Metabolic Biomarkers for Monitoring in Situ Anaerobic Hydrocarbon Degradation

During the past 15 years researchers have made great strides in understanding the metabolism of hydrocarbons by anaerobic bacteria. Organisms capable of utilizing benzene, toluene, ethylbenzene, xylenes, alkanes, and polycyclic aromatic hydrocarbons have been isolated and described. In addition, the mechanisms of degradation for these compounds have been elucidated. This basic research has led to the development of methods for detecting in situ biodegradation of petroleum-related pollutants in anoxic groundwater. Knowledge of the metabolic pathways used by anaerobic bacteria to break down hydrocarbons has allowed us to identify unique intermediate compounds that can be used as biomarkers for in situ activity. One of these unique intermediates is 2-methylbenzylsuccinate, the product of fumarate addition to o-xylene by the enzyme responsible for toluene utilization. We have carried out laboratory studies to show that this compound can be used as a reliable indicator of anaerobic toluene degradation. Field studies confirmed that the biomarker is detectable in field samples and its distribution corresponds to areas where active biodegradation is predicted. For naphthalene, three biomarkers were identified [2-naphthoic acid (2-NA), tetrahydro-2-NA, and hexahydro-2-NA] that can be used in the field to identify areas of active in situ degradation

Long-term TNT and DNT contamination: 1-D modeling of natural attenuation in the vadose zone: case study, Portugal

The vadose zone of a trinitrotoluene (TNT) and dinitrotoluene (DNT) contaminated site was investigated to assess the mobility of those explosives under natural conditions. Located in the left margin of the River Tejo Basin, Portugal, the site is located on unconsolidated sediments. Wastewaters associated with the 50-year explosives production were disposed in excavated ponds, from where water would infiltrate and pollute the unsaturated and saturated parts of the local aquifers. Two boreholes were drilled to 9 m depth in such a former waste pond to investigate the contaminant's fate in the vadose zone. Sediment samples were taken every 1-2 m for analysis of the polynitroaromatics (p-NACs) and organic volatile compounds, pH, organic carbon content, cation exchange capacity and grain size analysis. The main contaminant was TNT representing >70 % of the total p-NACs concentration that peaked approximately 7 mg/kg in one borehole, even if the median in both boreholes was of similar to 1 mg/kg. DNT was 4-30 % of the total p-NACs and nitrotoluene (NT), up to 5 %. No other (volatile) organic compound was detected. The predominance of TNT as the main contaminant implies that any natural mass reduction has been inefficient to clean the site. Several 1-D model simulations of p-NACs cleaning of the vadose zone under natural conditions indicated that the most probable scenario of combined advection and partitioning will only remove TNT after 10's of years, whereas DNT and NT will hardly be removed. Such low concentrations and long times for the p-NACs removal, suggest that by now those compounds have been washed-out to a level below standard limits

Metagenomic Analysis of the Bioremediation of Diesel-Contaminated Canadian High Arctic Soils

As human activity in the Arctic increases, so does the risk of hydrocarbon pollution events. On site bioremediation of contaminated soil is the only feasible clean up solution in these remote areas, but degradation rates vary widely between bioremediation treatments. Most previous studies have focused on the feasibility of on site clean-up and very little attention has been given to the microbial and functional communities involved and their ecology. Here, we ask the question: which microorganisms and functional genes are abundant and active during hydrocarbon degradation at cold temperature? To answer this question, we sequenced the soil metagenome of an ongoing bioremediation project in Alert, Canada through a time course. We also used reverse-transcriptase real-time PCR (RT-qPCR) to quantify the expression of several hydrocarbon-degrading genes. Pseudomonas species appeared as the most abundant organisms in Alert soils right after contamination with diesel and excavation (t = 0) and one month after the start of the bioremediation treatment (t = 1m), when degradation rates were at their highest, but decreased after one year (t = 1y), when residual soil hydrocarbons were almost depleted. This trend was also reflected in hydrocarbon degrading genes, which were mainly affiliated with Gammaproteobacteria at t = 0 and t = 1m and with Alphaproteobacteria and Actinobacteria at t = 1y. RT-qPCR assays confirmed that Pseudomonas and Rhodococcus species actively expressed hydrocarbon degradation genes in Arctic biopile soils. Taken together, these results indicated that biopile treatment leads to major shifts in soil microbial communities, favoring aerobic bacteria that can degrade hydrocarbons

ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing

Influence of Uranium on Bacterial Communities: A Comparison of Natural Uranium-Rich Soils with Controls

This study investigated the influence of uranium on the indigenous bacterial community structure in natural soils with high uranium content. Radioactive soil samples exhibiting 0.26% - 25.5% U in mass were analyzed and compared with nearby control soils containing trace uranium. EXAFS and XRD analyses of soils revealed the presence of U(VI) and uranium-phosphate mineral phases, identified as sabugalite and meta-autunite. A comparative analysis of bacterial community fingerprints using denaturing gradient gel electrophoresis (DGGE) revealed the presence of a complex population in both control and uranium-rich samples. However, bacterial communities inhabiting uraniferous soils exhibited specific fingerprints that were remarkably stable over time, in contrast to populations from nearby control samples. Representatives of Acidobacteria, Proteobacteria, and seven others phyla were detected in DGGE bands specific to uraniferous samples. In particular, sequences related to iron-reducing bacteria such as Geobacter and Geothrix were identified concomitantly with iron-oxidizing species such as Gallionella and Sideroxydans. All together, our results demonstrate that uranium exerts a permanent high pressure on soil bacterial communities and suggest the existence of a uranium redox cycle mediated by bacteria in the soil

Discovery of enzymes for toluene synthesis from anoxic microbial communities

Microbial toluene biosynthesis was reported in anoxic lake sediments more than three decades ago, but the enzyme catalyzing this biochemically challenging reaction has never been identified. Here we report the toluene-producing enzyme PhdB, a glycyl radical enzyme of bacterial origin that catalyzes phenylacetate decarboxylation, and its cognate activating enzyme PhdA, a radical S-adenosylmethionine enzyme, discovered in two distinct anoxic microbial communities that produce toluene. The unconventional process of enzyme discovery from a complex microbial community (>300,000 genes), rather than from a microbial isolate, involved metagenomics- and metaproteomics-enabled biochemistry, as well as in vitro confirmation of activity with recombinant enzymes. This work expands the known catalytic range of glycyl radical enzymes (only seven reaction types had been characterized previously) and aromatic-hydrocarbon-producing enzymes, and will enable first-time biochemical synthesis of an aromatic fuel hydrocarbon from renewable resources, such as lignocellulosic biomass, rather than from petroleum

Genomic Analysis of the Hydrocarbon-Producing, Cellulolytic, Endophytic Fungus Ascocoryne sarcoides

The microbial conversion of solid cellulosic biomass to liquid biofuels may provide a renewable energy source for transportation fuels. Endophytes represent a promising group of organisms, as they are a mostly untapped reservoir of metabolic diversity. They are often able to degrade cellulose, and they can produce an extraordinary diversity of metabolites. The filamentous fungal endophyte Ascocoryne sarcoides was shown to produce potential-biofuel metabolites when grown on a cellulose-based medium; however, the genetic pathways needed for this production are unknown and the lack of genetic tools makes traditional reverse genetics difficult. We present the genomic characterization of A. sarcoides and use transcriptomic and metabolomic data to describe the genes involved in cellulose degradation and to provide hypotheses for the biofuel production pathways. In total, almost 80 biosynthetic clusters were identified, including several previously found only in plants. Additionally, many transcriptionally active regions outside of genes showed condition-specific expression, offering more evidence for the role of long non-coding RNA in gene regulation. This is one of the highest quality fungal genomes and, to our knowledge, the only thoroughly annotated and transcriptionally profiled fungal endophyte genome currently available. The analyses and datasets contribute to the study of cellulose degradation and biofuel production and provide the genomic foundation for the study of a model endophyte system

Design Constraints on a Synthetic Metabolism

A metabolism is a complex network of chemical reactions that converts sources of energy and chemical elements into biomass and other molecules. To design a metabolism from scratch and to implement it in a synthetic genome is almost within technological reach. Ideally, a synthetic metabolism should be able to synthesize a desired spectrum of molecules at a high rate, from multiple different nutrients, while using few chemical reactions, and producing little or no waste. Not all of these properties are achievable simultaneously. We here use a recently developed technique to create random metabolic networks with pre-specified properties to quantify trade-offs between these and other properties. We find that for every additional molecule to be synthesized a network needs on average three additional reactions. For every additional carbon source to be utilized, it needs on average two additional reactions. Networks able to synthesize 20 biomass molecules from each of 20 alternative sole carbon sources need to have at least 260 reactions. This number increases to 518 reactions for networks that can synthesize more than 60 molecules from each of 80 carbon sources. The maximally achievable rate of biosynthesis decreases by approximately 5 percent for every additional molecule to be synthesized. Biochemically related molecules can be synthesized at higher rates, because their synthesis produces less waste. Overall, the variables we study can explain 87 percent of variation in network size and 84 percent of the variation in synthesis rate. The constraints we identify prescribe broad boundary conditions that can help to guide synthetic metabolism design

A genomic catalog of Earth’s microbiomes

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes