Use of the University of Minnesota Biocatalysis/Biodegradation Database for study of microbial degradation

Microorganisms are ubiquitous on earth and have diverse metabolic transformative capabilities important for environmental biodegradation of chemicals that helps maintain ecosystem and human health. Microbial biodegradative metabolism is the main focus of the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD). UM-BBD data has also been used to develop a computational metabolic pathway prediction system that can be applied to chemicals for which biodegradation data is currently lacking. The UM-Pathway Prediction System (UM-PPS) relies on metabolic rules that are based on organic functional groups and predicts plausible biodegradative metabolism. The predictions are useful to environmental chemists that look for metabolic intermediates, for regulators looking for potential toxic products, for microbiologists seeking to understand microbial biodegradation, and others with a wide-range of interests

The University of Minnesota pathway prediction system: predicting metabolic logic

The University of Minnesota pathway prediction system (UM-PPS, http://umbbd.msi.umn.edu/predict/) recognizes functional groups in organic compounds that are potential targets of microbial catabolic reactions, and predicts transformations of these groups based on biotransformation rules. Rules are based on the University of Minnesota biocatalysis/biodegradation database (http://umbbd.msi.umn.edu/) and the scientific literature. As rules were added to the UM-PPS, more of them were triggered at each prediction step. The resulting combinatorial explosion is being addressed in four ways. Biodegradation experts give each rule an aerobic likelihood value of Very Likely, Likely, Neutral, Unlikely or Very Unlikely. Users now can choose whether they view all, or only the more aerobically likely, predicted transformations. Relative reasoning, allowing triggering of some rules to inhibit triggering of others, was implemented. Rules were initially assigned to individual chemical reactions. In selected cases, these have been replaced by super rules, which include two or more contiguous reactions that form a small pathway of their own. Rules are continually modified to improve the prediction accuracy; increasing rule stringency can improve predictions and reduce extraneous choices. The UM-PPS is freely available to all without registration. Its value to the scientific community, for academic, industrial and government use, is good and will only increas

Field-scale remediation of atrazine-contaminated soil using recombinant Escherichia coli expressing atrazine chlorohydrolase

We performed the first field-scale atrazine remediation study in the United States using chemically killed, recombinant organisms. This field study compared biostimulation methods for enhancing atrazine degradation with a novel bioaugmentation protocol using a killed and stabilized whole-cell suspension of recombinant Escherichia coli engineered to overproduce atrazine chlorohyrolase, AtzA. AtzA dechlorinates atrazine, producing non-toxic and non-phytotoxic hydroxyatrazine. Soil contaminated by an accidental spill of atrazine (up to 29 000 p.p.m.) supported significant populations of indigenous microorganisms capable of atrazine catabolism. Laboratory experiments indicated that supplementing soil with carbon inhibited atrazine biodegradation, but inorganic phosphate stimulated atrazine biodegradation. A subsequent field-scale study consisting of nine (0.75m3) treatment plots was designed to test four treatment protocols in triplicate. Control plots contained moistened soil; biostimulation plots received 300 p.p.m. phosphate; bioaugmentation plots received 0.5% (w/w) killed, recombinant E. coli cells encapsulating AtzA; and combination plots received phosphate plus the enzyme-containing cells. After 8 weeks, atrazine levels declined 52% in plots containing killed recombinant E. coli cells, and 77% in combination plots. In contrast, atrazine levels in control and biostimulation plots did not decline significantly. These data indicate that genetically engineered bacteria overexpressing catabolic genes significantly increased degradation in this soil heavily contaminated with atrazine

The University of Minnesota pathway prediction system: predicting metabolic logic

The University of Minnesota pathway prediction system (UM-PPS, http://umbbd.msi.umn.edu/predict/) recognizes functional groups in organic compounds that are potential targets of microbial catabolic reactions, and predicts transformations of these groups based on biotransformation rules. Rules are based on the University of Minnesota biocatalysis/biodegradation database (http://umbbd.msi.umn.edu/) and the scientific literature. As rules were added to the UM-PPS, more of them were triggered at each prediction step. The resulting combinatorial explosion is being addressed in four ways. Biodegradation experts give each rule an aerobic likelihood value of Very Likely, Likely, Neutral, Unlikely or Very Unlikely. Users now can choose whether they view all, or only the more aerobically likely, predicted transformations. Relative reasoning, allowing triggering of some rules to inhibit triggering of others, was implemented. Rules were initially assigned to individual chemical reactions. In selected cases, these have been replaced by super rules, which include two or more contiguous reactions that form a small pathway of their own. Rules are continually modified to improve the prediction accuracy; increasing rule stringency can improve predictions and reduce extraneous choices. The UM-PPS is freely available to all without registration. Its value to the scientific community, for academic, industrial and government use, is good and will only increase

Design and Construction of Deinococcus Radiodurans for Biodegradation of Organic Toxins at Radioactive DOE Waste Sites

Seventy million cubic meters of ground and three trillion liters of groundwater have been contaminated by leaking radioactive waste generated in the United States during the Cold War. A cleanup technology is being developed based on the extremely radiation resistant bacterium Deinococcus radiodurans that is being engineered to express bioremediating functions. Research aimed at developing D. radiodurans for organic toxin degradation in highly radioactive waste sites containing radionuclides, heavy metals, and toxic organic compounds was started by this group.Work funded by the existing grant has already contributed to eleven papers on the fundamental biology of D. radiodurans and its design for bioremediation of highly radioactive waste environment

Design and Construction of Deinococcus radiodurans for Biodegradation of Organic Toxins at Radioactive DOE Waste Sites

Immense volumes of radioactive waste, generated from nuclear weapons production during the Cold War, were disposed directly to the ground. The current expense of remediating these polluted sites is driving the development of alternative remediation strategies using microorganisms. The bacterium Deinococcus radiodurans is the most radiation resistant organism known and can grow in highly irradiating (>60 Gray/h) environments (1). Numerous microorganisms (e.g., Pseudomonas sp.) have been described, and studied in detail, for their ability to transform and degrade a variety of organic pollutants (e.g., toluene), present at many radioactive DOE waste sites. Detoxification of the organic toxins at these sites is an important goal in remediating or stabilizing contaminated sites as well as preventing their further dissemination. The aim of this project is to engineer strains of D. radiodurans that are capable of degrading organic/aromatic hydrocarbons present in radioactive mixed waste sites--sites that contain mixtures of toxic organic compounds, radionuclides and heavy metals. Conventional bioremediating organisms are unable to survive at many of these sites because of their sensitivity to radiation. Generally, microorganisms are sensitive to the damaging effects of ionizing radiation, and most of the bacteria currently being studied as candidates for bioremediation are no exception. For example, Pseudomonas sp. is very sensitive to radiation (more sensitive than E. coli) and is not suited to remediate radioactive wastes. Therefore, radiation resistant microorganisms that can remediate toxic organic compounds need to be found in nature or engineered in the laboratory to address this problem

Methodological Advances to Study Contaminant Biotransformation: New Prospects for Understanding and Reducing Environmental Persistence?

Complex microbial communities in environmental systems play a key role in the detoxification of chemical contaminants by transforming them into less active metabolites or by complete mineralization. Biotransformation, i.e., transformation by microbes, is well understood for a number of priority pollutants, but a similar level of understanding is lacking for many emerging contaminants encountered at low concentrations and in complex mixtures across natural and engineered systems. Any advanced approaches aiming to reduce environmental exposure to such contaminants (e.g., novel engineered biological water treatment systems, design of readily degradable chemicals, or improved regulatory assessment strategies to determine contaminant persistence a priori) will depend on understanding the causal links among contaminant removal, the key driving agents of biotransformation at low concentrations (i.e., relevant microbes and their metabolic activities), and how their presence and activity depend on environmental conditions. In this Perspective, we present the current understanding and recent methodological advances that can help to identify such links, even in complex environmental microbiomes and for contaminants present at low concentrations in complex chemical mixtures. We discuss the ensuing insights into contaminant biotransformation across varying environments and conditions and ask how much closer we have come to designing improved approaches to reducing environmental exposure to contaminants

Fragmentative and stereochemical isomerization probes for homolytic carbon to phosphorus bond scission catalyzed by bacterial carbon-phosphorus lyase

Three bacterial strains, Agrobacterium radiobacter, Klebsiella oxytoca, and Kluyvera ascorbata, isolated by enrichment culture for carbon to phosphorus bond cleavage ability, were analyzed for the mode of C---P bond fission. The cleavage of alkyl phosphonic acids to alkanes and inorganic phosphates proceeded both aerobically and anaerobically, and growth on trideuteromethylphosphonic acid yielded trideuteromethane as product. These data indicate that functionalization of the organic moiety does not precede carbon to phosphorus bond cleavage. As probes for radical intermediates, cyclopropylmethylphosphonic acid and cis-1,2-dideutero-1-propenylphosphonic acid were used in growth experiments and the gaseous hydrocarbon products were examined. With the cyclopropylmethylphosphonic acid probe, all three bacteria produced methylcyclopropane, but only K. oxytoca and K. ascorbata also generated the acyclic olefin 1-butene, and then only in very low quantity (0.6 and 0.3% versus methylcyclopropane, respectively). With the propenylphosphonic acid probe, cis-1,2-dideuteropropene was formed with greater than 98% retention of configuration with each bacterial strain. Only for K. oxytoca was the alternate product, in this case trans-1,2-dideuteropropene, clearly detected at 1.5%. Thus, C---P bond fission may yield radical intermediates that are trapped efficiently at the enzyme active site or, alternatively, homolysis of the C---P bond may occur as a minor reaction pathway.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26489/1/0000025.pd

The University of Minnesota Biocatalysis/Biodegradation Database: improving public access

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.msi.umn.edu/) began in 1995 and now contains information on almost 1200 compounds, over 800 enzymes, almost 1300 reactions and almost 500 microorganism entries. Besides these data, it includes a Biochemical Periodic Table (UM-BPT) and a rule-based Pathway Prediction System (UM-PPS) (http://umbbd.msi.umn.edu/predict/) that predicts plausible pathways for microbial degradation of organic compounds. Currently, the UM-PPS contains 260 biotransformation rules derived from reactions found in the UM-BBD and scientific literature. Public access to UM-BBD data is increasing. UM-BBD compound data are now contributed to PubChem and ChemSpider, the public chemical databases. A new mirror website of the UM-BBD, UM-BPT and UM-PPS is being developed at ETH Zürich to improve speed and reliability of online access from anywhere in the world