LO10: Application of system biology in bioremediation


Environmental pollutants have become a major global concern, given their undesirable recalcitrant and xenobiotic compounds. A variety of polycyclic aromatic hydrocarbons (PAHs), xenobiotics, chlorinated and nitro-aromatic compounds were depicted to be highly toxic, mutagenic and carcinogenic for living organisms.

Some of the sources of these contaminants are; chemical (dying, agriculture, pharmaceuticals, etc) petrochemical (oil rafineries, fuel spills), metal (iron and steel industry, shipbuilding, etc.) energy (power plants), mining industries and water supply and sewage works. These contaminants have impacts on nature. While various physico-chemical processes have been developed for treating these pollutants; these approaches are often prohibitively expensive, non-specific, or have the potential for introducing secondary contamination. However, microbial population may also degrade the pollutant and considered as one of the environment friendly and cost-effective method for restorationof ecological niches contaminated with chemical pollutants. As a result, there has been an increased interest in eco-friendly bio-based treatments commonly known as bioremediation. Though bioremediation has been used to varying degrees for more than 60 years, for example petroleum land farming, it historically has been implemented as a very ‘black box’ engineering solution whereamendments are added and the pollutants are degraded. This approach is often successful but all to often the results are less than desirable, that is, no degradation of the contaminant or even production of more toxic daughter products. The key to successful bioremediation is to harness the naturally occurring catabolic capability of microbes to catalyze transformations of environmental pollutants.


Bioremediation is the exploitation of biological activities for mitigation (and wherever possible complete elimination) of the noxious effects caused by environmental pollutants in given sites. If the process occurs in the same place afflicted by pollution then an in situ bioremediation scenario occurs. In contrast, deliberate relocation of the contaminated material (soil and water) into a different place to intensify biocatalysis originates an ex situ case. In bioremediation, microorganisms with biological activity, including algae, bacteria, fungi, and yeast, can be used in their naturally occurring forms.

Figure 1. Types of microorganisms used in bioremediation processes (Coelho et
al. 2015).

Figure 1. Types of microorganisms used in bioremediation processes (Coelho et al. 2015).

Figure 1 shows the main types of microorganisms used in these processes, based on a search for papers reporting microorganisms and bioremediation studies the microorganisms that have been most commonly used are bacteria and fungi, although yeast and algae are also frequently applied

Types of organisms used in bioremediation

Typically, bioremediation is based on the cometabolism action of one organism or a consortium of microorganisms. In this process, the transformation of contaminants presents a little efficiency or no benefit to the cell, and therefore this process is described as nonbeneficial biotransformation. Several studies have shown that many organisms (prokaryotes and eukaryotes) have a natural capacity to biosorb toxic heavy metal ions. Examples of microorganisms studied and strategically used in bioremediation treatments for heavy metals include the following: (1) bacteria: Arthrobacter spp., Pseudomonas veronii (Vullo et al. 2008), Burkholderia spp., Kocuria flava, Bacillus cereus and Sporosarcina; (2) fungi: Penicillium canescens, Aspergillus versicolor, and Aspergillus fumigatus; (3) algae: Cladophora fascicularis, Spirogyra spp. and Cladophora spp. and Spirogyra spp. and Spirullina spp and (4) yeast: Saccharomyces cerevisiae and Candida utilis. Prokaryotes (bacteria and archaeans) are distinguished from eukaryotes (protists, plants, fungi, and animals). The cellular structure of eukaryotes is characterized by the presence of a nucleus and other membrane-enclosed organelles. Also, the ribosomes in prokaryotes are smaller (70S) than in eukaryotes (80S). The way in which microorganisms interact with heavy metal ions is partially dependent on whether they are eukaryotes or prokaryotes, wherein eukaryotes are more sensitive to metal toxicity than prokaryotes. The possible modes of interaction are (a) active extrusion of metal, (b) intracellular chelation (in eukaryotes) by various metal-binding peptides, and (c) transformation into other chemical species with reduced toxicity. For bioremediation to be effective, microorganisms must enzymatically attack the pollutants and convert them to harmless products. Bacteria and higher organisms have developed mechanisms associated with resistance to toxic metals and rendering them innocuous. Several microbes, including aerobes, anaerobes, and fungi, are involved in the enzymatic degradation process. Most of bioremediation systems are run under aerobic conditions, but anaerobic conditions make it possible microbial organisms to degrade otherwise recalcitrant molecules. Because several different types of pollutants can be present at a contaminated site, various types of microorganisms are required for effective remediation. Some types of microorganism are able to degrade petroleum hydrocarbons and use them as a source of carbon and energy. However, the choice of the organisms employed is variable, depending on the chemical nature of the polluting agents, and needs to be selected carefully as they only survive in the presence of a limited range of chemical contaminants. The efficiency of the degradation process is related to the potential of the particular microorganism to introduce molecular oxygen into the hydrocarbon and to generate the intermediates that subsequently enter the general energy yielding metabolic pathway of the cell. Some bacteria search the contaminant and move toward it because they flexibly exhibit the potential as a chemotactic response. Numerous microorganisms can utilize oil as a source of food, and many of them produce potent surface-active compounds that can emulsify oil in water and facilitate its removal. Bacteria that can degrade petroleum products include species of Pseudomonas, Aeromonas, Moraxella, Beijerinckia, Flavobacteria, Chrobacteria, Nocardia, Corynebacteria, Modococci, Streptomyces, Bacilli, Arthrobacter, Aeromonas, and cyanobacteria and some yeasts. For example, Pseudomonas putida MHF 7109 can be isolated from cow dung microbial consortia for the biodegradation of selected petroleum hydrocarbon compounds, such as benzene, toluene, and o-xylene (BTX).

Bioremediation strategies

In many cases the clean-up contaminated sites have been carried out using physical and chemical methods such as immobilization, removal (dig and dump), thermal, and solvent treatments. However, advances in biotechnology have seen the development of biological methods of contaminant degradation and removal, a process known as bioremediation. Potentially bioremediation is cheaper than the chemical and physical options, can deal with lower concentrations of contaminants more effectively, although the process may take longer.

The strategies for bioremediation in both soil and water can be as follows:

  • Use the indigenous microbial population
  • Encourage the indigenous population
  • Bioaugmentation; the addition of adapted or designed inoculants
  • Addition of genetically modified micro-organisms
  • Phytoremediation

If the process occurs in the same place afflicted by pollution then an in situ bioremediation scenario occurs. In contrast, deliberate relocation of the contaminated material (soil and water) into a different place to intensify biocatalysis originates an ex situ case.

In situ and ex situ methods

Bioremediation technologies can be broadly classified as ex situ and in situ. Ex situ technologies are those treatments which involve the physical removal of the contaminated material for treatment process.

If the process occurs in the same place afflicted by pollution, then an in situ bioremediation scenario occurs. These techniques are generally the most desirable options due to lower cost and less disturbance since they provide the treatment in place avoiding excavation and transport of contaminants. In situ treatment is limited by the depth of the soil that can be effectively treated. In many soils, effective oxygen diffusion for desirable rates of bioremediation extend to a range of only a few centimeters to about 30 cm into the soil, although depths of 60 cm and greater have been effectively treated in some cases. The most important land treatments are:

Bioventing is the most common in situ treatment and involves supplying air and nutrients through wells to contaminated soil to stimulate the indigenous bacteria. Bioventing employs low air flow rates and provides only the amount of oxygen necessary for the biodegradation while minimizing volatilization and release of contaminants to the atmosphere. It works for simple hydrocarbons and can be used where the contamination is deep under the surface.

In situ biodegradation involves supplying oxygen and nutrients by circulating aqueous solutions through contaminated soils to stimulate naturally occurring bacteria to degrade organic contaminants. It can be used for soil and groundwater. Generally, this technique includes conditions such as the infiltration of water-containing nutrients and oxygen or other electron acceptors for groundwater treatment.

Biosparging involves the injection of air under pressure below the water table to increase groundwater oxygen concentrations and enhance the rate of biological degradation of contaminants by naturally occurring bacteria. Biosparging increases the mixing in the saturated zone and there- by increases the contact between soil and groundwater. The ease and low cost of installing small-diameter air injection points allows considerable flexibility in the design and construction of the system.

Bioaugmentation. Bioremediation frequently involves the addition of microorganisms indigenous or exogenous to the contaminated sites. Two factors limit the use of added microbial cultures in a land treatment unit: 1) nonindigenous cultures rarely compete well enough with an indigenous population to develop and sustain useful population levels and 2) most soils with long-term exposure to biodegradable waste have indigenous microorganisms that are effective degrades if the land treatment unit is well managed.

Ex situ bioremediation deliberate relocation of the contaminated material (soil and water) into a different place to intensify biocatalysis originates an ex situ case. These techniques involve the excavation or removal of contaminated soil from ground.

Landfarming is a simple technique in which contaminated soil is excavated and spread over a pre- pared bed and periodically tilled until pollutants are degraded. The goal is to stimulate indigenous biodegradative microorganisms and facilitate their aerobic degradation of contaminants. In general, the practice is limited to the treatment of superficial 10–35 cm of soil. Since landfarming has the potential to reduce monitoring and maintenance costs, as well as clean-up liabilities, it has received much attention as a disposal alternative.

Composting is a technique that involves combining contaminated soil with nonhazardous organic amendants such as manure or agricultural wastes. The presence of these organic materials supports the development of a rich microbial population and elevated temperature characteristic of composting.

Biopiles are a hybrid of landfarming and composting. Essentially, engineered cells are con- structed as aerated composted piles. Typically used for treatment of surface contamination with petroleum hydrocarbons they are a refined version of landfarming that tend to control physical losses of the contaminants by leaching and volatilization. Biopiles provide a favorable environment for indigenous aerobic and anaerobic microorganisms.

Bioreactors. Slurry reactors or aqueous reactors are used for ex situ treatment of contaminated soil and water pumped up from a contaminated plume. Bioremediation in reactors involves the processing of contaminated solid material (soil, sediment, sludge) or water through an engineered containment system. A slurry bioreactor may be defined as a containment vessel and apparatus used to create a three-phase (solid, liquid, and gas) mixing condition to increase the bioremediation rate of soil-bound and water-soluble pollutants as a water slurry of the contaminated soil and biomass (usually indigenous microorganisms) capable of degrading target contaminants. In general, the rate and extent of biodegradation are greater in a bioreactor system than in situ or in solid-phase systems because the contained environment is more manageable and hence more controllable and predictable. Despite the advantages of reactor systems, there are some disadvantages. The contaminated soil requires pretreatment (e.g., excavation) or alternatively the contaminant can be stripped from the soil via soil washing or physical extraction (e.g., vacuum extraction) before being placed in a bioreactor. Table 1 summarizes the bioremediation strategies.

Table 1. Summary of bioremediation strategies

Technology Examples Benefits Limitations Factors to consider
In situ In situ bioremediation Biosparging Bioventing Bioaugmentation Most cost efficient Noninvasive Relatively passive Natural attenuation processes Environmental constraints Extended treatment time Monitoring difficulties Biodegradative abilities of indigenous microorganisms Presence of metals and other inorganics Environmental parameters Biodegradability of pollutants Chemical solubility Geological factors Distribution of pollutants
Treats soil and water
Ex situ Landfarming Composting Biopiles Cost efficient Space requirements Extended treatment time Need to control abiotic loss See above
Low cost Mass transfer problem Bioavailability limitation
Can be done on site
Bioreactors Slurry reactors Aqueous reactors Rapid degradation kinetic Optimized environmental parameters Enhances mass transfer Effective use of inoculants and surfactants Soil requires excavation Relatively high cost capital Relatively high operating cost See above Bioaugmentation Toxicity of amendments Toxic concentrations of contaminants

Advantages and disadvantages of bioremediation


  • Bioremediation is a natural process and is therefore perceived by the public as an acceptable waste treatment process for contaminated material such as soil. Microbes able to degrade the contaminant increase in numbers when the contaminant is present; when the contaminant is degraded, the biodegradative population declines. The residues for the treatment are usually harmless products and include carbon dioxide, water, and cell biomass.
  • Theoretically, bioremediation is useful for the complete destruction of a wide variety of contaminants. Many compounds that are legally considered to be hazardous can be transformed to harmless products. This eliminates the chance of future liability associated with treatment and disposal of contaminated material.
  • Instead of transferring contaminants from one environmental medium to another, for example, from land to water or air, the complete destruction of target pollutants is possible.
  • Bioremediation can often be carried out on site, often without causing a major disruption of normal activities. This also eliminates the need to transport quantities of waste off site and the potential threats to human health and the environment that can arise during transportation.
  • Bioremediation can prove less expensive than other technologies that are used for clean-up of hazardous waste.


  • Bioremediation is limited to those compounds that are biodegradable. Not all compounds are susceptible to rapid and complete degradation.
  • There are some concerns that the products of biodegradation may be more persistent or toxic than the parent compound.
  • Biological processes are often highly specific. Important site factors required for success include the presence of metabolically capable microbial populations, suitable environmental growth conditions, and appropriate levels of nutrients and contaminants.
  • It is difficult to extrapolate from bench and pilot-scale studies to full-scale field operations.
  • Research is needed to develop and engineer bioremediation technologies that are appropriate for sites with complex mixtures of contaminants that are not evenly dispersed in the environment.

Contaminants may be present as solids, liquids, and gases.

  • Bioremediation often takes longer than other treatment options, such as excavation and removal of soil or incineration.
  • There is no accepted definition of “clean”, evaluating performance of bioremediation is difficult, and there are no acceptable endpoints for bioremediation treatments (Vidali, 2001).

Environmental factors for bioremediation


Although the microorganisms are present in contaminated soil, they cannot necessarily be there in the numbers required for bioremediation of the site. Their growth and activity must be stimulated. Biostimulation usually involves the addition of nutrients and oxygen to help indigenous microorganisms. These nutrients are the basic building blocks of life and allow microbes to create the necessary enzymes to break down the contaminants. All of them will need nitrogen, phosphorous, and carbon. Carbon is the most basic element of living forms and is needed in greater quantities than other elements. In addition to hydrogen, oxygen, and nitrogen it constitutes about 95% of the weight of cells.

Phosphorous and sulfur contribute with 70% of the remainders. The nutritional requirement of carbon to nitrogen ratio is 10:1, and carbon to phosphorous is 30:1.

Environmental requirements

Microbial growth and activity are readily affected by pH, temperature, and moisture. Although microorganisms have been also isolated in extreme conditions, most of them grow optimally over a narrow range, so that it is important to achieve optimal conditions. If the soil has too much acid it is possible to rinse the pH by adding lime. Temperature affects biochemical reactions rates, and the rates of many of them double for each 10 °C rise in temperature. Above a certain temperature, however, the cells die. Plastic covering can be used to enhance solar warming in late spring, summer, and autumn. Available water is essential for all the living organisms, and irrigation is needed to achieve the optimal moisture level. The amount of available oxygen will determine whether the system is aerobic or anaerobic. Hydrocarbons are readily degraded under aerobic conditions, whereas chlorurate compounds are degraded only in anaerobic ones. To increase the oxygen amount in the soil it is possible to till or sparge air. In some cases, hydrogen peroxide or magnesium peroxide can be introduced in the environment. Soil structure controls the effective delivery of air, water, and nutrients. To improve soil structure, materials such as gypsum or organic matter can be applied. Low soil permeability can impede movement of water, nutrients, and oxygen; hence, soils with low permeability may not be appropriate for in situ clean-up techniques.

Influence of environmental factors on biodegradation

Earlier studies of bioremediation trials were not performed under natural environmental conditions. Therefore, the impact of environmental factors on the bioremediation process was never expected. However, after the investigation of in situ bioremediation approaches now it is feasible to understand the bioremediation process is influenced significantly by environmental factors such as the physiological and chemical ambience of the contaminated environment, bioavailability of nutrients, concentration and properties of co-contaminants, level of contamination, community organization of the indigenous microbial communities. Various abiotic and biotic factors play important role in bioremediation. Their dynamic interactions occur in concrete abiotic conditions which are defined by physico-chemical conditions like O2 supply, electron transport, water, temperature, pH, salt concentration, many of which. The above environmental factors determine the dynamic of endogenous microbial community structures along with the availability of given chemical and energy source.

The factors at play in bioremediation scenarios include more elements than just the biological catalysts and the contaminants discussed above. Their dynamic interactions occur in concrete abiotic settings which are defined by a whole of physico-chemical conditions: O2 tension, electron acceptors, water, temperature, granulation, and others, many of which change over time and the course of the catalysis. Such abiotic conditions determine the species composition of the endogenous microbial communities as much as (or more than) the availability of given chemical species as C and energy source. Bioremediation is a case of multiscale complexity which is not amenable to the typically reductionist approaches (e.g. one compound, one strain, and one pathway) that have dominated many studies on biodegradation. How to overcome this impasse?

Since microbes are the drivers of bioremediation, shifts in the composition and activity of a microbial community may impact the fate of a contaminant in the environment Recent studies have employed next-generation sequencing approaches to better understand the microbial communities involved in various bioremediation interventions. These approaches have greatly expanded our understanding of the microbial processes involved in bioremediation as well as the impact of various response strategies for contaminant cleanup. The use of molecular biology and metagenomics has also greatly expanded our understanding of the biological systems found in these contaminated environments and in many cases have greatly enhanced our understanding of the microbial world. Here, we seek to provide a key background on metagenomic approaches and summarize how these tools have been employed to understand contaminated environments in an effort to inform the best practices for environmental cleanup.

Bioremediation requires the integration of huge amounts of data from various sources: chemical structure and reactivity of organic compounds; sequence, structure and function of proteins (enzymes); comparative genomics; environmental microbiology; and so on.

Systems biology

The process of bioremediation employs a microbial community to clean up an environmental contaminant. The rates of contaminant detoxification are dependent on a number of factors including the composition of the native microbial community, the environmental conditions, and the nature of the contaminant. Therefore, optimization of bioremediation requires combining complex variables together to understand and predict the fate of environmental contaminants. stems biology—the study of the systematic properties and dynamic interactions in a biological system has been employed to understand complex biological systems and how they will respond to various perturbations. A systems biology approach to understanding environmental systems and bioremediation can be employed to investigate complex environmental microbial communities and the environmental constraints on contaminant degradation.

There is need to in silico study for predicting the possible degradation pathways by using various computational tools. There are large number of databases and computer programs available to perform the computational analysis for assisting the development and implementation of microbial bioremediation. The huge data from biology mainly in the form of DNA, RNA and protein sequences is putting heavy demand on computers and computational scientists. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem levels. A systems biology approach is being adopted to unravel key processes to understand, optimize, predict and evaluate microbial function and survival strategies in the ecosystem of interest. To use a systems biology approach to bioremediation projects they must involve the characterization of microbial community composition, cellular and molecular activity and are complicated by the presence of toxic chemicals that alters the normal behavior of the microbial community.

Some important components of systems biology are the use of computational approaches to develop a predictive understanding of the systems response to a perturbation and understanding contaminant remediation as it combines many levels of a system to predict the fate of environmental contaminants.

It is strongly believed that there are three dimensions for the effectiveness of vital bioremediation process; that is, chemical landscape (nutrients-to-be, electron donors/acceptors and stressors) abiotic landscape, and catabolic landscape of which only the catabolic landscape is genuinely biological. The chemical landscape has a dynamic interplay with the biological interventions on the abiotic background of the site at stake. This includes humidity, conductivity, temperature, matrix conditions, redox status, etc.

Figure 2. Systems biology connections to bioremediation (Koehmel et al.

Figure 2. Systems biology connections to bioremediation (Koehmel et al. 2016)

To gain an understanding of complex in situ bioremediation processes, monitoring techniques that inventory and monitor terminal electron acceptors and electron donors, enzyme probes that measure functional activity in the environment, functional genomic microarrays, phylogenetic microarrays, metabolomics, proteomics, and quantitative PCR can provide unprecedented insights into the key microbial reactions employed (Figure 3). In general terms, an ecosystem consists of communities, populations, cells, protein, RNA, and DNA. We can analyze DNA, RNA, and protein at the cellular levels to understand the impacts on the cells, and analyze community and populations to understand effect of bioremediation on structure/function relationships (Figure 3).

Figure 3. Systems biology from molecules to ecosystems

Figure 3. Systems biology from molecules to ecosystems

A system-level understanding of a biological system can be derived from insight into four key properties:

1) System structures. These include the network of gene interactions and biochemical pathways, as well as the mechanisms by which such interactions modulate the physical properties of intracellular and multicellular structures.

2) System dynamics. How a system behaves over time under various conditions can be understood through metabolic analysis, sensitivity analysis, dynamic analysis methods such as phase portrait and bifurcation analysis, and by identifying essential mechanisms underlying specific behaviors. Bifurcation analysis traces time-varying change(s) in the state of the system in a multidimensional space where each dimension represents a particular concentration of the biochemical factor involved.

3) The control method. Mechanisms that systematically control the state of the cell can be modulated to minimize malfunctions and provide potential therapeutic targets for treatment of disease.

4) The design method. Strategies to modify and construct biological systems having desired properties can be devised based on definite design principles and simulations, instead of blind trial-and-error.

Progress in any of the above areas requires breakthroughs in our understanding of computational sciences, genomics, and measurement technologies, and integration of such discoveries with existing knowledge.

Omics approaches are central to systems biology. Metagenomics—the analysis of the total genomic content of a microbial community—has been widely applied to understanding microbial communities in environmental systems (Figure 4). Other ‘omics techniques, including metatranscriptomics (community RNA analysis) and metaproteomics (community protein analysis), have been more recently applied to environmental microbial communities.

Multiple approaches can be applied to understanding different levels of a microbial community. Each of these techniques investigates a particular biological molecule (DNA, RNA, or Protein) thorough analysis of each of these molecules extracted from an environmental community yields key insights into the taxonomic composition a community, the functional potential of a community, or the genes and proteins currently being expressed Techtman and Hazen, 2016.


Genomic is a powerful computer technology used to understand the structure and function of all genes in an organism based on knowing the organism’s entire DNA sequence. The field includes intensive efforts to determine the entire DNA sequence of organisms and fine-scale genetic mapping efforts. Metagenomics is the study of the genomes in a microbial community and constitutes the first step to studying the microbiome. Metagenomics allows us to investigate the composition of a microbial community. Genomic studies consider the genetic material of a specific organism, while metagenomics (meta meaning beyond) refers to studies of genetic material of entire communities of organisms. This process usually involves nextgeneration sequencing (NGS) after the DNA is extracted from the samples. NGS produces a large volume of data in the form of short reads, from which a microbial community profile or other information can be pieced together just like gathering information from the pieces of a puzzle. Although whole-metagenome sequencing (WMS) provides a partial glimpse into the functional profile of a microbial community, it is better inferred using metatranscriptomics, which involves sequencing the complete (meta)transcriptome of the microbial community. Metagenomics provides access to the functional gene composition of microbial communities and thus gives a much broader description than phylogenetic surveys, which are often based only on the diversity of one gene, for instance the 16S rRNA gene. On its own, metagenomics gives genetic information on potentially novel biocatalysts or enzymes, genomic linkages between function and phylogeny for uncultured organisms, and evolutionary profiles of community function and structure. It can also be complemented with metatranscriptomic or metaproteomic approaches to describe expressed activities. Metagenomics is also a powerful tool for generating novel hypotheses of microbial function; the remarkable discoveries of proteorhodopsin-based photoheterotrophy or ammonia-oxidizing Archaea attest to this fact. The rapid and substantial cost reduction in next-generation sequencing has dramatically accelerated the development of sequence-based metagenomics. In fact, the number of metagenome shotgun sequence datasets has exploded in the past few years. In the future, metagenomics will be used in the same manner as 16S rRNA gene fingerprinting methods to describe microbial community profiles. It will therefore become a standard tool for many laboratories and scientists working in the field of microbial ecology.

Metagenomic approaches often take two forms—targeted metagenomics or shotgun metagenomics (Figure 4). In targeted metagenomics—or microbiomics—the diversity of a single gene is probed to identify the full complement of sequences of a particular gene in an environment. Targeted metagenomics is most often employed to investigate both the phylogenetic diversity and relative abundance of a particular gene in a sample. This approach is regularly used to investigate the diversity of small subunit rRNA sequences (16S/18S rRNA) in a sample. Microbial ecologists routinely use small subunit rRNA sequencing to understand the taxonomic diversity of an environment. It can also be applied as a tool to investigate the impact of environmental contaminants in altering microbial community structure. To perform targeted metagenomics, environmental DNA is extracted, and the gene of interest is PCR amplified using primers designed to amplify the greatest diversity of sequences for that gene of interest. The strength of targeted metagenomics is that it provides a fairly comprehensive catalog of the microbial taxa present in a set of samples and allows for in-depth comparison of shifts in microbial diversity before and after a perturbation.

Figure 4. Metagenomic approaches to understanding microbial communities.

Figure 4. Metagenomic approaches to understanding microbial communities.

In shotgun metagenomics, the total genomic complement of an environmental community is probed through genomic sequencing (Figure 4). In this approach, environmental DNA is extracted and then fragmented to prepare sequencing libraries. These libraries are then sequenced to determine the total genomic content of that sample. Shotgun metagenomics is a powerful technique where the functional potential of a microbial community can be identified.

Shotgun metagenomics is often most limited by the depth of sequencing. Microarray-based techniques have been developed. PhyloChip and GeoChip are the two most commonly used microarray technologies. PhyloChip is a 16S rRNA-based microarray able to probe the diversity of 10,993 sub-families in 147 phyla (Hazen et al. 2010). GeoChip is a functional gene microarray able to probe the diversity of 152,414 genes from 410 gene categories. Microarray techniques are not dependent on the depth of sequencing to provide comprehensive insights into the microbial community. They also have the advantage of providing rigorous annotation for the various taxa/genes present on the chip alleviatingthe limitation of the need for good homologs in the database to achieve accurate classification. Microarray-based approaches are, however, limited in that only the genes on the chip can be detected, thus limiting the potential for discovery of new genes or pathways in a sample. Microarray- based approaches are often a helpful complement to sequencing-based approaches as an additional line of evidence.


Using a proteomics approach, the physiological changes in an organism during bioremediation provide further insight into bioremediation-related genes and their regulation.. Metatranscriptomics and metaproteomics are increasingly being applied to environmental systems (Figure 4). These approaches provide key insights into the actively expressed genes in a microbial community and are thus good indicators for the microbial functions being expressed under the conditions at the time of sampling. In metatranscriptomics, RNA is extracted from an environmental sample. The RNA is converted into cDNA and sequenced in a similar fashion to metagenomics (Figure 4). This approach provides an inventory of the actively expressed genes in a sample. Metaproteomics does not involve nucleic acid sequencing, but rather high-resolution mass spectrometry combined with enzymatic digests of proteins and liquid chromatography. Metaproteomics provides insights into the complement of proteins found in an environmental sample including posttranslational modifications in proteins that may impact their activity.

By focusing on what genes are expressed by the entire microbial community, metatranscriptomics sheds light on the active functional profile of a microbial community. The metatranscriptome provides a snapshot of the gene expression in a given sample at a given moment and under specific conditions by capturing the total mRNA. As for metagenomics, it is now possible to perform whole metatranscriptomics shotgun sequencing. This (meta)genome-wide expression provides the expression and functional profile of a microbiome. When processing reads, a typical metatranscriptomics analysis pipeline will either (1) map reads to a reference genome or (2) perform de novo assembly of the reads into transcript contigs and supercontigs. The first strategy, in a manner similar to the alignment-based methods in WMS, maps reads to reference databases, thus gathering information to infer the relative expression of individual genes. The second strategy infers the same but with assembled sequences. The first strategy is limited by the information in the database of reference genomes. The second strategy is limited by the ability of software programs to assemble contigs and supercontigs correctly from short reads data. tools and techniques. The application of metatranscriptomics to the study of the microbiome is far less common relative to other omics reviewed in this article. Most analysis pipelines described in the literature were built ad hoc. The majority of these methods follow the aforementioned first strategy based on read mapping.

Metabolomics is the comprehensive analysis by which all metabolites of a sample (small molecules released by the organism into the immediate environment) are identified and quantified. The metabolome is considered the most direct indicator of the health of an environment or of the alterations in homeostasis (i.e. dysbiosis). Variation in the production of signature metabolites are related to changes in activity of metabolic routes, and therefore, metabolomics represents an applicable approach to pathway analysis. Additionally, the application of metabolomics for drug discovery and pharmacogenomics represents a promising avenue for personalized medicine. The metabolomic profile associated with the microbiome may show a strong dependence on environmental factors (e.g. diet, exposure to xenobiotics, and environmental stressors), providing valuable information not just about the characteristics of the microbiome but also about the interactions of the microbial community with the host environment. Thus, metabolomics aims to improve our understanding of the role of the microbiome in the transformation of nutrients and pollutants as well as other abiotic factors that may affect the homeostasis of the host environment. The analysis pipeline for spectral metabolomic data involves three steps: (1) preprocessing, (2) statistical analysis, and (3) machine learning techniques for pattern recognition. In the first step, denoising and peak-picking improve the quality of the data to be processed.

Several in silico softwares, pipelines, web resources and algorithms have been developed to interpret or correlate molecular and x-omics data. Nonetheless, bioinformatic resources of bioremediation are still scarce. The University of Minnesota Biocatalysis/Biodegradation Database (UMBBD) has enlisted 200 pathways, 1350 reactions, 1195 compounds, >1000 enzymes, 491 microorganism entries and 259 biotransformation rules encompassing microbial bioremediation (http://umbbd.msi.umn.edu/) (Gao et al. 2011). Metarouter is yet another system for maintaining heterogeneous information related to bioremediation and biodegradation in a framework that allows updating query modifications (Desai et al. 2010). The system can be accessed and administrated through a web interface (Pazos et al. 2005). Other software platforms re: Kyoto Encyclopedia of Genes and Genomes (KEGG) at http://www.genome.ad.jp/kegg/kegg.html. (Moriya et al. 2010); Boehringer Mannhein Biochemical Pathways (BMBP) on the ExPASy server, Switzerland (http://www.expasy.org/cgi-bin/search-biochem-index); International Society for the Study of Xenobiotics (http://www.issx.org); PathDB; Methabolic Pathways Database at NCGR (http://www.ncgr.org/Pathdb/) etc.

Existing computational database, software and tools and their collective integration will help to determine the environmental fate of any compounds more precisely and accurately.

Practical Applications

Radionuclide biotransformation

Groundwater and soil at the Area 3 FRC site in Oak Ridge is not only contaminated with Uranium (up to 200 mM), but poses a unique bioremediation problem due to its low pH (3), high nitrate (200 mM), and high calcium concentrations along with presence of chlorinated organic solvents. Research at this site by various investigators exemplifies successful application of systems biology tools to reveal a deeper understanding of the microbiology at play in the subsurface. Previously, 16S clone library-based community analysis during an in situ biostimulation test at this site have identified Desulfovibrio,Geobacter, Anaeromyxobacter, Desulfosporosinus, Acidovorax, and Geothrix spp. present concomitant with U(VI) reduction (Cardenas et al. 2008). Clone libraries of functional gene markers like dsrAB, nirK, nirS, amoA, and pmoA showed high microbial diversity in functional genes. However, recent metagenomic analysis from well FW106 specifically using a random shotgun sequencing-based strategy revealed a highly enriched community dominated by denitrifying b-Proteobacteria and g-Proteobacteria. Geo-Chip analysis of several groundwater monitoring wells reported widespread diversity of dsrAB genes, which showed that sulfate-reducing bacteria were key players in U(VI) reduction. During the U(VI) reoxidation phase as studied in a sediment column with samples from FRC, observed decrease in biomass, but increase in microbial activity. Using the PhyloChip, the study showed no decline in Geobacter or Geothrix spp. during the reoxidation phase, but members of Actinobacteria, Firmicutes, Acidobacteria, and Desulfovibrionaceae exhibited increased abundance. GeoChip analysis during the reoxidation phase from field samples showed a decline in dsr genes but reoxidation did not appear to effect microbial functional diversity suggesting that the microbial community was able to recover and continue to reduce U(VI) in the post oxidation phase

Metals bioimmobilization

The Hanford 100H area adjacent to the Columbia River in Washington is contaminated with Chromium (Cr) as a result of being a weapons production site. In 2004, Hydrogen Release Compound HRCtm was injected in an effort to mediate sustained bioimmobilization of Cr(VI) in situ by stimulating indigenous microbial flora Hubbard et al. (2008) used time-lapse seismic and radar tomographic geophysical monitoring to determine spatiotemporal distribution of the injected HRC and biogeochemical transformations associated with Cr(VI) bioremediation post injection of HRC. Direct cell counts revealed that while cell numbers reached 108 cells/ml, Cr(VI) levels decreased from 100 ppb to below background levels within a year. PhyloChip analysis showed enrichment of sulfate reducers along with nitrate reducers, iron reducers, and methanogenic populations during this time. Targeted enrichments resulted in isolation of sulfate-reducing Desulfovibrio vulgaris like strain RCH1, nitrate reducing strain Pseudomonas stutzeri strain RCH2, and iron-reducing strain Geobacter metallireducens strain RCH3, all capable of Cr(VI) reduction. mFlowFISH (integrated fluorescence in situ hybridization and flow cytometry) analysis was able to detect and sort Pseudomonads similar to strain RCH2 directly from Hanford 100H field water samples collected in 2009 and 2010.

Hydrocarbon bioremediation

The dependence of petroleum-based energy source has fueled industrial growth and prosperity. However, it also brought dispersal of hydrocarbons into different environments. Fortunately, the organic nature of hydrocarbons enables microbes to metabolize these petroleum compounds as substrates. Notable reviews on a systems biology approach to bioremediation are Atlas and Hazen (2011), Harayama et al. (2004), Zhou et al. (2011), Fredrickson et al. (2008), de Lorenzo (2008) and Chakraborty et al. (2012). The MC252 oil spill in the Gulf of Mexico in 2010 was the largest in US history. Many environmental factors distinguished this spill from previous ones, including hydrocarbon composition, environmental variables, depth of the spill, and the availability of systems biology tools. Information on chemical analyses is crucial in support of a system’s biology approach for oil bioremediation in the MC252 spill. While Camilli et al. (2010) concluded that microbial respiration rates within the deep plume were extremely low based on dissolved oxygen concentration, measurement of microbial respiration rates, enzyme activity, phosphate concentration, and polar membrane lipid concentration in surface water affected by the oil spill. Edwards et al. (2011) concluded that enzyme activities and respiration rates were found to be higher inside the oil slick. Valentine et al. (2010) investigated the fate of methane, propane, and ethane gases of the deep hydrocarbon plume at depth greater than 799 m, and found that propane and ethane were degraded faster than methane.13C-labled substrates, as well as 13C and 3H tracers, were used to measure d13C-DIC. In another study, methane was found to be the most abundant hydrocarbon released during the MC252 spill, and that there was a rapid response of methanotrophic bacteria rapidly respiring the released methane. PhyloChip, clone library, GeoChip, phospholipid fatty acid (PLFA), and isotope chemistry were used to compare microbial communities inside and outside the deep plume (Hazen et al. 2010). The results identified Oceanospirillales, which were found to degrade hydrocarbons at 58°C inside the plume. The GeoChip demonstrated genes that were significantly correlated to concentration of oil contaminants, such as phdC1 (naphthalene degradation), and alkB (oxidation of alkanes), as well as a shift in C, N, P, S cycling processes in the deep plume samples. The involvement of federal agencies and pending lawsuits is the impetus for a concerted effort in collating all data collected resulting in a comprehensive database useful for researchers. By integrating chemical analyses with studies utilizing a systems biology approach, there was an unprecedented near real-time understanding of chemical and biological reactions involved in the hydrocarbon degradation. In order to gain a more comprehensive understanding of the microbiological processes, data from transcriptomics studies will provide information on whether the cultivatable dominant microbes are the in situ active ones, and proteomics studies will identify enzymes central to hydrocarbon degradation.

Chlorinated solvents bioremediation

Chlorinated solvents, such as TCE and dichloroethene (DCE), are recalcitrant carcinogenic compounds that persist in the environment once released. Microbes, such as Dehalococcoides, are capable of using the chlorinated solvents as electron acceptors anaerobically and dechlorinating the compounds to ethene. Another biodegradation pathway is the aerobic co-metabolism of the chlorinated compounds to carbon dioxide and chloride by microbes such as methane-oxidizers with methane monooxygenases (MMOs) (. Descriptions of techniques that monitor mass loss, geochemical fingerprints, isotope fractionation associated with biodegradation, microbial communities in biostimulation and natural attenuation studies, quantitative real-time PCR methods targeting reductive dehalogenase genes are included in several reviews. Between 1955 and 1972, low-level radioactive isotopes, sewage and chlorinated solvents were injected into the aquifer through a 95 m deep well at Test Area North (TAN) in Idaho National Laboratory. The plume contained TCE concentrations ranging from 5 ppb to 300 ppm extending for more than 2 km. An enhanced in situ bioremediation pilot study started in 1999 to treat the chlorinated solvents contaminated groundwater by injecting the electron donor Lactate to stimulate in situ reductive dechlorination. A comparison of microbial communities in the core and groundwater samples was assessed by characterizing total biomass, PLFA analysis, culturing and community-level physiological profiling (CLPP) using Biolog GN microplates (Lehman et al. 2004). DGGE analysis indicated that wells with high concentrations of chlorinated solvents had different microbial communities from wells with minimal concentrations of the contaminants, and that attached, and the free-living microbes had different functional and composition profile Additionally, qPCR of the Dehalococcoides sp. 16S rRNA genes provided the most convincing result in quantifying dechlorinating potential of a community compared to community analysis by terminal restriction fragment length polymorphism (T-RFLP), and RFLP analysis with clone sequencing. Erwin et al. (2005) demonstrated the presence of bacteria harboring MMOs and potential of TCE co-metabolism at TAN from a pristine area using PCR amplification to generate a function gene fragment library and sequencing. Stable carbon isotope ratios of groundwater samples taken in 2000 confirmed the complete conversion of TCE to ethene, and minimal biodegradation of t-DCE (Song et al. 2002). Using the PhyloChip for bacterial composition characterization, a decrease in reductive dechlorinating organisms and an increase in methane-oxidizing microbes capable of aerobic co-metabolism of TCE was observed. Further studies that would complement the investigation at the TAN site would be to employ a shotgun proteomics approach as reported by Werner et al. (2009) Their method allowed for detection of peptides, such as FdhA, TceA, PceA, and HupL that could potentially be used as bioindicators of chlorinated ethene dehalorespiration.


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