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Diversity and dynamics of microbial communities in engineered environments and their implications for process stability
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Diversity and dynamics of microbial communities in engineered environments and their implications for process stability Aurelio Briones and Lutgarde Raskiny The availability of molecular biological tools for studying microbial communities in bioreactors and other engineered systems has resulted in remarkable insights linking diversity and dynamics to process stability. As engineered systems are often more manageable than large-scale ecosystems, and because parallels between engineered environments and other ecosystems exist, the former can be used to elucidate some unresolved ecological issues. For example, the process stability of methanogenic bioreactors containing well-defined trophic groups appears to depend on the diversity of the functional groups within each trophic level as well as on how these functional groups complement each other. In addition to using engineered systems to study general ecological questions, microbial ecologists and environmental engineers need to investigate conditions, processes, and interactions in engineered environments in order to make the ecological engineering of bioreactor design and operation more practicable. Addresses Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 North Mathews Avenue, Urbana, IL 61801, USA e-mail: [email protected] y e-mail: [email protected]
or other engineered environments. Although the similarities and contrasts between these two problems may be intuitively obvious, until recently, methodological limitations have hindered the experimental characterization of complex microbial communities in engineered and other environments. As it is difficult to directly observe microorganisms and measure their activities in situ, our knowledge about the ecology of microbial communities depended for a long time on cultivation-based studies. At present, there is little doubt that cultured (or even culturable) microorganisms represent but a tiny fraction of the total microbial community in most environments. Therefore, any knowledge gained from cultivation-based approaches can at best reflect a partial picture, or in some cases can be totally misleading. The situation has changed with the advent of numerous molecular biological tools, which preclude the need for cultivation. It should be noted, however, that cultivationbased methods cannot be totally supplanted in ecological research. For example, the ratio of culturable cells to total cells in a microcosm can provide a useful measure of the successional state in an ecosystem [4]. Furthermore, detailed physiological studies, which are often important in ecological research, almost always require cultivation of relevant microorganisms.
Current Opinion in Biotechnology 2003, 14:270–276 This review comes from a themed section on Environmental biotechnology Edited by Ian M Head and Mark J Bailey 0958-1669/03/$ – see front matter ß 2003 Elsevier Science Ltd. All rights reserved. DOI 10.1016/S0958-1669(03)00065-X
Abbreviations PCR polymerase chain reaction
Introduction The question of how the diversity and dynamics of communities contribute to ecosystem stability is a contentious and evolving issue [1]. Moreover, the applicability of certain classical tenets in ecological theory (e.g. trophic cascades) to microbial communities appears to be doubtful in certain ecosystems [2,3]. Nevertheless, any investigation linking microbial community dynamics to process stability deals with basic ecological issues. How an ecologist grapples with these issues in order to better understand the sustainability of an ecosystem has obvious parallels to maintaining the process stability of bioreactors Current Opinion in Biotechnology 2003, 14:270–276
The most widely employed molecular approaches to study microbial community structure begin with the polymerase chain reaction (PCR). This method’s relative simplicity and extreme sensitivity allow us to easily amplify signature sequences (usually fragments of either 16S rRNA or a unique functional gene) corresponding to target population(s) from almost any environment. PCR products can then be analyzed by DNA fingerprinting methods [5,6], yielding a snapshot of the community structure. Each unique PCR product can also be sequenced (after cloning or separation in fingerprinting electrophoresis gels) to provide information on population identity and thus characterize the community’s structure. Numerous biases inherent to PCR preclude straightforward quantification of populations based on amplification products [7]. Nevertheless, reliable PCR-based quantification can be achieved using specially designed primers and sensitive optical detection [8,9]. At present, however, oligonucleotide probe-based hybridization methods are more widely employed for quantitative purposes [10]. These include membrane hybridization and fluorescence in situ hybridization (FISH), with the latter also offering the advantage of visualizing spatial distributions of microorganisms in a sample. Recent advances in probe hybridization methods www.current-opinion.com
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include the development of molecular beacons [11] and peptide nucleic acid (PNA) probes [12], both of which offer greatly improved signal-to-noise ratios (C Xi, M Balberg, S Boppart, L Raskin, unpublished data). The availability of these and numerous other methods now allows us to better integrate the information gained from (microbial) ecological research with the design and optimization of bioreactors and other engineered systems. In this review, we describe recent advances in ecological and environmental engineering research that deal with relationships between stability, community dynamics and community diversity. We also emphasize parallels between large-scale ecosystems and engineered environments as recognizing these parallels can lead to a better integration of concepts and theories in community and ecosystem ecology as well as improvements in bioreactor design.
Ecosystem, community, process and functional stability Our understanding of ecosystem stability has changed through the years. From mostly intuitive beginnings, our present understanding owes much to recent advances in theory and research [13,14]. Pimm [15] identified an array of properties (e.g. resistance, resilience and temporal variability), which are commonly used to describe ecosystem stability. These properties are applied to characterize two components of an ecosystem: the biotic component (communities) and the process component, which is usually seen as the flow of matter or energy among the functional compartments of the ecosystem. Characterization of each of these components in an open, complex, and large-scale ecosystem is a daunting task, prompting a division of labor that has resulted in two ecological subdisciplines: community ecology and ecosystem ecology. To this day, the full integration of these branches remains one of ecology’s biggest challenges [14]. Bioreactors and other engineered systems offer a setting that is generally far more manageable, in terms of studying processes, than most large-scale ecosystems. Nevertheless, the aforementioned methodological limitations, coupled with limited exposure to ecological research, have led many environmental engineers to describe stability almost entirely in terms of processes and functions, often failing to take into account the community component. Interactions between microbial ecologists and environmental engineers, combined with the availability of new methods to characterize community structure, offer exciting opportunities to integrate the concepts and theories of community and ecosystem ecology into a unified picture. This should lead to better ways to describe and predict how all types of stability develop, how they are maintained, and how an engineered system can recover from unstable periods. At this stage, however, it is not clear to what extent findings obtained from engineered systems can be generalized across ecosystems. www.current-opinion.com
How community dynamics give rise to functional stability through functional redundancy For most of the past century, equilibrium-based views on ecosystem stability attained the status of dogma in ecology. However, it is becoming clear that equilibrium-based concepts of stability apply mainly to aggregate community or ecosystem properties, whereas individual populations are generally in a state of flux even under stable conditions [16,17,18]. Ecosystem stability coupled with constant population flux is a more likely outcome as the number of populations increases due to a statistical ‘averaging effect’ (i.e. in the absence of strong population interactions, the stability of aggregate properties may result from purely stochastic fluctuations in population abundances) [19]. This partly explains the positive correlation between biodiversity and ecosystem stability. While Doak et al. [19] described this correlation as a ‘statistical inevitability’, there are biological processes (namely, competition and functional complementation) that underlie this averaging effect. We are only now beginning to link community dynamics with processes and functions in engineered systems. However, some evidence tends to indicate that levels of individual populations fluctuate in a functionally stable community. Fernandez et al. [20] monitored the community dynamics of Bacteria and Archaea in a functionally stable, continuously mixed methanogenic reactor for 605 days and found differences in the levels of diversity and dynamics between the bacterial and archaeal domains. The population diversity within the bacterial domain was nearly four times higher than in the archaeal domain, and the bacterial populations displayed a highly variable pattern of temporal variation, despite stable system function and constant environmental conditions. In contrast, archaeal populations displayed less temporal variability and exhibited a more defined pattern of dominance and succession. Similar results were observed in another methanogenic reactor system, a fluidized bed reactor fed with vinasse (wine distillation waste) in which the biomass was immobilized on powder from porous volcanic stone [21]. However, nonequilibrium behavior of populations under functionally stable conditions is not always observed. In a series of full-scale, aerobic reactors treating pharmaceutical wastewater, LaPara and colleagues [22,23] showed a relatively stable community structure during an 87-day period of reasonably constant influent characteristics. Moderate shifts in populations were observed only subsequent to changes in influent properties. A more stable community structure in this case could be explained by the difference in scale between a full-scale wastewater treatment plant and the anaerobic bioreactors described above. An equilibrium model based on island biogeography would predict a more stable community structure in the full-scale plants Current Opinion in Biotechnology 2003, 14:270–276
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[24]. However, it is also tempting to hypothesize that systems selecting for functionally more flexible populations (e.g. facultative bacteria) may compensate for the need for higher population diversity, therefore dampening population fluctuations. By contrast, methanogenic reactors require the presence and activity of at least three defined trophic groups — fermenting bacteria, syntrophic bacteria, and methanogens — of which the latter two certainly cannot be considered functionally flexible. In this case, a higher degree of population diversity among fermenting bacteria (leading to population oscillations) would be expected to maintain stability. The methanogens and syntrophic bacteria in this system parallel keystone or driver species in higher ecological systems [25,26]. As there are fewer representatives of these functional groups, and because they exert stronger influences upon overall system function, the bulk of diversity and functional redundancy ultimately rests on the functionally weaker species — the fermenting bacteria. A large amount of theoretical and experimental work would be required to fully examine this hypothesis. At present, there are no common standards for measuring process stability. In the cases cited above, the stability of the aerobic reactors was monitored mainly through chemical oxygen demand (COD) measurements, whereas in the anaerobic reactors it was also possible to measure metabolic intermediates, such as volatile fatty acids, methane and hydrogen [27]. Therefore, the explanation for the apparent contradictions between aerobic and anaerobic systems may also rest upon methodological difficulties in evaluating functional stability. At this point, however, these problems do not appear to be insurmountable, and it will be interesting to see how future studies will resolve the issue of community dynamics in anaerobic/methanogenic versus aerobic systems. Regardless of the nature of community dynamics in a constant environment, a stable system must possess the ability to maintain process stability in response to disturbance(s). This does not imply that the microbial community be stably maintained. In experiments conducted on replicated, continuously mixed methanogenic reactors that maintained two different microbial communities, designated the high-spirochaete and low-spirochaete reactor sets, the less stable community structure was correlated to more stable function [28]. In this case, the less stable community was one that displayed greater temporal variation of bacterial populations in response to substrate (glucose) shock. This high-spirochaete community responded to glucose perturbation by shifting the relative abundance of fermenting bacteria and then returning to structural characteristics close to those before the perturbation after functional performance had stabilized. By contrast, reactors that were dominated by streptococci prior to glucose perturbation (the low-spirochaete reactor set) showed minimal community changes in response to substrate Current Opinion in Biotechnology 2003, 14:270–276
shock. These results were correlated to the substrate processing structure that developed in each reactor type prior to perturbation: substrate processing through parallel pathways was associated with a functionally more stable (resilient) system, in contrast to serial processing of substrate [27]. In other words, a system with more pathways toward methane production was functionally more stable than one that relied on a series of interdependent metabolic events. An important outcome of these and other experiments is the realization that population diversity alone does not drive ecosystem stability. The positive relationship between the presence of multiple pathways towards a product (parallel processing of substrate) and functional stability parallels theoretical concepts in higher ecological organization [29]. Ecosystem stability is the outcome not of population diversity per se, but of functional redundancy, which is ensured by the presence of a reservoir of species able to perform the same ecological function. Recognizing the diversity and the links within each key functional group of a system can lead to better ways to model diversity and function [30], as well as helping to improve process stability [31]. It is now clear that, even using molecular techniques, identification of every species in most environments is a daunting task [32]. Nevertheless, much progress has been made in linking identity to function among key microbial players in a variety of engineered systems [33,34]. Armed with this knowledge, we can begin to explain the discrepancy in performance between similarly constructed bioreactors [35]. However, only by gaining a better understanding of functional diversity and interactions between functional groups and abiotic components can we hope to achieve the level of understanding required to predict system performance under a given set of conditions.
Recognizing conditions, processes and interactions that promote stability – a prerequisite for ecological engineering Ecological engineering is a term used to describe the process of designing and operating bioreactors and other engineered systems to foster the development of specific microbial communities that can accommodate the desired functional processes [36]. As pointed out by Grady and Filipe [37], environmental engineers have been practicing ecological engineering, either consciously or unconsciously, ever since the first bioreactor was built. It requires an understanding of ecological principles, the physiological requirements of the desired population(s), and the spatial juxtapositioning of various populations. In large-scale ecosystems, functionally minor populations typically predominate over keystone or driver populations [25,29]. Nevertheless, interactions arising from www.current-opinion.com
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both strong and minor populations are important for maintaining ecosystem stability [1,38,39]. Thus, both groups of populations need to be monitored when practicing ecological engineering to design and operate bioreactors. For example, the various trophic levels in a methanogenic bioreactor are represented by several functional groups differing in their degree of diversity [20, 27,28]. The less diverse Archaea, represented mostly by the methanogens, are the drivers [40] in this system, while the populations in the more diverse bacterial domain, representing most of the fermenting bacteria, play individually minor roles compared with the methanogens. Therefore, it is not surprising that many studies have focused on identifying and quantifying methanogens and closely associated syntrophic bacteria, as reactor performance is expected to be more highly dependent on the dynamics of these functional groups. However, in the long run, even minor players are expected to contribute strong effects depending on the heterogeneity or perturbations on the system [38] and the degree of species richness [39]. Thus, for anaerobic bioreactors that are subjected to a wide range of perturbations over time, it becomes crucial to be able to characterize the so-called minor populations and their interactions. Ecological engineering of bioreactors can most easily be illustrated by considering a study in which a bioreactor was designed to accomplish a single function: the removal of soluble mercury from wastewater [41]. Reactor performance was better in the presence of multiple species of mercury-resistant bacteria than with monocultures with the ability to detoxify mercury [42]. In a simple system designed for maintaining a single functional group of bacteria, each member is important to system function. Increasing the number of members in the system (i.e. increasing the functional redundancy) ensures a reservoir of functional responses to disturbances through time, thus ensuring a functionally more stable system performance. In a simple bioreactor, where each population is functionally important, there is a straightforward relationship between functional redundancy and stability. Excellent examples of microbial communities that typically incorporate many of the characteristics of functional stability are found in biofilms and granules. These structures, which can be defined as aggregates of microorganisms and organic and inorganic matter held together by extracellular polysaccharides, are often formed in engineered systems. In the case of biofilms, the microorganisms require the presence of a surface to adhere to and grow on. This definition, however, fails to reflect the degree of structural and functional elegance that can be achieved in these microbial aggregates [43]. Within a single reactor system, biofilm communities have been shown to be highly distinct from the suspended biomass [44,45], which in some cases is also reflected by higher population diversity in the sessile (biofilm) communities [46]. It should be www.current-opinion.com
noted that studies that have compared the functional diversities in microbial aggregates with those in corresponding planktonic communities are scarce. Due to the spatial localization of populations and functions in biofilms and granules, local effects can have significant impact on bioreactor function. For example, McMahon et al. [47] showed that process stability in a methanogenic reactor could be disrupted by a vigorous and continuous mixing regime, which presumably disrupted the spatial juxtaposition of syntrophic bacteria and their methanogenic partners. The higher process stability of minimally mixed reactors extended to times of substrate perturbation, confirming the resistance of the system to shock loadings [48]. These experiments demonstrate the importance of recognizing the complementary functional niches in a bioreactor system. For a complex task such as anaerobic wastewater treatment, functional niche complementarity can also be achieved by spatial or temporal separation of functional groups, as methane production relies on the interdependence between trophic levels. Nevertheless, this does not always function optimally in a homogeneous environment (like that found in a single, continuously mixed reactor). For example, a higher degree of heterogeneity is achieved in an anaerobic baffled reactor, a bioreactor with multiple, interconnected compartments [49] that has been shown to perform better than conventional (i.e. one-compartment) anaerobic bioreactors [50,51]. The advantages of compartmentalization are enhanced significantly if granules that settle well are formed [52]. In ecological terms, one level of niche complementation (bioreactor compartments) allows for the development of ecosystem processes in defined sequence, whereas the second level (granulation) ensures the retention of a higher diversity and hence functional redundancy of microorganisms within the reactor [53,54]. We can expect further innovations with compartmentalized bioreactors, which appear to show the most promise in the area of anaerobic treatment of complex wastewaters [55,56]. This will be a challenging problem in ecological engineering, as proper juxtapositioning of functional niches is crucial; promoting differences in community structure in the different compartments of a bioreactor without ensuring functional complementation will not lead to improved system performance [57]. In general, ecological engineering of complex processes has resulted in more system heterogeneity, as fostering the right populations requires the proper niches to be provided for each functional group. Enhancing this heterogeneity through granulation or biofilm development can be effective, as discussed above, but other methods can also be explored. For example, membrane bioreactors may have a high potential for maintaining process stability [58–60]. Another approach that may be considered Current Opinion in Biotechnology 2003, 14:270–276
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consists of introducing heterogeneity at a more temporal scale, such as providing substrate pulses to encourage the growth of desired microorganisms. For example, it may be possible to operate anaerobic bioreactors using fluctuating propionate levels in order to encourage the growth of propionate-degrading syntrophic bacteria so that propionate degradation, and thus functional stability, is enhanced during shock loads. McMahon and colleagues [47] (KD McMahon et al., unpublished data) demonstrated indirectly that this approach may have merit by showing that anaerobic digesters with a history of poor performance (characterized by relatively high propionate levels) tolerated severe overload conditions better than digesters that had previously performed very well (characterized by low propionate levels). The development of communities that are more resilient in the long term due to pulse disturbances has been demonstrated in other ecosystems, and the stability developed therein is the result of heterogeneity operating in both temporal and spatial scales [61].
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Conclusions Microbial ecologists are in a unique position to integrate the theories and concepts of community dynamics to ecosystem functions. Arguably, the most manageable systems to perform this task are bioreactors and other engineered environments. Preliminary findings suggest that complex bioreactor designs in many ways mirror the interactions and processes of large-scale ecosystems. It has been demonstrated that stability is better correlated not to population diversity per se, but to functional redundancy. Processes and interactions that promote functional stability usually result from greater functional redundancy and functional niche complementation. Biofilms and granules incorporate the characteristics of functional stability within highly compact structures. Although functional stability is highly dependent on the role of functionally important populations, it is also crucial to be able to characterize so-called minor species (i.e. their functional groupings and interactions) in order to better understand stability over long time periods and after a wide range of perturbations. An improved understanding of functional redundancy and the interactions between functional compartments of a bioreactor should lead to more rational ecological engineering approaches.
Acknowledgements Funding for AB was provided by the Illinois Department of Natural Resources (Contract No. HWR01168) and by the WaterCAMPWS – US National Science Foundation (Grant No. 0120978).
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Diversity and dynamics of microbial communities in engineered environments and their implications for process stability Aurelio Briones and Lutgarde Raskiny The availability of molecular biological tools for studying microbial communities in bioreactors and other engineered systems has resulted in remarkable insights linking diversity and dynamics to process stability. As engineered systems are often more manageable than large-scale ecosystems, and because parallels between engineered environments and other ecosystems exist, the former can be used to elucidate some unresolved ecological issues. For example, the process stability of methanogenic bioreactors containing well-defined trophic groups appears to depend on the diversity of the functional groups within each trophic level as well as on how these functional groups complement each other. In addition to using engineered systems to study general ecological questions, microbial ecologists and environmental engineers need to investigate conditions, processes, and interactions in engineered environments in order to make the ecological engineering of bioreactor design and operation more practicable. Addresses Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 North Mathews Avenue, Urbana, IL 61801, USA e-mail: [email protected] y e-mail: [email protected]
or other engineered environments. Although the similarities and contrasts between these two problems may be intuitively obvious, until recently, methodological limitations have hindered the experimental characterization of complex microbial communities in engineered and other environments. As it is difficult to directly observe microorganisms and measure their activities in situ, our knowledge about the ecology of microbial communities depended for a long time on cultivation-based studies. At present, there is little doubt that cultured (or even culturable) microorganisms represent but a tiny fraction of the total microbial community in most environments. Therefore, any knowledge gained from cultivation-based approaches can at best reflect a partial picture, or in some cases can be totally misleading. The situation has changed with the advent of numerous molecular biological tools, which preclude the need for cultivation. It should be noted, however, that cultivationbased methods cannot be totally supplanted in ecological research. For example, the ratio of culturable cells to total cells in a microcosm can provide a useful measure of the successional state in an ecosystem [4]. Furthermore, detailed physiological studies, which are often important in ecological research, almost always require cultivation of relevant microorganisms.
Current Opinion in Biotechnology 2003, 14:270–276 This review comes from a themed section on Environmental biotechnology Edited by Ian M Head and Mark J Bailey 0958-1669/03/$ – see front matter ß 2003 Elsevier Science Ltd. All rights reserved. DOI 10.1016/S0958-1669(03)00065-X
Abbreviations PCR polymerase chain reaction
Introduction The question of how the diversity and dynamics of communities contribute to ecosystem stability is a contentious and evolving issue [1]. Moreover, the applicability of certain classical tenets in ecological theory (e.g. trophic cascades) to microbial communities appears to be doubtful in certain ecosystems [2,3]. Nevertheless, any investigation linking microbial community dynamics to process stability deals with basic ecological issues. How an ecologist grapples with these issues in order to better understand the sustainability of an ecosystem has obvious parallels to maintaining the process stability of bioreactors Current Opinion in Biotechnology 2003, 14:270–276
The most widely employed molecular approaches to study microbial community structure begin with the polymerase chain reaction (PCR). This method’s relative simplicity and extreme sensitivity allow us to easily amplify signature sequences (usually fragments of either 16S rRNA or a unique functional gene) corresponding to target population(s) from almost any environment. PCR products can then be analyzed by DNA fingerprinting methods [5,6], yielding a snapshot of the community structure. Each unique PCR product can also be sequenced (after cloning or separation in fingerprinting electrophoresis gels) to provide information on population identity and thus characterize the community’s structure. Numerous biases inherent to PCR preclude straightforward quantification of populations based on amplification products [7]. Nevertheless, reliable PCR-based quantification can be achieved using specially designed primers and sensitive optical detection [8,9]. At present, however, oligonucleotide probe-based hybridization methods are more widely employed for quantitative purposes [10]. These include membrane hybridization and fluorescence in situ hybridization (FISH), with the latter also offering the advantage of visualizing spatial distributions of microorganisms in a sample. Recent advances in probe hybridization methods www.current-opinion.com
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include the development of molecular beacons [11] and peptide nucleic acid (PNA) probes [12], both of which offer greatly improved signal-to-noise ratios (C Xi, M Balberg, S Boppart, L Raskin, unpublished data). The availability of these and numerous other methods now allows us to better integrate the information gained from (microbial) ecological research with the design and optimization of bioreactors and other engineered systems. In this review, we describe recent advances in ecological and environmental engineering research that deal with relationships between stability, community dynamics and community diversity. We also emphasize parallels between large-scale ecosystems and engineered environments as recognizing these parallels can lead to a better integration of concepts and theories in community and ecosystem ecology as well as improvements in bioreactor design.
Ecosystem, community, process and functional stability Our understanding of ecosystem stability has changed through the years. From mostly intuitive beginnings, our present understanding owes much to recent advances in theory and research [13,14]. Pimm [15] identified an array of properties (e.g. resistance, resilience and temporal variability), which are commonly used to describe ecosystem stability. These properties are applied to characterize two components of an ecosystem: the biotic component (communities) and the process component, which is usually seen as the flow of matter or energy among the functional compartments of the ecosystem. Characterization of each of these components in an open, complex, and large-scale ecosystem is a daunting task, prompting a division of labor that has resulted in two ecological subdisciplines: community ecology and ecosystem ecology. To this day, the full integration of these branches remains one of ecology’s biggest challenges [14]. Bioreactors and other engineered systems offer a setting that is generally far more manageable, in terms of studying processes, than most large-scale ecosystems. Nevertheless, the aforementioned methodological limitations, coupled with limited exposure to ecological research, have led many environmental engineers to describe stability almost entirely in terms of processes and functions, often failing to take into account the community component. Interactions between microbial ecologists and environmental engineers, combined with the availability of new methods to characterize community structure, offer exciting opportunities to integrate the concepts and theories of community and ecosystem ecology into a unified picture. This should lead to better ways to describe and predict how all types of stability develop, how they are maintained, and how an engineered system can recover from unstable periods. At this stage, however, it is not clear to what extent findings obtained from engineered systems can be generalized across ecosystems. www.current-opinion.com
How community dynamics give rise to functional stability through functional redundancy For most of the past century, equilibrium-based views on ecosystem stability attained the status of dogma in ecology. However, it is becoming clear that equilibrium-based concepts of stability apply mainly to aggregate community or ecosystem properties, whereas individual populations are generally in a state of flux even under stable conditions [16,17,18]. Ecosystem stability coupled with constant population flux is a more likely outcome as the number of populations increases due to a statistical ‘averaging effect’ (i.e. in the absence of strong population interactions, the stability of aggregate properties may result from purely stochastic fluctuations in population abundances) [19]. This partly explains the positive correlation between biodiversity and ecosystem stability. While Doak et al. [19] described this correlation as a ‘statistical inevitability’, there are biological processes (namely, competition and functional complementation) that underlie this averaging effect. We are only now beginning to link community dynamics with processes and functions in engineered systems. However, some evidence tends to indicate that levels of individual populations fluctuate in a functionally stable community. Fernandez et al. [20] monitored the community dynamics of Bacteria and Archaea in a functionally stable, continuously mixed methanogenic reactor for 605 days and found differences in the levels of diversity and dynamics between the bacterial and archaeal domains. The population diversity within the bacterial domain was nearly four times higher than in the archaeal domain, and the bacterial populations displayed a highly variable pattern of temporal variation, despite stable system function and constant environmental conditions. In contrast, archaeal populations displayed less temporal variability and exhibited a more defined pattern of dominance and succession. Similar results were observed in another methanogenic reactor system, a fluidized bed reactor fed with vinasse (wine distillation waste) in which the biomass was immobilized on powder from porous volcanic stone [21]. However, nonequilibrium behavior of populations under functionally stable conditions is not always observed. In a series of full-scale, aerobic reactors treating pharmaceutical wastewater, LaPara and colleagues [22,23] showed a relatively stable community structure during an 87-day period of reasonably constant influent characteristics. Moderate shifts in populations were observed only subsequent to changes in influent properties. A more stable community structure in this case could be explained by the difference in scale between a full-scale wastewater treatment plant and the anaerobic bioreactors described above. An equilibrium model based on island biogeography would predict a more stable community structure in the full-scale plants Current Opinion in Biotechnology 2003, 14:270–276
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[24]. However, it is also tempting to hypothesize that systems selecting for functionally more flexible populations (e.g. facultative bacteria) may compensate for the need for higher population diversity, therefore dampening population fluctuations. By contrast, methanogenic reactors require the presence and activity of at least three defined trophic groups — fermenting bacteria, syntrophic bacteria, and methanogens — of which the latter two certainly cannot be considered functionally flexible. In this case, a higher degree of population diversity among fermenting bacteria (leading to population oscillations) would be expected to maintain stability. The methanogens and syntrophic bacteria in this system parallel keystone or driver species in higher ecological systems [25,26]. As there are fewer representatives of these functional groups, and because they exert stronger influences upon overall system function, the bulk of diversity and functional redundancy ultimately rests on the functionally weaker species — the fermenting bacteria. A large amount of theoretical and experimental work would be required to fully examine this hypothesis. At present, there are no common standards for measuring process stability. In the cases cited above, the stability of the aerobic reactors was monitored mainly through chemical oxygen demand (COD) measurements, whereas in the anaerobic reactors it was also possible to measure metabolic intermediates, such as volatile fatty acids, methane and hydrogen [27]. Therefore, the explanation for the apparent contradictions between aerobic and anaerobic systems may also rest upon methodological difficulties in evaluating functional stability. At this point, however, these problems do not appear to be insurmountable, and it will be interesting to see how future studies will resolve the issue of community dynamics in anaerobic/methanogenic versus aerobic systems. Regardless of the nature of community dynamics in a constant environment, a stable system must possess the ability to maintain process stability in response to disturbance(s). This does not imply that the microbial community be stably maintained. In experiments conducted on replicated, continuously mixed methanogenic reactors that maintained two different microbial communities, designated the high-spirochaete and low-spirochaete reactor sets, the less stable community structure was correlated to more stable function [28]. In this case, the less stable community was one that displayed greater temporal variation of bacterial populations in response to substrate (glucose) shock. This high-spirochaete community responded to glucose perturbation by shifting the relative abundance of fermenting bacteria and then returning to structural characteristics close to those before the perturbation after functional performance had stabilized. By contrast, reactors that were dominated by streptococci prior to glucose perturbation (the low-spirochaete reactor set) showed minimal community changes in response to substrate Current Opinion in Biotechnology 2003, 14:270–276
shock. These results were correlated to the substrate processing structure that developed in each reactor type prior to perturbation: substrate processing through parallel pathways was associated with a functionally more stable (resilient) system, in contrast to serial processing of substrate [27]. In other words, a system with more pathways toward methane production was functionally more stable than one that relied on a series of interdependent metabolic events. An important outcome of these and other experiments is the realization that population diversity alone does not drive ecosystem stability. The positive relationship between the presence of multiple pathways towards a product (parallel processing of substrate) and functional stability parallels theoretical concepts in higher ecological organization [29]. Ecosystem stability is the outcome not of population diversity per se, but of functional redundancy, which is ensured by the presence of a reservoir of species able to perform the same ecological function. Recognizing the diversity and the links within each key functional group of a system can lead to better ways to model diversity and function [30], as well as helping to improve process stability [31]. It is now clear that, even using molecular techniques, identification of every species in most environments is a daunting task [32]. Nevertheless, much progress has been made in linking identity to function among key microbial players in a variety of engineered systems [33,34]. Armed with this knowledge, we can begin to explain the discrepancy in performance between similarly constructed bioreactors [35]. However, only by gaining a better understanding of functional diversity and interactions between functional groups and abiotic components can we hope to achieve the level of understanding required to predict system performance under a given set of conditions.
Recognizing conditions, processes and interactions that promote stability – a prerequisite for ecological engineering Ecological engineering is a term used to describe the process of designing and operating bioreactors and other engineered systems to foster the development of specific microbial communities that can accommodate the desired functional processes [36]. As pointed out by Grady and Filipe [37], environmental engineers have been practicing ecological engineering, either consciously or unconsciously, ever since the first bioreactor was built. It requires an understanding of ecological principles, the physiological requirements of the desired population(s), and the spatial juxtapositioning of various populations. In large-scale ecosystems, functionally minor populations typically predominate over keystone or driver populations [25,29]. Nevertheless, interactions arising from www.current-opinion.com
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both strong and minor populations are important for maintaining ecosystem stability [1,38,39]. Thus, both groups of populations need to be monitored when practicing ecological engineering to design and operate bioreactors. For example, the various trophic levels in a methanogenic bioreactor are represented by several functional groups differing in their degree of diversity [20, 27,28]. The less diverse Archaea, represented mostly by the methanogens, are the drivers [40] in this system, while the populations in the more diverse bacterial domain, representing most of the fermenting bacteria, play individually minor roles compared with the methanogens. Therefore, it is not surprising that many studies have focused on identifying and quantifying methanogens and closely associated syntrophic bacteria, as reactor performance is expected to be more highly dependent on the dynamics of these functional groups. However, in the long run, even minor players are expected to contribute strong effects depending on the heterogeneity or perturbations on the system [38] and the degree of species richness [39]. Thus, for anaerobic bioreactors that are subjected to a wide range of perturbations over time, it becomes crucial to be able to characterize the so-called minor populations and their interactions. Ecological engineering of bioreactors can most easily be illustrated by considering a study in which a bioreactor was designed to accomplish a single function: the removal of soluble mercury from wastewater [41]. Reactor performance was better in the presence of multiple species of mercury-resistant bacteria than with monocultures with the ability to detoxify mercury [42]. In a simple system designed for maintaining a single functional group of bacteria, each member is important to system function. Increasing the number of members in the system (i.e. increasing the functional redundancy) ensures a reservoir of functional responses to disturbances through time, thus ensuring a functionally more stable system performance. In a simple bioreactor, where each population is functionally important, there is a straightforward relationship between functional redundancy and stability. Excellent examples of microbial communities that typically incorporate many of the characteristics of functional stability are found in biofilms and granules. These structures, which can be defined as aggregates of microorganisms and organic and inorganic matter held together by extracellular polysaccharides, are often formed in engineered systems. In the case of biofilms, the microorganisms require the presence of a surface to adhere to and grow on. This definition, however, fails to reflect the degree of structural and functional elegance that can be achieved in these microbial aggregates [43]. Within a single reactor system, biofilm communities have been shown to be highly distinct from the suspended biomass [44,45], which in some cases is also reflected by higher population diversity in the sessile (biofilm) communities [46]. It should be www.current-opinion.com
noted that studies that have compared the functional diversities in microbial aggregates with those in corresponding planktonic communities are scarce. Due to the spatial localization of populations and functions in biofilms and granules, local effects can have significant impact on bioreactor function. For example, McMahon et al. [47] showed that process stability in a methanogenic reactor could be disrupted by a vigorous and continuous mixing regime, which presumably disrupted the spatial juxtaposition of syntrophic bacteria and their methanogenic partners. The higher process stability of minimally mixed reactors extended to times of substrate perturbation, confirming the resistance of the system to shock loadings [48]. These experiments demonstrate the importance of recognizing the complementary functional niches in a bioreactor system. For a complex task such as anaerobic wastewater treatment, functional niche complementarity can also be achieved by spatial or temporal separation of functional groups, as methane production relies on the interdependence between trophic levels. Nevertheless, this does not always function optimally in a homogeneous environment (like that found in a single, continuously mixed reactor). For example, a higher degree of heterogeneity is achieved in an anaerobic baffled reactor, a bioreactor with multiple, interconnected compartments [49] that has been shown to perform better than conventional (i.e. one-compartment) anaerobic bioreactors [50,51]. The advantages of compartmentalization are enhanced significantly if granules that settle well are formed [52]. In ecological terms, one level of niche complementation (bioreactor compartments) allows for the development of ecosystem processes in defined sequence, whereas the second level (granulation) ensures the retention of a higher diversity and hence functional redundancy of microorganisms within the reactor [53,54]. We can expect further innovations with compartmentalized bioreactors, which appear to show the most promise in the area of anaerobic treatment of complex wastewaters [55,56]. This will be a challenging problem in ecological engineering, as proper juxtapositioning of functional niches is crucial; promoting differences in community structure in the different compartments of a bioreactor without ensuring functional complementation will not lead to improved system performance [57]. In general, ecological engineering of complex processes has resulted in more system heterogeneity, as fostering the right populations requires the proper niches to be provided for each functional group. Enhancing this heterogeneity through granulation or biofilm development can be effective, as discussed above, but other methods can also be explored. For example, membrane bioreactors may have a high potential for maintaining process stability [58–60]. Another approach that may be considered Current Opinion in Biotechnology 2003, 14:270–276
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consists of introducing heterogeneity at a more temporal scale, such as providing substrate pulses to encourage the growth of desired microorganisms. For example, it may be possible to operate anaerobic bioreactors using fluctuating propionate levels in order to encourage the growth of propionate-degrading syntrophic bacteria so that propionate degradation, and thus functional stability, is enhanced during shock loads. McMahon and colleagues [47] (KD McMahon et al., unpublished data) demonstrated indirectly that this approach may have merit by showing that anaerobic digesters with a history of poor performance (characterized by relatively high propionate levels) tolerated severe overload conditions better than digesters that had previously performed very well (characterized by low propionate levels). The development of communities that are more resilient in the long term due to pulse disturbances has been demonstrated in other ecosystems, and the stability developed therein is the result of heterogeneity operating in both temporal and spatial scales [61].
This reference is a good starting point for the reader to become acquainted with current issues related to biodiversity and ecological stability. 2.
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Conclusions Microbial ecologists are in a unique position to integrate the theories and concepts of community dynamics to ecosystem functions. Arguably, the most manageable systems to perform this task are bioreactors and other engineered environments. Preliminary findings suggest that complex bioreactor designs in many ways mirror the interactions and processes of large-scale ecosystems. It has been demonstrated that stability is better correlated not to population diversity per se, but to functional redundancy. Processes and interactions that promote functional stability usually result from greater functional redundancy and functional niche complementation. Biofilms and granules incorporate the characteristics of functional stability within highly compact structures. Although functional stability is highly dependent on the role of functionally important populations, it is also crucial to be able to characterize so-called minor species (i.e. their functional groupings and interactions) in order to better understand stability over long time periods and after a wide range of perturbations. An improved understanding of functional redundancy and the interactions between functional compartments of a bioreactor should lead to more rational ecological engineering approaches.
Acknowledgements Funding for AB was provided by the Illinois Department of Natural Resources (Contract No. HWR01168) and by the WaterCAMPWS – US National Science Foundation (Grant No. 0120978).
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