sea ecosystem throughsedimentation of colonized particles (Decho andHerndl, 1995; Turley et al., 1995). Microbialaggregates provide a link between the dilute dis-solved carbon and higher trophic levels as foodfor larval species and protozoa (Pomeroy, 1974;Karl, 1994) and serve to transfer surface waternutrients to the benthos via sedimentation(Passow, 2002; Turner, 2002).

Interactions among microbial populations inaggregated communities are also modulated byregulatory processes that alter gene expressionin relationship to population density. Regulatedprocesses are those that are adaptive only whenthe population density reaches a critical thresh-old number (the “quorum”). These sensingmechanisms are addressed in the following sec-tion on the metabolic dimension.

The Metabolic Dimension

The previous sections emphasized the role ofdiffusion and reaction in regulating the chemicalstructure of a microbial system. The metabolic


dimension underlies the chemical reactions gov-erning the flux of energy and matter through thesystem. Each microbial population must derivesufficient free energy of reaction for mainte-nance and growth. The biochemical explanationfor how the total free energy available is par-celed out among the populations is the meta-bolic dimension. This dimension encompassesfactors regulating the biochemical response andactivity of populations in any system. We nowhave only a sketchy understanding of the meta-bolic dimension and limit our discussion toselected examples of how quorum sensing, syn-trophy, and symbiosis govern the metabolicdimension to shape microbial structure andfunction.

QUOREM SENSING: A LANGUAGE FORINTER- AND INTRAPOPULATION COM-MUNICATION. It is increasingly apparent thatspecific signalling molecules modulate reactionswithin microbial communities (Fuqua et al.,2001; Fuqua and Greenberg, 2003; Xavier andBassler, 2003). The term “quorum sensing” wasintroduced to describe signaling systems medi-ated by diffusible molecules (autoinducers,primarily different forms of peptides andhomoserine lactones [HSLs]) that regulateexpression of genes that are most beneficialwhen a critical number of microorganisms (thequorum) is present in a locale. The peptide andHSL types of autoinducers primarily controlreactions within a single population, for example,in the production of extracellular hydrolasesduring tissue invasion or in light generationwhen colonizing particles or inhabiting special-ized light organs of certain marine animals (seethe subsection Symbiotic Associations). How-ever, a recently described furanone autoinducer(AI-2) has been implicated in signaling betweendisparate species of bacteria (Xavier and Bassler,2003). A role of AI-2 in interspecies communica-tion is receiving experimental support, such as arecent study by McNab et al. (2003) showing thatinterspecies autoinduction is required for thecoordinated development of a biofilm comprisedof two species of oral microbes,

Porphyromonasgingivalis

and

Streptococcus gordonii

.Recognition of the widespread occurrence of

quorum sensing among microbial species sug-gests there is frequently an active and rich dia-logue between cells comprising one or morepopulations (Fuqua et al., 1994; Fuqua et al.,1996; Hastings and Greenberg, 1999). To date,most examples have been defined in the contextof disease or symbiosis, and they include suchdiverse processes as bioluminescence, antibioticbiosynthesis and resistance, production of EPS,swarming, plasmid conjugal transfer, and theproduction of a variety of virulence determi-nants. Recent studies have revealed the signifi-

cance of quorum sensing in regulating theformation of biofilms (Davies et al., 1998; Huberet al., 2001; Fuqua and Greenberg, 2002; Fig. 6).An especially fruitful lab model for understand-ing the possible role of quorum sensing has beenthe genetically tractable pathogen,

Pseudomonasaeruginosa

, which forms biofilms in the lungs ofcystic fibrosis patients, marking the advancementof a serious and recalcitrant infection of the host.Mutations in the HSL receptors and gene regu-lation have shown that an active quorum sensingpathway is required for the proper developmentof the characteristic

P. aeruginosa

biofilm com-prised of columns of cells embedded in a polysac-charide matrix with open channels betweenthem. This biofilm structure is likely importantfor nutrient exchange with the bulk liquid phase.The induction of biofilm formation is also asso-

Fig. 6. Biofilm development and quorum sensing. a) Thesteps involved in a biofilm development. b) Confocal micro-scope images of a

P. aeruginosa

biofilm developing over timeon a microscope slide. The cells are producing green fluores-cent protein. The mushroom- and tower-like structures thatappear by 8 days are 100

µ

m high. (The images in b) werekindly provided by M. Welsh, P. Singh, and E. P. Greenberg[University of Iowa, United States].)

a Biofilm development

Planktonic bacteria(free living) Quorum

sensingMature biofilm community

Microcolonies

Attachment

b

Nature Reviews | Molecular Cell Biology

8 days

3 days

1.5 days

8 hours


ciated with an increase in resistance to antibiot-ics. Mutants deficient in the production of thespecific HSL formed a flat, undifferentiatedbiofilm.

Although there have been few studies of thepossible environmental functions of quorumsensing, there is a growing consensus that thisand other chemical signaling systems are a fun-damental element of community structure andactivity (Fuqua et al., 1996; Fuqua et al., 2001;Hastings and Greenberg, 1999; Xavier andBassler, 2003). Aggregated microbial communi-ties, regulated in part through quorum sensing,are increasingly viewed as highly adaptive andresilient systems of organization.

SYNTROPHIC ASSOCIATIONS. The meta-bolic connections among different populationscan range from highly specific to generic. Anexample of a generic association may be simplythe use of a vitamin or growth factor released byseveral other cohabiting populations. This typeof interaction would not be expected to exert asmuch control over the organization of a micro-bial system or community as connections thatspecifically link energy recovery between twometabolic pathways. The best examples of sys-tems structured by the parceling of available freeenergy among interacting populations are foundin anaerobic habitats such as the sediment andmat systems described earlier. The anaerobicdecomposition of organic material is carried outby the cooperation of several general physiolog-ical groups of microorganisms (Schink, 1988).Although a variety of other functional assem-blages are present in anaerobic habitats, for thepurposes of discussing syntrophic associations inthe metabolic dimension, only four main groupsare considered here. In the absence of electronacceptors used for anaerobic respiration (e.g.,oxyanions of sulfate and nitrate, and oxidizedmetals), the following four microbial groups aregenerally recognized to participate synergisti-cally in the anaerobic degradation of organicmatter: 1) hydrolytic and fermentative bacteria,which degrade complex biopolymers (e.g., plantcell wall components), and monomers (sugars),and oligomers into acetate, hydrogen, carbondioxide, and a mixture of short chain fatty acids,alcohols, succinate, and lactate; 2) proton-reduc-ing acetogenic bacteria, which convert fattyacids, alcohols, succinate, and lactate to acetate,hydrogen, and carbon dioxide; 3) hydrogen-oxidizing methanogens, which convert hydrogenand carbon dioxide (as well as other quantita-tively less important compounds) to methaneand water; and 4) acetoclastic methanogens,which convert acetate into methane and carbondioxide.

The complete mineralization of organic matteris dependent upon the cooperative growth of all

four groups and is sustained by the microbiallymediated (via methanogens groups 3 and 4)removal of hydrogen (and acetate). Interdepen-dent growth (syntrophy) was first observed byBryant and associates (Bryant et al., 1967; Bry-ant et al., 1977; Wolin and Miller, 1982). Notably,this discovery was a consequence of a failure ofthe pure culture technique! An organism thoughtcapable of methanogenic growth on ethanol(

Methanobacillus omelianskii

) was found to be asyntrophic association of two species of prokary-otes. One bacterium oxidized ethanol to hydro-gen, acetate, and CO

2

(group 2 type). The secondwas a hydrogenotrophic methanogen (group 3type). Neither organism was capable of growthon ethanol alone. The energetic basis of this obli-gate association is the relationship between freeenergy and hydrogen concentration. The fermen-tation of ethanol is only favorable at low hydro-gen concentrations (negative free energy). Thus,although the ethanol-oxidizing bacterium couldinitiate fermentation in a closed system (the testtube), hydrogen accumulation soon made thisreaction energetically unfavorable. Enter themethanogen—its consumption of hydrogen per-mitted a continuous fermentation of ethanol.The methanogen was later formally described(

Methanobacterium bryantii

), but its syntrophicbacterial partner has since been lost.

Although interspecies hydrogen transfer wasdiscovered in a closed system, the test tube, it isnow recognized to determine higher order struc-ture and activity in both natural and engineeredsystems. One dramatic example is the granulestructure that develops in anaerobic reactorsdesigned to treat industrial waste streams(Sekiguchi et al., 1999). Within upflow anaerobicsludge blanket (UASB) reactors, the four func-tional assemblages promote the anaerobicdegradation of organic industrial waste. Thesemicrobiota are retained in the reactor by forma-tion of dense granules of millimetric size, theirsize controlled by balancing sedimentation withmetered upward fluid flow in the reactor. Initialstudies of the USAB granules using molecularprobes to resolve the distribution revealed finelayering of population types, suggesting tightmetabolic connections. The general architectureof each granule consists of a methanogenic core(Archaea), serving to consume hydrogen, CO

2

,and acetate, surrounded by outer shells (layers)of fermentative bacteria (groups 1 and 2) thatsustain the oxidation of the waste stream compo-nents such as propionate, sucrose, and acetate(Fig. 7).

Anaerobic methane oxidation (ANME) isanother example of a layered syntrophic associ-ation of an inner core of Archaea surroundedby sulfate reducing bacteria (

Desulfosarcina

-

Desulfococcus

group; Boetius et al., 2000;


Orphan et al., 2001; Teske et al., 2001; Michaeliset al., 2003). It has been hypothesized that thisassociation (like the layered granules above)involves methane oxidation to hydrogen and car-bon dioxide. If the concentration of hydrogenremains low, this conversion is energeticallyfavorable, although the energy yield is the lowestknown to fuel a microbial metabolism. Removalof the hydrogen is accomplished by hydrogenoxidizing sulfate reducers. Kruger et al. (2004)have isolated from microbial mats a nickel-con-taining protein, which is similar to methyl-coen-zyme M reductase from methanogenic Archaea,the enzyme catalyzing the final step in the pro-duction of methane. The metabolic reactionsbetween the Archaea and sulfate reducers resultin the formation of CaCO

3

reefs that measure1 m wide by 4 m high in the anaerobic regionsof the Black Sea (Fig. 8).

SYMBIOTIC ASSOCIATIONS. Multicellu-lar eukaryotes originated in a microbial world.Thus, a complete understanding of the multicel-lular condition cannot be separated from perva-

sive and intimate associations with prokaryotes.These associations have influenced the evolu-tion, development, and physiology of all multi-cellular life forms (reviewed in McFall-Ngai[2001] and McFall-Ngai [2002]). The phenome-non of symbiosis has been known and studiedsince De Bary (1879) defined it as two dissimilarorganisms living in close association and rangesfrom the beneficial to the pathogenic. Since thenthe study of prokaryotic contributions to theevolution, development and functioning of plantand animal systems has become a highly activearea of investigation (Seckbach, 2002; Bourtzisand Miller, 2003). In medicine there is growingawareness that the so-called “normal flora” isimportant to both health and disease (Rook andStanford, 1998; Relman and Falkow, 2001;Hooper et al., 2002; Hooper, 2004). In responseto the need for microbiologists and animal andplant biologists to work in concert to enableprogress in understanding the details of theseinteractions, a discipline of Cellular Microbiol-ogy was suggested in 1996 to encompass research

Fig. 7. Sections from mesophilic and thermophilic granules viewed by scanning electron microscopy (SEM) and confocallaser scanning microscopy (CLSM). A) SEM of the surface of granules, B) SEM of internal structure illustrating filamentsand rods within layers of the granule, C) and D) are sections simultaneously hybridized with Cy-5-labeled bacterial-domainprobe (EUB338; green) and rhodamine-labeled archaeal-domain probe (ARC915; red). (From Sekiguchi et al. [1999].)

A B

C D

375 µm 200 µm

20 µm 50 µm


devoted to characterizing bacterial interactionswith eukaryotic cells (Cossart et al., 1996).Although the initial focus was on understandingpathogens, the field has expanded its scope toinclude the benign and beneficial associations ofbacteria with host cells. Here we focus our dis-cussion only on the beneficial bacterial associa-tions and emphasize that examples presentedhere are by no means the only or the most impor-tant associations but are fairly well studiedsystems that have provided insights intomechanisms.

All multicellular eukaryotic organisms, includ-ing humans, harbor bacteria that serve somefunction and range in complexity from hundredsof species comprising the populations of themammalian gut to the simplified monospecificcultures in specialized organs such as root nod-ules of legumes and light organs of marine ani-mals. The potential for cooperative associationprovides an evolutionary driving force for boththe host and the symbiont. Bacterial symbiontsof eukaryotes often confer unique abilities thatenable their host to survive on resources thatwould otherwise be unavailable. Examplesinclude: chemoautotrophs (within the largeworms, nematodes, bivalves and shrimp) livingon sulfide or methane in a variety of marinehabitats (Cary et al., 1997; Deming et al., 1997;Streams et al., 1997; Polz et al., 1998b; Fisher,1990; Fujiwara et al., 2001); the production oftoxins and antibiotics by bacteria (Kobayashiand Ishibashi, 1993; Faulkner et al., 1994; Wallset al., 1995; Kaufman et al., 1998; Currie, 1999;Davidson et al., 2001); the production of light(Hastings et al., 1987; Haygood, 1993); bacteriathat degrade cellulose and fix nitrogen in ship-

worm bivalves and terrestrial termites to allowthe hosts to live on wood (Breznak, 1982; Water-bury et al., 1983; Lilburn et al., 2001; Distel et al.,2002); and the associations of cyanobacteria witha variety of fungi to fix carbon and nitrogen(lichens). The activities of certain microbe-hostassociations, such as gut flora of termites and thenitrogen-fixing

Rhizobium

spp. of legumes,influence the structure and function of entireecosystems.

The host environment in turn impacts theadaptations of the bacterial partner, which maylive, divide and grow either extracellularly (usu-ally associated with specific tissue or organ sys-tems) or intracellularly. There is a continuum ofdependence on the partnership ranging frombacteria that are free-living and opportunisticallycolonize the host (i.e.,

Vibrio fischeri

and

Rhizo-bium

) to obligate intracellular symbionts that areunable to live outside of host cells, having lost avariety of genes as a result of their lifestyle(Baumann et al., 1995; Douglas, 1997; Werren,1997; Tamas et al., 2002). The severe reductionof the genome sizes in

Buchnera

of aphids is awell-studied example (Ochman and Moran,2001; Wilcox et al., 2003). The smallest genomes(0.6–1.5 megabases [Mb]) among bacteria arefound in obligate intracellular parasites and sym-bionts (Casjens, 1998). Similarly, the host may beable to live without the symbiont under certainconditions (legumes where there is sufficientnitrogen), or they may lose independence alto-gether. One of the most dramatic examples ofsymbiotic dependence is the loss of the entiredigestive system of hydrothermal vent-associ-ated tubeworms,

Riftia

spp., which rely entirelyon their bacteria for sustenance.

Fig. 8. Image of microbial reef struc-tures. A) Tip of chimney-like struc-ture. B) Broken structure at about 1 mheight. The surface of the structureconsists of gray-black microbial mat;the interior of the mat is pink. Thegreenish-gray core consists of porouscarbonate. (From Michaelis et al.[2003].)

A B

20 cm 20 cm


The vent annelid

Riftia pachyptila

has beenprofoundly modified from its ancestral form totake advantage of the capabilities of its bacterialpartner. This annelid has given up its entire diges-tive system (no mouth, gut or anus), replacing itwith a specialized organ (the trophosome) har-boring carbon-fixing sulfide-oxidizing bacteria(reviewed in Fisher [1990] and Fisher [1995]; Fig.9). Early development of

Riftia

is similar to othermarine annelids; a swimming larva locates andsettles in an appropriate location near a hydro-thermal vent. The developing worm must thenrecruit appropriate free living bacteria capableof collaborating in an ensuing metamorphosisthat results in the loss of the digestive tract toform the trophosome, highly vascularized andpacked with intracellular gamma proteobacterialsymbionts. A multihemoglobin system found inthe red blood and coelomic fluid of these wormsaccomplishes the delivery of both oxygen and

sulfide in a manner that keeps free sulfide levelslow but supplies enough to maintain the demandsof the symbiont (Fisher et al., 1988; Goffredi etal., 1997a; Zal et al., 1998). The free-living bacte-ria have not been characterized, and the rolesthey play in the ecosystem’s nutrient cycling out-side of the tubeworms, or how they transition toan intracellular lifestyle, are not known.

The early recruitment and colonization of abacterial symbiont presents a challenge to bothpartners. The bacteria must evade, or tolerate,host immune defenses and then persist withoutovergrowth. In turn the host must selectivelyrecruit and encourage growth of its necessarypartner without compromising its own health.Several model systems have served to providedetailed understanding of the multiple levels ofinteraction involved in forming and sustaining asymbiotic association. These systems share thefollowing characteristics that render them more

Fig. 9. Bacterial induction of morphological and biochemical adaptations in animals:

Riftia pachyptila

as an example. Thedispersal stage resembles other annelid larvae, but upon acquisition of bacterial symbionts, the juvenile loses the digestivetract to form a specialized organ, the trophosome, that houses bacterial cells within host bacteriocytes. In addition to obviousmorphological changes, the worm has evolved hemoglobin specialized for transport of both oxygen and sulfide (Childress etal., 1987; Southward, 1999; Bright and Sorgo, 2003; Bright, personal communication).

dispersal stage:swimming, feedinglarva

intracellularbacteria

bacteriocytes

bacteriocytemembrane

nutrients

Tube

Plume

Heart

Trophosome cross section

capiliarysettling juvenilewith digestivetract

free-living bacteriabind to and enterjuvenile inducingmetamorphosis

loss of mouth, gut,anus—formation oftrophosomewith bacteriocytes

rapid growth using sulfide as energy source

Trophosome

Ventral bloodvessel

Adaptations include multiplehemoglobins that bind andtransport both oxygen andsulfide—keeping free sulfidelow to avoid poisoning

O2 CO2HS–

HS–O2

CO2


amenable to study: 1) the bacterial partner canbe cultured separately from the host, 2) the hostcan be studied without the symbiont, 3) geneticmanipulation of the bacteria is possible, and 4)the intact lifecycle (or at least early colonizationevents) can be maintained in the lab (reviewedin McFall-Ngai [2002] and Seckbach [2002]).Notable examples of such systems include the

Vibrio

-squid and

Rhizobium

-legume symbioses(McFall-Ngai, 1999; Ruby, 1999; Stougaerd,2000; Lum and Hirsch, 2003). These have yieldedinsight into the biochemistry and genes involvedin the initiation, negotiations, colonization, andpersistence of the bacterial cells in the host. Keysets of characters that are important for coloni-zation of metazoan and metaphytan hostsinclude motility, chemotaxis, adhesion, biofilmformation, and quorum sensing (Ruby, 1999;Hirsch and McFall-Ngai, 2000). Many of theseare also important in pathogenic associations. In

Euprymna scolopes

, modes of defense againstcolonization by the wrong bacteria include oxi-dative stress produced by the host and surfaceadhesins enabling only specific bacteria to enterand bind to host tissue (Weis et al., 1996; Smallet al., 1999; Aeckersberg et al., 2001). Further-more, to avoid overgrowth, the squid has evolveda behavior of ejecting most of the bacteria at theend of the night, when light is no longer needed,and then allowing the remaining 5% to grow upagain during the day while the squid is concealedin the sand. The influence of localized increase innumbers of

Vibrio fischeri

in the water column isnot known (Lee and Ruby, 1994; Ruby and Lee,1998).

We anticipate that this nascent field will begreatly enriched by development of additionalmodel systems, offering comparative frameworkto study theme and variation in symbiotic sys-tems. Recently developed systems that haveproven amenable to dissection of the associationin the lab include

Xenorhabdus

-nematode,

Aer-omonas

-leech, and

Acidovorax

-earthworm asso-ciations. Genetic examination of

Xenorhabdus

spp. and

Photorhabdus

spp. (nematode sym-bionts; Vivas and Goodrich-Blair, 2001;Heungens et al., 2002; Ffrench-Constant et al.,2003; Martens et al., 2003) and

Aeromonas

sp.(leech symbiont; Graf, 1999; Braschler et al.,2003) has identified genes important for the asso-ciation. Initial characterization of a specific asso-ciation between

Acidovorax

spp. bacteria andLumbricid earthworms suggests that this associ-ation is amenable to laboratory study (Fig. 10).Not studied until recently (Schramm et al., 2003),these bacteria have been brought into culture,are vertically transmitted, and likely contributeto nitrogenous waste processing.

Key features that enable bacteria to associatestably with a eukaryotic host are still elusive. The

more complete understanding of the complexgenetic and metabolic systems of interaction isa central challenge in symbiosis research. Withcomplete genome sequences becoming available,comparisons are possible that may reveal com-monalties between bacteria able to associatewith hosts and those that do not. To date, themajority of the genomes sequenced are frompathogens of humans or symbionts dependenton close interaction with a eukaryotic host(Ochman and Moran, 2001). Although this is abias reflective of the human desire to understanddisease, it offers comparative opportunities toexamine which genes confer the ability to asso-ciate stably with a eukaryotic host. Certainlythere are pathogenicity islands, sets of genes thatconfer virulence to normally nonpathogenic bac-teria such as

E. coli

. However, there are alsoexamples of symbiosis islands that confer theability to invade and associate with the host ina positive way, as in the rhizobium-legumeinteraction (500 kb inserted at a tRNA locus inthe plant symbiont

Mesorhizobium loti

; Sullivanand Ronson, 1998). A recent review examiningthese issues suggests that lineages are eitherparasitic or symbiotic and do not switch, suchthat the deep branching pattern of clades indi-cates one or the other lifestyle (Moran andWernegreen, 2000a).

The Temporal System

Diel, Seasonal, and Annual Variation in Structure and Activity

The temporal dimension of microbial commu-nity structure and activity is determined by acomplex interaction of the physical environmenton regular daily, seasonal, and annual cycles thatinfluences biology across local, regional andglobal scales. In aquatic habitats, changes in thestability of the water column related to temper-ature-mediated changes in water density influ-ence nutrient distribution that ultimately altersmicrobial activity, community structure, andinteractions with higher trophic levels. How thecommunity is shaped by these changes varies andultimately influences the productivity of themicrobial community. Since prokaryotes arethe only biota capable of recovering the diluteorganic substrates generally present in aquaticsystems (“the microbial loop;” Fig. 11), theirresponses to predictable diel, seasonal, or annualvariables are fundamental parameters governingthe flux of energy in aquatic habitats (Pomeroy,1974; Azam et al., 1983; Williams, 2000). Themost obvious environmental variables thatchange on a diel cycle are light (

>

400 nm) andtemperature. Light positively influences primary


Fig. 11. Microbial loop of the upperwater column showing the connec-tions between different trophic levels.

Dissolved Organic Matter

NutrientsAvailable N, P and Cand trace elements

Microbial Loop VirusesBacteria

Ciliates

MetazoaGrazing

ZooplanktonPredators

Flagellates

Primary ProductionAlgae

Cyanobacteria

Fig. 10. Earthworm bacterial symbionts. A.) Schematic diagram of the earthworm nephridium showing the directions of flowand the three lobes of the organ. B.) and C.) Laser scanning confocal images of bacterial symbionts of the earthwormnephridia labeled with an

Acidovorax

-specific oligonucleotide probe. B.) Cross section through the ampulla of adult

Eiseniafoetida

. C.) Upper inset, low magnification image showing ampulla visible in each of several segments of a juvenile worm,partially colonized ampulla of a juvenile, and cross section showing the binding of the bacterial cells to the tissue.

septumnephridostome

intakefirst loop

second loop

ampulla

third loopnephridium

gut

pore toexterior

A. C. Early colonization of Juvenile ampulla

B. LSM of Ampulla

100 µm

5 µm

200 µm

Seana K. Davidson


production among cyanobacteria but also inflictsUV radiation damage and creates oxidativestress that reduces both primary and secondaryproduction (Garcia-Pichel et al., 1994; Herndlet al., 1994; Ramsing et al., 1997; Pakulski et al.,1998; Booth et al., 2001b). Examples of variablesinfluencing the seasonal distribution of bacterialspecies are light (Moore et al., 1998; Casamayoret al., 2002), temperature (Murray et al., 1998;Pernthaler et al., 1998; Crump et al., 2003), nutri-ents (LeBaron et al., 2001; MacGregor et al.,2001; Ovreas et al., 2003; Simek et al., 2003),changes in organic matter quantity and quality(Van Hannen et al., 1999a; Van Hannen et al.,1999b; Crump et al., 2003), abundance of grazers(Pernthaler et al., 2001; Simek et al., 2001a;Simek et al., 2003), and episodic viral lysis (VanHannen et al., 1999b; Suttle, 2000; Fuhrman,2001; Hahn and Hofle, 2001). Interannual cli-matic changes also impact the physical structureof the oceanic water column, which influencesnutrient cycling and leads to shifts in the micro-bial community structure. We present a fewexamples from aquatic systems that illustrate thecomplex interaction of physics and biology ondiel, seasonal, and annual time scales that influ-ence microbial community structure and activity.

DIEL FLUCTUATIONS IN MICROBIALGENE EXPRESSION. Here we present a fewexamples of regulation of gene expressiongoverning responses to regularly changingconditions. During daily fluctuations in light,temperature and other physical parameters,there is potential for damage as well as the needto take advantage of optimal conditions fornutrient and energy acquisition. The ability toanticipate diel cycles of these parameters andadjust gene expression on a regular schedulemay have an adaptive advantage. Recent com-parative analyses of complete genomes haverevealed that homologues of the key genesinvolved in circadian regulation (

kai

genes) arewidely distributed among bacteria and archaea,implicating a more general adaptive significanceamong prokaryotes of the ability to anticipateregularly changing environmental circumstance(Dvornyk et al., 2003). Autotrophic and het-erotrophic prokaryotes exhibit diel shifts inactivity regulated by

kai

genes, which belong tothe RecA superfamily of DNA binding proteins(Mori et al., 2002), including nitrogen fixation,cell division, and other metabolic processes,although the clocking mechanism is not yetunderstood (Dvornyk et al., 2003). Synchrony ofthe endogenous clock and the environmentaltemporal cycle has been shown to increase thefitness of cyanobacteria (Ouyang et al., 1998).

Diel changes in expression also occur in directresponse to an environmental variable ratherthan being governed by a circadian gene. For

example, RecA expression occurs on a diel cyclebut in response to DNA damage in the form ofcyclobutane pyrimidine dimers (CPD)resultingfrom absorbance of light in the ultraviolet wave-length (as reviewed in Holm-Hansen et al. [1993],Mitchell and Karentz [1993], Moran and Zepp[2000b], and Jeffrey et al. [2000]). The number ofCPD lesions increases over the course of a day,causing mutations if not repaired. In response,bacterioplankton have coordinated RecA-mediated DNA repair and replication over thediel cycle (Herndl et al., 1994; Pakulski et al.,1998), with RecA protein induction peaking atdusk (Booth et al., 2001b). Since the efficiency ofDNA repair varies among bacterial species(Arrieta et al., 2000), diel fluctuation in UV isexpected to influence the population structure ofmicrobial communities in the euphotic zone ofaquatic systems. These are just two examplesof strategies employed by bacteria in responseto environmental change on a diel scale, and theyemphasize that activities and structure oscillateover time in often predictable patterns.

SEASONAL FLUCTUATIONS IN MICRO-BIAL POPULATIONS. The potential impact ofextreme seasonal changes in chemical and phys-ical variables on a microbial system is wellillustrated by a study of the high mountainLake Gossenkollesee (Pernthaler et al., 1998).Changes in light, temperature, nutrients, andorganic matter quantity and quality resulted inbacterial populations that were annually recur-rent and seasonally variable. Stratification of thewater column occurred from June through Sep-tember with warming of the surface layers, fol-lowed by thermal mixing as temperatures cooledin November and then by ice cover throughoutthe winter and spring. Algae demonstrated a sea-sonal peak in productivity from Decemberthrough February as an under-ice bloom (Fig.12A). This bloom correlated with bacterialproductivity (Sommaruga et al., 1997). Duringautumnal thermal mixing, the total microbialbiomass declined (Fig. 12A) followed by a peakduring December, once ice formation hadoccurred. In contrast,

Alcaligenes

sp. showed anannual maximum in November indicating thattotal biomass estimates often mask fluxes inindividual populations (Fig. 12B). Following icecover, succession continued to occur beneath theice at temperatures ranging from 0 to 4.2

o

C. Forexample,

Rhodoferax

spp. decreased at the onsetof the under-ice algal bloom and then increasedafter the under-ice algae declined (Fig. 12B).During the ice cover melt, bacterial populationsresponded to associated inputs of organic carbonfrom the melting ice, thermal mixing of the watercolumn, and increased temperature. The tightcoupling of seasonal variables and microbialpopulation succession in these lake systems


offers opportunities to analyze and betterresolve the dynamic interactions between biol-ogy, chemistry, and physics in natural systems.Seasonal changes in microbial composition andactivity have been investigated and found inother systems including soil, lake sediment, theMediterranean Sea, and a few oceans (Cannavoet al., 2004; Gallagher et al., 2004; Hasegawa andOkino, 2004; Short et al., 2004; Tanaka andRassoulzadegan, 2004).

Interaction with higher trophic levels throughgrazing also influences the seasonal distributionof bacterial species in aquatic systems (asreviewed by Strom, 2000). For example, a sea-sonal change in nutrient inputs can stimulate arapid increase of heterotrophic microbial popu-lations which in turn stimulates grazing andgrowth of protists in aquatic systems (Simek etal., 2003). Grazing by nanoflagellates and pro-tists can be responsible for changes in morpho-logical structure, physiological status of thebacteria (Posch et al., 1999), and taxonomic shifts

in the bacterial populations (Hahn, 1999; Simeket al., 2001b), affecting overall cell number andsecondary productivity (Simek et al., 2001b;Simek et al., 2003).

Seasonal fluctuations in predation on bacteriaby viruses can also alter the distribution of bac-teria in a community (as reviewed by Suttle[2000] and Fuhrman [2000]). Since virusesrequire contact with a host cell, the density of thebacterial cells affects the probability of infection.This implies that since the dominant competitivebacteria is reduced and the rare bacteria are notlysed, viral dynamics in bacterial communitiesmay influence the number of bacterial speciesthat can co-exist in a resource limited environ-ment (Fuhrman, 1999). While viral infectionsdon’t lead to extinction, they do shift the relativeabundance and growth rates of bacteria on aseasonal timescale. For example, Van Hannen etal. (1999b) showed that the bacterial communitystructure in freshwater mesocosms was constantuntil viral lysis of a spring cyanobacterial bloom.The reduction in cyanobacteria was followedby transient blooms of

Cytophaga

and

Actino-mycetes

suggesting that these bacterial popula-tions grew on organic matter generated fromlysed spring cyanobacterial bloom.

ANNUAL VARIATIONS IN MICROBIALPOPULATIONS. With the awareness that glo-bal warming may indeed be altering climate,there is growing interest in how this will influ-ence longer time scale oscillations in climate pat-terns, and how, in turn, this alters the microbialactivities in the oceans and soils globally. Anexample of a well-studied climatic oscillation,called “El Nino-Southern Oscillation” (ENSO),occurs every 2–7 years (Fiedler, 2002). In non-ENSO years, the trade winds blow in a westerlydirection along the equator resulting in increasedsea surface height in the west (about 0.5 m). Inthe eastern equatorial Pacific, water upwellsfrom the deep ocean, causes a decrease in seasurface temperature (about 8°C), and inputsnutrients (NO3) that fuel algal blooms in anotherwise nutrient limited sea.

During ENSO, the trade winds relax, reducingupwelling, nutrient enrichment (NO3), and pri-mary productivity (Le Bourgne et al., 2002).These change then influence secondary produc-tivity and food web structure. The warming of theupper surface waters enhances thermal stratifica-tion, decreasing the influx of inorganic nutrients(NO3 and Si) and selecting for N2-fixing cyano-bacteria (as opposed to Si-dependent diatoms).Studies in the North Pacific subtropical gyre sug-gest that altered nutrient fluxes associated withclimate variation have contributed to a shift fromeukaryotic primary producers to an array ofautotrophic (Karl et al., 2001) and photohet-erotrophic prokaryotes (Beja et al., 2000; Beja et

Fig. 12. Seasonal dynamics of primary producers and bacte-ria at 4 m in Lake Gossenkollesee, an oligotrophic highmountain lake in the Central Alps of Austria. A.) Seasonalfluctuation in chlorophyll a (m) and bacterial cells stainedwith 4’,6’-di-amidino-2-phenylindole (DAPI) (l) at 4 m. Thehorizontal bar indicates the period of ice cover. B.) Popula-tion dynamics of cells hybridizing with probes GKS16 (Rhod-oferax) (n) and GKS98 (Alcaligenes) (s). (From Pernthaleret al. [1998].)

6

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105

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al., 2001; Beja et al., 2002) that now dominatesthe upper water column in the North Pacific Sub-tropical Gyre. Thus, the gradual increase in seaand atmospheric temperatures has the potentialto alter the time scale and intensity of the ENSO,along with other climatic cycles, influencing theoscillations in microbial ecosystems controllingmajor biogeochemical cycles (Herbert andDixon, 2003; Luo et al., 2003; Philander andFedorov, 2003).

Emerging Technologies Will EnableCharacterization of Structure andFunction Methodological advancements con-tinue to refine our understanding of microbialcommunities within an ecological context.Molecular analyses, often based on comparative16S rRNA sequencing, are now commonly usedto explore patterns of diversity and to a lesserextent abundance. These studies have revealed aremarkable diversity of life previously obscuredby the limitations of established culture-baseddescriptions. Continued refinement of methodsto enable more comprehensive measurements ofmicrobial populations will begin to illuminatethe relationships between population dynamics,physical variables, and the flux of energy andnutrients (carbon, nitrogen, phosphorus, sulfuror other elements).

We anticipate that two analytical develop-ments will greatly enable this research. First,devices or methods capable of making rapid mul-tiple measurements of genotypic and cellularactivities (e.g., DNA microarrays) will providehigh resolution mapping of temporal and spatialvariations in population genotypes and expres-sion patterns. Second, the development ofdevices or methods capable of measuring theactivities at the level of individual cells willdefine the variability of cellular activity undergiven conditions and advance culture capabili-ties. Advances in nanotechnology and microflu-idics will likely be key to realizing this secondanalytical need (Lidstrom and Meldrum, 2003;Hong et al., 2004).

We are now at the leading edge of a revolutionin analytical methods that will inform at the levelof populations and the single cell. Since this levelof resolution will ultimately allow microbiolo-gists to “see the world as microbes see it,” thistechnology will have a profound impact on allaspects of microbiology. Here we highlight onlya few promising areas of development for thestudy of prokaryotes in a more natural context.

MICROAUTORADIOGRAPHY ANDFISH. A common indirect measurement ofmicrobial activity has been based on thymidineincorporation into DNA (Fuhrman and Azam,1980; Fuhrman and Azam, 1982). This and simi-lar approaches (Kirchman et al., 1985) provide

an estimate of growth rate averaged over manybacterial groups (see Kirchman and Ducklow,1993). The contribution of specific populations tobulk processes has been partially revealed bycombining the established methods of microau-toradiography (MAR) and fluorescence in situhybridization (FISH; Lee et al., 1999; Ouverneyand Fuhrman 1999; Cottrell and Kirchman, 2000;Cottrell and Kirchman, 2003). MAR is based onthe incorporation of a specific radioactive sub-strate added exogenously to an experimental sys-tem or environmental sample under controlledconditions. Substrate is generally selected withsome understanding of processes intrinsic to acommunity. Most commonly, cells are fixed to astandard microscope slide, coated with a photo-graphic emulsion, and cells that have assimilatedadded substrate scored by counting silver grainsthat develop following an appropriate period ofexposure (Brock and Brock, 1966). Currentlyavailable imaging devices (e.g., phosphoimagersand beta-emission imagers), although offeringwide dynamic ranges, as yet lack the resolutionof photographic emulsion (Anderson et al., 1997;Andreasen and Nielsen, 1997; Laniece et al.,1998). FISH using oligonucleotide probes thattarget varying taxonomic levels from species tohigher order phyla are then used to identifywhich taxa have assimilated added substrate.For example, a general probe for the bacterialdomain was used to demonstrate that the capac-ity to assimilate thymidine is broadly distributedamong bacteria inhabiting different ecosystems(Bouvier and del Giorgio, 2001; Cottrell andKirchman, 2003).

Combined MAR and FISH now provides amethod to link novel populations (those identi-fied by rRNA sequence alone) with specific phys-iological attributes (Nielsen et al., 1998; Lee etal., 1999). Processes and organisms investigatedso far include nitrification (Daims et al., 2001a),phosphate accumulation (Nielsen and Nielsen,2002), sulfate reduction (Ito et al., 2002), and insitu physiology of Thiothrix in activated sludge(Nielsen et al., 2000). Recently MAR-FISH hasbeen combined with the redox dye 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) to identifyactively respiring cells in filaments of Thiothrix(Nielsen, 2003). An important caveat of interpre-tation is that the method detects uptake of asubstrate but does not necessarily imply growth.Microorganisms accumulating certain sub-strates or compounds (such as phosphate) forstorage can be mistaken for actively growingpopulations.

ISOTOPIC ANALYSES. Stable isotope anal-ysis of microbial communities has been used toidentify sources of organic carbon that supportbacterial growth in a variety of aquatic systems(Coffin et al., 1989; Hullar et al., 1996). The use


of molecular methods together with stableisotope analysis has served to develop linksbetween phylogenetic affiliation and metabolismof specific populations (Coffin et al., 1989; Kelleyet al. 1998; Boetius et al., 2000; Radajewski et al.,2000; Radajewski et al., 2002; Radajewski et al.,2003; Orphan et al., 2001; Whitby et al., 2001;Boschker and Middleburg, 2002; MacGregor etal., 2002; Michaelis et al., 2003). An exemplarymethod is stable isotope probing (SIP) of nucleicacids (Radajewski et al., 2000). As described forMAR-FISH, these analyses are constrained bythe requirement to incubate an environmentalsample with substrate (labeled with a heavy iso-tope) in an enclosed system. Following incuba-tion, DNA (or RNA) is extracted and separatedon a density gradient, the heavy fraction derivedfrom populations having incorporated thelabeled substrate into their nucleic acids. Func-tional and taxonomic gene markers are thenused to characterize those populations contribut-ing to the heavy (or light) DNA fractions. Recentstudies have used 16S rRNA sequence analysesof the heavy DNA fraction to demonstrate con-sumption of 13C-labeled methanol by membersof the Acidobacterium division and Alphapro-teobacteria (Radajewski et al., 2000), incorpora-tion of 13C -labeled CO2 by autotrophic nitrifiers(Whitby et al., 2001), and incorporation of 13C -labeled phenol by populations metabolizing phe-nol in bioreactors (Manefield et al., 2002). SIPhas also been used in conjunction with otherbiomarkers, such as fatty acids, to identify gen-eral assemblages of microorganisms contributingto specific activities in the environment (asreviewed in Boschker and Middleburg, 2002).The method has primary utility in assessingassimilatory reactions in contained environmen-tal samples that allow for significant enrichmentwith the labeled substrate and require relativelyshort incubation periods. Substrates for dissimi-latory reactions (e.g., denitrification of nitrate)cannot be directly measured via incorporationinto nucleic acids, and long incubations maycontribute to indirect labeling of populationsvia leakage of labeled metabolites from primaryconsumers (cross feeding). Genomic studiescombined with SIP have the potential to eluci-date functional diversity in relation to microbialcommunity structure (Wellington et al., 2003).

More recently, FISH has been combined withsecondary ion mass spectrometry (SIMS) tomeasure isotopic composition of individual cells(Orphan et al., 2001) involved in anaerobicmethane oxidation. Another recently describedrRNA-based approach used biotin-labeled DNAprobes to selectively recover specific rRNApopulations for isotopic characterization(MacGregor et al., 2002). In combination withradiotracer approaches, this technique can be

used to measure biogeochemical fluxes throughspecific microbial populations.

DNA MICROARRAYS. DNA-based meth-ods are now commonly used for more directanalysis of community structure. Even so, nostudy has yet to fully resolve the populationstructure of a natural microbial community. Thisis primarily because available formats for nucleicacid-based characterization are not suitable forextensive or intensive analyses. Fingerprintingmethods such as denaturing gradient gel electro-phoresis (Muyzer et al., 1996) and terminalrestriction fragment length polymorphisms anal-ysis (Liu et al., 1997) provide a relatively rapidoverview of changing community structure butdo not serve to either resolve or identify all con-tributing populations, and interpretations sufferfrom the limitations of polymerase chain reac-tion (PCR) biases (Suzuki and Giovannoni,1996; Polz and Cavanaugh, 1998a). An alterna-tive format based on hybridization of complexnucleic acid mixtures to dense arrays of DNAprobes (DNA microarrays) offers the potentialfor rapid and high-resolution analysis ofsequence composition. Each array element iscomprised of a specific DNA probe (an oligomeror PCR amplification product) designed tohybridize to a specific target sequence. Microar-rays were initially developed for expression anal-ysis as a natural outgrowth of genomics—theDNA probes designed to target all genes in aspecific target organism. Microarrays also pro-vide a format suited to more holistic analyses ofmicrobial communities (Guschin et al., 1997;Gibson et al., 2002).

Initial applications of microarrays in microbialecology have been primarily demonstrationstudies, using probes targeting a selected set ofconserved genes to evaluate population struc-ture (e.g., ribosomal RNA genes) or potentialactivity (e.g., nitrification, denitrification, andmethanotrophy; Loy et al., 2002; Bodrossy et al.,2003; El Fantroussi et al., 2003; Taroncher-Oldenburg et al., 2003). Most have relied onPCR amplification to generate sufficient targetfor hybridization and therefore suffer from therecognized limitations of PCR amplification ofmixed environmental gene targets—not all genesare equally amplified. However, the greater chal-lenge is interpretation of hybridization events.Unlike expression analysis of a single organism,characterization of an environmental samplemay be confounded by far greater and undefinedgenetic complexity (Torsvik et al., 1990). Envi-ronmental studies have therefore relied uponindependent assessments, generally by limitedsequence analysis of the amplification productsapplied to the microarray, to confirm hybridiza-tion results (Cho and Tiedje, 2001; Koizumi et al.,2002; Bodrossy et al., 2003). Since different envi-


ronments present different compositions ofnontarget populations, independent validationwould be required for each application. Thus,before DNA microarrays will become robusttools for analysis of environmental systems, val-idation must become an integrated design fea-ture. For example, on-chip thermal dissociationanalysis (El Fantroussi et al., 2003) providedan additional criterion for assessing whetherhybridization originates from a target or closelyrelated nontarget sequence. We anticipate thatfuture developments will allow hybridization ofDNA and RNA isolated directly from environ-mental samples, and thus avoid the biases ofPCR amplifications.

The Future

This is only a selected sampling of the rapidlychanging technology landscape that will enablehigh-resolution analyses of microbial communitystructure and function. In discussing these fewtechnical advances, we have also omitted manyimportant developments in high throughputmethods for culturing environmental organisms(Connon and Giovannoni, 2002; Zengler et al.,2002). Recent development here suggests thatthe isolation of microorganisms that have“resisted” cultivation in the past will soon becommonplace. This exciting development willplace tremendous demands on microbial physi-ologists, and we anticipate that high throughputmethods of physiological and genetic character-ization will naturally develop as the number ofmicroorganisms in culture dramatically expands.The development of nanotechnology promises toprovide tools to study the physiology of singlecells and the measurement of fluxes on scalesthat are relevant to the microbial cell. Althoughapplications of current methods are associatedwith many limitations of format and interpreta-tion, continued advances in technology willlargely determine the future of environmentalmicrobiology as we continue to resolve the struc-ture and function of complex communities thatsustain our biosphere.

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