Central Role of the Cell in Microbial Ecology · the microbial cell as the deﬁning entity in environmental mi-crobiology and microbial ecology. From the level of a cell we can “zoom

MICROBIOLOGY AND MOLECULAR BIOLOGY REVIEWS, Dec. 2009, p. 712–729 Vol. 73, No. 41092-2172/09/$12.00 doi:10.1128/MMBR.00027-09Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Central Role of the Cell in Microbial EcologyKarsten Zengler*

Bioengineering Department, University of California, San Diego, La Jolla, California 92093

INTRODUCTION .......................................................................................................................................................712ISOLATION TECHNIQUES.....................................................................................................................................713OBSERVING MICROBIAL GROWTH...................................................................................................................714WHY ARE MOST BACTERIA CURRENTLY NOT CULTIVATED? .................................................................714

The Legend of the Unculturable Bacteria ...........................................................................................................714The Medium: So Many Choices, So Little Time ................................................................................................715“Dos and Don’ts” in Cultivation ..........................................................................................................................716Watching the Grass Grow: Slow-Growing Microorganisms .............................................................................717

ROLE OF CULTIVATION IN MICROBIAL ECOLOGY ....................................................................................717Multiscale Measurements......................................................................................................................................717Listening Carefully: Bacterial Communications ................................................................................................718The 16S rRNA Is Dead; Long Live the 16S rRNA.............................................................................................719Implications of Genome Heterogeneity and Plasticity.......................................................................................720

Pure cultures .......................................................................................................................................................720Natural populations............................................................................................................................................721

ORDERS OF MAGNITUDE IN MICROBIOLOGY: FROM TRILLIONS TO A SINGLE CELL ................721Synchronization.......................................................................................................................................................721Single-Cell Techniques...........................................................................................................................................721

TOP-DOWN AND BOTTOM-UP APPROACHES IN MICROBIAL ECOLOGY .............................................722CONCLUSION............................................................................................................................................................723ACKNOWLEDGMENTS ...........................................................................................................................................724REFERENCES ............................................................................................................................................................724

INTRODUCTION

There has always been a great fascination in seeing micro-biology in action. Whether it is during controlled fermentationwhile making wine or beer, watching satellite images of oceanwater changing color due to an algal bloom, or sensing thetypical (microbially produced) smell of soil after a rain shower,observing microbiological processes in our daily life reminds usthat we share the planet with myriad unseen microorganisms.Making these microbes visible by looking at colonies on anagar plate or examining them under the microscope, for ex-ample, represents an even greater appeal—and not only tomicrobiologists. This visualization by isolating, growing, andcultivating microorganisms is a task that represents the dailyroutine in many molecular and environmental microbiologylaboratories around the world. Now, at a time when varioushigh-throughput data sets are available to address questions inenvironmental microbiology and microbial ecology, the isola-tion and cultivation of microorganisms have lost the appealthey had for hundreds of years. This review is centered aroundthe microbial cell as the defining entity in environmental mi-crobiology and microbial ecology. From the level of a cell wecan “zoom in” and obtain comprehensive information on mol-ecules and their interactions that define physiology and thephenotype of the cell. The cell level also allows us to “zoomout” and examine the interaction of the cell with other organ-

isms and the environment and to investigate how these inter-changes shape communities and habitats. This review there-fore not only will highlight isolation and cultivation methodsthat allow us to obtain a cell for subsequent analysis in the firstplace but also will assess how and to what extent data obtainedfrom experiments with pure cultures can be extrapolated toanswer questions in microbial ecology. At the same time, thisreview will evaluate how data obtained at the molecular levelas well as the community level can be beneficial to one’s knowl-edge of the cell.

Microorganisms in the environment interact on various lev-els with the microbial community and the environment itself,and the isolation of an organism will in most cases disruptthese interactions. It is therefore important to understand whatforms of interactions exist in the environment and to predictwhat changes in phenotype might occur when these interac-tions are omitted during cultivation in the laboratory. Recentadvances in sequencing technologies have revealed a tremen-dous diversity on the microbial genome level, not only withindefined cultures in the laboratory but also within microbialpopulations in the environment (100, 168, 225). Understandingwhat effect genome heterogeneity has on physiology and phe-notype is essential to interpret the vast genomic data nowbecoming available. The genomic repertoire lays the founda-tion for microorganisms to adapt and evolve in response tochanging conditions in multiple ways, not only in nature butalso in the laboratory. Determining the underlying principlesand causal effects that these adaptations have on the cell’sphenotype and fitness is essential; otherwise, the analysis ofcommunity-wide data can only be of a descriptive nature.

* Mailing address: University of California, San Diego, 417 Powell-Focht Bioengineering Hall, 9500 Gilman Drive, La Jolla, CA 92093-0412. Phone: (858) 822-1168. Fax: (858) 822-3120. E-mail: [email protected].

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When using cells as a kind of stepping-stone to move frommolecular biology data to natural populations and whole en-vironments, it is crucial to evaluate the robustness of this pro-cess. This means that we have to carefully estimate the impli-cations that can be drawn from our data. The following willtherefore cover a wide range of subjects, from biological pro-cesses on a molecular level to individual microorganisms, fromindividual organisms to populations, and from populations tothe environment.

Since the terms isolation, growth, and cultivation are oftenused synonymously, it will be beneficial to briefly define themhere so that they can be distinguished throughout this review.

“Isolation” of an organism (or multiple organisms at a time)describes the process by which individual cells are physicallyseparated from each other and/or from matrix material, suchas water, air, soil particles, or eukaryotic tissues. Isolationtherefore represents the most crucial step during the process ofobtaining pure cultures. Isolation also includes the process bywhich defined cocultures are obtained for further cultivation.

For microorganisms, “growth” implies the division of a bac-terial cell, resulting in duplication of the cell number. Measur-ing and observing bacterial growth, especially in the environ-ment, can be challenging since the rates of growth and of death(e.g., due to apoptosis, grazing by eukaryotic predators, or celllysis by phages) can be identical, resulting in net growth thatwill be zero.

Traditionally the terms “culture” and “cultivation” are usedto describe a defined bacterial population that can be grownand maintained in the laboratory, usually at a scale that in-volves billions of cells at a time. Cultivation is not exclusive topure cultures but can include mixed populations and stableconsortia that are propagated in the laboratory for a prolongedperiod of time.

Microorganisms are isolated, grown, and cultivated in thelaboratory for many reasons. Examples are the enumeration ofbacteria with a certain function or role in nutrient cycling, information and degradation of organic and inorganic molecules,or in bioremediation and energy production. Other examplesinclude the testing of Koch’s postulates, identification of or-ganisms that carry specific genetic information (gene or path-way), evaluation of phylogeny and physiology, and discovery ofnovel enzymes and chemical entities (e.g., anti-infectives) forindustrial and pharmaceutical applications. As broad as thescientific goals are the cultivation methods used to accomplishthem. Depending on whether a defined group of microorgan-isms is targeted (e.g., new bacterial or algal strains for biofuelproduction) or whether “as many as possible” different strainsshould be isolated (e.g., for diversity assessment or to accom-pany metagenomic studies), the most suitable methods andtheir refinement will differ substantially. However, having mi-croorganisms in culture allows for the direct study of morphol-ogy, physiology, genetics, and pathogenicity in great detail,tasks which are difficult to accomplish when solely moleculartools are used.

Advances in molecular biological techniques over the lastthree decades have spurred cultivation-independent develop-ments. In medical diagnostics, for example, isolation and cul-tivation have been replaced by advances in molecular methodsthat can identify specific microbes or genetic markers moreaccurately, often faster, and more cost-effectively. However,

one has to keep in mind that these markers were initially linkedto a certain disease by work that was performed with microbialpure cultures.

ISOLATION TECHNIQUES

Physical separation of individual cells (or groups of cells) isessential to cultivation efforts. This isolation step can takeplace before or after cells are grown (see below). There areseveral methods to physically separate cells, probably the mostcommon of which is separation of cells by spreading them ontoa solid medium. This method was introduced by Robert Kochover a century ago (118) to visualize, isolate, and ultimatelycultivate microorganisms. Although several advances havebeen made in isolating bacteria on solidified medium sinceKoch first used agar-solidified medium (108), the basic princi-ple of isolating bacteria by spreading them on plates and “pick-ing” colonies remains unchanged. The underlying concept isthat a single bacterial cell, spread on an agar plate (or solidmedium made with other gelling agents), will start to divideand consequently form a colony that is visible by the naked eyeor by microscopy. These colonies can then be separated fromeach other using various tools, e.g., a loop or toothpick, de-pending on the colony size. The process is defined by a sepa-ration step (spreading cells onto a plate), a growth step (colonyformation), and the actual isolation step (colony picking). Themost critical step here is the colony formation. It was recog-nized early on that the majority of cells observed under themicroscope will not form colonies on solid media (38), a phe-nomenon that over half a century later became known as “thegreat plate count anomaly” (201). However, it is important tonote that bacterial cultures can undergo certain adaptationsduring these isolation and growth procedures. For example,some strains that were not able to grow on solid media beforewere adapted to form colonies on agar plates after severalattempts (35) (different forms of adaptation will be discussedin more detail below). Other microbes (e.g., some strictly an-aerobic microorganisms) will not form colonies on surfaces butinstead can be grown inside solid media, a phenomenon thatresulted in the use of agar shakes or agar dilution series forisolation purposes (233). Conversely, there are bacteria thatrequire surfaces to grow on (e.g., gliding bacteria), and isola-tion and cultivation of these organisms is hindered by the useof liquid media (189).

Methods by which cells are isolated before growth takesplace include the use of flow cytometry (61, 165), microfluidics(141, 211), or micromanipulation using focused laser beams(so-called optical tweezers) (69, 105). These techniques are allsensitive enough to detect and subsequently separate individ-ual cells (Fig. 1). An approach that does not require single-celldetection for separation is the isolation of bacteria by microen-capsulation (249). A more commonly used technique is theisolation of bacteria via liquid serial dilution (27, 39, 49, 189).This technique is applied especially in cases where bacteria donot form colonies on solid surfaces or where media cannot beadequately solidified with agar, e.g., due to low pH (221).Recently a method that uses nanofibrous cellulose to solidifymedia even at low pH and therefore can support growth ofacidophiles has been described (46, 220).

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OBSERVING MICROBIAL GROWTH

There are several methods with various sensitivities to mea-sure and describe bacterial growth (Fig. 1). Most often, growthis observed by turbidity, using a photometer, or just by lookingat a culture; these methods are suitable if �105 cells per mil-liliter are present. Detecting microbial growth, qualitatively orquantitatively, sounds trivial, but not all bacterial cells are ableto form visible colonies on solid medium plates, and thereforegrowth cannot be detected conveniently by the naked eye.Even within pure cultures, it is known that the rate of colonyformation is not uniform and that several cells might form onlymicrocolonies which cannot be detected by the naked eye (104,235). Therefore, several researchers applied microscopy to ob-serve colony formation on solid agar (112) or membrane sys-tems (60, 114). Even after prolonged incubation of 1 to 6months, many colonies of soil bacteria can still be present asmicrocolonies and might never grow larger (108, 228). Similar“self-limiting” growth behavior has been observed for oligo-trophic marine bacteria (35, 170). Detecting growth by micros-copy, which normally allows a detection of �103cells/ml, in-creases the sensitivity compared to that of turbiditymeasurements, which require higher cell densities (Fig. 1). Amethod that allows for the detection of even fewer cells is thecombination of isolating cells by encapsulation in microcap-sules and sorting by flow cytometry (250). Instead of a flowcytometer, this encapsulation technique can also be combinedwith a microfluidic approach to monitor division of cells (122).Microfluidics can also be applied to observe the division ofsingle cells directly. Advanced methods have been developedthat allow monitoring and screening of large numbers of or-ganisms at the same time. Flow cytometry, for example, allowsthe screening of 5,000 to 50,000 events per second (249), andhigh-throughput approaches using new technologies, such as aGigaMatrix (128) and a microdish (102), have been developedto be applied for miniaturized culture volumes, allowing thegrowth and screening of millions of cells in a highly compart-mentalized format. An advantage of these high-throughputmethods is that they are capable of growing and screeningmany organisms at a time so that cultivation of previouslyuncultivated ones becomes more likely (102, 249). Further-more, there are a variety molecular biology tools that measurevarious cellular components and infer growth from these data(see below).

WHY ARE MOST BACTERIA CURRENTLYNOT CULTIVATED?

The Legend of the Unculturable Bacteria

Over the last decade there has been some discussion aboutthe general culturability of microorganisms. Several authorsreferred to organisms that were known by their molecularfingerprints (mainly 16S rRNA gene sequences) but could notbe brought into culture at that time as they were “uncultur-able.” Clearly, this word has been used in an imprecise way,since many formerly “unculturable” organisms later becamepart of our culture collections (72). However, the majority ofmicroorganisms in any given environment have not been cul-tivated (yet) even when sophisticated media and new cultiva-tion and isolation methods are applied. One possible reason isthat researchers tend to stick to a handful of different media(at most) and do not spend time and effort to optimize nutri-tional needs, i.e., medium compositions as well as physico-chemical parameters such as temperature, pH, salinity, andgrowth atmosphere. The notion that cultivation attempts failbecause exotic compounds serve as exclusive carbon sourcesfor growth is probably not correct. There are many successstories where former “unculturable” microorganisms (in somecases known for decades) have been cultivated in the labora-tory using common nutrients (25, 204, 226); to rely exclusivelyon exotic substrates (140) is therefore more likely the excep-tion than the norm. However, we should note that varioussignal molecules, as discussed later in this review, seem to playan important role during cultivation and that isolation proce-dures likely disrupt this signaling. Cultivation success is prob-ably not hampered exclusively by what is offered to the micro-organisms for growth but, importantly, on how much of thesenutrients is provided—plenty can often be too much. Mediacontaining high concentrations of nutrients, often a billion to atrillion times more than what microbes encounter in theirnatural environment, can have inhibitory effects (1, 158). Bac-teria seem to have developed different strategies to adapt tochanging nutrient concentrations in the environment, whichconsequently will determine if they are able to form colonieson nutrient-rich agar plates (8). Therefore, microorganismsthat have the capability to adapt and cope with high concen-trations of nutrients are often overrepresented in cultivation-based studies (107) and ultimately in our culture collections

FIG. 1. Microbial growth can be directly determined without the use of molecular biology techniques. Methods used to determine opticaldensity or cell numbers vary in their sensitivity. (A) Visualizing the turbidity of a culture with the naked eye allows detection of �105 cells/ml.(B) Observing cells under the microscope allows detection of �103 cells/ml. (C) The use of a flow cytometer in combination with encapsulationof cells detects up to 101 cells total. (D) Growth (division) of single microbial cells can be monitored by microscopy, and cells can subsequentlybe isolated using microfluidic and micromanipulation devices. In addition to microscopy, flow cytometry also allows for detection and isolation ofindividual cells.

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(117). As a response, several techniques that use low concen-trations of nutrients for isolation and cultivation efforts haveemerged (10, 59, 83, 103, 112, 114, 170, 249). However, grow-ing bacteria at a low concentration of nutrients will logicallyresult in low biomass gains. Large culture volumes becomenecessary (170) to obtain enough biomaterial for physiologicaland genetic studies, and techniques to observe growth (Fig. 1)have to be adapted accordingly (see above). Decades ago, anelegant way to circumvent the necessity of large culture vol-umes was introduced by Novick and Szilard (156), who werethe first to use flowthrough setups for growing cells under aconstant supply of nutrients (a chemostat). Since then, chemo-stats have been an excellent tool in microbiology for variousapproaches, such the study of pure cultures, competition ex-periments (125), and the study of mixed cultures and microbialconsortia (57, 205). Another benefit of flowthrough setups isthat inhibitory (by)products which tend to accumulate inclosed cultures are diluted or removed from the system. How-ever, using chemostats for enrichment and isolation of micro-organisms from environmental samples has often not beenpossible without thoughtful modifications, since many organ-isms tend to attach to surfaces of the setup, form biofilms, andpotentially out-compete their planktonic counterparts (116). Amodified flowthrough setup for cultivation purposes, whichprovides a constant nutrient flow at low concentrations buteliminates the formation of biofilms, has been the incubationand growth of separated cells in microcapsules (117, 250).

The Medium: So Many Choices, So Little Time

I have touched already on some reasons and theories whycultivation of the majority of microorganisms in the laboratoryhas failed so far. In the following I will emphasize and discussthat the selection of the microorganism targeted for cultivationdefines all of the following growth and cultivation steps. First,there is the choice of separation and isolation methods (seeabove), which consequently determines the selection of liquidor solid medium for growing cells. Second, it is fundamental todetermine if any contact of cell to cell or cell to substrate isessential for the targeted microorganism to grow. An encap-sulation method (249), for example, is of limited use if directcell-to-substrate contact is required for oxidation and reduc-tion reactions and subsequent growth. Such substrates are, forexample, long-chain hydrocarbons and other crude oil compo-nents that serve as electron donors or an electrode in a fuel-cellthat serves as an electron acceptor. Third, the composition ofthe medium is also critical for the cultivation success. However,we tend to use vitamin and trace element solutions that havebeen developed decades ago without rethinking and redesign-ing their composition. Medium components are known to havean effect on cultivation efficiency, including carbon and energysources (44), various inorganic chemicals and salts (52, 231),signal compounds (22, 31, 80), and trace elements, vitamins,and amino acids (87, 88, 134). Basically, every component ofthe medium other than water has been demonstrated to havean inhibitory effect on certain microorganisms. Accounting forall these inhibitory effects by varying every component of astandard medium can be a daunting task (Fig. 2). To illustratethis, I picked a medium which is commonly used to growanaerobic bacteria and that contains 33 different components

(29). By changing the concentration of a single component ata time, one would need to generate and test 33 different media;accounting for increasing as well as decreasing concentrationsof this component would result in 66 different medium com-binations to be evaluated. Changing any two components ofthe medium at the same time (increasing and decreasing theirconcentrations) would result in 2,112 different medium com-binations to study. Variation of any 22 components at a timewould require an inconceivable �1015 (1 quadrillion � 1,000billion) medium combinations, clearly an unrealistic effort(Fig. 2). Furthermore, these are only variations of an existingmedium, reflecting a medium “optimization” effort. This effortwould neither include other electron acceptors nor account foradditional potential electron donors (e.g., carbon sources),and, more importantly, it does not include differing environ-mental conditions (pH, temperature, salinity, buffering capac-ity, pressure, and gas atmospheres such as different carbondioxide or oxygen concentrations). It has often been cited thatthe media which are routinely used for most cultivation effortsdo not allow growth of most microorganisms in the laboratory.It is surprising that not more attention has been paid to theimprovement of cultivation methods but that instead the ma-jority of microorganisms are categorized as “unculturable.”This might be the case for some organisms, but there is clearly(a lot of) room for rational optimization of just medium com-positions, which has been documented by a number of studies(44, 54).

The recent success of new cultivation techniques and the useof modified media to gain access to previously noncultivatedmicroorganisms demonstrates that many organisms can be iso-lated and maintained in culture in the laboratory (131). Inaddition, it was realized that cultivation of “new” microorgan-isms might be nominal when nutrient-rich, “off-the-shelf me-dia” are being used. When cultivating any kind of microorgan-ism, conditions should be adapted to natural environmentalconditions, by at least adjusting the pH, salinity, and temper-ature (and in some cases pressure [247]) to simulate environ-mental conditions. While this effort has increasingly become aroutine, only few studies consider variations in atmosphericpressures. Many cultivation attempts are performed exclusivelyunder oxic (�20% O2) or anoxic conditions, but only a fewstudies account for low oxygen requirements of microaero-philic microorganisms. Molecular oxygen, however, representsone of the most reactive elements on our planet; only fluorineexhibits a greater electronegativity (the ability of an atom todraw electrons) (162). The reactivity of oxygen and reactiveoxygen compounds such as hydrogen peroxide, superoxide,and hydroxyl radical has been well described in the literature(3, 124). Bacterial life existed on this planet before elementaloxygen was introduced into the atmosphere and with it anincrease of oxidized compounds, such as the common electronacceptors nitrate and sulfate (166). During the time of the slowoxidation event on our planet, microorganisms had billions ofyears to adapt to various oxygen concentrations and ultimatelydevelop fully aerobic metabolisms, utilizing oxygen at atmo-spheric concentrations. There is a broad range of requirementsand tolerances toward oxygen among microorganisms betweenthe strictly anaerobic and fully aerobic bacteria. Some anaer-obic microbes do not tolerate any level of oxygen; others tol-erate various concentrations and have different levels of inhi-



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bition (42, 135). Other bacteria require oxygen for their energymetabolism but are extremely sensitive to higher oxygen con-centrations (139, 161). These fundamental differences in oxy-gen requirement and tolerance had already been described byWinogradsky in the 1880s (236). The degree of flexibility inregard to oxygen not only defines the ecological niches ofspecific organisms but largely affects cultivation success (202).Recently, several microaerophilic organisms that thrive strictlyat the oxic-anoxic interface and tolerate oxygen only at specificand low concentrations have been isolated (55, 153, 193, 216).To maximize the cultivation success, the simulation of thenatural environmental conditions is critical, and the degree ofspecificity increases with the specificity of the requirementsand tolerances of the organism. The smaller the ecologicalniche where the microorganism can thrive is defined, the morespecifically the medium has to be prepared and the environ-mental conditions have to be simulated to allow cultivation.Unfortunately, thorough investigations of the ecological nicheon scales relevant to microorganisms are sparse. Due to thelack of detailed and high-resolution measurements, research-ers tend to simplify what the ecological niche of an organismconsist of. However, only such high-resolution measurement ofvarying environmental parameters (17) offers a peek into the“living room” of a microbe—a necessary insight if we want theorganisms to feel at home in the laboratory.

“Dos and Don’ts” in Cultivation

Growth of microbes in the laboratory is dependent on themedium and the cultivation conditions that are applied. Thisincludes the equipment and materials that are being used forcultivation. It has been known for many years that chemicalsleaking out of plastic and rubber laboratory supplies (pipettes,cultivation plates and trays, rubber stoppers, and tubing) canhave inhibitory effects on bacterial growth (204), and severaladditional bioactive contaminants have been identified (144).The release of substances into incubation setups changes thecomposition of the medium and the environmental conditions.For example, if organic solvents are used as growth substrates,concentration of bioactive compounds leaching out of plasticcontainers can have inhibitory effects. Even filter material usedfor sterile filtration may have negative effects on bacterialgrowth. Therefore, it is desirable that contact with plastic andrubber materials be kept to a minimum during cultivation. Apretreatment of the lab equipment, e.g., by boiling rubberstoppers and tubing with 1 N NaOH followed by additionalboiling in ultrapure H2O prior to use, can also improve culti-vation efficiency (K. Zengler, unpublished data). Inhibitoryeffects have also been linked to certain types of glassware aswell as in general to the use of new glassware. To my knowl-edge, it has never been determined what actually causes theinhibitory effect of certain glassware, but boron nitrides and

FIG. 2. A combinatorics example illustrates the vast number of medium combinations possible by variation of its components. Starting with astandard medium containing 33 components (plus water) and changing one component at a time (gray line) led to 33 different media. Accountingfor variants in concentrations (increasing or decreasing concentration for each component [black line]) resulted in 66 different medium combi-nations. Depending on the total number of components in the medium that will be varied to account for inhibitory effects, the potential numberof combinations will reach over 109 (for one component at a time [gray line]) and 1014 (to account for two variations in concentration).



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other chemicals have been suspected to be slowly releasedfrom the glass and to be responsible for inhibitory effects (108).A thorough washing step, especially for new glassware, canreduce these inhibitions. Also, the quality of water that is usedto prepare the medium is of great importance. Chemical im-purities of water and gelling agents (such as agar or gellan) notonly can affect cultivation success but are known to change thephenotypic behavior of microbes (109, 232). As an example, itwas found that in members of the order Actinomycetales theexpression of pathways encoding certain secondary metabolitesis favored when media are prepared with tap water versusdouble-distilled water. Autoclaving time and its negative sideeffects (i.e., formation of reactive oxygen species or Maillardreaction products) can also have an impact on the cultures (76,110, 195). Physical stress may also have an effect on cultivationefficiency. Certain microorganisms may disagree with JamesBond’s “shaken, not stirred” when it comes to their preferredgrowth environment and grow much better without any agita-tion.

Watching the Grass Grow: Slow-Growing Microorganisms

Even if all the steps mentioned so far are carefully consid-ered, many cultivation attempts will still fail, because the re-searcher has not been patient enough. This is something thathas to be especially taken into account when assigning a cul-tivation project to a graduate student, who has only a limitedtime frame available to complete his or her projects. Part ofthis has to do with the way bacterial growth is determined andmeasured (see above), but it also has to do with the fact thatgrowth rates of most microorganisms in the environment aremuch lower than what we are used to from very commonlaboratory bacteria such as Escherichia coli (Fig. 3). Incubationtimes can reach several months before formation of colonies oreven microcolonies can be observed (109, 184, 249). Somecultures and consortia grow so slowly that it takes years beforevisible biomass is observed, with an anaerobic hydrocarbon-degrading methanogenic consortium (248) being one of the

slowest-growing laboratory cultures reported (Fig. 3). In thiscase, microbial activity during the first year of cultivation ofthis consortium had to be inferred by measuring production ofmethane, and slight changes in turbidity (optical density at 600nm of �0.1) could be observed only after 3 years of incubation(248). The success of cultivation of organisms with such lowgrowth rates depends not only on the patience of the re-searcher but also, even more importantly, on “good timing” forthe cultivation steps (Fig. 3). While some microbes can beisolated and grown in a matter of hours or days, others requireincubation times that range from months to years. It is knownthat certain microorganisms are specifically adapted to slowgrowth (8) and have developed an advantage for, for example,avoidance of lysis by phages (215). Microbial growth is largelydependent on the Gibbs free energy available and mainte-nance energy requirements of the organism (185). However,syntrophic cultures, which survive on maintenance Gibbs freeenergies that are much lower than the theoretical values, havebeen studied in the laboratory (190). There are even reports ofmicroorganisms in subsurface sediments that make a livingwith maintenance energies that are orders of magnitude lowerthan minimum values obtained from laboratory-derived exper-iments. Estimates of doubling times and resulting communityturnover for subsurface microorganisms are between 100 and2,000 years (18). Clearly, microorganisms with such growthrates are not suitable for any classical kind of cultivation ex-periment. So far it is not known whether all members of thesecommunities can adapt to more rapid growth if provided withsufficient nutrients in the laboratory.

ROLE OF CULTIVATION IN MICROBIAL ECOLOGY

Multiscale Measurements

It is important to be aware that comprehensive studies inmicrobial ecology are not restricted to members of the Bacteriaand Archaea alone but have to include all members of themicrobial community, such as fungi, protists, and viruses. Al-though not discussed in this review, it has been recognized thatviruses can substantially influence bacterial and eukaryotic(protist and metazoan) host metabolisms, which consequentlyhas broad implications for the environmental “fitness” of thesepopulations (21, 234). Viruses are the most abundant biologi-cal entity in nature, and several sequence-based surveys haverevealed an enormous viral and phage diversity (180). How-ever, most diversity surveys have focused exclusively on bacte-ria and/or archaea. A comprehensive study comparing theratios of microbial and viral populations based on community-wide data has only recently been performed (50). Given thatstudies of viral and bacterial diversity are already challenging(50, 98, 180), eukaryotic microorganisms (fungi as well as pro-tists) are often ignored as members of the microbial commu-nity in most surveys. Fungi, which play an important ecologicalrole particularly in soil environments, are key players for thedecomposition and cycling of nutrients, and therefore theiractivity is directly linked to bacterial nutrient cycles. Althoughmycologists have been collecting and growing fungi for severalhundred years, the �80,000 fungal species described so farrepresent only about 5% of the estimated total diversity (89).Another group of microorganisms that was described by

FIG. 3. Two growth curves of E. coli (optical density [OD] at 660nm [red line]) and a methanogenic consortium (gas production in ml[black line]) plotted in the same graph over time (days) illustrate twoextremes in microbial growth rates. Successful cultivation of microor-ganisms depends on the growth stage of the organisms and the correcttiming of isolation. After 2 years of cultivation, the methanogenicconsortium exhibited exponential growth, while viable cells from the E.coli culture could no longer be recovered. (Adapted from reference248 by permission from Macmillan Publishers Ltd., copyright 1999.)



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Hooke and van Leeuwenhoek in the 17th century are theprotists, which represent highly diverse taxa of single-cell eu-karyotic organisms that play an essential ecological role in anyaquatic environment (33, 111).

Environments are characterized by both their biological andphysicochemcial parameters. Ideally, a comprehensive analysisof any environment includes the spatial and temporal assess-ment of the composition of its viral, prokaryotic, and eukary-otic communities and their interactions (63) along with high-resolution measurements of the environmental parametersshaping these communities—a daunting task. To make it evenmore complicated, we know that the phenotype of a cell, forexample, is determined by subcellular components. To under-stand the various forms of interactions between organisms andbetween living cells and their abiotic environment, it becomesnecessary to elucidate parts of their subcellular (i.e., molecu-lar) diversity. Such a comprehensive analysis bridges 17 ordersof magnitude (147), from molecular interaction at the DNAlevel (10�10 meter) to single cells (10�6 meter) to whole envi-ronments (from local [101 meters] to global [107 meters]scales). In addition to spatial scales, temporal scales of similarorders of magnitude have to be accounted for as well. Pro-cesses range from molecular events that happen in microsec-onds (10�6 s) to growth rates on the order of thousands ofyears (1011 s). Data obtained at the lowest level (DNA inter-action) can often not directly be used to explain processes atthe highest level (environment) because there is insufficientinformation available on how various data sets can be linkedand integrated quantitatively as well as qualitatively. For ex-ample, a quantitative, genome-wide correlation between tran-scription and translation in vivo does not yet exist becausemany of the underlying principles, such as transcription andtranslation efficiency, are yet not fully understood. It is alsounclear at the moment to what extent this correlation variesbetween different organisms (43). As a result, quantitative in-terpretation of processes on a community level using transcrip-tomic and proteomic data remains challenging. The cell as thedefining entity in these studies can therefore provide a valuablestepping-stone to bridge this gap (see below). This stepping-stone becomes especially useful when multiple data sets arebeing integrated in a rational manner.

Listening Carefully: Bacterial Communications

One example of molecular diversity that can define andshape microbial diversity is bacterial communication. Whenmicroorganisms are physically separated from each other, thiscommunication can be hindered, resulting in unsuccessful cul-tivation attempts. Any cultivation technique that excludes cell-to-cell communication is eliminating a part of molecular diver-sity that might be critical to the growth of a particularmicroorganism. Efforts have been made to simulate this kindof communication in the laboratory, for example, by addingsignal compounds (22, 23, 26, 79, 80) or by keeping the micro-bial community as a whole intact (114, 249). Intercelluar com-munication is widespread within microorganisms and repre-sents the foundation for several aspects of growth andphysiology, cell cycling, molecular clocks, and oscillation. Mi-croorganisms “speak a variety of languages” using moleculeswhich have distinct molecular structures, such as acyl-homo-

serine lactones, �-butyrolactones, 3-hydroxy palmitic acidmethyl ester, quinolones, autoinducer-2, and cyclic dipeptidesand peptides of various lengths (for a review, see reference227). Communication can have multiple effects, e.g., “silenc-ing” of competitors (132) and induction of growth as well asdeath (143, 154). The various signals can promote one-way,two-way, and multiple-way communications and are not lim-ited to intraspecies communication (e.g., formation of fruitingbodies or growth induction) but also take place between bac-teria of different phylogenies as well as between members ofdifferent kingdoms (for example, between bacteria and eu-karyotes) (15, 172, 174). Crucial to all kinds of communicationis that the signals are easily perceived. It makes perfect sensethat organisms react not only to environmental signals such asnutrient supply (e.g., by two-component systems) but also tosignals from “friend or foe” to gain a competitive advantage. Inorder to screen for suitable growth conditions, bacteria have tomonitor their environment closely in order to switch from adormant to an active growth state. This is also highly relevantfor the cultivation of microorganisms in the laboratory. Signalsthat trigger this change of state in microorganisms can includethe availability of nutrients as well as substances released byother growing organisms that function as signals, such as pep-tidoglycan fragments or proteins (148, 191). Recently, anotherhypothesis has been formulated by Slava Epstein (56), whichproposes a stochastic awakening of cells. In contrast to previ-ously described processes, this change from a state of dor-mancy to a state of active growth would not require any signalmolecule but rather would be stochastic. An awakening ofdormant cells is assumed to result from random bursts (noise)in transcription or translation (171). Such stochastic eventsthat trigger changes in the phenotype have been recently de-scribed at a single-molecule/single-cell level for E. coli (30, 36,53, 75, 245). It has been shown that even a single mRNA copywithin a single cell can lead to bursts in protein expression andthat therefore not only transcription but also posttranscrip-tional effects are responsible for stochastic protein expressionprofiles (34). It has been demonstrated that the random dis-sociation of a single protein molecule (repressor) from theDNA can result in large bursts of protein expression in E. coli,ultimately determining the cell’s phenotype (36). In principle,the awakening of dormant cells by random molecular eventstherefore seems possible. However, although this randomswitch from a dormant into an active state is intriguing, thistheory might have limited use for K-strategists (bacteria thatare adapted to slow growth in nutrient-sparse environments[8]), as pointed out by Peter Janssen (106). It is also importantto keep in mind that not every cell of a clonal population,especially in a heterogeneous environment, will encounteridentical conditions. Natural environments cannot be com-pared to our usual laboratory setups where nutrients are beingkept evenly distributed by shaking or stirring. A single mole-cule of some kind (a signal molecule as well as an electronacceptor or donor) might be absorbed by a single cell andinitiate a transcriptional cascade, yet the genetically identicalcell next to it will not be exposed to this molecule and thereforewill not set off a similar transcriptional response eventuallyresulting in cell division and growth. Natural (clonal) microbialpopulations are not synchronized (see below), which repre-sents a huge ecological advantage. Concentrations of nutrients



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as well as signal molecules can be significantly different on asingle cell-level, especially at ultralow (single-molecule) con-centrations. The awakening of single cells in their natural en-vironment could therefore still be a response to an environ-mental trigger, e.g., a few nutrient molecules that are sufficientenough to initiate a transcriptional response. Evaluating thedifference and effects of random and nonrandom responses ina natural population will be essential to our understanding ofdynamic microbial processes. This also reemphasizes the ne-cessity for high-resolution and high-sensitivity measurementsof environmental parameters to accompany microbiologicalstudies.

The 16S rRNA Is Dead; Long Live the 16S rRNA

Estimates about microbial diversity have changed drasticallyover the last decade, mainly due to advances in detection,computational modeling methods, and algorithms applied andthe changing concept of what defines a microbial species (100,138, 168, 196, 223). For example, the numbers of differentspecies or operational taxonomic units (182) within a soil sam-ple vary from below 500 (99) to 2,000 (186), 10,000 (218),21,000 (179), and half a million (51) and even up to nearly 107

cells (24, 71). Part of this discrepancy is due to the diversity ofthe samples themselves (70, 129, 179); another part is likelydue to the varying approaches used to estimate the diversity(167, 168). When analyzing diversity over temporal and spatialscales (see above), it is essential that a marker that is relativelystable and is not mutating rapidly under perturbation or envi-ronmental pressure will be used. Some molecules at the verycenter of biology, which, for example, translate genetic infor-mation into proteins or convert energy in the form of ATP, areless likely to be subject to rapid mutations and therefore couldserve as an evolutionary marker molecule (177). This conceptwas first perceived by George Fox and Carl Woese and con-sequently resulted in the use of sequence information (rRNAgene sequences) to study phylogeny and evolution (66, 238,240). Their discovery was paramount to our current under-standing of phylogenetic relationships and the evolution of lifeon our planet and led to the description of the three domainsof life (239).

The use of a phylogenetic marker enabled the discovery ofthus-far-undiscovered forms of microbial life. Early studies byNorman Pace and coworkers paved the way for the discoveryof the endless microbial diversity that we know today (48, 73,199, 200). Since then diversity studies have been carried out inalmost every imaginable environment, leading to the discoveryof a microbial world that dominates the biosphere but is (inmost cases) impossible to sample properly (167, 241). The 16SrRNA gene, which today represents the basis for microbialecology studies, is hence a perfect molecule to study phylog-eny, evolution, and molecular diversity. It also allows for in-sightful comparisons of different environments and ecologicalniches (78). The use of molecular surveys in microbial ecologyis yet another example where data from the molecular level areutilized and extrapolated to the cell level. However, withoutdetailed physicochemical parameters from the microenviron-ment, ideally on the cell level, these data will likely allow onlysuperficial interpretation (137). There currently exists a com-prehensive yet still rapidly growing 16S rRNA gene sequence

database; however, reports from metagenomic surveys indicatethat current 16S rRNA gene primers are not “universal” andthat some organisms might be missed by approaches targetingthe gene directly (14, 97).

The rRNA is, however, not a good marker when it comes tophysiology, since physiology and phylogeny are not necessarilycorrelated. There are some phylogenetic groups (e.g., methan-ogenic archaea) where this correlation still holds true, butthere are many examples where phylogeny and physiology donot match. An rRNA gene sequence is therefore not wellsuited to predict the function, i.e., phenotype, of an organism.For identification purposes, new cultures and environmentalgenome sequences are generally put into context with theirribosomal sequence. At times the phylogenetic context is usedto imply that organisms with similar 16S rRNA gene sequencescarry out similar functions or have an identical metabolism, butidentical 16S rRNA genes do not automatically translate intoidentical physiologies, identical phenotypes, or identical patho-genicities and similar functions. The phylogenetic context of anorganism can only provide a prediction. To what extent thephylogeny matches the predicted physiology has to be ulti-mately confirmed through experiments. In addition, it is im-portant to keep in mind that the 16S rRNA gene commonlyused for these analyses lacks the resolution at the species level(121, 181). I am avoiding here the discussion about how todefine a microbial species (146, 176), but in any case it isessential to recognize that even if diversity surveys at the spe-cies level become abundant in the future, different strains andsubpopulations of the same species can have very differentproperties (see below). High-resolution diversity surveys there-fore would not solve the current dilemma but would move it toanother level (from genus to species). This intraspecies diver-sity has traditionally been assessed by cumbersome DNA-DNAhybridization, multilocus sequence typing, or average nucleo-tide identity methods (120) requiring large DNA quantities orsubstantial genomic information. However, novel sequencingtechniques, in combination with DNA amplification methodsusing miniscule amounts of DNA, have already started to re-place these efforts (6, 164). Whole-genome sequencing andresequencing recently became broadly affordable and subse-quently paved the way for comprehensive comparativegenomic studies (244). It is now possible to analyze severalgenomes of one particular group of organisms simultaneouslyby comparing whole genomes and identifying shared genes andnonoverlapping sequences—a so-called pan-genome (130, 173,214). This analysis has revealed a vast genomic diversity withinsubpopulations (see below). This diversity of course increasessubstantially when organisms with “almost” identical 16SrRNA genes are included in the study, e.g., E. coli and Shigella.Konstantinidis and coworkers estimated that the pan-genomeof E. coli-Shigella spp. would increase by �300 new genes(equaling �5% of all genes in E. coli) for every new genomethat is sequenced and added to the study (119). If the genomicdiversity within a population is expanding, it is likely that thephenotypic diversity increases as well. In addition to adapta-tion and evolution through mutation (see below), which canhave profound impacts on microbial physiology, genetic mate-rial is transferred by horizontal gene transfer (HGT) betweenclosely related organisms as well between different kingdomsof life. HGT can be mediated by the exchange of plasmids,



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transformation, and transduction (68, 82, 188, 208). Since ad-aptation and HGT take place at different rates and affectdifferent genes in different organisms (67, 177), a direct corre-lation between phylogeny and physiology (phenotype) is ex-tremely difficult to determine. Although this direct link be-tween phylogeny and physiology is not achievable in mostcases, the rRNA gene(s) still represents one of the few markersthat allows for cross-kingdom and cross-phylum comparison,which makes it so ideal for diversity assessments and compar-ison studies. The common question in microbial ecology, “whoare out there and what are they doing?,” however, still awaitsan answer in most cases. Fundamental steps toward this goalhave been made, and recent developments include functionalmetagenomic approaches (115, 207) and the combination of insitu hybridization techniques with microautoradiography, sec-ondary ion mass spectrometry, or Raman spectroscopy (85, 96,133, 150, 159, 160).

Implications of Genome Heterogeneity and Plasticity

After microbial strains have been identified in the environ-ment and successfully propagated in the laboratory, the ques-tion arises as to how and at what level these strains (and dataobtained from them) can be compared to their counterparts inthe original environment. Genomes of different strains belong-ing to the same species can vary substantially (5, 37, 145, 163,229). A well-studied case is the virulent E. coli O157:H7 strain,for which it is known that the genome not only is around 25%larger than that of the laboratory strain K-12 but also encodes1,632 proteins and 20 tRNAs that are not present in K-12 (90).Of these proteins, only 10% are assumed to have virulence-specific functions, leaving around 1,500 proteins being strainspecific independent of virulence (90). Clearly, this high num-ber of proteins can potentially lead to various differences in cellcomposition, physiology, and metabolism (12, 81). Sequencediversity within a whole group of strains was first described forthe pathogen Streptococcus agalactiae (213). When six strainswere analyzed, they shared �80% of any single genome, re-sulting in around 20% of each genome consisting of partiallyshared as well as strain-specific genes (213). Similar trendshave been shown for other organisms such as Haemophilusinfluenzae (94), Helicobacter pylori (77), Prochlorococcus (37),and Sulfolobus islandicus (175). Intraspecies variations (�1%divergent 16S rRNA gene sequences) have also been demon-strated for natural populations of Ferroplasma acidarmanus(4), Prochlorococcus (37), and Vibrio splendidus (217). In ad-dition, vast differences in the locations of mobile genetic ele-ments and clustered regularly interspaced short palindromicrepeats within individual organisms and populations have beenreported, representing a glimpse into the history of viral en-counters for these cells (7, 126, 187). Potential mechanismsthat will lead to these variants (ecotypes) in natural popula-tions have been debated in the past. Evidence for both clonalpopulations (206) and recombining populations (194) has beendescribed (for a review, see reference 230).

Overall, these examples highlight the vast genetic diversity ofsubpopulations within a single defined species. It was men-tioned earlier that part of this genetic diversity can be virulencespecific, but how significant are small genetic variations for thephysiology and phenotype of different organisms? It has been

demonstrated that even relatively small changes in the genome(single-nucleotide polymorphisms [SNPs] as well as insertionsand deletions [indels]) can have substantial effects on the phe-notype and fitness of the strains (13, 169). Mutations can takeplace in structural genes influencing membrane fluidity (246);in metabolic enzymes they can reroute carbon and energyfluxes and increase metabolic efficiency (65, 101); and in reg-ulatory elements or in the transcription machinery (e.g., tran-scription factors and the RNA polymerase or promoter region)they can have effects on transcription/translation speed, tran-script stability, and strength of induction and repression ofgenes (40). It has been demonstrated that organisms adaptrapidly on the molecular level to changing environmental con-ditions by increasing mRNA expression levels (11, 41, 47, 93).Organisms can also adapt their metabolic capabilities, e.g.,utilizing substrates that previously have not supported growth.E. coli, which normally does not grow aerobically with citrate,was able to do so after 31,500 generations, suggesting that theinability to transport citrate aerobically had been resolved (19).

What are the consequences of these findings for studies inmicrobial ecology? How will this affect the interpretation ofdata obtained from laboratory cultures as well as environmen-tal genomic surveys? It has been suggested that evolution ex-periments carried out in the laboratory reflect adaptation andselection patterns found in natural populations (197). Onelimitation of these laboratory experiments, however, is thatenvironmental changes and selection pressures are manifoldand cannot, or can only insufficiently, be simulated in thelaboratory. Another limitation is that evolution is communal(224), and therefore experiments with single organisms canonly glance at the potential genetic diversity that has beenevolved in nature (183). Nevertheless, these laboratory exper-iments are essential in order to understand the general prin-ciples and mechanisms underlying adaptation and evolution.

Pure cultures. The immense genome plasticity observed inpure culture experiments also raises some questions aboutisolation and cultivation efforts. If organisms readily adapt ona genome level to conditions provided in the laboratory, what“kind” of organisms will then be isolated and propagated in thelaboratory? While microorganisms are cultivated in the labo-ratory (e.g., by enrichment cultivation), it is often observed thatthe culture grows faster and faster after each transfer: theculture has adapted to the conditions provided (41). There arealso several reports in the literature where isolated strainscould be adapted over time to grow on certain media; e.g.,isolates could be propagated to form colonies on agar plates onwhich the original isolate was unable to grow (35, 44). Adap-tation to culture conditions can be due to changes in thetranscriptional machinery, but it also can be due to activationof cryptic pathways (84, 123, 149). It is also known that organ-isms undergo genetic changes over time even when cultivatedunder the same conditions, resulting in genetically diverse sub-populations (64, 169, 183, 242). In most cases this “geneticdrift” will remain unrecognized by the researcher. Does thismean that all the organisms in our culture collections representgenetically altered strains that are well adapted to conditionsprovided by the researcher in the laboratory but have no direct(genetic and/or phenotypic) counterpart in their natural habi-tat? It also raises the question of how genetically “pure” theorganisms in our laboratories really are, since they could the-



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oretically consist of multiple members of a subpopulation. Aneffective preservation of laboratory strains at various timepoints after isolation therefore is crucial for the investigations.

Besides differences in individual cells that are based on thegenome or on stochastic bursts in transcription (see above), ithas also been known since the late 1950s that cells can inheritdifferent traits on a nongenetic basis just by asymmetric celldivision (157). This cell individuality is based on a randomdistribution of proteins, such as enzymes and efflux pumps,before and after cell division and will lead to cells that aregenetically identical but that exhibit different phenotypes be-cause of differences in their cell composition (136, 203, 222).Based on the number of these proteins per cell, these differ-ences in phenotype can be passed on to the following genera-tion(s) and can be regarded as a “molecular memory,” which isdifferent for each individual cell.

Natural populations. Assuming that natural microbial pop-ulations are characterized by cell individuality (198) and vastgenetic heterogeneity, would a selective pressure applied bycultivation as well as adaptation to laboratory conditions con-sequently result in the isolation of very similar cultures (on thegenome level)? In other words, would cultivation by itself rep-resent such a strong selection that only one or two individualswould dominate all the isolates obtained from one sample?Exactly the opposite seems to be the case. Thompson andcoworkers obtained 232 Vibrio splendidus isolates from marinewater samples (out of 333 total isolates), which exhibited largeheterogeneity throughout their genomes (217). Similar trendshave been reported for bacteria from low-diversity environ-ments (4, 9). However, isolation of strains at different times,even from these low-diversity environments, will not necessar-ily result in identical strains. For example, two strains of Salini-bacter ruber (M8 and M31), which were used for describing thisspecies, have not yet been reisolated from the same environ-ment (J. Anton, personal communication). The natural popu-lation, on the other hand, can be quite stable; almost identicalenvironmental sequence types were found at the same siteeven after a greater-than-4-year time interval in sampling (4).Targeted reisolation of identical strains (ecotypes) can be dif-ficult, and it remains to be seen if this is due to biases inculturability, unnoticed changes of the habitat, or just the ex-treme genome heterogeneity existing in these populations.

Analyzing genome heterogeneity in microbial populationsinvolves studying whether substitutions in the genome are syn-onymous or nonsynonymous, meaning whether the mutationinfluences coding of the amino acid, thus affecting translationand protein structure (155, 178). It is important to keep inmind that although it is often assumed, synonymous or silentmutations do not always have to be neutral. There are indica-tions that some synonymous mutations can affect the fitness ofthe organism (113). A reason for this may be changes affectingregulatory elements and transcription. For example, cansynonymous mutations have an impact on the promoterstrength, resulting in subsequent changes of expression level?Another effect on transcription levels by synonymous muta-tions is due to changes in codon usage. Also, mutations canbe condition specific, meaning that they can be silent underone condition but can have an effect on fitness under anothercondition. When studying causal effects of genetic heterogene-ity in natural populations, it would in principle be possible to

specifically target genes of interest from the natural commu-nity, study them in greater detail, and by doing so link thegenetic diversity to phenotypic diversity. Unfortunately, inmost cases it will not be possible to a priori predict what genemutations will result in what kind of phenotype (101). In ad-dition, changes in the genomes (SNPs and indels) that lead tothe described phenotypic differences can be so subtle that theymight be undetected by certain sequence approaches, due toerror rates in sequencing and insufficient coverage which pre-vent the identification of these SNPs/indels, especially in thecontext of a genetically diverse population.

ORDERS OF MAGNITUDE IN MICROBIOLOGY: FROMTRILLIONS TO A SINGLE CELL

Synchronization

Most studies in microbiology are traditionally performed ona community level. Since the sensitivity levels of those tech-niques are seldom suitable to work at a single-cell level, mil-lions of cells are needed to perform most experiments (Fig. 1).However, this also means that data are generated from mil-lions, billions, or often even trillions of individual cells. Thedata therefore represent an average of results obtained fromlarge numbers of individual cells. All these individual cells existin different stages of their life cycle, since bacterial cultures aregenerally not synchronized—they are not doing exactly thesame thing at any given moment. For most questions, theseconditions are suitable and synchronized cultures are not anecessity. Although continuous cultivation in a chemostat(156) provides more constant conditions than batch cultures,the cells are still not in a synchronized stage. Truly synchro-nized cultures are obtained, for example, by the use of a tem-perature-sensitive allele of the essential DNA replication pro-tein DnaC (32), which allows the initiation to be synchronizedafter heat shock treatment (237). Another method is the use ofthe amino acid analog DL-serine hydroxamate, which induces astringent response (62). Following the release of the stringentresponse, the cells initiate replication in synchrony. A methodthat allows for synchronized cells without genetic (237) orchemical (62) perturbation, is the so-called “baby machine”described by Helmstetter and Cummings (91, 92). This methodrelies on cells that are affixed to a membrane. When mediumflows through the membrane, newly divided daughter cells arereleased, whereas the parents remain bound to the membraneand produce other cells. All cells released at the same time areat the same growth stage (division stage) (91, 92). These ap-proaches are intriguing, yet they have so far been describedonly for E. coli, and synchronized studies of other organismsare limited. For most experiments, synchronized cultures willnot be available, and we have to be aware not only that ourdata represent average results from many individual cells butalso that these cells exist in different growth stages and thatthey can differ in their cellular composition (e.g., have differentproteins).

Single-Cell Techniques

In order to circumvent issues of culturability, cell individu-ality, and genome heterogeneity and plasticity, as well as dif-



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ferent growth stages, it can be greatly beneficial to study singlecells. However, work with single cells of microorganisms be-yond visualization by microscopy is still in its infancy. Individ-ual components of single cells, such as nucleic acids, proteins,fatty acids, and lipids, are present in such low quantities that inmost cases a direct measurement is not possible. For example,a single cell contains only a few femtograms of DNA. However,due to recent developments in DNA amplification techniques,it became possible to amplify these few femtograms of DNAfrom a single cell to quantities usable by standard techniques(45, 212, 252). This allowed for the sequencing of genomes oforganisms that had not been cultivated before or from whichgenomic information was limited to the information obtainedby metagenomic surveys (2, 95, 141, 151, 164, 243, 251). Elu-cidation of molecule classes other than DNA which are not asstable (e.g., mRNA) or which cannot be amplified is still chal-lenging for prokaryotes at a single-cell level (209, 210). Since agenome sequence by itself does not provide information aboutthe current metabolic state of an individual cell, methods toaddress this question have been developed. Recent studiescombined single-cell measurements of non-DNA moleculeswith time-lapse microscopy techniques to elucidate dynamiccapabilities (136). Great progress has been made in elucidatingsingle-cell individuality for pure cultures, since fluorescent tagscan be introduced into the genome, allowing for dynamic mon-itoring of molecules such as enzymes, regulators, and RNApolymerase (28, 30, 203, 222). Elucidation of cell individualityin natural populations or in cultures for which a genetic systemdoes not exist is still much more challenging. Combinations offluorescence in situ hybridization or halogen in situ hybridiza-tion with microautoradiography (133, 160), secondary ion massspectrometry (85, 150, 159), or Raman spectroscopy (96) arecurrently being applied successfully to obtain informationabout metabolism and cell composition in natural populations.An advantage of noninvasive methods, such as secondary ionmass spectrometry, Raman spectroscopy, and Fourier trans-form infrared spectroscopy (152, 253), is that they allow fordownstream processing of the cells (e.g., DNA amplification).Interpretation of single-cell studies for natural populations canbe challenging not only because of environmental heterogene-ity but also because of the genetically heterogeneous back-ground of targeted cells. Nongenetic differences in cell com-position, the nonsynchronized stage of genetically identicalcells, and the lack of measurements over various time scalesfurther complicate a comprehensive understanding in manycases. However, it is anticipated that further advancements ofthese innovative single-cell methods in combination with high-resolution measurements of environmental parameters will al-low us to gain detailed insights into microbial communities—one cell at a time.

TOP-DOWN AND BOTTOM-UP APPROACHES INMICROBIAL ECOLOGY

In general, various methods used in microbial ecology can begrouped into bottom-up and top-down approaches (Fig. 4).Depending on the specific question, different methods allowdifferent avenues to be used to obtain the answers. The over-arching goal of all these methods is to understand the role ofmicroorganisms in the environment, meaning microbial inter-

actions and the mutual influence of microbial cells with theirbiotic and abiotic environments (where the environment couldbe another organism). For many questions it is suitable toconsider the microbial community as well as the environmentas a “black box” where physical, chemical, and biological pa-rameters can be analyzed as “bulk,” e.g., by microelectrodes,automated remote sensing, rate measurements, labeling stud-ies, and gene surveys (Fig. 4). These methods have the greatadvantage that parameters can be measured in situ, which isindispensable if perturbations to the environment are beingstudied. These “black box” approaches in general do not in-tend to link specific organisms or individual cells with a specificprocesses measured. Many of the meta-omics methods, whichcan be considered to be a kind of “molecular black box” ap-proach, set out to make this link (86, 142, 192). Progress to-ward this goal has recently been made by combining a meta-genomic approach with stable isotope probing, resulting infunctional active community data (115, 207). In-depth knowl-edge about phenotype, metabolism, and transcription andtranslation on a cellular level can only be inferred by top-downapproaches, since direct measurement are so far lacking, butthese are likely to become available in the future. In contrast,

FIG. 4. Top-down and bottom-up approaches in microbial ecology,spanning orders of magnitude in spatial resolution. Top-down ap-proaches (including but not limited to biodiversity assessments, ratemeasurements, isotope signature determination, and various “-omics”studies) utilize data sets which are in general not organism (individual)specific. Interpretation of these data often relies on previous knowl-edge (e.g., in the form of a molecular biology database). Bottom-upapproaches (e.g., cultivation or single-cell techniques and various“-omics” methods) focus on single organisms. Knowledge gained bystudying individual organisms or defined communities is consequentlyextrapolated to larger communities and the environment. Both con-cepts have advantages and limitations (see text) and are clearly depen-dent on the scientific goal.



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bottom-up approaches utilize direct measurements performedat the cell level (Fig. 4). These approaches include isolationand cultivation techniques as well as various single-cell tech-niques, which allow for direct phenotype determination.

Top-down and bottom-up approaches should not be re-garded as isolated approaches but instead should be inte-grated. For example, genome information obtained by a met-agenomic approach can help guide cultivation (221), or viceversa, data derived from pure culture experiments can be uti-lized for comparative genomics to gain insights into the phys-iology of environmental populations (219). These studies havein common that they used the cell as a stepping-stone (seeIntroduction) to integrate data that originated from variouslevels of complexity and at various temporal and spatial scales(Fig. 4). To understand and ultimately predict functions ofcomplex biological systems, large data sets generated by vari-ous methods have to be analyzed, an approach that now isreferred to as “systems biology.” This analysis undoubtedlyinvolves computational methods for data integration as well asfor model building. Computational systems analysis has beensuccessfully implemented for various single microorganisms bybuilding functional biological networks using computationalbottom-up (58) as well as top-down (20) approaches, and ef-forts at integrating both approaches as well as utilizing themfor microbial communities are currently being pursued.

CONCLUSION

In light of the genome-level diversity which trumps phylo-genetic diversity (determined by rRNA gene sequences) byorders of magnitude, Nigel Goldenfeld and Carl Woese rhe-torically asked “…how valid is the very concept of an organismin isolation?” (74). It is unlikely that we will achieve an in-depth understanding of microbial ecology by cultivating allmembers of the microbial community or by making inferencesabout their function in the environment from the informationon their phenotypes displayed in the laboratory. Evidently, inmost cases, we are not able to cultivate them in the first place.If the cultivation hurdle has been overcome, we often fail toaccurately assess what role this particular isolate plays in theenvironment or even if this microbe has any identical counter-part in the environment. This is due in part to the limitedresolution of the 16S rRNA gene and the tremendous geneticdiversity of subpopulations of different organisms. It is alsounrealistic to assume that we will be able to solve questions inenvironmental microbiology solely by applying various meta-omics approaches without having comprehensive and experi-mentally validated databases with which to map and comparethem. With next-generation sequencing and automated anno-tation readily available, we are now in a situation where it canbe faster to obtain a complete genome sequence rather than agrowth curve (127). Does this mean that we have to describe allbiodiversity, cultivate and study all variants, and treat each cellas an individual before comprehensive understanding can beachieved? Not at all—it depends on the level of understandingthat is required to answer our research questions. For example,we know that all human physiology is identical: we all usevarious carbon sources as electron donors and oxygen as aterminal electron acceptor. Sequence information tells us thatthere are differences within the genomes of individuals, but

they do not affect basic physiology. However, we know thatthese variations can effect pigmentation, tolerance toward cer-tain foods, and susceptibility to diseases and drugs, which ex-plains why different groups of people get easily sunburned, arelactose tolerant, or develop a certain disease that can be curedby a certain drug. Understanding the traits of a group of indi-viduals therefore allows us to recognize the niche of this groupand ultimately understand human biology as a whole. Thisshould also be the case for microorganisms; depending on thequestions asked, we have to consider common traits of groupsof individual cells.

I believe that a comprehensive understanding of microbialcommunities can be achieved only by the synergy betweentop-down and bottom-up approaches, with the cell as a junc-tion between them (Fig. 4). The central unit in microbial ecol-ogy therefore has to be the microbial cell (Fig. 4). A censusalone, no matter how detailed and on what level of complexityit is performed, will not allow for a comprehensive view of agiven environment. Counting, even sequencing, all individualsof a certain group of animals (as an example from macro-ecology) will not give us detailed information about their be-havior or physiology. Additional information will be needed;e.g., what do these animals live on, who might live on them,and how is their habitat defined? For a microorganism thiswould mean acquiring detailed knowledge about other micro-organisms (bacteria and archaea but also protists, fungi, andviruses) present in that environment as well as performingcomprehensive analyses of the ecological niche. Studying theorganism in captivity (as a culture in the laboratory) will alsonot allow us to really understand its role in the environment,but it will enable us to formulate hypotheses and theories,originated from direct measurements, which can be, andshould be, tested “in the wild.” Microorganisms cannot beregarded as just the sum of their parts (genome, proteome, andmetabolome). Only the rational integration of different datasets (their “parts list”) will advance our knowledge of variousmicrobial phenotypes in the environment. The knowledge ofthe genome, transcriptome, proteome, and metabolome of anorganism does not consequently lead to a systems-level under-standing of this microbe; these data have to be assessed in atimely and condition-specific manner and rationally integratedin order to fathom the dynamics of microbial life.

Understanding and predicting bacterial phenotypes involvesknowledge about how genetic information is transcribed andtranslated into proteins. The regulation of this informationflow is essential to generate a systems-level understanding,both for a single organism and ultimately on the communitylevel. When studying microbial ecology, it is important to usethe cell as a central unit, a kind of stepping-stone, to overcomelimitations of individual data represented at various scales ofresolution, spatial as well as temporal. A similar concept hasbeen perceived for human biology, where in analogy to micro-bial ecology, data from various cell types have to be integratedinto a whole (the human body). Sydney Brenner, Nobel laure-ate in medicine, stated, “I believe very strongly that the fun-damental unit, the correct level of abstraction, is the cell andnot the genome” (unpublished lecture, Columbia University,2003). In the same way we use molecular data in human biol-ogy to understand processes on the cellular level, the organlevel, and finally on the level of human physiology, we can use



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the microbial cell as a central unit for understanding of pro-cesses on a community level and finally an environmental level.Assuming that microbial cells are central to completing thelink between various forms of diversity for subsequently un-derstanding complex systems, then it is most beneficial to ob-tain as much information as possible about the cell as a whole.Cultivation of microorganisms, when possible, enables thesedetailed studies under dynamic conditions and allows us toformulate biological principles and generate a knowledge base,onto which “-omics” data can be mapped and linked to. Therational integration of various data sets obtained by top-downand bottom-up approaches is therefore crucial for any systems-level approach on which we are embarking, from a single cellin the laboratory to whole microbial communities in the envi-ronment. Around the turn of the last century, tremendousadvances in environmental microbiology that still shape anddefine our current research were made (16, 236). Today, 120years later, we are again at a point in time where enormousbreakthroughs are being made. These advances are possiblenot only because of novel technology and methods availablebut mainly because of interdisciplinary research that bridgesthe gap between molecules, single cells, and microbial commu-nities. What better time than now is there to be a microbiol-ogist?

ACKNOWLEDGMENTS

I am tremendously thankful to Wiebke Ziebis for fruitful discus-sions, valuable insights, and critical review of the manuscript. I alsothank Marc Abrams and Kenyon Applebee for editorial help.

This work was supported in part by the Office of Science (BER),U.S. Department of Energy, grants DE-FC02-02ER63446 and DE-FG02-08ER64686.

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