The potential of metabolomics tools in bioremediation studies

As a post-genomics tool, metabolomics is a young and vibrant field of science in its exponential growth phase. Metabolome analysis has become very popular recently, and novel techniques for acquiring and analyzing metabolomics data continue to emerge that are useful for a variety of biological studies. The bioremediation field has a lot to gain from the advances in this emerging area. Thus, this review article focuses on the potential of various experimental and conceptual approaches developed for metabolomics to be applied in bioremediation research, such as strategies for elucidation of biodegradation pathways using isotope distribution analysis and molecular connectivity analysis, the assessment of mineralization process using metabolic footprinting analysis, and the improvement of the biodegradation process via metabolic engineering. We demonstrate how the use of metabolomics tools can significantly extend and enhance the power of existing bioremediation approaches by providing a better overview of the biodegradation process.     

A MOD(ern) perspective on literature curation

Curation of biological data is a multi-faceted task whose goal is to create a structured, comprehensive, integrated, and accurate resource of current biological knowledge. These structured data facilitate the work of the scientific community by providing knowledge about genes or genomes and by generating validated connections between the data that yield new information and stimulate new research approaches. For the model organism databases (MODs), an important source of data is research publications. Every published paper containing experimental information about a particular model organism is a candidate for curation. All such papers are examined carefully by curators for relevant information. Here, four curators from different MODs describe the literature curation process and highlight approaches taken by the four MODs to address: (1) the decision process by which papers are selected, and (2) the identification and prioritization of the data contained in the paper. We will highlight some of the challenges that MOD biocurators face, and point to ways in which researchers and publishers can support the work of biocurators and the value of such support.     

Recent developments in microbial biotransformation and biodegradation of dioxins

Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), commonly known as dioxins (PCDD/Fs), are toxic environmental pollutants formed from various sources. Elimination of these pollutants from the environment is a difficult task due to their persistent and ubiquitous nature. Removal of dioxins by biological degradation (biodegradation) is considered a feasible method as an alternative to other expensive physicochemical approaches. Biodegradation of dioxins has been extensively studied in several microorganisms, and details concerning biodiversity, biodegradation, biochemistry and molecular biology of this process have accumulated during the last three decades. There are several microbial mechanisms responsible for biodegradation of dioxins, including oxidative degradation by dioxygenase-containing aerobic bacteria, bacterial and fungal cytochrome P-450, fungal lignolytic enzymes, reductive dechlorination by anaerobic bacteria, and direct ether ring cleavage by fungi containing etherase-like enzymes. Many attempts have been made to bioremediate PCDD/Fs using this basic knowledge of microbial dioxin degradation. This review emphasizes the present knowledge and recent advancements in the microbial biotransformation, biodegradation and bioremediation of dioxins.     

Influence of mass transfer on stable isotope fractionation

Biodegradation of contaminants is a common remediation strategy for subsurface environments. To monitor the success of such remediation means a quantitative assessment of biodegradation at the field scale is required. Nevertheless, the reliable quantification of the in situ biodegradation process it is still a major challenge. Compound-specific stable isotope analysis has become an established method for the qualitative analysis of biodegradation in the field and this method is also proposed for a quantitative analysis. However, to use stable isotope data to obtain quantitative information on in situ biodegradation requires among others knowledge on the influence of mass transfer processes on the observed stable isotope fractionation. This paper reviews recent findings on the influence of mass transfer processes on stable isotope fractionation and on the quantitative interpretation of isotope data. Focus will be given on small-scale mass transfer processes controlling the bioavailability of contaminants. Such bioavailability limitations are known to affect the biodegradation rate and have recently been shown to affect stable isotope fractionation, too. Theoretical as well as experimental studies addressing the link between bioavailability and stable isotope fractionation are reviewed and the implications for assessing biodegradation in the field are discussed.     

Integrated analysis of gene expression by association rules discovery

Background  

Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process.     

Effect of scale-up and seasonal variation on biokinetics in the enhanced bioremediation of petroleum hydrocarbon-contaminated soil

The biodegradation rate of petroleum hydrocarbon-contaminated soil was evaluated by the effect of temperature variation through bioaugmentation and biostimulation. In this study, biokinetics of batch-, pilot-, and field-scale biodegradation were performed by the optimization of enhanced biodegradation, minimizing the inhibitory effects of seasonal variations such as the rainy and cold winter seasons. From the relationship between remedial timescale and initial concentration, the biokinetic isolines of the biodegradation were smaller in the winter than those in the other seasons. The scale-up of biodegradation process led to enhance its activation energy, and then the field-scale remedial action should be performed in the way to lower the activation energy from the chemical diffusion and microbial activation. Therefore, a remedial or field worker can obtain the remedial timescale from the given apparent data of biokinetics with respect to initial TPH concentration only after the simple remedial investigation.     

Applied models to biodegradation kinetics of lubricant and vegetable oils in wastewater

Bioremediation technologies are used in order to remove pollutants from the environment in a safe, economical and harmless way during the treatment of waste, especially with the use of techniques such as biodegradation. A lubricant and vegetable oil contaminated water sample was studied in order to evaluate the biodegradability of different types of oils, considering the relevance of the obtained data in the bioremediation procedures. The objective of this paper is to use respirometry technique as a biodegradation process data source, and then apply to the obtained data the experimental design of mathematical models to characterize and determinate how the different types of oils are capable of affecting the parameters in biodegradation kinetics. The kinetics was then evaluated through selected models with a reasonable fit to experimental data. The Bartha and Pramer respirometer is used as a method to accurately measure the CO₂ formation in the organic compounds degradation by microorganisms. Therefore, the difference in biodegradation efficiency process is compared in the different groups of oils using mathematical models fitting the obtained data for the kinetics of biodegradation. The results demonstrated that used lubricant automotive oils are more susceptible to the biodegradation process, since their molecular structures had already been altered after use. In general, automotive lubricant oils shown better performance in biodegradation than vegetable oils. The models proposed for the obtained data in each of these assays demonstrated that vegetable oils biodegradation rate tends to decrease faster and end sooner than the automotive oils. Also, the modeling predicted that higher rates of biodegradation and total CO₂ production are to be expected in automotive lubricant oils rather than vegetable oils.     

Bioremediation of DDT-Contaminated Soils: A Review

The insecticide 1,1,1-trichloro-2,2-bis-(4-chlorophenyl)ethane (DDT) has been used extensively since the 1940s for control of agricultural pests, and is still used in many tropical countries for mosquito control. Despite a ban on DDT use in most industrialized countries since 1972, DDT and its related residues (DDTr) persist in the environment and pose animal and human health risks. Abiotic processes such as volatilization, adsorption, and photolysis contribute to the dissipation of DDTr in soils, often without substantial alteration of the chemical structure. In contrast, biodegradation has the potential to degrade DDTr significantly and reduce soil concentrations in a cost-effective manner. Many bacteria and some fungi transform DDT, forming products with varying recalcitrance to further degradation. DDT biodegradation is typically co-metabolic and includes dechlorination and ring cleavage mechanisms. Factors that influence DDTr biodegradation in soil include the composition and enzymatic activity of the soil microflora, DDTr bioavailability, the presence of soil organic matter as a co-metabolic substrate and (or) inducer, and prevailing soil conditions, including aeration, pH, and temperature. Understanding how these factors affect DDTr biodegradation permits rational design of treatments and amendments to stimulate biodegradation in soils. The DDTr-degrading organisms, processes and approaches that may be useful for bioremediation of DDTr-contaminated soils are discussed, including in situ amendments, ex situ bioreactors and sequential anaerobic and aerobic treatments.     

Hierarchical classification of microorganisms based on high‐dimensional phenotypic data

The classification of microorganisms by high‐dimensional phenotyping methods such as FTIR spectroscopy is often a complicated process due to the complexity of microbial phylogenetic taxonomy. A hierarchical structure developed for such data can often facilitate the classification analysis. The hierarchical tree structure can either be imposed to a given set of phenotypic data by integrating the phylogenetic taxonomic structure or set up by revealing the inherent clusters in the phenotypic data. In this study, we wanted to compare different approaches to hierarchical classification of microorganisms based on high‐dimensional phenotypic data. A set of 19 different species of molds (filamentous fungi) obtained from the mycological strain collection of the Norwegian Veterinary Institute (Oslo, Norway) is used for the study. Hierarchical cluster analysis is performed for setting up the classification trees. Classification algorithms such as artificial neural networks (ANN), partial least‐squared discriminant analysis and random forest (RF) are used and compared. The 2 methods ANN and RF outperformed all the other approaches even though they did not utilize predefined hierarchical structure. To our knowledge, the RF approach is used here for the first time to classify microorganisms by FTIR spectroscopy.      

Equation discovery for systems biology: finding the structure and dynamics of biological networks from time course data

Reconstructing biological networks, such as metabolic and signaling networks, is at the heart of systems biology. Although many approaches exist for reconstructing network structure, few approaches recover the full dynamic behavior of a network. We survey such approaches that originate from computational scientific discovery, a subfield of machine learning. These take as input measured time course data, as well as existing domain knowledge, such as partial knowledge of the network structure. We demonstrate the use of these approaches on illustrative tasks of finding the complete dynamics of biological networks, which include examples of rediscovering known networks and their dynamics, as well as examples of proposing models for unknown networks.     

Chemical Vapor Intrusion from Soil or Groundwater to Indoor Air: Significance of Unsaturated Zone Biodegradation of Aromatic Hydrocarbons

The soil vapor to indoor air exposure pathway is considered in a wide number of risk-based site management programs. In screening-level assessments of this exposure pathway, models are typically used to estimate the transport of vapors from either subsurface soils or groundwater to indoor air. Published studies indicate that the simple models used to evaluate this exposure pathway often over estimate the impact for aromatic hydrocarbons (e.g., benzene, toluene, ethylbenzene, and xy-lene or BTEX), while showing reasonable agreement for estimates of chlorinated hydrocarbon impacts (e.g., PCE, TCE, DCE). Aerobic biodegradation of the petroleum hydrocarbons is most often attributed as the source of this disparity in the model/ data comparisons. This paper looks at the significance of aerobic biodegradation of aromatic hydrocarbons as part of the assessment of chemical vapor intrusion from soil or groundwater to indoor air. A review of relevant literature summarizing the available field data as well as various modeling approaches that include biodegradation is presented. This is followed by a simple modeling analysis that demonstrates the potential importance of biodegradation in the assessment of the soil vapor to indoor air exposure pathway. The paper concludes with brief discussions of other model considerations that are often not included in simple models but may have a significant impact on the intrusion of vapors into indoor air.     

Natural Attenuation Rate Clarifications: The True Picture is in the Details

The term “Natural Attenuation” (NA) has been defined as naturally occurring processes in soil and groundwater environments that act without human intervention to reduce the mass, toxicity, mobility, volume, or concentration of contaminants in those media. Monitored natural attenuation (MNA) protocols generally involve the collection of biogeochemical data from groundwater monitoring wells at sites. The data are correlated in time and space with the various chemicals of concern (COC's) to establish predominant biodegradation mechanisms. Modelers using the first-order decay expression typically use the rate coefficient as a calibration parameter and adjust it until the transport model results match field data. With this approach, uncertainties with a number of parameters (e.g., dispersion, sorption, biodegradation, etc.) are lumped together in a single calibration parameter. The problems associated with the lumped parameter approach are illustrated using two commonly used models, BIOSCREEN and Buscheck/Alcantar Analytical Solution, in a variety of practical examples. The natural attenuation decay rate estimated using the lumped parameter approach is distinguished from a biodegradation rate established by isolating processes and examining biodegradation lines of evidence. The half-life determined from empirical data using the lumped parameter approach is often mistakenly interchanged with a biodegradation half-life when it is an all-encompassing half-life based on the interaction of numerous processes. Isolation of the processes, as they are represented in the governing transport equation, and a rationale approach at parameter estimation to avoid the potential pitfalls of the all-inclusive “attenuation rate,” are provided. In closing, it is imperative to implement the following steps to dissern lumped process degradation rates from biodegradation half-lives: (a) be sure the rate/half-life processes are clarified as to what they encompass, (b) establish exactly how the rate/half-life was determined, (c) make certain other processes, such as dispersion, were estimated correctly, and (d) if the half-life is presented as a first-order biodegradation rate, examine the available lines of evidence to substantiate it.     

A declarative constraint-based method for analyzing discrete genetic regulatory networks

Dynamical modeling has proven useful for understanding how complex biological processes emerge from the many components and interactions composing genetic regulatory networks (GRNs). However, the development of models is hampered by large uncertainties in both the network structure and parameter values. To remedy this problem, the models are usually developed through an iterative process based on numerous simulations, confronting model predictions with experimental data and refining the model structure and/or parameter values to repair the inconsistencies. In this paper, we propose an alternative to this generate-and-test approach. We present a four-step method for the systematic construction and analysis of discrete models of GRNs by means of a declarative approach. Instead of instantiating the models as in classical modeling approaches, the biological knowledge on the network structure and its dynamics is formulated in the form of constraints. The compatibility of the network structure with the constraints is queried and in case of inconsistencies, some constraints are relaxed. Common properties of the consistent models are then analyzed by means of dedicated languages. Two such languages are introduced in the paper. Removing questionable constraints or adding interesting ones allows to further analyze the models. This approach allows to identify the best experiments to be carried out, in order to discriminate sets of consistent models and refine our knowledge on the system functioning. We test the feasibility of our approach, by applying it to the re-examination of a model describing the nutritional stress response in the bacterium Escherichia coli.     

Biodegradation of endocrine‐disrupting compounds by ligninolytic fungi: mechanisms involved in the degradation

Without any doubt, endocrine‐disrupting compounds (EDCs) represent an environmental risk for wildlife and human beings. Endocrine‐disrupting effects were found for many chemicals in products for personal use, industrial compounds and even in classical persistent organic pollutants (POPs). In order to understand the fate of EDCs in the environment, it is highly important to identify and to clarify the biodegradation mechanisms that can lead to their decomposition. Ligninolytic fungi (LF) are interesting microorganisms that are capable of participating in a variety of versatile decomposition mechanisms. The microorganisms represent a useful model group and, moreover, LF or their enzymes can be actively used for decontamination. Potential optimization of the decontamination process provides another important reason why it is necessary for understanding the mechanisms of EDC transformation. This minireview summarizes current knowledge about the LF biodegradation mechanisms of the most important micropollutants (xenoestrogens), including nonylphenols, bisphenol A and 17α‐ethinylestradiol and polychlorinated biphenyls as POPs with endocrine‐disrupting potency. Generally, LF exhibit the ability to either polymerize the target pollutants or to substantially decompose the original structure using ligninolytic enzymes and cytochrome P‐450. Moreover, most of the transformation processes are accompanied by reduction of the endocrine‐disrupting activity or ecotoxicity.     

聚乙烯醇生物降解研究进展

聚乙烯醇(PVA)是一种在纺织和化工行业中广泛使用的难降解的高分子聚合物。随着人们对纺织工业清洁生产的关注,如何在退浆工艺中就实现对PVA的生物降解、减少PVA废水的排放,并避免化学退浆过程中高温和氧化造成的棉纤维损伤,是近年来纺织生物技术领域的研究热点。由于PVA降解菌种类不多、培养周期长,PVA降解酶酶活不高、提取不容易等原因,使PVA的生化降解研究还局限在PVA降解菌的筛选、PVA降解酶的酶学性质研究等方面,PVA降解酶还未在纺织工业上得到应用。本文综述了近年来国内外在PVA降解菌筛选、PVA降解酶提取及酶学性质、PVA生化降解机理等方面的研究进展,并讨论了PVA生化降解研究中存在的问题及发展方向。     

Elimination of methane generated from landfills by biofiltration: a review

The production of biogas in landfills, its composition and the problems resulting from its generation are all reviewed. Biofiltration is a promising option for the control of emissions to atmosphere of the methane contained in biogas issued from the smaller and/or older landfills. A detailed review of the methane biofiltration literature is presented. The microorganisms, mainly the methanotrophs, involved in the methane biodegradation process, and their needs in terms of oxygen and carbon dioxide utilization, are described. Moreover, the influence of nutrients such as copper, nitrogen and phosphorus, and the process operating conditions such as temperature, pH and moisture content of the biofilter bed, are also presented. Finally, the performance of various filter beds, in terms of their elimination capacities, is presented for laboratory scale biofilters and landfill covers.     

Modeling cancer: integration of "omics" information in dynamic systems

The last 10 years have seen the rise of many technologies that produce an unprecedented amount of genome-scale data from many organisms. Although the research community has been successful in exploring these data, many challenges still persist. One of them is the effective integration of such data sets directly into approaches based on mathematical modeling of biological systems. Applications in cancer are a good example. The bridge between information and modeling in cancer can be achieved by two major types of complementary strategies. First, there is a bottom-up approach, in which data generates information about structure and relationship between components of a given system. In addition, there is a top-down approach, where cybernetic and systems-theoretical knowledge are used to create models that describe mechanisms and dynamics of the system. These approaches can also be linked to yield multi-scale models combining detailed mechanism and wide biological scope. Here we give an overall picture of this field and discuss possible strategies to approach the major challenges ahead.     

Covariate selection strategies for causal inference: Classification and comparison

When causal effects are to be estimated from observational data, we have to adjust for confounding. A central aim of covariate selection for causal inference is therefore to determine a set that is sufficient for confounding adjustment, but other aims such as efficiency or robustness can be important as well. In this paper, we review six general approaches to covariate selection that differ in the targeted type of adjustment set. We discuss and illustrate their advantages and disadvantages using causal diagrams. Moreover, the approaches and different ways of implementing them are compared empirically in an extensive simulation study. We conclude that there are considerable differences between the approaches but none of them is uniformly best, with performance depending on the chosen adjustment method as well as the true confounding structure. Any prior structural knowledge on the causal relations is helpful to choose the most appropriate method.     

Melanosome degradation: fact or fiction

Our mini review summarizes what is known about the (bio)degradation of melanosomes. Unlike melanosome biogenesis where our knowledge enables us to explain it in molecular terms posing many interesting questions on the relation between lysosomes and melanosomes, melanosome degradation has remained 'terra incognita'. Observations at optical and ultrastructural levels describe the disintegration of melanosomes in the lysosomal compartment (in auto- and heterophagosomes). Histochemical studies suggest the participation of acid hydrolases in the process of melanosome degradation. Biochemical data confirm the ability of lysosomal hydrolases to degrade melanosome constituents except the melanin moiety. The similarity of melanin structure to that of polycyclic aromatic hydrocarbons suggests that melanin should be sensitive mainly, if not exclusively, to oxidative breakdown. In vitro melanin can indeed be decomposed by an oxidative attack and the degradation is accompanied by fluorescence and decreasing absorbance. From enzymes engaged in the biotransformation of polycyclic hydrocarbons only phagosomal NADPH oxidase meets the criteria (particularly as for compartmental and catalytic properties) to be involved in melanin biodegradation. The in vivo biodegradation of melanin has so far been clearly demonstrated in Aspergillus and fungi melanins.     

Metaproteome analysis to determine the metabolically active part of a thermophilic microbial community producing biogas from agricultural biomass

Complex consortia of microorganisms are responsible for biogas production. A lot of information about the taxonomic structure and enzymatic potential of such communities has been collected by a variety of gene-based approaches, yet little is known about which of all the assumable metabolic pathways are active throughout the process of biogas formation. To tackle this problem, we established a protocol for the metaproteomic analysis of samples taken from biogas reactors fed with agricultural biomass. In contrast to previous studies where an anaerobic digester was fed with synthetic wastewater, the complex matrix in this study required the extraction of proteins with liquid phenol and the application of paper bridge loading for 2-dimensional gel electrophoresis. Proteins were subjected to nanoHPLC (high-performance liquid chromatography) coupled to tandem mass spectrometry for characterization. Several housekeeping proteins as well as methanogenesis-related enzymes were identified by a MASCOT search and de novo sequencing, which proved the feasibility of our approach. The establishment of such an approach is the basis for further metaproteomic studies of biogas-producing communities. In particular, the apparent status of metabolic activities within the communities can be monitored. The knowledge collected from such experiments could lead to further improvements of biogas production.