Exploratory Hydrocarbon Drilling Impacts to Arctic Lake Ecosystems

Recent attention regarding the impacts of oil and gas development and exploitation has focused on the unintentional release of hydrocarbons into the environment, whilst the potential negative effects of other possible avenues of environmental contamination are less well documented. In the hydrocarbon-rich and ecologically sensitive Mackenzie Delta region (NT, Canada), saline wastes associated with hydrocarbon exploration have typically been disposed of in drilling sumps (i.e., large pits excavated into the permafrost) that were believed to be a permanent containment solution. However, failure of permafrost as a waste containment medium may cause impacts to lakes in this sensitive environment. Here, we examine the effects of degrading drilling sumps on water quality by combining paleolimnological approaches with the analysis of an extensive present-day water chemistry dataset. This dataset includes lakes believed to have been impacted by saline drilling fluids leaching from drilling sumps, lakes with no visible disturbances, and lakes impacted by significant, naturally occurring permafrost thaw in the form of retrogressive thaw slumps. We show that lakes impacted by compromised drilling sumps have significantly elevated lakewater conductivity levels compared to control sites. Chloride levels are particularly elevated in sump-impacted lakes relative to all other lakes included in the survey. Paleolimnological analyses showed that invertebrate assemblages appear to have responded to the leaching of drilling wastes by a discernible increase in a taxon known to be tolerant of elevated conductivity coincident with the timing of sump construction. This suggests construction and abandonment techniques at, or soon after, sump establishment may result in impacts to downstream aquatic ecosystems. With hydrocarbon development in the north predicted to expand in the coming decades, the use of sumps must be examined in light of the threat of accelerated permafrost thaw, and the potential for these industrial wastes to impact sensitive Arctic ecosystems.     

Disordered microbial communities in the upper respiratory tract of cigarette smokers

Cigarette smokers have an increased risk of infectious diseases involving the respiratory tract. Some effects of smoking on specific respiratory tract bacteria have been described, but the consequences for global airway microbial community composition have not been determined. Here, we used culture-independent high-density sequencing to analyze the microbiota from the right and left nasopharynx and oropharynx of 29 smoking and 33 nonsmoking healthy asymptomatic adults to assess microbial composition and effects of cigarette smoking. Bacterial communities were profiled using 454 pyrosequencing of 16S sequence tags (803,391 total reads), aligned to 16S rRNA databases, and communities compared using the UniFrac distance metric. A Random Forest machine-learning algorithm was used to predict smoking status and identify taxa that best distinguished between smokers and nonsmokers. Community composition was primarily determined by airway site, with individuals exhibiting minimal side-of-body or temporal variation. Within airway habitats, microbiota from smokers were significantly more diverse than nonsmokers and clustered separately. The distributions of several genera were systematically altered by smoking in both the oro- and nasopharynx, and there was an enrichment of anaerobic lineages associated with periodontal disease in the oropharynx. These results indicate that distinct regions of the human upper respiratory tract contain characteristic microbial communities that exhibit disordered patterns in cigarette smokers, both in individual components and global structure, which may contribute to the prevalence of respiratory tract complications in this population.     

Improved characterization of medically relevant fungi in the human respiratory tract using next-generation sequencing

Background

Fungi are important pathogens but challenging to enumerate using next-generation sequencing because of low absolute abundance in many samples and high levels of fungal DNA from contaminating sources.

Results

Here, we analyze fungal lineages present in the human airway using an improved method for contamination filtering. We use DNA quantification data, which are routinely acquired during DNA library preparation, to annotate output sequence data, and improve the identification and filtering of contaminants. We compare fungal communities and bacterial communities from healthy subjects, HIV+ subjects, and lung transplant recipients, providing a gradient of increasing lung impairment for comparison. We use deep sequencing to characterize ribosomal rRNA gene segments from fungi and bacteria in DNA extracted from bronchiolar lavage samples and oropharyngeal wash. Comparison to clinical culture data documents improved detection after applying the filtering procedure.

Conclusions

We find increased representation of medically relevant organisms, including Candida, Cryptococcus, and Aspergillus, in subjects with increasingly severe pulmonary and immunologic deficits. We analyze covariation of fungal and bacterial taxa, and find that oropharyngeal communities rich in Candida are also rich in mitis group Streptococci, a community pattern associated with pathogenic polymicrobial biofilms. Thus, using this approach, it is possible to characterize fungal communities in the human respiratory tract more accurately and explore their interactions with bacterial communities in health and disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0487-y) contains supplementary material, which is available to authorized users.     

Polygenic inheritance of canopy wilting in soybean [<Emphasis Type="Italic">Glycine max</Emphasis> (L.) Merr.]

As water demand for agriculture exceeds water availability, cropping systems need to become more efficient in water usage, such as deployment of cultivars that sustain yield under drought conditions. Soybean cultivars differ in how quickly they wilt during water-deficit stress, and this trait may lead to yield improvement during drought. The objective of this study was to determine the genetic mechanism of canopy wilting in soybean using a mapping population of recombinant inbred lines (RILs) derived from a cross between KS4895 and Jackson. Canopy wilting was rated in three environments using a rating scale of 0 (no wilting) to 100 (severe wilting and plant death). Transgressive segregation was observed for the RIL population with the parents expressing intermediate wilting scores. Using multiple-loci analysis, four quantitative trait loci (QTLs) on molecular linkage groups (MLGs) A2, B2, D2, and F were detected (P ≤ 0.05), which collectively accounted for 47% of the phenotypic variation of genotypic means over all three environments. An analysis of the data by state revealed that 44% of the observed phenotypic variation in the Arkansas environments could be accounted for by these QTLs. Only the QTL on MLG F was detected at North Carolina where it accounted for 16% of the phenotypic variation. These results demonstrate that the genetic mechanism controlling canopy wilting was polygenic and environmentally sensitive and provide a foundation for future research to examine the importance of canopy wilting in drought tolerance of soybean.     

Diversity among bacteria isolated from the deep subsurface

Culturable bacteria from the deep subsurface (179 m) at Cerro Negro, New Mexico were isolated and characterized. The average number of viable aerobic bacteria was estimated to be 5×10⁵g^–1 of sediment, but only about 0.1% of these could be recovered on agar medium when incubated under aerobic conditions. Of 158 strains isolated from this depth, 92 were characterized by cellular fatty acid profiles (FAME), 36 by analysis of partial 16S rDNA sequences, and 44 by rep-PCR genome fingerprint analysis using three different sets of oligonucleotide primers (REP, BOX, or ERIC). These analyses showed the majority of isolates (67%) were Gram-positive bacteria and primarily members of genera with a high %G+C DNA. The remaining isolates were -subdivisionProteobacteria (19%) and members of the flavobacteria group (14%). The diversity indices based on these different methods of characterization were very high suggesting this subsurface habitat harbors a highly diverse microbial community.     

Iterative orthology prediction uncovers new mitochondrial proteins and identifies C12orf62 as the human ortholog of COX14, a protein involved in the assembly of cytochrome c oxidase

Background

Orthology is a central tenet of comparative genomics and ortholog identification is instrumental to protein function prediction. Major advances have been made to determine orthology relations among a set of homologous proteins. However, they depend on the comparison of individual sequences and do not take into account divergent orthologs.

Results

We have developed an iterative orthology prediction method, Ortho-Profile, that uses reciprocal best hits at the level of sequence profiles to infer orthology. It increases ortholog detection by 20% compared to sequence-to-sequence comparisons. Ortho-Profile predicts 598 human orthologs of mitochondrial proteins from Saccharomyces cerevisiae and Schizosaccharomyces pombe with 94% accuracy. Of these, 181 were not known to localize to mitochondria in mammals. Among the predictions of the Ortho-Profile method are 11 human cytochrome c oxidase (COX) assembly proteins that are implicated in mitochondrial function and disease. Their co-expression patterns, experimentally verified subcellular localization, and co-purification with human COX-associated proteins support these predictions. For the human gene C12orf62, the ortholog of S. cerevisiae COX14, we specifically confirm its role in negative regulation of the translation of cytochrome c oxidase.

Conclusions

Divergent homologs can often only be detected by comparing sequence profiles and profile-based hidden Markov models. The Ortho-Profile method takes advantage of these techniques in the quest for orthologs.     

New resources for functional analysis of omics data for the genus <Emphasis Type="Italic">Aspergillus</Emphasis>

Background

Detailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus Aspergillus comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely A. nidulans.

Results

Based on protein homology, we mapped 97% of the 3,498 GO annotated A. nidulans genes to at least one of seven other Aspergillus species: A. niger, A. fumigatus, A. flavus, A. clavatus, A. terreus, A. oryzae and Neosartorya fischeri. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all Aspergillus species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institute's website (http://www.broadinstitute.org/fetgoat/index.html). To demonstrate the value of those new resources for functional analysis of omics data for the genus Aspergillus, we performed two case studies analyzing microarray data recently published for A. nidulans, A. niger and A. oryzae.

Conclusions

We mapped A. nidulans GO annotation to seven other Aspergilli. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus Aspergillus. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.