Chronology of PAH and PCB pollution using sediment core in the Golden Horn estuary (Sea of Marmara)

The sources and depositional history of 16 polycyclic aromatic hydrocarbons (PAHs) and 18 polychlorinated biphenyl (PCBs) congeners in the Golden Horn estuary (İstanbul) were investigated using a dated sediment core for the period between 1880 and 2012. The concentrations of PAHs and PCBs were calculated for every 4 cm slices of the sediment core and ranged from 1203.5 to 3441.4 ng/g and 5.4 to 41.4 ng/g, respectively. The diagnostic ratios indicated that the maximum PAH values correspondence to combustion after a crude oil-carrying Romanian tanker (Independenta) accident in the İstanbul Strait in 1979. The historical deposition of PAHs and PCBs in the Golden Horn was influenced by municipal effluent and heavy industrial dischargers approximately 50 years. When the Silahtarağa thermal power plant (TPP) was operating, PCB pollution rose; however, after a thorough rehabilitation effort and the outlawing of PCB use in the 1990s, pollution levels significantly tended to decrease.

Flexible comparative genomics of prokaryotic transcriptional regulatory networks

Background

Comparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.

Results

Here we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.

Conclusions

Our results demonstrate the applicability of the CGB pipeline in multiple settings. CGB’s ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

Assessment of transfer methods for comparative genomics of regulatory networks in bacteria

Background

Comparative genomics can leverage the vast amount of available genomic sequences to reconstruct and analyze transcriptional regulatory networks in Bacteria, but the efficacy of this approach hinges on the ability to transfer regulatory network information from reference species to the genomes under analysis. Several methods have been proposed to transfer regulatory information between bacterial species, but the paucity and distributed nature of experimental information on bacterial transcriptional networks have prevented their systematic evaluation.

Results

We report the compilation of a large catalog of transcription factor-binding sites across Bacteria and its use to systematically benchmark proposed transfer methods across pairs of bacterial species. We evaluate motif- and accuracy-based metrics to assess the results of regulatory network transfer and we identify the precision-recall area-under-the-curve as the best metric for this purpose due to the large class-imbalanced nature of the problem. Methods assuming conservation of the transcription factor-binding motif (motif-based) are shown to substantially outperform those assuming conservation of regulon composition (network-based), even though their efficiency can decrease sharply with increasing phylogenetic distance. Variations of the basic motif-based transfer method do not yield significant improvements in transfer accuracy. Our results indicate that detection of a large enough number of regulated orthologs is critical for network-based transfer methods, but that relaxing orthology requirements does not improve results. Using the transcriptional regulators LexA and Fur as case examples, we also show how DNA-binding domain sequence similarity can yield confounding results as an indicator of transfer efficiency for motif-based methods.

Conclusions

Counter to standard practice, our evaluation of metrics to assess the efficiency of methods for regulatory network information transfer reveals that the area under precision-recall (PR) curves is a more precise and informative metric than that of receiver-operating-characteristic (ROC) curves, confirming similar findings in other class-imbalanced settings. Our systematic assessment of transfer methods reveals that simple approaches to both motif- and network-based transfer of regulatory information provide equal or better results than more elaborate methods. We also show that there are not effective predictors of transfer efficacy, substantiating the long-standing practice of manual curation in comparative genomics analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1113-7) contains supplementary material, which is available to authorized users.

The Verrucomicrobia LexA-Binding Motif: Insights into the Evolutionary Dynamics of the SOS Response

The SOS response is the primary bacterial mechanism to address DNA damage, coordinating multiple cellular processes that include DNA repair, cell division, and translesion synthesis. In contrast to other regulatory systems, the composition of the SOS genetic network and the binding motif of its transcriptional repressor, LexA, have been shown to vary greatly across bacterial clades, making it an ideal system to study the co-evolution of transcription factors and their regulons. Leveraging comparative genomics approaches and prior knowledge on the core SOS regulon, here we define the binding motif of the Verrucomicrobia, a recently described phylum of emerging interest due to its association with eukaryotic hosts. Site directed mutagenesis of the Verrucomicrobium spinosum recA promoter confirms that LexA binds a 14 bp palindromic motif with consensus sequence TGTTC-N4-GAACA. Computational analyses suggest that recognition of this novel motif is determined primarily by changes in base-contacting residues of the third alpha helix of the LexA helix-turn-helix DNA binding motif. In conjunction with comparative genomics analysis of the LexA regulon in the Verrucomicrobia phylum, electrophoretic shift assays reveal that LexA binds to operators in the promoter region of DNA repair genes and a mutagenesis cassette in this organism, and identify previously unreported components of the SOS response. The identification of tandem LexA-binding sites generating instances of other LexA-binding motifs in the lexA gene promoter of Verrucomicrobia species leads us to postulate a novel mechanism for LexA-binding motif evolution. This model, based on gene duplication, successfully addresses outstanding questions in the intricate co-evolution of the LexA protein, its binding motif and the regulatory network it controls.

From data repositories to submission portals: rethinking the role of domain-specific databases in CollecTF

Domain-specific databases are essential resources for the biomedical community, leveraging expert knowledge to curate published literature and provide access to referenced data and knowledge. The limited scope of these databases, however, poses important challenges on their infrastructure, visibility, funding and usefulness to the broader scientific community. CollecTF is a community-oriented database documenting experimentally validated transcription factor (TF)-binding sites in the Bacteria domain. In its quest to become a community resource for the annotation of transcriptional regulatory elements in bacterial genomes, CollecTF aims to move away from the conventional data-repository paradigm of domain-specific databases. Through the adoption of well-established ontologies, identifiers and collaborations, CollecTF has progressively become also a portal for the annotation and submission of information on transcriptional regulatory elements to major biological sequence resources (RefSeq, UniProtKB and the Gene Ontology Consortium). This fundamental change in database conception capitalizes on the domain-specific knowledge of contributing communities to provide high-quality annotations, while leveraging the availability of stable information hubs to promote long-term access and provide high-visibility to the data. As a submission portal, CollecTF generates TF-binding site information through direct annotation of RefSeq genome records, definition of TF-based regulatory networks in UniProtKB entries and submission of functional annotations to the Gene Ontology. As a database, CollecTF provides enhanced search and browsing, targeted data exports, binding motif analysis tools and integration with motif discovery and search platforms. This innovative approach will allow CollecTF to focus its limited resources on the generation of high-quality information and the provision of specialized access to the data.Database URL: http://www.collectf.org/.

CollecTF: a database of experimentally validated transcription factor-binding sites in Bacteria

The influx of high-throughput data and the need for complex models to describe the interaction of prokaryotic transcription factors (TF) with their target sites pose new challenges for TF-binding site databases. CollecTF (http://collectf.umbc.edu) compiles data on experimentally validated, naturally occurring TF-binding sites across the Bacteria domain, placing a strong emphasis on the transparency of the curation process, the quality and availability of the stored data and fully customizable access to its records. CollecTF integrates multiple sources of data automatically and openly, allowing users to dynamically redefine binding motifs and their experimental support base. Data quality and currency are fostered in CollecTF by adopting a sustainable model that encourages direct author submissions in combination with in-house validation and curation of published literature. CollecTF entries are periodically submitted to NCBI for integration into RefSeq complete genome records as link-out features, maximizing the visibility of the data and enriching the annotation of RefSeq files with regulatory information. Seeking to facilitate comparative genomics and machine-learning analyses of regulatory interactions, in its initial release CollecTF provides domain-wide coverage of two TF families (LexA and Fur), as well as extensive representation for a clinically important bacterial family, the Vibrionaceae.