Functional gene clustering via gene annotation sentences, MeSH and GO keywords from biomedical literature

Gene function annotation remains a key challenge in modern biology. This is especially true for high-throughput techniques such as gene expression experiments. Vital information about genes is available electronically from biomedical literature in the form of full texts and abstracts. In addition, various publicly available databases (such as GenBank, Gene Ontology and Entrez) provide access to gene-related information at different levels of biological organization, granularity and data format. This information is being used to assess and interpret the results from high-throughput experiments. To improve keyword extraction for annotational clustering and other types of analyses, we have developed a novel text mining approach, which is based on keywords identified at the level of gene annotation sentences (in particular sentences characterizing biological function) instead of entire abstracts. Further, to improve the expressiveness and usefulness of gene annotation terms, we investigated the combination of sentence-level keywords with terms from the Medical Subject Headings (MeSH) and Gene Ontology (GO) resources. We find that sentence-level keywords combined with MeSH terms outperforms the typical 'baseline' set-up (term frequencies at the level of abstracts) by a significant margin, whereas the addition of GO terms improves matters only marginally. We validated our approach on the basis of a manually annotated corpus of 200 abstracts generated on the basis of 2 cancer categories and 10 genes per category. We applied the method in the context of three sets of differentially expressed genes obtained from pediatric brain tumor samples. This analysis suggests novel interpretations of discovered gene expression patterns.     

Plant communities on ironstone outcrops: a diverse and endangered Brazilian ecosystem

Mountain areas are recognized centres of endemism and diversity on account of their isolation and altitudinal diversity. In tropical regions, mountain tops usually stand as islands of xeric vegetation among mesophytic assemblages. Unlike the vegetation growing on other rock outcrops lithologies, such as inselbergs (granite/gneiss) or campos rupestres (quartz/arenite), ironstone outcrop plant communities still lack systematic studies in Brazil. These outcrops (locally known as canga) share most of the characteristics of other rock outcrops, such as isolation and edapho-climatic harshness, but differ in that they are the object of opencast mining, and thus subjected to irrecoverable degradation. In addition, they are expected to harbour metal-tolerant and hyperaccumulator plant species. A botanical survey of two ironstone outcrop locations in the most important mining region of southeastern Brazil, the Iron Quadrangle, revealed a high within-site (138 and 160 species per site), and between-site diversity (only 27% of common species), totaling 64 families and 234 species among basal families and eudicots (154 species), monocots (68 species), and ferns (12 species). Canga crusts are rich in dicots, several of which play an important role in community structuring, together with the more usual monocot aggregations. Distinct plant communities are found associated to different microhabitats within the iron crust, depending primarily on the amount of soil and moisture retention in the different microtopographies. The environmental uniqueness, high diversity, lack of studies and rapid destruction of these ecosystems pose an immediate challenge for their conservation.     

Long‐term datasets: From descriptive to predictive data using ecoinformatics

This Special Feature includes contributions on data‐processing of large ecological datasets under the heading ecoinformatics. Herewith the latter term is now al so established in the Journal of Vegetation Science. Ecoinfomatics is introduced as a rapid growing field within community ecology which is generating exciting new developments in ecology and in particular vegetation ecology. In our field, ecoinformatics deals with the understanding of patterns of species distributions at local and regional scales, and on the assemblages of species in relation to their properties, the local environment and their distribution in the region. Community ecology using ecoinformatics is related to bioinformatics, community ecology, biogeography and macroecology. We make clear how ecoinformatics in vegetation science and particularly the IAVS Working Group on Ecoinformatics has developed from the work of the old Working Group for Data Processing which was active during the 1970s and 1980s. Recent developments, including the creation of TURBOVEG and Syn Bio Sys in Europa and VEGBANK in the USA, form a direct link with these pioneer activities, both scientifically and personally. The contributions collected in this Special Feature present examples of seco‐infeveral types of the use of databases and the application of programmes and models. The main types are the study of long‐term vegetation dynamics in different cases of primary and secondary succession and the understanding of successional developments in terms of species traits. Among the future developments of great significance we mention the use of a variety of different large datasets for the study of the distribution and ecology and conservation of rare and threatened species.     

Survey of phosphorylation near drug binding sites in the Protein Data Bank (PDB) and their effects

While it is currently estimated that 40 to 50% of eukaryotic proteins are phosphorylated, little is known about the frequency and local effects of phosphorylation near pharmaceutical inhibitor binding sites. In this study, we investigated how frequently phosphorylation may affect the binding of drug inhibitors to target proteins. We examined the 453 non‐redundant structures of soluble mammalian drug target proteins bound to inhibitors currently available in the Protein Data Bank (PDB). We cross‐referenced these structures with phosphorylation data available from the PhosphoSitePlus database. Three hundred twenty‐two of 453 (71%) of drug targets have evidence of phosphorylation that has been validated by multiple methods or labs. For 132 of 453 (29%) of those, the phosphorylation site is within 12 Å of the small molecule‐binding site, where it would likely alter small molecule binding affinity. We propose a framework for distinguishing between drug‐phosphorylation site interactions that are likely to alter the efficacy of drugs versus those that are not. In addition we highlight examples of well‐established drug targets, such as estrogen receptor alpha, for which phosphorylation may affect drug affinity and clinical efficacy. Our data suggest that phosphorylation may affect drug binding and efficacy for a significant fraction of drug target proteins. Proteins 2015; 83:25–36. © 2014 Wiley Periodicals, Inc.     

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence,full structure,and active site microenvironment similarity

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods.     

Topsoil translocation for Brazilian savanna restoration: propagation of herbs,shrubs, and trees

Topsoil translocation has been used for vegetation restoration throughout the world, but it has been poorly tested within savannas. This study describes Brazilian savanna (cerrado) regeneration for the first 3 years following topsoil translocation. The topsoil was stripped from 2.5 ha of savanna and spread on 1 ha of an abandoned laterite quarry in the Federal District, Brazil. We assessed vegetation structure and species composition in 18 circular plots (3.14/m²) after 5 and 15 months and in 30 circular plots after 37 months. In the last floristic survey, the coverage of herbs was estimated using the step‐point method. To verify the source of regeneration, a total of 181 shrubs and trees were excavated over the first 2 surveys. After 3 years, 24, 40, and 21 species of herbs, shrubs, and trees, respectively, had been recorded by the surveys. Of the 33 families found, Fabaceae, Poaceae, and Asteraceae were the most representative. At 5 and 15 months, 91 and 83% of the individuals (shrubs and trees combined) were derived from resprouting, respectively. Shrub and tree stem density reached 3.2/m² at 5 months, but declined to 0.5/m² at 37 months. By the final survey, native and exotic grasses completely covered the ground. Topsoil translocation was effective for the propagation of native herbs, shrubs, and trees, despite the need to control invasive grasses. The large number of shrub and tree resprouts from roots suggests that the bud bank is an important component of the topsoil for savanna restoration.     

Dietary Intakes and Health Risk of Toxic and Essential Heavy Metals through the Food Chain in Agricultural,Industrial, and Coal Mining Areas of Northern India

Minerals can enter the food chain through industrial and mining activities. Soil-to-vegetable transfer is higher than soil-to-cereal, but human consumption of metals is attributable to balanced diets containing both vegetables and cereals and drinking water. However, the impact of location on intakes of metals from predominantly cereal-based Indian diets is not clear. Hence, the present study was undertaken in selected Agricultural, Industrial, and Coal Mining Areas (AA, IA, CMA) around the Allahabad District in Northern India to compare transfer of toxic metals, Pb, Cd, Cr and essential metals, Fe, Zn, Cu, Co in soil and water to common crops: cereals (rice, wheat, maize) and vegetables (spinach, potato), and to assess Daily Intake of Metal (DIM) and consequent Health Risk Index (HRI). The overall content of all metals, except Cu, in water, soils, and crops followed the pattern CMA > IA > AA. Transfer factors (TFs) followed the sequence spinach > potato > cereals. Quantitatively, however, cereals contribute maximally to a balanced diet, so DIM and HRI were higher from cereals than vegetables. Even though spinach had the highest TFs, cereals contributed maximally to HRI. CMA had the highest metal content so locally grown cereals contributed significantly to intake of both toxic and essential metals.     

Edge effects across boundaries between natural and restored jarrah (Eucalyptus marginata) forests in south‐western Australia

Edge effects are a widespread and ubiquitous ecological phenomenon, yet they remain poorly studied across edges between restored and natural forests. To address this lack of knowledge, we studied vertebrate communities across edges between 3‐year old restored mine‐pits and adjacent unmined forest in the jarrah (Eucalyptus marginata) forest of south‐western Australia. We found that mammal communities showed no edge response but reptile communities did. Overall reptile abundance and Morethia obscura abundance were higher in unmined forest along edges, Egernia napoleonis abundance was lower in unmined forest along edges, while Pogona minor abundance was lower in restored mine‐pits along edges. Predictive models were unable to predict species edge responses, due to the lack of knowledge of the ecology of jarrah forest reptiles, but proved useful in identifying potential ecological mechanisms behind observed edge responses and suggested that potential mechanisms were likely different for each species. Our study is the first to show edge responses in both habitats forming the edge between restored and natural forests, emphasizing the importance of studying both habitats forming the edge. Our results also suggest that, despite being poorly studied, edge responses are common across edges between restored and natural forest and result from a variety of ecological mechanisms. An increased understanding of the ecological mechanisms driving edge responses across edges between restored and natural forests will improve our ability to integrate restored areas into cross‐landscape management and, ultimately, improve our ability to manage landscapes for biodiversity conservation.     

The Streptomyces leeuwenhoekii genome: de novo sequencing and assembly in single contigs of the chromosome,circular plasmid pSLE1 and linear plasmid pSLE2

Background

Next Generation DNA Sequencing (NGS) and genome mining of actinomycetes and other microorganisms is currently one of the most promising strategies for the discovery of novel bioactive natural products, potentially revealing novel chemistry and enzymology involved in their biosynthesis. This approach also allows rapid insights into the biosynthetic potential of microorganisms isolated from unexploited habitats and ecosystems, which in many cases may prove difficult to culture and manipulate in the laboratory. Streptomyces leeuwenhoekii (formerly Streptomyces sp. strain C34) was isolated from the hyper-arid high-altitude Atacama Desert in Chile and shown to produce novel polyketide antibiotics.

Results

Here we present the de novo sequencing of the S. leeuwenhoekii linear chromosome (8 Mb) and two extrachromosomal replicons, the circular pSLE1 (86 kb) and the linear pSLE2 (132 kb), all in single contigs, obtained by combining Pacific Biosciences SMRT (PacBio) and Illumina MiSeq technologies. We identified the biosynthetic gene clusters for chaxamycin, chaxalactin, hygromycin A and desferrioxamine E, metabolites all previously shown to be produced by this strain (J Nat Prod, 2011, 74:1965) and an additional 31 putative gene clusters for specialised metabolites. As well as gene clusters for polyketides and non-ribosomal peptides, we also identified three gene clusters encoding novel lasso-peptides.

Conclusions

The S. leeuwenhoekii genome contains 35 gene clusters apparently encoding the biosynthesis of specialised metabolites, most of them completely novel and uncharacterised. This project has served to evaluate the current state of NGS for efficient and effective genome mining of high GC actinomycetes. The PacBio technology now permits the assembly of actinomycete replicons into single contigs with >99 % accuracy. The assembled Illumina sequence permitted not only the correction of omissions found in GC homopolymers in the PacBio assembly (exacerbated by the high GC content of actinomycete DNA) but it also allowed us to obtain the sequences of the termini of the chromosome and of a linear plasmid that were not assembled by PacBio. We propose an experimental pipeline that uses the Illumina assembled contigs, in addition to just the reads, to complement the current limitations of the PacBio sequencing technology and assembly software.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1652-8) contains supplementary material, which is available to authorized users.     

SeqMaT: A sequence manipulation tool for phylogenetic analysis

Most bioinformatics tools require specialized input formats for sequence comparison and analysis. This is particularly true for molecular phylogeny programs, which accept only certain formats. In addition, it is often necessary to eliminate highly similar sequences among the input, especially when the dataset is large. Moreover, most programs have restrictions upon the sequence name. Here we introduce SeqMaT, a Sequence Manipulation Tool. It has the following functions: data format conversion,sequence name coding and decoding,redundant and highly similar sequence removal, anddata mining utilities. SeqMaT was developed using Java with two versions, web-based and standalone. A standalone program is convenient to manipulate a large number of sequences, while the web version will guarantee wide availability of the tool for researchers and practitioners throughout the Internet. AVAILABILITY: The database is available for free at http://glee.ist.unomaha.edu/seqmat.