Systemic approaches to biodegradation

Quantifying the Role of Simultaneous Transformation Pathways in the Fate of the Novel Aquatic Herbicide Florpyrauxifen-Benzyl

Predicting the fate of organic compounds in the environment is challenging due to the inability of laboratory studies to replicate field conditions. We used the intentionally applied aquatic herbicide florpyrauxifen-benzyl (FPB) as a model compound to investigate the contribution of multiple transformation pathways to organic compound fate in lakes. FPB persisted in five Wisconsin lakes for 5-7 days with an in-lake half-life of <2 days. FPB formed four transformation products, with the bioactive product florpyrauxifen persisting up to 30 days post-treatment. Parallel laboratory experiments showed that FPB degrades to florpyrauxifen via base-promoted hydrolysis. Hydroxy-FPB and hydroxy-florpyrauxifen were identified as biodegradation products, while dechloro-FPB was identified as a photoproduct. Material balance calculations using both laboratory rates and field product concentrations demonstrated that hydrolysis (∼47% of loss), biodegradation (∼20%), sorption (∼13%), and photodegradation (∼4%) occurred on similar timescales. Furthermore, the combined results demonstrated that abiotic and plant-catalyzed hydrolysis of FPB to florpyrauxifen, followed by biodegradation of florpyrauxifen to hydroxy-florpyrauxifen, was the dominant transformation pathway in lakes. This study demonstrates how combined field and laboratory studies can be used to elucidate the role of simultaneous and interacting pathways in the fate of organic compounds in aquatic environments.

Engineering the Substrate Specificity of Toluene Degrading Enzyme XylM Using Biosensor XylS and Machine Learning

Enzyme engineering using machine learning has been developed in recent years. However, to obtain a large amount of data on enzyme activities for training data, it is necessary to develop a high-throughput and accurate method for evaluating enzyme activities. Here, we examined whether a biosensor-based enzyme engineering method can be applied to machine learning. As a model experiment, we aimed to modify the substrate specificity of XylM, a rate-determining enzyme in a multistep oxidation reaction catalyzed by XylMABC in Pseudomonas putida. XylMABC naturally converts toluene and xylene to benzoic acid and toluic acid, respectively. We aimed to engineer XylM to improve its conversion efficiency to a non-native substrate, 2,6-xylenol. Wild-type XylMABC slightly converted 2,6-xylenol to 3-methylsalicylic acid, which is the ligand of the transcriptional regulator XylS in P. putida. By locating a fluorescent protein gene under the control of the Pm promoter to which XylS binds, a XylS-producing Escherichia coli strain showed higher fluorescence intensity in a 3-methylsalicylic acid concentration-dependent manner. We evaluated the 3-methylsalicylic acid productivity of XylM variants using the fluorescence intensity of the sensor strain as an indicator. The obtained data provided the training data for machine learning for the directed evolution of XylM. Two cycles of machine learning-assisted directed evolution resulted in the acquisition of XylM-D140E-V144K-F243L-N244S with 15 times higher productivity than wild-type XylM. These results demonstrate that an indirect enzyme activity evaluation method using biosensors is sufficiently quantitative and high-throughput to be used as training data for machine learning. The findings expand the versatility of machine learning in enzyme engineering.

Remediation techniques for elimination of heavy metal pollutants from soil: A review

Contaminated soil containing toxic metals and metalloids is found everywhere globally. As a consequence of adsorption and precipitation reactions, metals are comparatively immobile in subsurface systems. Hence remediation techniques in such contaminated sites have targeted the solid phase sources of metals such as sludges, debris, contaminated soils, or wastes. Over the last three decades, the accumulation of these toxic substances inside the soil has increased dramatically, putting the ecosystem and human health at risk. Pollution of heavy metal have posed severe impacts on human, and it affects the environment in different ways, resulting in industrial anger in many countries. Various procedures, including chemical, biological, physical, and integrated approaches, have been adopted to get rid of this type of pollution. Expenditure, timekeeping, planning challenges, and state-of-the-art gadget involvement are some drawbacks that need to be properly handled. Recently in situ metal immobilization, plant restoration, and biological methods have changed the dynamics and are considered the best solution for removing metals from soil. This review paper critically evaluates and analyzes the numerous approaches for preparing heavy metal-free soil by adopting different soil remediation methods.

Lessons From Insect Fungiculture: From Microbial Ecology to Plastics Degradation

Anthropogenic activities have extensively transformed the biosphere by extracting and disposing of resources, crossing boundaries of planetary threat while causing a global crisis of waste overload. Despite fundamental differences regarding structure and recalcitrance, lignocellulose and plastic polymers share physical-chemical properties to some extent, that include carbon skeletons with similar chemical bonds, hydrophobic properties, amorphous and crystalline regions. Microbial strategies for metabolizing recalcitrant polymers have been selected and optimized through evolution, thus understanding natural processes for lignocellulose modification could aid the challenge of dealing with the recalcitrant human-made polymers spread worldwide. We propose to look for inspiration in the charismatic fungal-growing insects to understand multipartite degradation of plant polymers. Independently evolved in diverse insect lineages, fungiculture embraces passive or active fungal cultivation for food, protection, and structural purposes. We consider there is much to learn from these symbioses, in special from the community-level degradation of recalcitrant biomass and defensive metabolites. Microbial plant-degrading systems at the core of insect fungicultures could be promising candidates for degrading synthetic plastics. Here, we first compare the degradation of lignocellulose and plastic polymers, with emphasis in the overlapping microbial players and enzymatic activities between these processes. Second, we review the literature on diverse insect fungiculture systems, focusing on features that, while supporting insects' ecology and evolution, could also be applied in biotechnological processes. Third, taking lessons from these microbial communities, we suggest multidisciplinary strategies to identify microbial degraders, degrading enzymes and pathways, as well as microbial interactions and interdependencies. Spanning from multiomics to spectroscopy, microscopy, stable isotopes probing, enrichment microcosmos, and synthetic communities, these strategies would allow for a systemic understanding of the fungiculture ecology, driving to application possibilities. Detailing how the metabolic landscape is entangled to achieve ecological success could inspire sustainable efforts for mitigating the current environmental crisis.

Field Test of In Situ Groundwater Treatment Applying Oxygen Diffusion and Bioaugmentation Methods in an Area with Sustained Total Petroleum Hydrocarbon (TPH) Contaminant Flow

Contamination of groundwater by petroleum hydrocarbons is a widespread environmental problem in many regions. Contamination of unsaturated and saturated zones could also pose a significant risk to human health. The main purpose of the study was to assess the efficiency of biodegradation of total petroleum hydrocarbon (TPH) in situ, in an area with loam and sandy loam soils, and to identify features and characteristics related to groundwater treatment in an area with a persistent flow of pollutants. We used methods of biostimulation (oxygen as stimulatory supplement) and bioaugmentation to improve water quality. Oxygen was added to the groundwater by diffusion through silicone tubing. The efficiency of groundwater treatment was determined by detailed monitoring. Implementation of the applied measure resulted in an average reduction in TPH concentration of 73.1% compared with the initial average concentration (4.33 mg/L), and in the local area, TPH content was reduced by 95.5%. The authors hope that this paper will contribute to a better understanding of the topic of groundwater treatment by in situ biodegradation of TPH. Further studies on this topic are particularly needed to provide more data and details on the efficiency of groundwater treatment under adverse geological conditions.

Alternative Strategies for Microbial Remediation of Pollutants via Synthetic Biology

Continuous contamination of the environment with xenobiotics and related recalcitrant compounds has emerged as a serious pollution threat. Bioremediation is the key to eliminating persistent contaminants from the environment. Traditional bioremediation processes show limitations, therefore it is necessary to discover new bioremediation technologies for better results. In this review we provide an outlook of alternative strategies for bioremediation via synthetic biology, including exploring the prerequisites for analysis of research data for developing synthetic biological models of microbial bioremediation. Moreover, cell coordination in synthetic microbial community, cell signaling, and quorum sensing as engineered for enhanced bioremediation strategies are described, along with promising gene editing tools for obtaining the host with target gene sequences responsible for the degradation of recalcitrant compounds. The synthetic genetic circuit and two-component regulatory system (TCRS)-based microbial biosensors for detection and bioremediation are also briefly explained. These developments are expected to increase the efficiency of bioremediation strategies for best results.

Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models

Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems.

Modelling of the methyl halide biodegradation in bacteria and its effect on environmental systems

Methyl halide group of pesticides are being used widely in past decades as fumigant but due to their hazardous effect, these pesticides are not sold directly. They are volatile and gaseous in nature and may easily come in the contact of trophosphere and stratosphere. In troposphere, they are harmful to the living beings; nevertheless, in stratosphere they react with ozone and degrade the ozone layers. In this study, we have investigated the in-silico pathways of methyl halide and its toxic effect on living systems like pest, humans and environment. Till date, limited studies provide the understanding of degradation of methyl halide and its effect on the environment. This leads to availability of scanty information for overall bio-magnifications of methyl halides at molecular and cellular level. The model developed in the present study explains how a volatile toxic compound not only affects living systems on earth but also on environmental layers. Hub nodes were also evaluated by investigating the developed model topologically. Methyl transferase system is identified as promising enzyme in response to degradation of methyl halides.

Different Dimensions in Microbial Community Adaptation and Function

With the omics tool, the challenges in understanding the microbial community functions are becoming more intriguing. It is the environment created scenario, which demands alignment of the different members of the community for the desired output leading to common condition for their survival. The resultant community pathways provide a broad umbrella of metabolic options giving the desired plasticity, which plays decision making role in the adaptation process. The initial step in community characterization must involve the discovery of key and core member of the community and monitoring the fluctuations in functional abundance over the space and time. The concept of entropy and metabolic fluxes must reflect the inner metabolic machinery of the taxon selection and route of functional operation in a community. The segregation of member based on their functional role and hierarchical level in the community must be an essential step to be followed by interaction mapping and measurement of metabolic fluxes to derive the flow of metabolites within the community. This conceptual framework and integrated omics tools with supported statistical modeling algorithm can help in bringing out finer details in the process of community functional adaptation in any given scenario.

Laboratory and field microcosms as useful experimental systems to study the bioaugmentation treatment of tannery effluents

Tannery effluents require effective treatment prior to their final disposal, and the use of native bacterial consortia could be an appropriate strategy for this purpose. In the present work, consortium SFC 500-1 was found to be highly tolerant to different metals, metalloids and aromatic compounds like phenols. It was also able to remove the black dye commonly used in tanneries. Moreover, it promoted a significant reduction in chemical oxygen demand and exhibited high capability for the simultaneous removal of Cr(VI) and phenol. However, the effectiveness of the remediation processes markedly varied from one experimental system (Erlenmeyer flasks) to another (field microcosm system), highlighting the importance of moving from a small-scale study system to one involving more realistic environmental scenarios. In addition, we found a decrease in the toxicity of the effluent treated with consortium SFC 500-1. Taken together, our results indicate that this consortium possesses great potential for the treatment of tannery effluents. We conclude that for the development of a bioremediation strategy, it is necessary to develop experiments at a larger scale under conditions similar to those of the original system, in order to complete the scenario first created by in vitro approaches.

Ecology of Contaminant Biotransformation in the Mycosphere: Role of Transport Processes

Fungi and bacteria often share common microhabitats. Their co-occurrence and coevolution give rise to manifold ecological interactions in the mycosphere, here defined as the microhabitats surrounding and affected by hyphae and mycelia. The extensive structure of mycelia provides ideal "logistic networks" for transport of bacteria and matter in structurally and chemically heterogeneous soil ecosystems. We describe the characteristics of the mycosphere as a unique and highly dynamic bacterial habitat and a hot spot for contaminant biotransformation. In particular, we emphasize the role of the mycosphere for (i) bacterial dispersal and colonization of subsurface interfaces and new habitats, (ii) matter transport processes and contaminant bioaccessibility, and (iii) the functional stability of microbial ecosystems when exposed to environmental fluctuations such as stress or disturbances. Adopting concepts from ecological theory, the chapter disentangles bacterial-fungal impacts on contaminant biotransformation in a systemic approach that interlinks empirical data from microbial ecosystems with simulation data from computational models. This approach provides generic information on key factors, processes, and ecological principles that drive microbial contaminant biotransformation in soil. We highlight that the transport processes create favorable habitat conditions for efficient bacterial contaminant degradation in the mycosphere. In-depth observation, understanding, and prediction of the role of mycosphere transport processes will support the use of bacterial-fungal interactions in nature-based solutions for contaminant biotransformation in natural and man-made ecosystems, respectively.

Hydrocarbon degraders establish at the costs of microbial richness, abundance and keystone taxa after crude oil contamination in permafrost environments

Oil spills from pipeline ruptures are a major source of terrestrial petroleum pollution in cold regions. However, our knowledge of the bacterial response to crude oil contamination in cold regions remains to be further expanded, especially in terms of community shifts and potential development of hydrocarbon degraders. In this study we investigated changes of microbial diversity, population size and keystone taxa in permafrost soils at four different sites along the China-Russia crude oil pipeline prior to and after perturbation with crude oil. We found that crude oil caused a decrease of cell numbers together with a reduction of the species richness and shifts in the dominant phylotypes, while bacterial community diversity was highly site-specific after exposure to crude oil, reflecting different environmental conditions. Keystone taxa that strongly co-occurred were found to form networks based on trophic interactions, that is co-metabolism regarding degradation of hydrocarbons (in contaminated samples) or syntrophic carbon cycling (in uncontaminated samples). With this study we demonstrate that after severe crude oil contamination a rapid establishment of endemic hydrocarbon degrading communities takes place under favorable temperature conditions. Therefore, both endemism and trophic correlations of bacterial degraders need to be considered in order to develop effective cleanup strategies.

From oil spills to barley growth - oil-degrading soil bacteria and their promoting effects

Heavy contamination of soils by crude oil is omnipresent in areas of oil recovery and exploitation. Bioremediation by indigenous plants in cooperation with hydrocarbon degrading microorganisms is an economically and ecologically feasible means to reclaim contaminated soils. To study the effects of indigenous soil bacteria capable of utilizing oil hydrocarbons on biomass production of plants growing in oil-contaminated soils eight bacterial strains were isolated from contaminated soils in Kazakhstan and characterized for their abilities to degrade oil components. Four of them, identified as species of Gordonia and Rhodococcus turned out to be effective degraders. They produced a variety of organic acids from oil components, of which 59 were identified and 7 of them are hitherto unknown acidic oil metabolites. One of them, Rhodococcus erythropolis SBUG 2054, utilized more than 140 oil components. Inoculating barley seeds together with different combinations of these bacterial strains restored normal growth of the plants on contaminated soils, demonstrating the power of this approach for bioremediation. Furthermore, we suggest that the plant promoting effect of these bacteria is not only due to the elimination of toxic oil hydrocarbons but possibly also to the accumulation of a variety of organic acids which modulate the barley's rhizosphere environment.

Interaction networks for identifying coupled molecular processes in microbial communities

BACKGROUND

Microbial communities adapt to environmental conditions for optimizing metabolic flux. Such adaption may include cooperative mechanisms eventually resulting in phenotypic observables as emergent properties that cannot be attributed to an individual species alone. Understanding the molecular basis of cross-species cooperation adds to utilization of microbial communities in industrial applications including metal bioleaching and bioremediation processes. With significant advancements in metagenomics the composition of microbial communities became amenable for integrative analysis on the level of entangled molecular processes involving more than one species, in turn offering a data matrix for analyzing the molecular basis of cooperative phenomena.

METHODS

We present an analysis framework aligned with a dynamical hierarchies concept for unraveling emergent properties in microbial communities, and exemplify this approach for a co-culture setting of At. ferrooxidans and At. thiooxidans. This minimum microbial community demonstrates a significant increase in bioleaching efficiency compared to the activity of individual species, involving mechanisms of the thiosulfate, the polysulfide and the iron oxidation pathway.

RESULTS

Populating gene-centric data structures holding rich functional annotation and interaction information allows deriving network models at the functional level coupling energy production and transport processes of both microbial species. Applying a network segmentation approach on the interaction network of ortholog genes covering energy production and transport proposes a set of specific molecular processes of relevance in bioleaching. The resulting molecular process model essentially involves functionalities such as iron oxidation, nitrogen metabolism and proton transport, complemented by sulfur oxidation and nitrogen metabolism, as well as a set of ion transporter functionalities. At. ferrooxidans-specific genes embedded in the molecular model representation hold gene functions supportive for ammonia utilization as well as for biofilm formation, resembling key elements for effective chalcopyrite bioleaching as emergent property in the co-culture situation.

CONCLUSIONS

Analyzing the entangled molecular processes of a microbial community on the level of segmented, gene-centric interaction networks allows identification of core molecular processes and functionalities adding to our mechanistic understanding of emergent properties of microbial consortia.

Refinement of biodegradation tests methodologies and the proposed utility of new microbial ecology techniques

Society's reliance upon chemicals over the last few decades has led to their increased production, application and release into the environment. Determination of chemical persistence is crucial for risk assessment and management of chemicals. Current established OECD biodegradation guidelines enable testing of chemicals under laboratory conditions but with an incomplete consideration of factors that can impact on chemical persistence in the environment. The suite of OECD biodegradation tests do not characterise microbial inoculum and often provide little insight into pathways of degradation. The present review considers limitations with the current OECD biodegradation tests and highlights novel scientific approaches to chemical fate studies. We demonstrate how the incorporation of molecular microbial ecology methods (i.e., 'omics') may improve the underlying mechanistic understanding of biodegradation processes, and enable better extrapolation of data from laboratory based test systems to the relevant environment, which would potentially improve chemical risk assessment and decision making. We outline future challenges for relevant stakeholders to modernise OECD biodegradation tests and put the 'bio' back into biodegradation.

Challenges for complex microbial ecosystems: combination of experimental approaches with mathematical modeling

In the past couple of decades, molecular ecological techniques have been developed to elucidate microbial diversity and distribution in microbial ecosystems. Currently, modern techniques, represented by meta-omics and single cell observations, are revealing the incredible complexity of microbial ecosystems and the large degree of phenotypic variation. These studies propound that microbiological techniques are insufficient to untangle the complex microbial network. This minireview introduces the application of advanced mathematical approaches in combination with microbiological experiments to microbial ecological studies. These combinational approaches have successfully elucidated novel microbial behaviors that had not been recognized previously. Furthermore, the theoretical perspective also provides an understanding of the plasticity, robustness and stability of complex microbial ecosystems in nature.

An insight into the origin and functional evolution of bacterial aromatic ring-hydroxylating oxygenases

Bacterial aromatic ring-hydroxylating oxygenases (RHOs) are multicomponent enzyme systems which have potential utility in bioremediation of aromatic compounds in the environment. To cope with the enormous diversity of aromatic compounds in the environment, this enzyme family has evolved remarkably exhibiting broad substrate specificity. RHOs are multicomponent enzymes comprising of a homo- or hetero-multimeric terminal oxygenase and one or more electron transport (ET) protein(s). The present study attempts in depicting the evolutionary scenarios that might have occurred during the evolution of RHOs, by analyzing a set of available sequences including those obtained from complete genomes. A modified classification scheme identifying four new RHO types has been suggested on the basis of their evolutionary and functional behaviours, in relation to structural configuration of substrates and preferred oxygenation site(s). The present scheme emphasizes on the fact that the phylogenetic affiliation of RHOs is distributed among four distinct 'Similarity classes', independent of the constituent ET components. Similar combination of RHO components that was previously considered to be equivalent and classified together [Kweon et al., BMC Biochemistry 9, 11 (2008)] were found here in distinct similarity classes indicating the role of substrate-binding terminal oxygenase in guiding the evolution of RHOs irrespective of the nature of constituent ET components. Finally, a model for evolution of the multicomponent RHO enzyme system has been proposed, beginning from genesis of the terminal oxygenase components followed by recruitment of constituent ET components, finally evolving into various 'extant' RHO types.

Integrated perspective for effective bioremediation

Identification of factors which can influence the natural attenuation process with available microbial genetic capacities can support the bioremediation which has been viewed as the safest procedure to combat with anthropogenic compounds in ecosystems. With the advent of molecular techniques, assimilatory capacity of an ecosystem can be defined with changing community dynamics, and if required, the essential genetic potential can be met through bioaugmentation. At the same time, intensification of microbial processes with nutrient balancing, expressing and enhancing the degradative capacities, could reduce the time frame of restoration of the ecosystem. The new concept of ecosystems biology has added greatly to conceptualize the networking of the evolving microbiota of the niche that helps in effective application of bioremediation tools to manage pollutants as additional carbon source.

Bioremediation approaches for organic pollutants: a critical perspective

Due to human activities to a greater extent and natural processes to some extent, a large number of organic chemical substances such as petroleum hydrocarbons, halogenated and nitroaromatic compounds, phthalate esters, solvents and pesticides pollute the soil and aquatic environments. Remediation of these polluted sites following the conventional engineering approaches based on physicochemical methods is both technically and economically challenging. Bioremediation that involves the capabilities of microorganisms in the removal of pollutants is the most promising, relatively efficient and cost-effective technology. However, the current bioremediation approaches suffer from a number of limitations which include the poor capabilities of microbial communities in the field, lesser bioavailability of contaminants on spatial and temporal scales, and absence of bench-mark values for efficacy testing of bioremediation for their widespread application in the field. The restoration of all natural functions of some polluted soils remains impractical and, hence, the application of the principle of function-directed remediation may be sufficient to minimize the risks of persistence and spreading of pollutants. This review selectively examines and provides a critical view on the knowledge gaps and limitations in field application strategies, approaches such as composting, electrobioremediation and microbe-assisted phytoremediation, and the use of probes and assays for monitoring and testing the efficacy of bioremediation of polluted sites.

Subpopulation-specific metabolic pathway usage in mixed cultures as revealed by reporter protein-based 13C analysis

Most large-scale biological processes, like global element cycling or decomposition of organic matter, are mediated by microbial consortia. Commonly, the different species in such consortia exhibit mutual metabolic dependencies that include the exchange of nutrients. Despite the global importance, surprisingly little is known about the metabolic interplay between species in particular subpopulations. To gain insight into the intracellular fluxes of subpopulations and their interplay within such mixed cultures, we developed here a (13)C flux analysis approach based on affinity purification of the recombinant fusion glutathione S-transferase (GST) and green fluorescent protein (GFP) as a reporter protein. Instead of detecting the (13)C labeling patterns in the typically used amino acids from the total cellular protein, our method detects these (13)C patterns in amino acids from the reporter protein that has been expressed in only one species of the consortium. As a proof of principle, we validated our approach by mixed-culture experiments of an Escherichia coli wild type with two metabolic mutants. The reporter method quantitatively resolved the expected mutant-specific metabolic phenotypes down to subpopulation fractions of about 1%.

Novel biological insights through metabolomics and 13C-flux analysis

Metabolomics and (13)C-flux analysis have become instrumental for analyzing cellular metabolism and its regulation. Driven primarily by technical advances in mass spectrometry-based analytics, they provide unmatched readouts on metabolic state and activity. Functional genomics leverages metabolomics for the discovery of novel enzymes and unexpected secondary activities of annotated enzymes. (13)C-flux analyses are frequently used for empirical elucidation of pathways in poorly characterized species and for network-wide analysis of mechanisms that realize energy and redox balancing. Integration of metabolomics, (13)C-flux analysis and other data enable the condition-dependent characterization of regulatory circuits that ultimately govern the metabolic phenotype.

Intertwined interspecies relationships: approaches to untangle the microbial network

In nature, microorganisms live by interacting with each other. Microbiological studies that only consider pure cultures are not sufficient to adequately describe the natural behaviour of microbes. Several microbial interactions have been recognized to affect the growth or metabolism of others; e.g. syntrophic cometabolism, competition, production of inhibitors or activators, and predation. It is believed that third-party organisms easily affect the two-species relationships and these relationships form the basis of interspecies networks within microbial communities. A microbial network contributes to 'functional redundancy' or 'structural diversity' and the microbial communities effectively act as a multicellular organism. It is necessary to understand not only the physiological activity of members within microbial communities but also their roles to regulate the activity or population of others. To access the microbial network, we require (i) comprehensive determination of all possible interspecies relationships among microbes, (ii) knock-out experiments by which certain members can be removed or suppressed, and (iii) supplemental addition of microbes or activation of certain members. Microbial network studies have started using defined microbial communities, i.e. a mixed culture that is composed of three or four species. In order to expand these studies to microflora in nature, microbial ecology requires the help of mathematical biology.

Creating reference datasets for systems biology applications using text mining

High-throughput experimental techniques are generating large data collections with the aim of identifying novel entities involved in fundamental cellular processes as well as drawing a systematic picture of the relationships between individual components. Determining the accuracy of the resulting data and the selection of a subset of targets for more careful characterizations often requires relying on information provided by manually annotated data repositories. These repositories are incomplete and cover only a small fraction of the knowledge contained in the literature. We propose in this paper the use of text-mining technologies to extract, organize, and present information relevant for a particular biological topic. The aims of the resulting approach are (1) to enable topic-centric biological literature navigation, (2) to assist in the construction of manually revised data repositories, (3) to provide prioritization of biological entities for experimental studies, and (4) to enable human interpretation of large-scale experiments by providing direct links of bio-entities to relevant descriptions in the literature.