In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria.

BACKGROUND: Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated. RESULTS: Here we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis. CONCLUSION: To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.

Bioprospecting Red Sea Coastal Ecosystems for Culturable Microorganisms and Their Antimicrobial Potential.

Microorganisms that inhabit unchartered unique soil such as in the highly saline and hot Red Sea lagoons on the Saudi Arabian coastline, represent untapped sources of potentially new bioactive compounds. In this study, a culture-dependent approach was applied to three types of sediments: mangrove mud (MN), microbial mat (MM), and barren soil (BS), collected from Rabigh harbor lagoon (RHL) and Al-Kharrar lagoon (AKL). The isolated bacteria were evaluated for their potential to produce bioactive compounds. The phylogenetic characterization of 251 bacterial isolates based on the 16S rRNA gene sequencing, supported their assignment to five different phyla: Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Planctomycetes. Fifteen putative novel species were identified based on a 16S rRNA gene sequence similarity to other strain sequences in the NCBI database, being ≤98%. We demonstrate that 49 of the 251 isolates exhibit the potential to produce antimicrobial compounds. Additionally, at least one type of biosynthetic gene sequence, responsible for the synthesis of secondary metabolites, was recovered from 25 of the 49 isolates. Moreover, 10 of the isolates had a growth inhibition effect towards Staphylococcus aureus, Salmonella typhimurium and Pseudomonas syringae. We report the previously unknown antimicrobial activity of B. borstelensis, P. dendritiformis and M. salipaludis against all three indicator pathogens. Our study demonstrates the evidence of diverse cultured microbes associated with the Red Sea harbor/lagoon environments and their potential to produce antimicrobial compounds.

Metagenomics as a preliminary screen for antimicrobial bioprospecting.

Since the composition of soil directs the diversity of the contained microbiome and its potential to produce bioactive compounds, many studies has been focused on sediment types with unique features characteristic of extreme environments. However, not much is known about the potential of microbiomes that inhabit the highly saline and hot Red Sea lagoons. This case study explores mangrove mud and the microbial mat of sediments collected from the Rabigh harbor lagoon and Al Kharrar lagoon for antimicrobial bioprospecting. Rabigh harbor lagoon appears the better location, and the best sediment type for this purpose is mangrove mud. On the other hand, Al Kharrar lagoon displayed increased anaerobic hydrocarbon degradation and an abundance of bacterial DNA associated with antibiotic resistance. Moreover, our findings show an identical shift in phyla associated with historic hydrocarbon contamination exposure reported in previous studies (that is, enrichment of Gamma- and Delta-proteobacteria), but we also report that bacterial DNA sequences associated with antibiotic synthesis enzymes are derived from Gamma-, Delta- and Alpha-proteobacteria. This suggests that selection pressure associated with hydrocarbon contamination tend to enrich the bacterial classes DNA associated with antibiotic synthesis enzymes. Although Actinobacteria tends to be the common target for research when it comes to antimicrobial bioprospecting, our study suggests that Firmicutes (Bacilli and Clostridia), Bacteroidetes, Cyanobacteria, and Proteobacteria should be antimicrobial bioprospecting targets as well. To the best of our knowledge, this is the first metagenomic study that analyzed the microbiomes in Red Sea lagoons for antimicrobial bioprospecting.

Rhizosphere microbiome metagenomics of gray mangroves (Avicennia marina) in the Red Sea.

Mangroves are unique, and endangered, coastal ecosystems that play a vital role in the tropical and subtropical environments. A comprehensive description of the microbial communities in these ecosystems is currently lacking, and additional studies are required to have a complete understanding of the functioning and resilience of mangroves worldwide. In this work, we carried out a metagenomic study by comparing the microbial community of mangrove sediment with the rhizosphere microbiome of Avicennia marina, in northern Red Sea mangroves, along the coast of Saudi Arabia. Our results revealed that rhizosphere samples presented similar profiles at the taxonomic and functional levels and differentiated from the microbiome of bulk soil controls. Overall, samples showed predominance by Proteobacteria, Bacteroidetes and Firmicutes, with high abundance of sulfate reducers and methanogens, although specific groups were selectively enriched in the rhizosphere. Functional analysis showed significant enrichment in 'metabolism of aromatic compounds', 'mobile genetic elements', 'potassium metabolism' and 'pathways that utilize osmolytes' in the rhizosphere microbiomes. To our knowledge, this is the first metagenomic study on the microbiome of mangroves in the Red Sea, and the first application of unbiased 454-pyrosequencing to study the rhizosphere microbiome associated with A. marina. Our results provide the first insights into the range of functions and microbial diversity in the rhizosphere and soil sediments of gray mangrove (A. marina) in the Red Sea.

Soil and Rhizosphere Associated Fungi in Gray Mangroves (Avicennia marina) from the Red Sea--A Metagenomic Approach.

Covering a quarter of the world's tropical coastlines and being one of the most threatened ecosystems, mangroves are among the major sources of terrestrial organic matter to oceans and harbor a wide microbial diversity. In order to protect, restore, and better understand these ecosystems, researchers have extensively studied their microbiology, yet few surveys have focused on their fungal communities. Our lack of knowledge is even more pronounced for specific fungal populations, such as the ones associated with the rhizosphere. Likewise, the Red Sea gray mangroves (Avicennia marina) remain poorly characterized, and understanding of their fungal communities still relies on cultivation-dependent methods. In this study, we analyzed metagenomic datasets from gray mangrove rhizosphere and bulk soil samples collected in the Red Sea coast, to obtain a snapshot of their fungal communities. Our data indicated that Ascomycota was the dominant phylum (76%-85%), while Basidiomycota was less abundant (14%-24%), yet present in higher numbers than usually reported for such environments. Fungal communities were more stable within the rhizosphere than within the bulk soil, both at class and genus level. This finding is consistent with the intrinsic patchiness in soil sediments and with the selection of specific microbial communities by plant roots. Our study indicates the presence of several species on this mycobiome that were not previously reported as mangrove-associated. In particular, we detected representatives of several commercially-used fungi, e.g., producers of secreted cellulases and anaerobic producers of cellulosomes. These results represent additional insights into the fungal community of the gray mangroves of the Red Sea, and show that they are significantly richer than previously reported.

Hi-Jack: a novel computational framework for pathway-based inference of host-pathogen interactions.

MOTIVATION: Pathogens infect their host and hijack the host machinery to produce more progeny pathogens. Obligate intracellular pathogens, in particular, require resources of the host to replicate. Therefore, infections by these pathogens lead to alterations in the metabolism of the host, shifting in favor of pathogen protein production. Some computational identification of mechanisms of host-pathogen interactions have been proposed, but it seems the problem has yet to be approached from the metabolite-hijacking angle. RESULTS: We propose a novel computational framework, Hi-Jack, for inferring pathway-based interactions between a host and a pathogen that relies on the idea of metabolite hijacking. Hi-Jack searches metabolic network data from hosts and pathogens, and identifies candidate reactions where hijacking occurs. A novel scoring function ranks candidate hijacked reactions and identifies pathways in the host that interact with pathways in the pathogen, as well as the associated frequent hijacked metabolites. We also describe host-pathogen interaction principles that can be used in the future for subsequent studies. Our case study on Mycobacterium tuberculosis (Mtb) revealed pathways in human-e.g. carbohydrate metabolism, lipids metabolism and pathways related to amino acids metabolism-that are likely to be hijacked by the pathogen. In addition, we report interesting potential pathway interconnections between human and Mtb such as linkage of human fatty acid biosynthesis with Mtb biosynthesis of unsaturated fatty acids, or linkage of human pentose phosphate pathway with lipopolysaccharide biosynthesis in Mtb. AVAILABILITY AND IMPLEMENTATION: Datasets and codes are available at http://cloud.kaust.edu.sa/Pages/Hi-Jack.aspx

Chemical compounds toxic to invertebrates isolated from marine cyanobacteria of potential relevance to the agricultural industry.

In spite of advances in invertebrate pest management, the agricultural industry is suffering from impeded pest control exacerbated by global climate changes that have altered rain patterns to favour opportunistic breeding. Thus, novel naturally derived chemical compounds toxic to both terrestrial and aquatic invertebrates are of interest, as potential pesticides. In this regard, marine cyanobacterium-derived metabolites that are toxic to both terrestrial and aquatic invertebrates continue to be a promising, but neglected, source of potential pesticides. A PubMed query combined with hand-curation of the information from retrieved articles allowed for the identification of 36 cyanobacteria-derived chemical compounds experimentally confirmed as being toxic to invertebrates. These compounds are discussed in this review.

Core microbial functional activities in ocean environments revealed by global metagenomic profiling analyses.

Metagenomics-based functional profiling analysis is an effective means of gaining deeper insight into the composition of marine microbial populations and developing a better understanding of the interplay between the functional genome content of microbial communities and abiotic factors. Here we present a comprehensive analysis of 24 datasets covering surface and depth-related environments at 11 sites around the world's oceans. The complete datasets comprises approximately 12 million sequences, totaling 5,358 Mb. Based on profiling patterns of Clusters of Orthologous Groups (COGs) of proteins, a core set of reference photic and aphotic depth-related COGs, and a collection of COGs that are associated with extreme oxygen limitation were defined. Their inferred functions were utilized as indicators to characterize the distribution of light- and oxygen-related biological activities in marine environments. The results reveal that, while light level in the water column is a major determinant of phenotypic adaptation in marine microorganisms, oxygen concentration in the aphotic zone has a significant impact only in extremely hypoxic waters. Phylogenetic profiling of the reference photic/aphotic gene sets revealed a greater variety of source organisms in the aphotic zone, although the majority of individual photic and aphotic depth-related COGs are assigned to the same taxa across the different sites. This increase in phylogenetic and functional diversity of the core aphotic related COGs most probably reflects selection for the utilization of a broad range of alternate energy sources in the absence of light.

A promoter-level mammalian expression atlas.

Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly 'housekeeping', whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.

A novel mercuric reductase from the unique deep brine environment of Atlantis II in the Red Sea.

A unique combination of physicochemical conditions prevails in the lower convective layer (LCL) of the brine pool at Atlantis II (ATII) Deep in the Red Sea. With a maximum depth of over 2000 m, the pool is characterized by acidic pH (5.3), high temperature (68 °C), salinity (26%), low light levels, anoxia, and high concentrations of heavy metals. We have established a metagenomic dataset derived from the microbial community in the LCL, and here we describe a gene for a novel mercuric reductase, a key component of the bacterial detoxification system for mercuric and organomercurial species. The metagenome-derived gene and an ortholog from an uncultured soil bacterium were synthesized and expressed in Escherichia coli. The properties of their products show that, in contrast to the soil enzyme, the ATII-LCL mercuric reductase is functional in high salt, stable at high temperatures, resistant to high concentrations of Hg(2+), and efficiently detoxifies Hg(2+) in vivo. Interestingly, despite the marked functional differences between the orthologs, their amino acid sequences differ by less than 10%. Site-directed mutagenesis and kinetic analysis of the mutant enzymes, in conjunction with three-dimensional modeling, have identified distinct structural features that contribute to extreme halophilicity, thermostability, and high detoxification capacity, suggesting that these were acquired independently during the evolution of this enzyme. Thus, our work provides fundamental structural insights into a novel protein that has undergone multiple biochemical and biophysical adaptations to promote the survival of microorganisms that reside in the extremely demanding environment of the ATII-LCL.

Exploration of miRNA families for hypotheses generation.

Technological improvements have resulted in increased discovery of new microRNAs (miRNAs) and refinement and enrichment of existing miRNA families. miRNA families are important because they suggest a common sequence or structure configuration in sets of genes that hint to a shared function. Exploratory tools to enhance investigation of characteristics of miRNA families and the functions of family-specific miRNA genes are lacking. We have developed, miRNAVISA, a user-friendly web-based tool that allows customized interrogation and comparisons of miRNA families for hypotheses generation, and comparison of per-species chromosomal distribution of miRNA genes in different families. This study illustrates hypothesis generation using miRNAVISA in seven species. Our results unveil a subclass of miRNAs that may be regulated by genomic imprinting, and also suggest that some miRNA families may be species-specific, as well as chromosome- and/or strand-specific.

Simplified method for predicting a functional class of proteins in transcription factor complexes.

BACKGROUND: Initiation of transcription is essential for most of the cellular responses to environmental conditions and for cell and tissue specificity. This process is regulated through numerous proteins, their ligands and mutual interactions, as well as interactions with DNA. The key such regulatory proteins are transcription factors (TFs) and transcription co-factors (TcoFs). TcoFs are important since they modulate the transcription initiation process through interaction with TFs. In eukaryotes, transcription requires that TFs form different protein complexes with various nuclear proteins. To better understand transcription regulation, it is important to know the functional class of proteins interacting with TFs during transcription initiation. Such information is not fully available, since not all proteins that act as TFs or TcoFs are yet annotated as such, due to generally partial functional annotation of proteins. In this study we have developed a method to predict, using only sequence composition of the interacting proteins, the functional class of human TF binding partners to be (i) TF, (ii) TcoF, or (iii) other nuclear protein. This allows for complementing the annotation of the currently known pool of nuclear proteins. Since only the knowledge of protein sequences is required in addition to protein interaction, the method should be easily applicable to many species. RESULTS: Based on experimentally validated interactions between human TFs with different TFs, TcoFs and other nuclear proteins, our two classification systems (implemented as a web-based application) achieve high accuracies in distinguishing TFs and TcoFs from other nuclear proteins, and TFs from TcoFs respectively. CONCLUSION: As demonstrated, given the fact that two proteins are capable of forming direct physical interactions and using only information about their sequence composition, we have developed a completely new method for predicting a functional class of TF interacting protein partners with high precision and accuracy.

Dragon TIS Spotter: an Arabidopsis-derived predictor of translation initiation sites in plants.

SUMMARY: In higher eukaryotes, the identification of translation initiation sites (TISs) has been focused on finding these signals in cDNA or mRNA sequences. Using Arabidopsis thaliana (A.t.) information, we developed a prediction tool for signals within genomic sequences of plants that correspond to TISs. Our tool requires only genome sequence, not expressed sequences. Its sensitivity/specificity is for A.t. (90.75%/92.2%), for Vitis vinifera (66.8%/94.4%) and for Populus trichocarpa (81.6%/94.4%), which suggests that our tool can be used in annotation of different plant genomes. We provide a list of features used in our model. Further study of these features may improve our understanding of mechanisms of the translation initiation. AVAILABILITY AND IMPLEMENTATION: Our tool is implemented as an artificial neural network. It is available as a web-based tool and, together with the source code, the list of features, and data used for model development, is accessible at http://cbrc.kaust.edu.sa/dts.

Importance of the genetic diversity within the Mycobacterium tuberculosis complex for the development of novel antibiotics and diagnostic tests of drug resistance.

Despite being genetically monomorphic, the limited genetic diversity within the Mycobacterium tuberculosis complex (MTBC) has practical consequences for molecular methods for drug susceptibility testing and for the use of current antibiotics and those in clinical trials. It renders some representatives of MTBC intrinsically resistant against one or multiple antibiotics and affects the spectrum and consequences of resistance mutations selected for during treatment. Moreover, neutral or silent changes within genes responsible for drug resistance can cause false-positive results with hybridization-based assays, which have been recently introduced to replace slower phenotypic methods. We discuss the consequences of these findings and propose concrete steps to rigorously assess the genetic diversity of MTBC to support ongoing clinical trials.

Conotoxins that confer therapeutic possibilities.

Cone snails produce a distinctive repertoire of venom peptides that are used both as a defense mechanism and also to facilitate the immobilization and digestion of prey. These peptides target a wide variety of voltage- and ligand-gated ion channels, which make them an invaluable resource for studying the properties of these ion channels in normal and diseased states, as well as being a collection of compounds of potential pharmacological use in their own right. Examples include the United States Food and Drug Administration (FDA) approved pharmaceutical drug, Ziconotide (Prialt(®); Elan Pharmaceuticals, Inc.) that is the synthetic equivalent of the naturally occurring ω-conotoxin MVIIA, whilst several other conotoxins are currently being used as standard research tools and screened as potential therapeutic drugs in pre-clinical or clinical trials. These developments highlight the importance of driving conotoxin-related research. A PubMed query from 1 January 2007 to 31 August 2011 combined with hand-curation of the retrieved articles allowed for the collation of 98 recently identified conotoxins with therapeutic potential which are selectively discussed in this review. Protein sequence similarity analysis tentatively assigned uncharacterized conotoxins to predicted functional classes. Furthermore, conotoxin therapeutic potential for neurodegenerative disorders (NDD) was also inferred.

Mutations and binding sites of human transcription factors.

Mutations in any genome may lead to phenotype characteristics that determine ability of an individual to cope with adaptation to environmental challenges. In studies of human biology, among the most interesting ones are phenotype characteristics that determine responses to drug treatments, response to infections, or predisposition to specific inherited diseases. Most of the research in this field has been focused on the studies of mutation effects on the final gene products, peptides, and their alterations. Considerably less attention was given to the mutations that may affect regulatory mechanism(s) of gene expression, although these may also affect the phenotype characteristics. In this study we make a pilot analysis of mutations observed in the regulatory regions of 24,667 human RefSeq genes. Our study reveals that out of eight studied mutation types, "insertions" are the only one that in a statistically significant manner alters predicted transcription factor binding sites (TFBSs). We also find that 25 families of TFBSs have been altered by mutations in a statistically significant manner in the promoter regions we considered. Moreover, we find that the related transcription factors are, for example, prominent in processes related to intracellular signaling; cell fate; morphogenesis of organs and epithelium; development of urogenital system, epithelium, and tube; neuron fate commitment. Our study highlights the significance of studying mutations within the genes regulatory regions and opens way for further detailed investigations on this topic, particularly on the downstream affected pathways.

Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences.

MOTIVATION: Recognition of poly(A) signals in mRNA is relatively straightforward due to the presence of easily recognizable polyadenylic acid tail. However, the task of identifying poly(A) motifs in the primary genomic DNA sequence that correspond to poly(A) signals in mRNA is a far more challenging problem. Recognition of poly(A) signals is important for better gene annotation and understanding of the gene regulation mechanisms. In this work, we present one such poly(A) motif prediction method based on properties of human genomic DNA sequence surrounding a poly(A) motif. These properties include thermodynamic, physico-chemical and statistical characteristics. For predictions, we developed Artificial Neural Network and Random Forest models. These models are trained to recognize 12 most common poly(A) motifs in human DNA. Our predictors are available as a free web-based tool accessible at http://cbrc.kaust.edu.sa/dps. Compared with other reported predictors, our models achieve higher sensitivity and specificity and furthermore provide a consistent level of accuracy for 12 poly(A) motif variants. CONTACT: vladimir.bajic@kaust.edu.sa SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DAMPD: a manually curated antimicrobial peptide database.

The demand for antimicrobial peptides (AMPs) is rising because of the increased occurrence of pathogens that are tolerant or resistant to conventional antibiotics. Since naturally occurring AMPs could serve as templates for the development of new anti-infectious agents to which pathogens are not resistant, a resource that contains relevant information on AMP is of great interest. To that extent, we developed the Dragon Antimicrobial Peptide Database (DAMPD, http://apps.sanbi.ac.za/dampd) that contains 1232 manually curated AMPs. DAMPD is an update and a replacement of the ANTIMIC database. In DAMPD an integrated interface allows in a simple fashion querying based on taxonomy, species, AMP family, citation, keywords and a combination of search terms and fields (Advanced Search). A number of tools such as Blast, ClustalW, HMMER, Hydrocalculator, SignalP, AMP predictor, as well as a number of other resources that provide additional information about the results are also provided and integrated into DAMPD to augment biological analysis of AMPs.

Overview of errors in the reference sequence and annotation of Mycobacterium tuberculosis H37Rv, and variation amongst its isolates.

Since its publication in 1998, the genome sequence of the Mycobacterium tuberculosis H37Rv laboratory strain has acted as the cornerstone for the study of tuberculosis. In this review we address some of the practical aspects that have come to light relating to the use of H37Rv throughout the past decade which are of relevance for the ongoing genomic and laboratory studies of this pathogen. These include errors in the genome reference sequence and its annotation, as well as the recently detected variation amongst isolates of H37Rv from different laboratories.