Tobias Czauderna

HTPheno: An image analysis pipeline for high-throughput plant phenotyping

BackgroundIn the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms.ResultsThis paper presents an image analysis pipeline (HTPheno) for high-throughput plant phenotyping. HTPheno is implemented as a plugin for ImageJ, an open source image processing software. It provides the possibility to analyse colour images of plants which are taken in two different views (top view and side view) during a screening. Within the analysis different phenotypical parameters for each plant such as height, width and projected shoot area of the plants are calculated for the duration of the screening. HTPheno is applied to analyse two barley cultivars.ConclusionsHTPheno, an open source image analysis pipeline, supplies a flexible and adaptable ImageJ plugin which can be used for automated image analysis in high-throughput plant phenotyping and therefore to derive new biological insights, such as determination of fitness.

VANTED v2: a framework for systems biology applications

BackgroundExperimental datasets are becoming larger and increasingly complex, spanning different data domains, thereby expanding the requirements for respective tool support for their analysis. Networks provide a basis for the integration, analysis and visualization of multi-omics experimental datasets.ResultsHere we present Vanted (version 2), a framework for systems biology applications, which comprises a comprehensive set of seven main tasks. These range from network reconstruction, data visualization, integration of various data types, network simulation to data exploration combined with a manifold support of systems biology standards for visualization and data exchange. The offered set of functionalities is instantiated by combining several tasks in order to enable users to view and explore a comprehensive dataset from different perspectives. We describe the system as well as an exemplary workflow.ConclusionsVanted is a stand-alone framework which supports scientists during the data analysis and interpretation phase. It is available as a Java open source tool from http://www.vanted.org

Different Hormonal Regulation of Cellular Differentiation and Function in Nucellar Projection and Endosperm Transfer Cells: A Microdissection-Based Transcriptome Study of Young Barley Grains

Nucellar projection (NP) and endosperm transfer cells (ETC) are essential tissues in growing barley (Hordeum vulgare) grains, responsible for nutrient transfer from maternal to filial tissues, endosperm/embryo nutrition, and grain development. A laser microdissection pressure catapulting-based transcriptome analysis was established to study NP and ETC separately using a barley 12K macroarray. A major challenge was to isolate high-quality mRNA from preembedded, fixed tissue while maintaining tissue integrity. We show that probes generated from fixed and embedded tissue sections represent largely the transcriptome (>70%) of nonchemically treated and nonamplified references. In NP, the top-down gradient of cellular differentiation is reflected by the expression of C3HC4-type ubiquitin ligases and different histone genes, cell wall biosynthesis and expansin/extensin genes, as well as genes involved in programmed cell death-related proteolysis coupled to nitrogen remobilization, indicating distinct areas simultaneously undergoing mitosis, cell elongation, and disintegration. Activated gene expression related to gibberellin synthesis and function suggests a regulatory role for gibberellins in establishment of the differentiation gradient. Up-regulation of plasmalemma-intrinsic protein and tonoplast-intrinsic protein genes indicates involvement in nutrient transfer and/or unloading. In ETC, AP2/EREBP-like transcription factors and ethylene functions are transcriptionally activated, a response possibly coupled to activated defense mechanisms. Transcriptional activation of nucleotide sugar metabolism may be attributed to ascorbate synthesis and/or cell wall biosynthesis. These processes are potentially controlled by trehalose-6-P synthase/phosphatase, as suggested by expression of their respective genes. Up-regulation of amino acid permeases in ETC indicates important roles in active nutrient uptake from the apoplastic space into the endosperm.

Path2Models: large-scale generation of computational models from biochemical pathway maps

BackgroundSystems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo, based on literature mining and the manual processing of pathway data.ResultsTo increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models. Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps.ConclusionsTo date, the project has resulted in more than 140 000 freely available models. Such a resource can tremendously accelerate the development of mathematical models by providing initial starting models for simulation and analysis, which can be subsequently curated and further parameterized.

Editing, validating and translating of SBGN maps

Motivation: The recently proposed Systems Biology Graphical Notation (SBGN) provides a standard for the visual representation of biochemical and cellular processes. It aims to support more efficient and accurate communication of biological knowledge between different research communities in the life sciences. However, to increase the use of SBGN, tools for editing, validating and translating SBGN maps are desirable. Results: We present SBGN-ED, a tool which allows the creation of all three types of SBGN maps from scratch or the editing of existing maps, the validation of these maps for syntactical and semantical correctness, the translation of networks from the KEGG and MetaCrop databases into SBGN and the export of SBGN maps into several file and image formats. Availability: SBGN-ED is freely available from http://vanted.ipk-gatersleben.de/addons/sbgn-ed. The web site contains also tutorials and example files. Contact: schreibe@ipk-gatersleben.de

Software support for SBGN maps

Motivation: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner. Availability and implementation: Milestone 2 was released in December 2011. Source code, example files and binaries are freely available under the terms of either the LGPL v2.1+ or Apache v2.0 open source licenses from http://libsbgn.sourceforge.net. Contact: sbgn-libsbgn@lists.sourceforge.net

MetaCrop 2.0: managing and exploring information about crop plant metabolism

MetaCrop is a manually curated repository of high-quality data about plant metabolism, providing different levels of detail from overview maps of primary metabolism to kinetic data of enzymes. It contains information about seven major crop plants with high agronomical importance and two model plants. MetaCrop is intended to support research aimed at the improvement of crops for both nutrition and industrial use. It can be accessed via web, web services and an add-on to the Vanted software. Here, we present several novel developments of the MetaCrop system and the extended database content. MetaCrop is now available in version 2.0 at http://metacrop.ipk-gatersleben.de.

Intraspecific hybrids of Arabidopsis thaliana revealed no gross alterations in endopolyploidy, DNA methylation, histone modifications and transcript levels

Arabidopsis accessions Col-0 and C24 and their reciprocal hybrids were employed as a model system to investigate the potential relationship between changes in DNA methylation, chromatin structure, endopolyploidization and gene expression in heterotic genotypes. Nucleolus size, endopolyploidization level and distribution of DNA and histone H3 methylation at the microscopic level does not differ between parents and their hybrids. Methylation sensitive amplified polymorphism revealed a largely constant pattern of DNA methylation (97% of signals analyzed) after intraspecific crosses. The parental expression profile of selected genes was maintained in hybrid offspring. No correlation was found between expression pattern and DNA methylation levels at restriction sites within 5′ regulatory regions. Thus, the results revealed only minor changes of chromatin properties and other nuclear features in response to intraspecific hybridization in Arabidopsis thaliana.

OPTIMAS-DW: A comprehensive transcriptomics, metabolomics, ionomics, proteomics and phenomics data resource for maize

BackgroundMaize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource for bioenergy. When looking at the problems of limited fossil fuels, the growth of the world’s population or the world’s climate change, it is important to find ways to increase the yield and biomass of maize and to study how it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology project maize plants were grown under a large set of controlled stress conditions, phenotypically characterised and plant material was harvested to analyse the effect of specific environmental conditions or developmental stages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plant material allowing the comparison of results across different omics domains. A data warehouse was developed to store experimental data as well as analysis results of the performed experiments.DescriptionThe OPTIMAS Data Warehouse (OPTIMAS-DW) is a comprehensive data collection for maize and integrates data from different data domains such as transcriptomics, metabolomics, ionomics, proteomics and phenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe the functions of the selected unigenes. Several treatment- and plant growth stage experiments were performed and measured data were filled into data templates and imported into the data warehouse by a Java based import tool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW including all data domains. Furthermore, the user can filter the data to extract information of particular interest. All data can be exported into different file formats for further data analysis and visualisation. The data analysis integrates data from different data domains and enables the user to find answers to different systems biology questions. Finally, maize specific pathway information is provided.ConclusionsWith OPTIMAS-DW a data warehouse for maize was established, which is able to handle different data domains, comprises several analysis results that will support researchers within their work and supports systems biological research in particular. The system is available at http://www.optimas-bioenergy.org/optimas_dw.

Toward Community Standards and Software for Whole-Cell Modeling

Objective: Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate comprehensive models of complex cells. Methods: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in the Systems Biology Markup Language. Results: Our analysis revealed several challenges to representing WC models using the current standards. Conclusion: We, therefore, propose several new WC modeling standards, software, and databases. Significance: We anticipate that these new standards and software will enable more comprehensive models.