Jung Soh

Metagenomics of Hydrocarbon Resource Environments Indicates Aerobic Taxa and Genes to be Unexpectedly Common

Oil in subsurface reservoirs is biodegraded by resident microbial communities. Water-mediated, anaerobic conversion of hydrocarbons to methane and CO2, catalyzed by syntrophic bacteria and methanogenic archaea, is thought to be one of the dominant processes. We compared 160 microbial community compositions in ten hydrocarbon resource environments (HREs) and sequenced twelve metagenomes to characterize their metabolic potential. Although anaerobic communities were common, cores from oil sands and coal beds had unexpectedly high proportions of aerobic hydrocarbon-degrading bacteria. Likewise, most metagenomes had high proportions of genes for enzymes involved in aerobic hydrocarbon metabolism. Hence, although HREs may have been strictly anaerobic and typically methanogenic for much of their history, this may not hold today for coal beds and for the Alberta oil sands, one of the largest remaining oil reservoirs in the world. This finding may influence strategies to recover energy or chemicals from these HREs by in situ microbial processes.

Exploring functional contexts of symbiotic sustain within lichen-associated bacteria by comparative omics

Symbioses represent a frequent and successful lifestyle on earth and lichens are one of their classic examples. Recently, bacterial communities were identified as stable, specific and structurally integrated partners of the lichen symbiosis, but their role has remained largely elusive in comparison to the well-known functions of the fungal and algal partners. We have explored the metabolic potentials of the microbiome using the lung lichen Lobaria pulmonaria as the model. Metagenomic and proteomic data were comparatively assessed and visualized by Voronoi treemaps. The study was complemented with molecular, microscopic and physiological assays. We have found that more than 800 bacterial species have the ability to contribute multiple aspects to the symbiotic system, including essential functions such as (i) nutrient supply, especially nitrogen, phosphorous and sulfur, (ii) resistance against biotic stress factors (that is, pathogen defense), (iii) resistance against abiotic factors, (iv) support of photosynthesis by provision of vitamin B12, (v) fungal and algal growth support by provision of hormones, (vi) detoxification of metabolites, and (vii) degradation of older parts of the lichen thallus. Our findings showed the potential of lichen-associated bacteria to interact with the fungal as well as algal partner to support health, growth and fitness of their hosts. We developed a model of the symbiosis depicting the functional multi-player network of the participants, and argue that the strategy of functional diversification in lichens supports the longevity and persistence of lichens under extreme and changing ecological conditions.

Phoenix 2: a locally installable large-scale 16S rRNA gene sequence analysis pipeline with Web interface.

We have developed Phoenix 2, a ribosomal RNA gene sequence analysis pipeline, which can be used to process large-scale datasets consisting of more than one hundred environmental samples and containing more than one million reads collectively. Rapid handling of large datasets is made possible by the removal of redundant sequences, pre-partitioning of sequences, parallelized clustering per partition, and subsequent merging of clusters. To build the pipeline, we have used a combination of open-source software tools and custom-developed Perl scripts. For our project we utilize hardware-accelerated searches, but it is possible to reconfigure the analysis pipeline for use with generic computing infrastructure only, with a considerable reduction in speed. The set of analysis results produced by Phoenix 2 is comprehensive, including taxonomic annotations using multiple methods, alpha diversity indices, beta diversity measurements, and a number of visualizations. To date, the pipeline has been used to analyze more than 1500 environmental samples from a wide variety of microbial communities, which are part of our Hydrocarbon Metagenomics Project (http://www.hydrocarbonmetagenomics.com). The software package can be installed as a local software suite with a Web interface. Phoenix 2 is freely available from http://sourceforge.net/projects/phoenix2.

Methanogenic biodegradation of two-ringed polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAH) are widespread in methane-rich subsurface environments, such as oil reservoirs and fuel-contaminated aquifers; however, little is known about the biodegradation of these compounds under methanogenic conditions. To assess the metabolism of PAH in the absence of electron acceptors, a crude oil-degrading methanogenic enrichment culture was tested for the ability to biodegrade naphthalene, 1-methylnaphthalene (1-MN), 2-methylnaphthalene (2-MN), and 2, 6-dimethylnaphthalene (2, 6-diMN). When methane was measured as an indicator of metabolism, nearly 400 μmol of methane was produced in the 2-MN- and 2, 6-diMN-amended cultures relative to substrate-unamended controls, which is close to the amount of methane stoichiometrically predicted based on the amount of substrate added (51-56 μmol). In contrast, no substantial methane was produced in the naphthalene- and 1-MN-amended enrichments. In time course experiments, metabolite analysis of enrichments containing 2-MN and 2, 6-diMN revealed the formation of 2-naphthoic acid and 6-methyl-2-naphthoic acid, respectively. Microbial community analysis by 454 pyrosequencing revealed that these PAH-utilizing enrichments were dominated by archaeal members most closely affiliated with Methanosaeta and Methanoculleus species and bacterial members most closely related to the Clostridiaceae, suggesting that these organisms play an important role in the methanogenic metabolism of the substituted naphthalenes in these cultures.

Rhizobiales as functional and endosymbiontic members in the lichen symbiosis of Lobaria pulmonaria L.

Rhizobiales (Alphaproteobacteria) are well-known beneficial partners in plant-microbe interactions. Less is known about the occurrence and function of Rhizobiales in the lichen symbiosis, although it has previously been shown that Alphaproteobacteria are the dominating group in growing lichen thalli. We have analyzed the taxonomic structure and assigned functions to Rhizobiales within a metagenomic dataset of the lung lichen Lobaria pulmonaria L. One third (32.2%) of the overall bacteria belong to the Rhizobiales, in particular to the families Methylobacteriaceae, Bradyrhizobiaceae, and Rhizobiaceae. About 20% of our metagenomic assignments could not be placed in any of the Rhizobiales lineages, which indicates a yet undescribed bacterial diversity. SEED-based functional analysis focused on Rhizobiales and revealed functions supporting the symbiosis, including auxin and vitamin production, nitrogen fixation and stress protection. We also have used a specifically developed probe to localize Rhizobiales by confocal laser scanning microscopy after fluorescence in situ hybridization (FISH-CLSM). Bacteria preferentially colonized fungal surfaces, but there is clear evidence that members of the Rhizobiales are able to intrude at varying depths into the interhyphal gelatinous matrix of the upper lichen cortical layer and that at least occasionally some bacteria also are capable to colonize the interior of the fungal hyphae. Interestingly, the gradual development of an endosymbiotic bacterial life was found for lichen- as well as for fungal- and plant-associated bacteria. The new tools to study Rhizobiales, FISH microscopy and comparative metagenomics, suggest a similar beneficial role for lichens than for plants and will help to better understand the Rhizobiales-host interaction and their biotechnological potential.

Transcriptome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants

BackgroundBenzylisoquinoline alkaloids (BIAs) represent a diverse class of plant specialized metabolites sharing a common biosynthetic origin beginning with tyrosine. Many BIAs have potent pharmacological activities, and plants accumulating them boast long histories of use in traditional medicine and cultural practices. The decades-long focus on a select number of plant species as model systems has allowed near or full elucidation of major BIA pathways, including those of morphine, sanguinarine and berberine. However, this focus has created a dearth of knowledge surrounding non-model species, which also are known to accumulate a wide-range of BIAs but whose biosynthesis is thus far entirely unexplored. Further, these non-model species represent a rich source of catalyst diversity valuable to plant biochemists and emerging synthetic biology efforts.ResultsIn order to access the genetic diversity of non-model plants accumulating BIAs, we selected 20 species representing 4 families within the Ranunculales. RNA extracted from each species was processed for analysis by both 1) Roche GS-FLX Titanium and 2) Illumina GA/HiSeq platforms, generating a total of 40 deep-sequencing transcriptome libraries. De novo assembly, annotation and subsequent full-length coding sequence (CDS) predictions indicated greater success for most species using the Illumina-based platform. Assembled data for each transcriptome were deposited into an established web-based BLAST portal (www.phytometasyn.ca) to allow public access. Homology-based mining of libraries using BIA-biosynthetic enzymes as queries yielded ~850 gene candidates potentially involved in alkaloid biosynthesis. Expression analysis of these candidates was performed using inter-library FPKM normalization methods. These expression data provide a basis for the rational selection of gene candidates, and suggest possible metabolic bottlenecks within BIA metabolism. Phylogenetic analysis was performed for each of 15 different enzyme/protein groupings, highlighting many novel genes with potential involvement in the formation of one or more alkaloid types, including morphinan, aporphine, and phthalideisoquinoline alkaloids. Transcriptome resources were used to design and execute a case study of candidate N-methyltransferases (NMTs) from Glaucium flavum, which revealed predicted and novel enzyme activities.ConclusionsThis study establishes an essential resource for the isolation and discovery of 1) functional homologues and 2) entirely novel catalysts within BIA metabolism. Functional analysis of G. flavum NMTs demonstrated the utility of this resource and underscored the importance of empirical determination of proposed enzymatic function. Publically accessible, fully annotated, BLAST-accessible transcriptomes were not previously available for most species included in this report, despite the rich repertoire of bioactive alkaloids found in these plants and their importance to traditional medicine. The results presented herein provide essential sequence information and inform experimental design for the continued elucidation of BIA metabolism.

LincRNA-p21 acts as a mediator of ING1b-induced apoptosis

ING1b is a tumor suppressor that affects transcription, cell cycle control and apoptosis. ING1b is deregulated in disease, and its activity is closely linked to that of p53. In addition to regulating protein-coding genes, we found that ING1b also influences the expression of large intergenic non-coding RNAs (lincRNAs). In particular, lincRNA-p21 was significantly induced after DNA-damage stress or by ING1b overexpression. Furthermore, lincRNA-p21 expression in response to DNA damage was significantly attenuated in cells lacking ING1b. LincRNA-p21 is also a target of p53 and can trigger apoptosis in mouse cell models. We found that this function of lincRNA-p21 is conserved in human cell models. Moreover, ING1b and p53 could function independently to influence lincRNA-p21 expression. However, their effects become more additive under conditions of stress. In particular, ING1b regulates lincRNA-p21 levels by binding to its promoter and is required for induction of lincRNA-p21 by p53. The ability of ING1b to cause apoptosis is also impaired in the absence of lincRNA-p21. Surprisingly, deletion of the ING1b plant homeodomain, which allows it to bind histones and regulate chromatin structure, did not alter regulation of lincRNA-p21. Our findings suggest that ING1b induces lincRNA-p21 expression independently of histone 3 lysine 4 trimethylation mark recognition and that lincRNA-p21 functions downstream of ING1b. Thus, regulation at the level of lincRNA-p21 may represent the point at which ING1b and p53 pathways converge to induce apoptosis under specific stress conditions.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

BackgroundLocating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them.ResultsSnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data.ConclusionsSnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/.

Roles of Thermophiles and Fungi in Bitumen Degradation in Mostly Cold Oil Sands Outcrops

ABSTRACT Oil sands are surface exposed in river valley outcrops in northeastern Alberta, where flat slabs (tablets) of weathered, bitumen-saturated sandstone can be retrieved from outcrop cliffs or from riverbeds. Although the average yearly surface temperature of this region is low (0.7°C), we found that the temperatures of the exposed surfaces of outcrop cliffs reached 55 to 60°C on sunny summer days, with daily maxima being 27 to 31°C. Analysis of the cooccurrence of taxa derived from pyrosequencing of 16S/18S rRNA genes indicated that an aerobic microbial network of fungi and hydrocarbon-, methane-, or acetate-oxidizing heterotrophic bacteria was present in all cliff tablets. Metagenomic analyses indicated an elevated presence of fungal cytochrome P450 monooxygenases in these samples. This network was distinct from the heterotrophic community found in riverbeds, which included fewer fungi. A subset of cliff tablets had a network of anaerobic and/or thermophilic taxa, including methanogens, Firmicutes, and Thermotogae, in the center. Long-term aerobic incubation of outcrop samples at 55°C gave a thermophilic microbial community. Analysis of residual bitumen with a Fourier transform ion cyclotron resonance mass spectrometer indicated that aerobic degradation proceeded at 55°C but not at 4°C. Little anaerobic degradation was observed. These results indicate that bitumen degradation on outcrop surfaces is a largely aerobic process with a minor anaerobic contribution and is catalyzed by a consortium of bacteria and fungi. Bitumen degradation is stimulated by periodic high temperatures on outcrop cliffs, which cause significant decreases in bitumen viscosity.

Unconventional microarray design reveals the response to obesity is largely tissue specific: analysis of common and divergent responses to diet-induced obesity in insulin-sensitive tissues

Obesity is a chronic condition involving the excessive accumulation of adipose tissue that adversely affects all systems in the body. The aim of the present study was to employ an unbiased, genome-wide assessment of transcript abundance in order to identify common gene expression pathways within insulin-sensitive tissues in response to dietary-induced diabetes. Following 20 weeks of chow or high-fat feeding (60% kcal), age-matched mice underwent a euglycemic-hyperinsulinemic clamp to assess insulin sensitivity. High-fat-fed animals were obese and highly insulin resistant, disposing of ∼75% less glucose compared with their chow-fed counterparts. Tissues were collected, and gene expression was examined by microarray in 4 tissues known to exhibit obesity-related metabolic disturbances: white adipose tissue, skeletal muscle, liver, and heart. A total of 463 genes were differentially expressed between diets. Analysis of individual tissues showed skeletal muscle to exhibit the largest number of differentially expressed genes (191) in response to high-fat feeding, followed by adipose tissue (169), liver (115), and heart (65). Analyses revealed that the response of individual genes to obesity is distinct and largely tissue specific, with less than 10% of transcripts being shared among tissues. Although transcripts are largely tissue specific, a systems approach shows numerous commonly activated pathways, including those involved in signal transduction, inflammation, oxidative stress, substrate transport, and metabolism. This suggests a coordinated attempt by tissues to limit metabolic perturbations occurring in early-stage obesity. Many identified genes were associated with a variety of disorders, thereby serving as potential links between obesity and its related health risks.