PathExpress update: the enzyme neighbourhood method of associating gene-expression data with metabolic pathways

The post-genomic era presents us with the challenge of linking the vast amount of raw data obtained with transcriptomic and proteomic techniques to relevant biological pathways. We present an update of PathExpress, a web-based tool to interpret gene-expression data and explore the metabolic network without being restricted to predefined pathways. We define the Enzyme Neighbourhood (EN) as a sub-network of linked enzymes with a limited path length to identify the most relevant sub-networks affected in gene-expression experiments. PathExpress is freely available at: http://bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/

LATERAL BRANCHING OXIDOREDUCTASE acts in the final stages of strigolactone biosynthesis inArabidopsis

Strigolactones are a group of plant compounds of diverse but related chemical structures. They have similar bioactivity across a broad range of plant species, act to optimize plant growth and development, and promote soil microbe interactions. Carlactone, a common precursor to strigolactones, is produced by conserved enzymes found in a number of diverse species. Versions of the MORE AXILLARY GROWTH1 (MAX1) cytochrome P450 from rice and Arabidopsis thaliana make specific subsets of strigolactones from carlactone. However, the diversity of natural strigolactones suggests that additional enzymes are involved and remain to be discovered. Here, we use an innovative method that has revealed a missing enzyme involved in strigolactone metabolism. By using a transcriptomics approach involving a range of treatments that modify strigolactone biosynthesis gene expression coupled with reverse genetics, we identified LATERAL BRANCHING OXIDOREDUCTASE (LBO), a gene encoding an oxidoreductase-like enzyme of the 2-oxoglutarate and Fe(II)-dependent dioxygenase superfamily. Arabidopsis lbo mutants exhibited increased shoot branching, but the lbo mutation did not enhance the max mutant phenotype. Grafting indicated that LBO is required for a graft-transmissible signal that, in turn, requires a product of MAX1. Mutant lbo backgrounds showed reduced responses to carlactone, the substrate of MAX1, and methyl carlactonoate (MeCLA), a product downstream of MAX1. Furthermore, lbo mutants contained increased amounts of these compounds, and the LBO protein specifically converts MeCLA to an unidentified strigolactone-like compound. Thus, LBO function may be important in the later steps of strigolactone biosynthesis to inhibit shoot branching in Arabidopsis and other seed plants

Putative cis-regulatory elements in genes highly expressed in rice sperm cells

<p>Abstract</p> <p>Background</p> <p>The male germ line in flowering plants is initiated within developing pollen grains via asymmetric division. The smaller cell then becomes totally encased within a much larger vegetative cell, forming a unique "cell within a cell structure". The generative cell subsequently divides to give rise to two non-motile diminutive sperm cells, which take part in double fertilization and lead to the seed set. Sperm cells are difficult to investigate because of their presence within the confines of the larger vegetative cell. However, recently developed techniques for the isolation of rice sperm cells and the fully annotated rice genome sequence have allowed for the characterization of the transcriptional repertoire of sperm cells. Microarray gene expression data has identified a subset of rice genes that show unique or highly preferential expression in sperm cells. This information has led to the identification of <it>cis</it>-regulatory elements (CREs), which are conserved in sperm-expressed genes and are putatively associated with the control of cell-specific expression.</p> <p>Findings</p> <p>We aimed to identify the CREs associated with rice sperm cell-specific gene expression data using <it>in silico </it>prediction tools. We analyzed 1-kb upstream regions of the top 40 sperm cell co-expressed genes for over-represented conserved and novel motifs. Analysis of upstream regions with the SIGNALSCAN program with the PLACE database, MEME and the Mclip tool helped to find combinatorial sets of known transcriptional factor-binding sites along with two novel motifs putatively associated with the co-expression of sperm cell-specific genes.</p> <p>Conclusions</p> <p>Our data shows the occurrence of novel motifs, which are putative CREs and are likely targets of transcriptional factors regulating sperm cell gene expression. These motifs can be used to design the experimental verification of regulatory elements and the identification of transcriptional factors that regulate sperm cell-specific gene expression.</p

Structure and evolutionary origin of Ca2+-dependent herring type II antifreeze protein

10.1371/journal.pone.0000548PLoS ONE26

Novel AlkB Dioxygenases—Alternative Models for In Silico and In Vivo Studies

Background: ALKBH proteins, the homologs of Escherichia coli AlkB dioxygenase, constitute a direct, single-protein repair system, protecting cellular DNA and RNA against the cytotoxic and mutagenic activity of alkylating agents, chemicals significantly contributing to tumor formation and used in cancer therapy. In silico analysis and in vivo studies have shown the existence of AlkB homologs in almost all organisms. Nine AlkB homologs (ALKBH1–8 and FTO) have been identified in humans. High ALKBH levels have been found to encourage tumor development, questioning the use of alkylating agents in chemotherapy. The aim of this work was to assign biological significance to multiple AlkB homologs by characterizing their activity in the repair of nucleic acids in prokaryotes and their subcellular localization in eukaryotes. Methodology and Findings: Bioinformatic analysis of protein sequence databases identified 1943 AlkB sequences with eight new AlkB subfamilies. Since Cyanobacteria and Arabidopsis thaliana contain multiple AlkB homologs, they were selected as model organisms for in vivo research. Using E. coli alkB2 mutant and plasmids expressing cyanobacterial AlkBs, we studied the repair of methyl methanesulfonate (MMS) and chloroacetaldehyde (CAA) induced lesions in ssDNA, ssRNA, and genomic DNA. On the basis of GFP fusions, we investigated the subcellular localization of ALKBHs in A. thaliana and established its mostly nucleo-cytoplasmic distribution. Some of the ALKBH proteins were found to change their localization upon MMS treatment. Conclusions: Our in vivo studies showed highly specific activity of cyanobacterial AlkB proteins towards lesions and nucleic acid type. Subcellular localization and translocation of ALKBHs in A. thaliana indicates a possible role for these proteins in the repair of alkyl lesions. We hypothesize that the multiplicity of ALKBHs is due to their involvement in the metabolism of nucleo-protein complexes; we find their repair by ALKBH proteins to be economical and effective alternative to degradation and de novo synthesis

A survey of visualization tools for biological network analysis

The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneity provides a challenge for the visualization of the data. There are a wide variety of graph representations available, which most often map the data on 2D graphs to visualize biological interactions. These methods are applicable to a wide range of problems, nevertheless many of them reach a limit in terms of user friendliness when thousands of nodes and connections have to be analyzed and visualized. In this study we are reviewing visualization tools that are currently available for visualization of biological networks mainly invented in the latest past years. We comment on the functionality, the limitations and the specific strengths of these tools, and how these tools could be further developed in the direction of data integration and information sharing

Oligomerization of ZFYVE27 (Protrudin) Is Necessary to Promote Neurite Extension

ZFYVE27 (Protrudin) was originally identified as an interacting partner of spastin, which is most frequently mutated in hereditary spastic paraplegia. ZFYVE27 is a novel member of FYVE family, which is implicated in the formation of neurite extensions by promoting directional membrane trafficking in neurons. Now, through a yeast two-hybrid screen, we have identified that ZFYVE27 interacts with itself and the core interaction region resides within the third hydrophobic region (HR3) of the protein. We confirmed the ZFYVE27's self-interaction in the mammalian cells by co-immunoprecipitation and co-localization studies. To decipher the oligomeric nature of ZFYVE27, we performed sucrose gradient centrifugation and showed that ZFYVE27 oligomerizes into dimer/tetramer forms. Sub-cellular fractionation and Triton X-114 membrane phase separation analysis indicated that ZFYVE27 is a peripheral membrane protein. Furthermore, ZFYVE27 also binds to phosphatidylinositol 3-phosphate lipid moiety. Interestingly, cells expressing ZFYVE27ΔHR3 failed to produce protrusions instead caused swelling of cell soma. When ZFYVE27ΔHR3 was co-expressed with wild-type ZFYVE27 (ZFYVE27WT), it exerted a dominant negative effect on ZFYVE27WT as the cells co-expressing both proteins were also unable to induce protrusions and showed cytoplasmic swelling. Altogether, it is evident that a functionally active form of oligomer is crucial for ZFYVE27 ability to promote neurite extensions

Experimental design and statistical rigor in phylogenomics of horizontal and endosymbiotic gene transfer

A growing number of phylogenomic investigations from diverse eukaryotes are examining conflicts among gene trees as evidence of horizontal gene transfer. If multiple foreign genes from the same eukaryotic lineage are found in a given genome, it is increasingly interpreted as concerted gene transfers during a cryptic endosymbiosis in the organism's evolutionary past, also known as "endosymbiotic gene transfer" or EGT. A number of provocative hypotheses of lost or serially replaced endosymbionts have been advanced; to date, however, these inferences largely have been post-hoc interpretations of genomic-wide conflicts among gene trees. With data sets as large and complex as eukaryotic genome sequences, it is critical to examine alternative explanations for intra-genome phylogenetic conflicts, particularly how much conflicting signal is expected from directional biases and statistical noise. The availability of genome-level data both permits and necessitates phylogenomics that test explicit, a priori predictions of horizontal gene transfer, using rigorous statistical methods and clearly defined experimental controls

Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships