Julian L. Fortney

Metagenome, metatranscriptome and single-cell sequencing reveal microbial response to Deepwater Horizon oil spill.

The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility, chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.

Microbial gene functions enriched in the Deepwater Horizon deep-sea oil plume

The Deepwater Horizon oil spill in the Gulf of Mexico is the deepest and largest offshore spill in the United State history and its impacts on marine ecosystems are largely unknown. Here, we showed that the microbial community functional composition and structure were dramatically altered in a deep-sea oil plume resulting from the spill. A variety of metabolic genes involved in both aerobic and anaerobic hydrocarbon degradation were highly enriched in the plume compared with outside the plume, indicating a great potential for intrinsic bioremediation or natural attenuation in the deep sea. Various other microbial functional genes that are relevant to carbon, nitrogen, phosphorus, sulfur and iron cycling, metal resistance and bacteriophage replication were also enriched in the plume. Together, these results suggest that the indigenous marine microbial communities could have a significant role in biodegradation of oil spills in deep-sea environments.

Deep-sea bacteria enriched by oil and dispersant from the Deepwater Horizon spill

The Deepwater Horizon oil spill resulted in a massive influx of hydrocarbons into the Gulf of Mexico (the Gulf). To better understand the fate of the oil, we enriched and isolated indigenous hydrocarbon-degrading bacteria from deep, uncontaminated waters from the Gulf with oil (Macondo MC252) and dispersant used during the spill (COREXIT 9500). During 20 days of incubation at 5°C, CO(2) evolution, hydrocarbon concentrations and the microbial community composition were determined. Approximately 60% to 25% of the dissolved oil with or without COREXIT, respectively, was degraded, in addition to some hydrocarbons in the COREXIT. FeCl(2) addition initially increased respiration rates, but not the total amount of hydrocarbons degraded. 16S rRNA gene sequencing revealed a succession in the microbial community over time, with an increase in abundance of Colwellia and Oceanospirillales during the incubations. Flocs formed during incubations with oil and/or COREXIT in the absence of FeCl(2) . Synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectromicroscopy revealed that the flocs were comprised of oil, carbohydrates and biomass. Colwellia were the dominant bacteria in the flocs. Colwellia sp. strain RC25 was isolated from one of the enrichments and confirmed to rapidly degrade high amounts (approximately 75%) of the MC252 oil at 5°C. Together these data highlight several features that provide Colwellia with the capacity to degrade oil in cold, deep marine habitats, including aggregation together with oil droplets into flocs and hydrocarbon degradation ability.

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using 14C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of 14C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)’s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.

Dynamic cyanobacterial response to hydration and dehydration in a desert biological soil crust

Biological soil crusts (BSCs) cover extensive portions of the earth’s deserts. In order to survive desiccation cycles and utilize short periods of activity during infrequent precipitation, crust microorganisms must rely on the unique capabilities of vegetative cells to enter a dormant state and be poised for rapid resuscitation upon wetting. To elucidate the key events involved in the exit from dormancy, we performed a wetting experiment of a BSC and followed the response of the dominant cyanobacterium, Microcoleus vaginatus, in situ using a whole-genome transcriptional time course that included two diel cycles. Immediate, but transient, induction of DNA repair and regulatory genes signaled the hydration event. Recovery of photosynthesis occurred within 1 h, accompanied by upregulation of anabolic pathways. Onset of desiccation was characterized by the induction of genes for oxidative and photo-oxidative stress responses, osmotic stress response and the synthesis of C and N storage polymers. Early expression of genes for the production of exopolysaccharides, additional storage molecules and genes for membrane unsaturation occurred before drying and hints at preparedness for desiccation. We also observed signatures of preparation for future precipitation, notably the expression of genes for anaplerotic reactions in drying crusts, and the stable maintenance of mRNA through dormancy. These data shed light on possible synchronization between this cyanobacterium and its environment, and provides key mechanistic insights into its metabolism in situ that may be used to predict its response to climate, and or, land-use driven perturbations.

Characterization of trapped lignin-degrading microbes in tropical forest soil

Lignin is often the most difficult portion of plant biomass to degrade, with fungi generally thought to dominate during late stage decomposition. Lignin in feedstock plant material represents a barrier to more efficient plant biomass conversion and can also hinder enzymatic access to cellulose, which is critical for biofuels production. Tropical rain forest soils in Puerto Rico are characterized by frequent anoxic conditions and fluctuating redox, suggesting the presence of lignin-degrading organisms and mechanisms that are different from known fungal decomposers and oxygen-dependent enzyme activities. We explored microbial lignin-degraders by burying bio-traps containing lignin-amended and unamended biosep beads in the soil for 1, 4, 13 and 30 weeks. At each time point, phenol oxidase and peroxidase enzyme activity was found to be elevated in the lignin-amended versus the unamended beads, while cellulolytic enzyme activities were significantly depressed in lignin-amended beads. Quantitative PCR of bacterial communities showed more bacterial colonization in the lignin-amended compared to the unamended beads after one and four weeks, suggesting that the lignin supported increased bacterial abundance. The microbial community was analyzed by small subunit 16S ribosomal RNA genes using microarray (PhyloChip) and by high-throughput amplicon pyrosequencing based on universal primers targeting bacterial, archaeal, and eukaryotic communities. Community trends were significantly affected by time and the presence of lignin on the beads. Lignin-amended beads have higher relative abundances of representatives from the phyla Actinobacteria, Firmicutes, Acidobacteria and Proteobacteria compared to unamended beads. This study suggests that in low and fluctuating redox soils, bacteria could play a role in anaerobic lignin decomposition.

Strategies for Enhancing the Effectiveness of Metagenomic-based Enzyme Discovery in Lignocellulolytic Microbial Communities

Producing cellulosic biofuels from plant material has recently emerged as a key US Department of Energy goal. For this technology to be commercially viable on a large scale, it is critical to make production cost efficient by streamlining both the deconstruction of lignocellulosic biomass and fuel production. Many natural ecosystems efficiently degrade lignocellulosic biomass and harbor enzymes that, when identified, could be used to increase the efficiency of commercial biomass deconstruction. However, ecosystems most likely to yield relevant enzymes, such as tropical rain forest soil in Puerto Rico, are often too complex for enzyme discovery using current metagenomic sequencing technologies. One potential strategy to overcome this problem is to selectively cultivate the microbial communities from these complex ecosystems on biomass under defined conditions, generating less complex biomass-degrading microbial populations. To test this premise, we cultivated microbes from Puerto Rican soil or green waste compost under precisely defined conditions in the presence dried ground switchgrass (Panicum virgatum L.) or lignin, respectively, as the sole carbon source. Phylogenetic profiling of the two feedstock-adapted communities using SSU rRNA gene amplicon pyrosequencing or phylogenetic microarray analysis revealed that the adapted communities were significantly simplified compared to the natural communities from which they were derived. Several members of the lignin-adapted and switchgrass-adapted consortia are related to organisms previously characterized as biomass degraders, while others were from less well-characterized phyla. The decrease in complexity of these communities make them good candidates for metagenomic sequencing and will likely enable the reconstruction of a greater number of full-length genes, leading to the discovery of novel lignocellulose-degrading enzymes adapted to feedstocks and conditions of interest.

Complete genome sequence of “Enterobacter lignolyticus” SCF1

In an effort to discover anaerobic bacteria capable of lignin degradation, we isolated “Enterobacter lignolyticus” SCF1 on minimal media with alkali lignin as the sole source of carbon. This organism was isolated anaerobically from tropical forest soils collected from the Short Cloud Forest site in the El Yunque National Forest in Puerto Rico, USA, part of the Luquillo Long-Term Ecological Research Station. At this site, the soils experience strong fluctuations in redox potential and are net methane producers. Because of its ability to grow on lignin anaerobically, we sequenced the genome. The genome of “E. lignolyticus” SCF1 is 4.81 Mbp with no detected plasmids, and includes a relatively small arsenal of lignocellulolytic carbohydrate active enzymes. Lignin degradation was observed in culture, and the genome revealed two putative laccases, a putative peroxidase, and a complete 4-hydroxyphenylacetate degradation pathway encoded in a single gene cluster.

PCR Amplification-Independent Methods for Detection of Microbial Communities by the High-Density Microarray PhyloChip

ABSTRACT Environmental microbial community analysis typically involves amplification by PCR, despite well-documented biases. We have developed two methods of PCR-independent microbial community analysis using the high-density microarray PhyloChip: direct hybridization of 16S rRNA (dirRNA) or rRNA converted to double-stranded cDNA (dscDNA). We compared dirRNA and dscDNA communities to PCR-amplified DNA communities using a mock community of eight taxa, as well as experiments derived from three environmental sample types: chromium-contaminated aquifer groundwater, tropical forest soil, and secondary sewage in seawater. Community profiles by both direct hybridization methods showed differences that were expected based on accompanying data but that were missing in PCR-amplified communities. Taxon richness decreased in RNA compared to that in DNA communities, suggesting a subset of 20% in soil and 60% in groundwater that is active; secondary sewage showed no difference between active and inactive populations. Direct hybridization of dscDNA and RNA is thus a viable alternative to PCR-amplified microbial community analysis, providing identification of the active populations within microbial communities that attenuate pollutants, drive global biogeochemical cycles, or proliferate disease states.

Natural Bacterial Communities Serve as Quantitative Geochemical Biosensors

ABSTRACT Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive. IMPORTANCE Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts. Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.