Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum

Background

The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set.

Results

In this work we propose a new gene set analysis method that computes a gene set score as the mean of absolute values of weighted moderated gene t-scores. The gene weights are designed to emphasize the genes appearing in few gene sets, versus genes that appear in many gene sets. We demonstrate the usefulness of the method when analyzing gene sets that correspond to the KEGG pathways, and hence we called our method P athway A nalysis with D own-weighting of O verlapping G enes (PADOG). Unlike most gene set analysis methods which are validated through the analysis of 2-3 data sets followed by a human interpretation of the results, the validation employed here uses 24 different data sets and a completely objective assessment scheme that makes minimal assumptions and eliminates the need for possibly biased human assessments of the analysis results.

Conclusions

PADOG significantly improves gene set ranking and boosts sensitivity of analysis using information already available in the gene expression profiles and the collection of gene sets to be analyzed. The advantages of PADOG over other existing approaches are shown to be stable to changes in the database of gene sets to be analyzed. PADOG was implemented as an R package available at: http://bioinformaticsprb.med.wayne.edu/PADOG/or http://www.bioconductor.org.     

From genome to function: the Arabidopsis aquaporins

Background

In the post-genomic era newly sequenced genomes can be used to deduce organismal functions from our knowledge of other systems. Here we apply this approach to analyzing the aquaporin gene family in Arabidopsis thaliana. The aquaporins are intrinsic membrane proteins that have been characterized as facilitators of water flux. Originally termed major intrinsic proteins (MIPs), they are now also known as water channels, glycerol facilitators and aqua-glyceroporins, yet recent data suggest that they facilitate the movement of other low-molecular-weight metabolites as well.

Results

The Arabidopsis genome contains 38 sequences with homology to aquaporin in four subfamilies, termed PIP, TIP, NIP and SIP. We have analyzed aquaporin family structure and expression using the A. thaliana genome sequence, and introduce a new NMR approach for the purpose of analyzing water movement in plant roots in vivo.

Conclusions

Our preliminary data indicate a strongly transcellular component for the flux of water in roots.     

Amer2 Protein Interacts with EB1 Protein and Adenomatous Polyposis Coli (APC) and Controls Microtubule Stability and Cell Migration

EB1 is key factor in the organization of the microtubule cytoskeleton by binding to the plus-ends of microtubules and serving as a platform for a number of interacting proteins (termed +TIPs) that control microtubule dynamics. Together with its direct binding partner adenomatous polyposis coli (APC), EB1 can stabilize microtubules. Here, we show that Amer2 (APC membrane recruitment 2), a previously identified membrane-associated APC-binding protein, is a direct interaction partner of EB1 and acts as regulator of microtubule stability together with EB1. Amer2 binds to EB1 via specific (S/T)xIP motifs and recruits it to the plasma membrane. Coexpression of Amer2 and EB1 generates stabilized microtubules at the plasma membrane, whereas knockdown of Amer2 leads to destabilization of microtubules. Knockdown of Amer2, APC, or EB1 reduces cell migration, and morpholino-mediated down-regulation of Xenopus Amer2 blocks convergent extension cell movements, suggesting that the Amer2-EB1-APC complex regulates cell migration by altering microtubule stability.     

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Background

Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult.

Results

S TAR N ET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. S TAR N ET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new H EAT S EEKER module.

Conclusion

S TAR N ET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a S TAR N ET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at http://vanburenlab.medicine.tamhsc.edu/starnet2.html, and does not require user registration.     

Application of robust optimization in matrix-based LCI for decision making under uncertainty

Purpose

When product systems are optimized to minimize environmental impacts, uncertainty in the process data may impact optimal decisions. The purpose of this article is to propose a mathematical method for life cycle assessment (LCA) optimization that protects decisions against uncertainty at the life cycle inventory (LCI) stage.

Methods

A robust optimization approach is proposed for decision making under uncertainty in the LCI stage. The proposed approach incorporates data uncertainty into an optimization problem in which the matrix-based LCI model appears as a constraint. The level of protection against data uncertainty in the technology and intervention matrices can be controlled to reflect varying degrees of conservatism.

Results and discussion

A simple numerical example on an electricity generation product system is used to illustrate the main features of this methodology. A comparison is made between a robust optimization approach, and decision making using a Monte Carlo analysis. Challenges to implement the robust optimization approach on common uncertainty distributions found in LCA and on large product systems are discussed. Supporting source code is available for download at https://github.com/renwang/Robust_Optimization_LCI_Uncertainty.

Conclusions

A robust optimization approach for matrix-based LCI is proposed. The approach incorporates data uncertainties into an optimization framework for LCI and provides a mechanism to control the level of protection against uncertainty. The tool computes optimal decisions that protects against worst-case realizations of data uncertainty. The robust optimal solution is conservative and is able to avoid the negative consequences of uncertainty in decision making.     

Interpreting the ash trend within ombrotrophic bog profiles: atmospheric dust depositions vs. mineralization processes. The Etang de la Gruère case study

Introduction

Ash peaks along ombrotrophic bog profiles may arise from several different processes. In a recent paper, Leifeld and co-authors (Plant Soil 341:349–361, 2011) argued that ash peaks along the Etang de la Gruère (EGr) peat bog profiles are signs of previous periods of higher peat decomposition rather that an indication of periods of elevated dust inputs.

Aims and methods

Here we question the approach and scrutinize results using published data on several peat cores from EGr, demonstrating that peaks in ash content at EGr are very reproducible when cores are carefully collected (e.g., using the Wardenaar corer), and age dated (using ²¹⁰Pb and ¹⁴C).

Results

Data clearly show that variations in ash content along bog profiles cannot be attributed simply, or exclusively, to differences in organic matter mineralization rate, and that averaging the ash contents and normalizing to a single ash peak leads to losses in valuable information and defeats the purpose of detailed paleoenvironmental reconstructions.

Conclusions

Comparing results obtained using sensitive spectroscopic and isotopic tools with the ash content profiles at EGr shows clearly that the distribution of ash and/or acid-insoluble ash cannot be used as a surrogate for the intensity of processes including organic matter mineralization, decomposition and/or humification.     

Estimating the parameters of a 3-D root distribution function from root observations with the trench profile method: case study with simulated and field-observed root data

Background and aims

Root length density (RLD) is a parameter that is difficult to measure, but crucial to estimate water and nutrient uptake by plants. In this study a novel approach is presented to characterize the 3-D root length distribution by supplementing data of the 3-D distribution of root intersections with data of root length density from a limited number of soil cores.

Methods

The method was evaluated in a virtual experiment using the RootTyp model and a field experiment with cauliflower (Brassica oleracea L. botrytis) and leek (Allium porrum, L.).

Results

The virtual experiment shows that total root length and root length distribution can be accurately estimated using the novel approach. Implementation of the method in a field experiment was successful for characterizing the growth of the root distribution with time both for cauliflower and leek. In contrast with the virtual experiment, total root length could not be estimated based upon root intersection measurements in the field.

Conclusions

The novel method of combining root intersection data with root length density data from core samples is a powerful tool to supply root water uptake models with root system information.     

Comparison of central versus peripheral delivery of pregabalin in neuropathic pain states

Background

Although pregabalin therapy is beneficial for neuropathic pain (NeP) by targeting the CaV??₂??-1 subunit, its site of action is uncertain. Direct targeting of the central nervous system may be beneficial for the avoidance of systemic side effects.

Results

We used intranasal, intrathecal, and near-nerve chamber forms of delivery of varying concentrations of pregabalin or saline delivered over 14 days in rat models of experimental diabetic peripheral neuropathy and spinal nerve ligation. As well, radiolabelled pregabalin was administered to determine localization with different deliveries. We evaluated tactile allodynia and thermal hyperalgesia at multiple time points, and then analyzed harvested nervous system tissues for molecular and immunohistochemical changes in CaV??₂??-1 protein expression. Both intrathecal and intranasal pregabalin administration at high concentrations relieved NeP behaviors, while near-nerve pregabalin delivery had no effect. NeP was associated with upregulation of CACNA2D1 mRNA and CaV??₂??-1 protein within peripheral nerve, dorsal root ganglia (DRG), and dorsal spinal cord, but not brain. Pregabalin's effect was limited to suppression of CaV??₂??-1 protein (but not CACNA2D1 mRNA) expression at the spinal dorsal horn in neuropathic pain states. Dorsal root ligation prevented CaV??₂??-1 protein trafficking anterograde from the dorsal root ganglia to the dorsal horn after neuropathic pain initiation.

Conclusions

Either intranasal or intrathecal pregabalin relieves neuropathic pain behaviours, perhaps due to pregabalin's effect upon anterograde CaV??₂??-1 protein trafficking from the DRG to the dorsal horn. Intranasal delivery of agents such as pregabalin may be an attractive alternative to systemic therapy for management of neuropathic pain states.     

Metallothioneins BcMT1 and BcMT2 from Brassica campestris enhance tolerance to cadmium and copper and decrease production of reactive oxygen species in Arabidopsis thaliana

Aims

Metallothioneins are cysteine-rich, metal-binding proteins, but their exact functions are not fully understood. In this study, we isolated two metallothionein genes, BcMT1 and BcMT2 from Brassica campestris to increase our understanding of metal tolerance mechanisms in Brassica plants.

Methods

Semi-quantitative RT-PCR was used to analyze expression of the two BcMTs genes. BcMT1 and BcMT2 were ectopically expressed in Arabidopsis thaliana. Quantitative real-time RT-PCR and GUS-staining method were used to select transgenic Arabidopsis plants. Cd and Cu concentrations were analyzed by flame atomic absorption spectrometry. Histochemical detection of H₂O₂ and O₂ ^?? were conducted by 3,3-diaminobenzidine and nitroblue tetrazoliu-staining methods.

Results

BcMT1 is expressed predominantly in roots, whereas BcMT2 is expressed mainly in leaves of B. campestris. Expression of BcMT1 was induced by both Cd and Cu, but expression of BcMT2 was enhanced only by Cd. Ectopic expression of BcMT1 and BcMT2 in Arabidopsis thaliana enhanced the tolerance to Cd and Cu and increased the Cu concentration in the shoots of the transgenic plants. Transgenic Arabidopsis accumulated less reactive oxygen species (ROS) than wild-type plants.

Conclusions

BcMT1 and BcMT2 increased Cd and Cu tolerance in transgenic Arabidopsis, and decreased production of Cd- and Cu-induced ROS, thereby protecting plants from oxidative damage.