Integrating ecology into biotechnology

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New high-throughput culture-independent molecular tools are allowing the scientific community to characterize and understand the microbial communities underpinning environmental biotechnology processes in unprecedented ways. By creatively leveraging these new data sources, microbial ecology has the potential to transition from a purely descriptive to a predictive framework, in which ecological principles are integrated and exploited to engineer systems that are biologically optimized for the desired goal. But to achieve this goal, ecology, engineering and microbiology curricula need to be changed from the very root to better promote interdisciplinarity.

Introduction

Ecology is the study of the distribution and abundance of organisms and their biotic and abiotic interactions in an environmental setting. Biotechnological processes often rely on microbial organisms contained within an engineered environment designed to allow some level of operator control. All too often, however, such processes overlook or ignore the microbial communities that underpin the process. This has not necessarily been due to a lack of interest in the underlying communities, but primarily because of a lack of tools with which to dissect and monitor microbial organisms in a cost-effective and timely fashion. To date, efforts to describe microbial communities of biotechnological relevance have been largely descriptive. However, a plethora of new high-throughput culture-independent molecular tools [1•] hold the promise of turning microbial ecology into a quantitative predictive science. Once the discipline becomes predictive, it can then be used to improve biotechnological processes in a directed manner, in much the same way that advances in aerodynamics, combustion and electronics translated into more efficient and cheaper automobiles. But first, environmental biotechnologists must survive the indigestion produced by a data overload from the new tools, and learn how to best use these data to create a quantitative predictive framework. In this review, we will mainly use wastewater treatment processes to illustrate the use of ecological principles in understanding biotechnological processes.

Section snippets

From tools to principles

Many authors before us have remarked on the revolutionary impact that molecular tools have had on the disciplines of microbial ecology and environmental biotechnology over the past two decades [2, 3•, 4, 5]. As we continue to move beyond the cataloging of 16S rRNA genes and begin to catalog whole (meta)genomes, (meta)transcriptomes, (meta)proteomes, and ultimately (meta)metabolomes [1•, 6, 7], the need to work within a framework designed to integrate data at a previously unimaginable scale is

A disturbing mind-set

Perhaps the most widely appreciated concept borrowed from ecologists by environmental biotechnologists is the proposed relationship between biodiversity and system stability [3•, 5, 11]. The latter can be characterized by measures of resistance, resilience, and scale of temporal variability. Although ecologists still debate whether positive correlations between diversity and stability are universal (and therefore useful for predictive purposes) [12, 13, 14, 15], much theoretical and

Community assembly: from pattern to process

If our design objectives become directed toward maintaining maximal diversity and functional redundancy, how does this influence our choice of process configuration and mode of operation? We could turn to neutral models such as the Unified Theory of Biodiversity and Biogeography [27] when considering ways to predict and control community assembly. This framework, based on the Island Theory of Biogeography [28], was developed mainly to explain patterns observed in communities of macroscale

An additional layer of complexity: trophic food web interactions

Microbial communities and populations in engineered systems are also subject to ‘top-down’ control exerted by predators such as viruses (bacteriophage) and protozoan bacteriovores (e.g. ciliates and flagellates). However, few studies have addressed either type of predator–prey dynamic. It is noteworthy that models designed to predict process performance, such as the series of Activated Sludge Models [53], do not include food-web interactions of any kind, despite the wealth of theoretical

Describe, explain, predict, control

Ecologists have long used models to try to quantitatively understand ecosystems. The goal of modeling is to integrate all available data to distill the main processes that drive the system. A good model should then be capable of predicting the behavior of the system to the required resolution. In fact, it is fair to say that if you cannot predict the behavior of the system you do not really understand it.

The challenge before us is to effectively integrate community-wide high-resolution

Bridging the gap between the disciplines

We have learned much about the links between community diversity, composition, and process performance in environmental biotechnology systems by applying the powerful molecular tools developed by microbiologists. However, there is still a great need to develop new curricula and concerted research efforts to better integrate the knowledge and tools of molecular microbiology and engineering [2]. We propose, as have others [3•, 5, 75], that students and practitioners of environmental biotechnology

Conclusions

These are exciting times to be working with biological systems. Microbial ecology as a discipline is on the verge of maturing beyond the descriptive phase and we can now begin to explain observed patterns based on processes that generate them. As is the case with macroscale ecology, our ultimate goal is to be able to predict the behavior of microbial populations and communities. This goal is especially relevant for applications to environmental biotechnology systems. Engineers hope to take the

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

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