Metagenomic mining for microbiologists

Microbial ecologists can now start digging into the accumulating mountains of metagenomic data to uncover the occurrence of functional genes and their correlations to microbial community members. Limitations and biases in DNA extraction and sequencing technologies impact sequence distributions, and therefore, have to be considered. However, when comparing metagenomes from widely differing environments, these fluctuations have a relatively minor role in microbial community discrimination. As a consequence, any functional gene or species distribution pattern can be compared among metagenomes originating from various environments and projects. In particular, global comparisons would help to define ecosystem specificities, such as involvement and response to climate change (for example, carbon and nitrogen cycle), human health risks (eg, presence of pathogen species, toxin genes and viruses) and biodegradation capacities. Although not all scientists have easy access to high-throughput sequencing technologies, they do have access to the sequences that have been deposited in databases, and therefore, can begin to intensively mine these metagenomic data to generate hypotheses that can be validated experimentally. Information about metabolic functions and microbial species compositions can already be compared among metagenomes from different ecosystems. These comparisons add to our understanding about microbial adaptation and the role of specific microbes in different ecosystems. Concurrent with the rapid growth of sequencing technologies, we have entered a new age of microbial ecology, which will enable researchers to experimentally confirm putative relationships between microbial functions and community structures.     

Genome mining for the discovery of new nitrilases in filamentous fungi

Purpose of work  

Our aim is to describe new fungal nitrilases whose sequences were published but whose catalytic properties were unknown. We adapted for expression in E. coli three of the genes and confirmed that the enzymes acted on organic nitriles.     

From genome mining to phenotypic microarrays: Planctomycetes as source for novel bioactive molecules

Most members of the phylum Planctomycetes share many unusual traits that are unique for bacteria, since they divide independent of FtsZ through asymmetric budding, possess a complex life cycle and comprise a compartmentalized cell plan. Besides their complex cell biological features Planctomycetes are environmentally important and play major roles in global matter fluxes. Such features have been successfully employed in biotechnological applications such as the anaerobic oxidation of ammonium in wastewater treatment plants or the utilization of enzymes for biotechnological processes. However, little is known about planctomycetal secondary metabolites. This is surprising as Planctomycetes have several key features in common with known producers of small bioactive molecules such as Streptomycetes or Myxobacteria: a complex life style and large genome sizes. Planctomycetal genomes with an average size of 6.9 MB appear as tempting targets for drug discovery approaches. To enable the hunt for bioactive molecules from Planctomycetes, we performed a comprehensive genome mining approach employing the antiSMASH secondary metabolite identification pipeline and found 102 candidate genes or clusters within the analyzed 13 genomes. However, as most genes and operons related to secondary metabolite production are exclusively expressed under certain environmental conditions, we optimized Phenotype MicroArray protocols for Rhodopirellula baltica and Planctomyces limnophilus to allow high throughput screening of putative stimulating carbon sources. Our results point towards a previously postulated relationship of Planctomycetes with algae or plants, which secrete compounds that might serve as trigger to stimulate the secondary metabolite production in Planctomycetes. Thus, this study provides the necessary starting point to explore planctomycetal small molecules for drug development.     

Adhesion-GPCRs: emerging roles for novel receptors

The G protein-coupled receptor (GPCR) family comprises the largest class of cell surface receptors found in metazoan proteomes. Within the novel GPCR subfamily of adhesion-GPCRs, approximately 150 distinct orthologues, from invertebrates to mammals, have been identified to date. All members of this family contain a large extracellular region, often containing common protein modules, coupled to a seven-transmembrane domain via a stalk region that seems to be crucial for functionality. Owing to their unique structure, restricted expression profile and involvement in several human diseases, adhesion-GPCRs have long been proposed to have vital dual roles in cellular adhesion and signalling. More recent studies have provided structural, evolutionary, developmental and immunological insights in relation to the adhesion-GPCR family.     

Automated genome mining for natural products

Background  

Discovery of new medicinal agents from natural sources has largely been an adventitious process based on screening of plant and microbial extracts combined with bioassay-guided identification and natural product structure elucidation. Increasingly rapid and more cost-effective genome sequencing technologies coupled with advanced computational power have converged to transform this trend toward a more rational and predictive pursuit.     

DAGchainer: a tool for mining segmental genome duplications and synteny

SUMMARY: Given the positions of protein-coding genes along genomic sequence and probability values for protein alignments between genes, DAGchainer identifies chains of gene pairs sharing conserved order between genomic regions, by identifying paths through a directed acyclic graph (DAG). These chains of collinear gene pairs can represent segmentally duplicated regions and genes within a single genome or syntenic regions between related genomes. Automated mining of the Arabidopsis genome for segmental duplications illustrates the use of DAGchainer.     

Identification of novel isoprene synthases through genome mining and expression in Escherichia coli

Isoprene is a naturally produced hydrocarbon emitted into the atmosphere by green plants. It is also a constituent of synthetic rubber and a potential biofuel. Microbial production of isoprene can become a sustainable alternative to the prevailing chemical production of isoprene from petroleum. In this work, sequence homology searches were conducted to find novel isoprene synthases. Candidate sequences were functionally expressed in Escherichia coli and the desired enzymes were identified based on an isoprene production assay. The activity of three enzymes was shown for the first time: expression of the candidate genes from Ipomoea batatas, Mangifera indica, and Elaeocarpus photiniifolius resulted in isoprene formation. The Ipomoea batatas isoprene synthase produced the highest amounts of isoprene in all experiments, exceeding the isoprene levels obtained by the previously known Populus alba and Pueraria montana isoprene synthases that were studied in parallel as controls.     

Gifted microbes for genome mining and natural product discovery

Actinomycetes are historically important sources for secondary metabolites (SMs) with applications in human medicine, animal health, and plant crop protection. It is now clear that actinomycetes and other microorganisms with large genomes have the capacity to produce many more SMs than was anticipated from standard fermentation studies. Indeed ~90 % of SM gene clusters (SMGCs) predicted from genome sequencing are cryptic under conventional fermentation and analytical analyses. Previous studies have suggested that among the actinomycetes with large genomes, some have the coding capacity to produce many more SMs than others, and that strains with the largest genomes tend to be the most gifted. These contentions have been evaluated more quantitatively by antiSMASH 3.0 analyses of microbial genomes, and the results indicate that many actinomycetes with large genomes are gifted for SM production, encoding 20–50 SMGCs, and devoting 0.8–3.0 Mb of coding capacity to SM production. Several Proteobacteria and Firmacutes with large genomes encode 20–30 SMGCs and devote 0.8–1.3 Mb of DNA to SM production, whereas cultured bacteria and archaea with small genomes devote insignificant coding capacity to SM production. Fully sequenced genomes of uncultured bacteria and archaea have small genomes nearly devoid of SMGCs.     

矿区生态规划的思考

在总结国内外生态规划研究现状,趋势的基础上,分析了研究矿区生态规划的必要性,意义,提出了矿区生态规划的研究目标、内容与方法,论述了矿区生态规划研究的特色,同时指出,矿区生态规划理论与方法的提出了与建立既是矿区可持续发展的需要,也是生态规划理论与方法在矿区的应用与发展,需要多学科专家、学者的积极参与和合作。     

Phytohormones: novel strategy for removing emerging contaminants and recovering resources

Microalgae have the ability to remove emerging contaminants (ECs) from wastewater and to recover resources, but this is limited by oxidative damage caused by the contaminants. Recently, phytohormones have been found to improve the tolerance of microalgae under oxidative stress, to promote the removal of ECs, and to enhance the synthesis of metabolites.     

Bootstrap, Bayesian probability and maximum likelihood mapping: exploring new tools for comparative genome analyses

Background  

Horizontal gene transfer (HGT) played an important role in shaping microbial genomes. In addition to genes under sporadic selection, HGT also affects housekeeping genes and those involved in information processing, even ribosomal RNA encoding genes. Here we describe tools that provide an assessment and graphic illustration of the mosaic nature of microbial genomes.     

Identification of novel esterases for the synthesis of sterically demanding chiral alcohols by sequence-structure guided genome mining

Six esterases isolated from sequence and structure-guided genome mining approaches were evaluated for the kinetic resolution of secondary and tertiary alcohols that find application in the fine chemical and pharmaceutical industries. Activity and enantioselectivity with E-values of up to 24 were determined towards a range of sterically demanding tertiary alcohol esters. Excellent enantioselectivity (E > 100) was also achieved in the hydrolysis of a less challenging secondary alcohol ester, menthyl acetate. These results highlight that these approaches can be used for the identification of novel esterases applicable to the preparation of commercially desirable alcohols.     

Bioinformatics tools for genome mining of polyketide and non-ribosomal peptides

Microbial natural products have played a key role in the development of clinical agents in nearly all therapeutic areas. Recent advances in genome sequencing have revealed that there is an incredible wealth of new polyketide and non-ribosomal peptide natural product diversity to be mined from genetic data. The diversity and complexity of polyketide and non-ribosomal peptide biosynthesis has required the development of unique bioinformatics tools to identify, annotate, and predict the structures of these natural products from their biosynthetic gene clusters. This review highlights and evaluates web-based bioinformatics tools currently available to the natural product community for genome mining to discover new polyketides and non-ribosomal peptides.     

SPR for molecular interaction analysis: a review of emerging application areas

PubMed searches identified four emerging application areas for surface plasmon resonance systems. Food analysis, proteomics, immunogenicity and drug discovery. These application areas are reviewed. In connection with the review of drug discovery applications a case study is presented. This study demonstrates the value of combining results from drug-target and ADME predictive assays for compound selection.     

Molecular MALDI imaging: an emerging technology for neuroscience studies

Mass spectrometry (MS) has become an essential tool for the detection, identification, and characterization of the molecular components of biological processes, such as those responsible for the dynamic properties of the nervous system. Generally, the application of these powerful techniques requires the destruction of the specimen under study, but recent technological advances have made it possible to apply the matrix-assisted laser desorption/ionization (MALDI) MS technique directly to tissue sections. The major advantage of direct MALDI analysis is that it enables the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue and avoiding time-consuming extraction, purification, and separation steps, which have the potential for introducing artifacts. With automation and the ability to display complex spectral data using imaging software, it is now possible to create multiple 2D maps of selected biomolecules in register with tissue sections, a method now known as MALDI Imaging, or MSI (for Mass Spectrometry Imaging). This creates, for example, an opportunity to correlate functional states, determined a priori with live recording or imaging, with the corresponding molecular maps obtained at the time the tissue is frozen and analyzed with MSI. We review the increasing application of MALDI Imaging to the analysis of molecular distributions of proteins and peptides in nervous tissues of both vertebrates and invertebrates, focusing in particular on recent studies of neurodegenerative diseases and early efforts to implement assays of neuronal development.