The target of rapamycin kinase affects biomass accumulation and cell cycle progression by altering carbon/nitrogen balance in synchronized Chlamydomonas reinhardtii cells.

Several metabolic processes tightly regulate growth and biomass accumulation. A highly conserved protein complex containing the target of rapamycin (TOR) kinase is known to integrate intra- and extracellular stimuli controlling nutrient allocation and hence cellular growth. Although several functions of TOR have been described in various heterotrophic eukaryotes, our understanding lags far behind in photosynthetic organisms. In the present investigation, we used the model alga Chlamydomonas reinhardtii to conduct a time-resolved analysis of molecular and physiological features throughout the diurnal cycle after TOR inhibition. Detailed examination of the cell cycle phases revealed that growth is not only repressed by 50%, but also that significant, non-linear delays in the progression can be observed. By using metabolomics analysis, we elucidated that the growth repression was mainly driven by differential carbon partitioning between anabolic and catabolic processes. Accordingly, the time-resolved analysis illustrated that metabolic processes including amino acid-, starch- and triacylglycerol synthesis, as well RNA degradation, were redirected within minutes of TOR inhibition. Here especially the high accumulation of nitrogen-containing compounds indicated that an active TOR kinase controls the carbon to nitrogen balance of the cell, which is responsible for biomass accumulation, growth and cell cycle progression.

Dynamics of lipids and metabolites during the cell cycle of Chlamydomonas reinhardtii.

Metabolites and lipids are the final products of enzymatic processes, distinguishing the different cellular functions and activities of single cells or whole tissues. Understanding these cellular functions within a well-established model system requires a systemic collection of molecular and physiological information. In the current report, the green alga Chlamydomonas reinhardtii was selected to establish a comprehensive workflow for the detailed multi-omics analysis of a synchronously growing cell culture system. After implementation and benchmarking of the synchronous cell culture, a two-phase extraction method was adopted for the analysis of proteins, lipids, metabolites and starch from a single sample aliquot of as little as 10-15 million Chlamydomonas cells. In a proof of concept study, primary metabolites and lipids were sampled throughout the diurnal cell cycle. The results of these time-resolved measurements showed that single compounds were not only coordinated with each other in different pathways, but that these complex metabolic signatures have the potential to be used as biomarkers of various cellular processes. Taken together, the developed workflow, including the synchronized growth of the photoautotrophic cell culture, in combination with comprehensive extraction methods and detailed metabolic phenotyping has the potential for use in in-depth analysis of complex cellular processes, providing essential information for the understanding of complex biological systems.

Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness.

Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.

Metabolomic analysis indicates a pivotal role of the hepatotoxin microcystin in high light adaptation of Microcystis.

Microcystis is a freshwater cyanobacterium frequently forming nuisance blooms in the summer months. The genus belongs to the predominant producers of the potent hepatotoxin microcystin. The success of Microcystis and its remarkable resistance to high light conditions are not well understood. Here, we have compared the metabolic response of Microcystis aeruginosa PCC7806, its microcystin-deficient ΔmcyB mutant (Mut) and the cyanobacterial model organism Synechocystis PCC6803 to high light exposure of 250 µmol photons m(-2) s(-1) using GC/MS-based metabolomics. Microcystis wild type and Mut show pronounced differences in their metabolic reprogramming upon high light. Seventeen per cent of the detected metabolites showed significant differences between the two genotypes after high light exposure. Whereas the microcystin-producing wild type shows a faster accumulation of glycolate upon high light illumination, loss of microcystin leads to an accumulation of general stress markers such as trehalose and sucrose. The study further uncovers differences in the high light adaptation of the bloom-forming cyanobacterium Microcystis and the model cyanobacterium Synechocystis. Most notably, Microcystis invests more into carbon reserves such as glycogen after high light exposure. Our data shed new light on the lifestyle of bloom-forming cyanobacteria, the role of the widespread toxin microcystin and the metabolic diversity of cyanobacteria.

High-resolution plant metabolomics: from mass spectral features to metabolites and from whole-cell analysis to subcellular metabolite distributions.

The main goal of metabolomics is the comprehensive qualitative and quantitative analysis of the time- and space-resolved distribution of all metabolites present in a given biological system. Because metabolite structures, in contrast to transcript and protein sequences, are not directly deducible from the genomic DNA sequence, the massive increase in genomic information is only indirectly of use to metabolomics, leaving compound annotation as a key problem to be solved by the available analytical techniques. Furthermore, as metabolites vary widely in both concentration and chemical behavior, there is no single analytical procedure allowing the unbiased and comprehensive structural elucidation and determination of all metabolites present in a given biological system. In this review the different approaches for targeted and non-targeted metabolomics analysis will be described with special emphasis on mass spectrometry-based techniques. Particular attention is given to approaches which can be employed for the annotation of unknown compounds. In the second part, the different experimental approaches aimed at tissue-specific or subcellular analysis of metabolites are discussed including a range of non-mass spectrometry based technologies.

On the role of the mitochondrial 2-oxoglutarate dehydrogenase complex in amino acid metabolism.

Mitochondria are tightly linked to cellular nutrient sensing, and provide not only energy, but also intermediates for the de novo synthesis of cellular compounds including amino acids. Mitochondrial metabolic enzymes as generators and/or targets of signals are therefore important players in the distribution of intermediates between catabolic and anabolic pathways. The highly regulated 2-oxoglutarate dehydrogenase complex (OGDHC) participates in glucose oxidation via the tricarboxylic acid cycle. It occupies an amphibolic branch point in the cycle, where the energy-producing reaction of the 2-oxoglutarate degradation competes with glutamate (Glu) synthesis via nitrogen incorporation into 2-oxoglutarate. To characterize the specific impact of the OGDHC inhibition on amino acid metabolism in both plant and animal mitochondria, a synthetic analog of 2-oxoglutarate, namely succinyl phosphonate (SP), was applied to living systems from different kingdoms, both in situ and in vivo. Using a high-throughput mass spectrometry-based approach, we showed that organisms possessing OGDHC respond to SP by significantly changing their amino acid pools. By contrast, cyanobacteria which lack OGDHC do not show perturbations in amino acids following SP treatment. Increases in Glu, 4-aminobutyrate and alanine represent the most universal change accompanying the 2-oxoglutarate accumulation upon OGDHC inhibition. Other amino acids were affected in a species-specific manner, suggesting specific metabolic rearrangements and substrate availability mediating secondary changes. Strong perturbation in the relative abundance of amino acids due to the OGDHC inhibition was accompanied by decreased protein content. Our results provide specific evidence of a considerable role of OGDHC in amino acid metabolism.

High-density kinetic analysis of the metabolomic and transcriptomic response of Arabidopsis to eight environmental conditions.

The time-resolved response of Arabidopsis thaliana towards changing light and/or temperature at the transcriptome and metabolome level is presented. Plants grown at 21°C with a light intensity of 150 µE m⁻² sec⁻¹ were either kept at this condition or transferred into seven different environments (4°C, darkness; 21°C, darkness; 32°C, darkness; 4°C, 85 µE m⁻² sec⁻¹; 21 °C, 75 µE m⁻² sec⁻¹; 21°C, 300 µE m⁻² sec⁻¹ ; 32°C, 150 µE m⁻² sec⁻¹). Samples were taken before (0 min) and at 22 time points after transfer resulting in (8×) 22 time points covering both a linear and a logarithmic time series totaling 177 states. Hierarchical cluster analysis shows that individual conditions (defined by temperature and light) diverge into distinct trajectories at condition-dependent times and that the metabolome follows different kinetics from the transcriptome. The metabolic responses are initially relatively faster when compared with the transcriptional responses. Gene Ontology over-representation analysis identifies a common response for all changed conditions at the transcriptome level during the early response phase (5-60 min). Metabolic networks reconstructed via metabolite-metabolite correlations reveal extensive environment-specific rewiring. Detailed analysis identifies conditional connections between amino acids and intermediates of the tricarboxylic acid cycle. Parallel analysis of transcriptional changes strongly support a model where in the absence of photosynthesis at normal/high temperatures protein degradation occurs rapidly and subsequent amino acid catabolism serves as the main cellular energy supply. These results thus demonstrate the engagement of the electron transfer flavoprotein system under short-term environmental perturbations.

Identification of enzyme activity quantitative trait loci in a Solanum lycopersicum x Solanum pennellii introgression line population.

Activities of 28 enzymes from central carbon metabolism were measured in pericarp tissue of ripe tomato fruits from field trials with an introgression line (IL) population generated by introgressing segments of the genome of the wild relative Solanum pennellii (LA0716) into the modern tomato cultivar Solanum lycopersicum M82. Enzyme activities were determined using a robotized platform in optimized conditions, where the activities largely reflect the level of the corresponding proteins. Two experiments were analyzed from years with markedly different climate conditions. A total of 27 quantitative trait loci were shared in both experiments. Most resulted in increased enzyme activity when a portion of the S. lycopersicum genome was substituted with the corresponding portion of the genome of S. pennellii. This reflects the change in activity between the two parental genotypes. The mode of inheritance was studied in a heterozygote IL population. A similar proportion of quantitative trait loci (approximately 30%) showed additive, recessive, and dominant modes of inheritance, with only 5% showing overdominance. Comparison with the location of putative genes for the corresponding proteins indicates a large role of trans-regulatory mechanisms. These results point to the genetic control of individual enzyme activities being under the control of a complex program that is dominated by a network of trans-acting genes.

Toward the storage metabolome: profiling the barley vacuole.

While recent years have witnessed dramatic advances in our capacity to identify and quantify an ever-increasing number of plant metabolites, our understanding of how metabolism is spatially regulated is still far from complete. In an attempt to partially address this question, we studied the storage metabolome of the barley (Hordeum vulgare) vacuole. For this purpose, we used highly purified vacuoles isolated by silicon oil centrifugation and compared their metabolome with that found in the mesophyll protoplast from which they were derived. Using a combination of gas chromatography-mass spectrometry and Fourier transform-mass spectrometry, we were able to detect 59 (primary) metabolites for which we know the exact chemical structure and a further 200 (secondary) metabolites for which we have strong predicted chemical formulae. Taken together, these metabolites comprise amino acids, organic acids, sugars, sugar alcohols, shikimate pathway intermediates, vitamins, phenylpropanoids, and flavonoids. Of the 259 putative metabolites, some 12 were found exclusively in the vacuole and 34 were found exclusively in the protoplast, while 213 were common in both samples. When analyzed on a quantitative basis, however, there is even more variance, with more than 60 of these compounds being present above the detection limit of our protocols. The combined data were also analyzed with respect to the tonoplast proteome in an attempt to infer specificities of the transporter proteins embedded in this membrane. Following comparison with recent observations made using nonaqueous fractionation of Arabidopsis (Arabidopsis thaliana), we discuss these data in the context of current models of metabolic compartmentation in plants.

Metabolomic and transcriptomic stress response of Escherichia coli.

Environmental fluctuations lead to a rapid adjustment of the physiology of Escherichia coli, necessitating changes on every level of the underlying cellular and molecular network. Thus far, the majority of global analyses of E. coli stress responses have been limited to just one level, gene expression. Here, we incorporate the metabolite composition together with gene expression data to provide a more comprehensive insight on system level stress adjustments by describing detailed time-resolved E. coli response to five different perturbations (cold, heat, oxidative stress, lactose diauxie, and stationary phase). The metabolite response is more specific as compared with the general response observed on the transcript level and is reflected by much higher specificity during the early stress adaptation phase and when comparing the stationary phase response to other perturbations. Despite these differences, the response on both levels still follows the same dynamics and general strategy of energy conservation as reflected by rapid decrease of central carbon metabolism intermediates coinciding with downregulation of genes related to cell growth. Application of co-clustering and canonical correlation analysis on combined metabolite and transcript data identified a number of significant condition-dependent associations between metabolites and transcripts. The results confirm and extend existing models about co-regulation between gene expression and metabolites demonstrating the power of integrated systems oriented analysis.

Combined transcript and metabolite profiling of Arabidopsis grown under widely variant growth conditions facilitates the identification of novel metabolite-mediated regulation of gene expression.

Regulation of metabolism at the level of transcription and its corollary metabolite-mediated regulation of transcription are well-documented mechanisms by which plants adapt to circumstance. That said the function of only a minority of transcription factor networks are fully understood and it seems likely that we have only identified a subset of the metabolites that play a mediator function in the regulation of transcription. Here we describe an integrated genomics approach in which we perform combined transcript and metabolite profiling on Arabidopsis (Arabidopsis thaliana) plants challenged by various environmental extremes. We chose this approach to generate a large variance in the levels of all parameters recorded. The data was then statistically evaluated to identify metabolites whose level robustly correlated with those of a particularly large number of transcripts. Since correlation alone provides no proof of causality we subsequently attempted to validate these putative mediators of gene expression via a combination of statistical analysis of data available in publicly available databases and iterative experimental evaluation. Data presented here suggest that, on adoption of appropriate caution, the approach can be used for the identification of metabolite mediators of gene expression. As an exemplary case study we document that in plants, as in yeast (Saccharomyces cerevisiae) and mammals, leucine plays an important role as a regulator of gene expression and provide a leucine response gene regulatory network.

Enzyme activity profiles during fruit development in tomato cultivars and Solanum pennellii.

Enzymes interact to generate metabolic networks. The activities of more than 22 enzymes from central metabolism were profiled during the development of fruit of the modern tomato cultivar Solanum lycopersicum 'M82' and its wild relative Solanum pennellii (LA0716). In S. pennellii, the mature fruit remains green and contains lower sugar and higher organic acid levels. These genotypes are the parents of a widely used near introgression line population. Enzymes were also profiled in a second cultivar, S. lycopersicum 'Moneymaker', for which data sets for the developmental changes of metabolites and transcripts are available. Whereas most enzyme activities declined during fruit development in the modern S. lycopersicum cultivars, they remained high or even increased in S. pennellii, especially enzymes required for organic acid synthesis. The enzyme profiles were sufficiently characteristic to allow stages of development and cultivars and the wild species to be distinguished by principal component analysis and clustering. Many enzymes showed coordinated changes during fruit development of a given genotype. Comparison of the correlation matrices revealed a large overlap between the two modern cultivars and considerable overlap with S. pennellii, indicating that despite the very different development responses, some basic modules are retained. Comparison of enzyme activity, metabolite profiles, and transcript profiles in S. lycopersicum 'Moneymaker' revealed remarkably little connectivity between the developmental changes of transcripts and enzymes and even less between enzymes and metabolites. We discuss the concept that the metabolite profile is an emergent property that is generated by complex network interactions.

Sample amount alternatives for data adjustment in comparative cyanobacterial metabolomics.

Here we describe an integrative protocol for metabolite extraction and the measurement of three cellular constituents, chlorophyll a, total protein, and glycogen from the same small volume of cyanobacterial cultures that can be used as alternative sample amount parameters for data adjustment in comparative metabolome studies. We conducted recovery experiments to assess the robustness and reproducibility of the measurements obtained for the cellular constituents. Also, we have chosen three profile-intrinsic parameters derived from gas chromatography-mass spectrometry (GC/MS) data in order to test their utility for spectral data adjustment. To demonstrate the relevance of these six parameters, we analyzed three cyanobacteria with greatly different morphologies, comprising a unicellular, a filamentous, and a filamentous biofilm-forming strain. Comparative analysis of GC/MS data from cultures grown under standardized conditions indicated that adjustment of the corresponding metabolite profiles by any of the measured cellular constituents or chosen intrinsic parameters led to similar results with respect to sample cohesion and strain separation. Twenty-one metabolites significantly enriched for the carbohydrate and amine superclasses are mainly responsible for strain separation, with a majority of the remaining metabolites contributing to sample group cohesion. Therefore, we conclude that any of the parameters tested in this study can be used for spectral data adjustment of cyanobacterial strains grown under controlled conditions. However, their use for the differentiation between different stresses or physiological states within a strain remains to be shown. Interestingly, both the adjustment approaches and statistical tests applied effected the detection of metabolic differences and their patterns among the analyzed strains.

Analysis of cytosolic and plastidic serine acetyltransferase mutants and subcellular metabolite distributions suggests interplay of the cellular compartments for cysteine biosynthesis in Arabidopsis.

In plants, the enzymes for cysteine synthesis serine acetyltransferase (SAT) and O-acetylserine-(thiol)-lyase (OASTL) are present in the cytosol, plastids and mitochondria. However, it is still not clearly resolved to what extent the different compartments are involved in cysteine biosynthesis and how compartmentation influences the regulation of this biosynthetic pathway. To address these questions, we analysed Arabidopsis thaliana T-DNA insertion mutants for cytosolic and plastidic SAT isoforms. In addition, the subcellular distribution of enzyme activities and metabolite concentrations implicated in cysteine and glutathione biosynthesis were revealed by non-aqueous fractionation (NAF). We demonstrate that cytosolic SERAT1.1 and plastidic SERAT2.1 do not contribute to cysteine biosynthesis to a major extent, but may function to overcome transport limitations of O-acetylserine (OAS) from mitochondria. Substantiated by predominantly cytosolic cysteine pools, considerable amounts of sulphide and presence of OAS in the cytosol, our results suggest that the cytosol is the principal site for cysteine biosynthesis. Subcellular metabolite analysis further indicated efficient transport of cysteine, gamma-glutamylcysteine and glutathione between the compartments. With respect to regulation of cysteine biosynthesis, estimation of subcellular OAS and sulphide concentrations established that OAS is limiting for cysteine biosynthesis and that SAT is mainly present bound in the cysteine-synthase complex.

Co-expression tools for plant biology: opportunities for hypothesis generation and caveats.

Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology.

Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism.

A systems approach has previously been used to follow the response behaviour of Arabidopsis thaliana plants upon sulphur limitation. A response network was reconstructed from a time series of transcript and metabolite profiles, integrating complex metabolic and transcript data in order to investigate a potential causal relationship. The resulting scale-free network allowed potential transcriptional regulators of sulphur metabolism to be identified. Here, three sulphur-starvation responsive transcription factors, IAA13, IAA28, and ARF-2 (ARF1-Binding Protein), all of which are related to auxin signalling, were selected for further investigation. IAA28 overexpressing and knock-down lines showed no major morphological changes, whereas IAA13- and ARF1-BP-overexpressing plants grew more slowly than the wild type. Steady-state metabolite levels and expression of pathway-relevant genes were monitored under normal and sulphate-depleted conditions. For all lines, changes in transcript and metabolite levels were observed, yet none of these changes could exclusively be linked to sulphur stress. Instead, up- or down-regulation of the transcription factors caused metabolic changes which in turn affected sulphur metabolism. Auxin-relevant transcription factors are thus part of a complex response pattern to nutrient starvation that serve as coordinators of the metabolic shifts driving sulphur homeostasis rather then as direct effectors of the sulphate assimilation pathway. This study provides the first evidence ever presented that correlates auxin-related transcriptional regulators with primary plant metabolism.

ProMEX: a mass spectral reference database for proteins and protein phosphorylation sites.

BACKGROUND: In the last decade, techniques were established for the large scale genome-wide analysis of proteins, RNA, and metabolites, and database solutions have been developed to manage the generated data sets. The Golm Metabolome Database for metabolite data (GMD) represents one such effort to make these data broadly available and to interconnect the different molecular levels of a biological system 1. As data interpretation in the light of already existing data becomes increasingly important, these initiatives are an essential part of current and future systems biology. RESULTS: A mass spectral library consisting of experimentally derived tryptic peptide product ion spectra was generated based on liquid chromatography coupled to ion trap mass spectrometry (LC-IT-MS). Protein samples derived from Arabidopsis thaliana, Chlamydomonas reinhardii, Medicago truncatula, and Sinorhizobium meliloti were analysed. With currently 4,557 manually validated spectra associated with 4,226 unique peptides from 1,367 proteins, the database serves as a continuously growing reference data set and can be used for protein identification and quantification in uncharacterized biological samples. For peptide identification, several algorithms were implemented based on a recently published study for peptide mass fingerprinting 2 and tested for false positive and negative rates. An algorithm which considers intensity distribution for match correlation scores was found to yield best results. For proof of concept, an LC-IT-MS analysis of a tryptic leaf protein digest was converted to mzData format and searched against the mass spectral library. The utility of the mass spectral library was also tested for the identification of phosphorylated tryptic peptides. We included in vivo phosphorylation sites of Arabidopsis thaliana proteins and the identification performance was found to be improved compared to genome-based search algorithms. Protein identification by ProMEX is linked to other levels of biological organization such as metabolite, pathway, and transcript data. The database is further connected to annotation and classification services via BioMoby. CONCLUSION: The ProMEX protein/peptide database represents a mass spectral reference library with the capability of matching unknown samples for protein identification. The database allows text searches based on metadata such as experimental information of the samples, mass spectrometric instrument parameters or unique protein identifier like AGI codes. ProMEX integrates proteomics data with other levels of molecular organization including metabolite, pathway, and transcript information and may thus become a useful resource for plant systems biology studies. The ProMEX mass spectral library is available at http://promex.mpimp-golm.mpg.de/.

Methods, applications and concepts of metabolite profiling: primary metabolism.

In the 1990s the concept of a comprehensive analysis of the metabolic complement in biological systems, termed metabolomics or alternately metabonomics, was established as the last of four cornerstones for phenotypic studies in the post-genomic era. With genomic, transcriptomic, and proteomic technologies in place and metabolomic phenotyping under rapid development all necessary tools appear to be available today for a fully functional assessment of biological phenomena at all major system levels of life. This chapter attempts to describe and discuss crucial steps of establishing and maintaining a gas chromatography/electron impact ionization/ mass spectrometry (GC-EI-MS)-based metabolite profiling platform. GC-EI-MS can be perceived as the first and exemplary profiling technology aimed at simultaneous and non-biased analysis of primary metabolites from biological samples. The potential and constraints of this profiling technology are among the best understood. Most problems are solved as well as pitfalls identified. Thus GC-EI-MS serves as an ideal example for students and scientists who intend to enter the field of metabolomics. This chapter will be biased towards GC-EI-MS analyses but aims at discussing general topics, such as experimental design, metabolite identification, quantification and data mining.

Identification of brassinosteroid-related genes by means of transcript co-response analyses.

The comprehensive systems-biology database (CSB.DB) was used to reveal brassinosteroid (BR)-related genes from expression profiles based on co-response analyses. Genes exhibiting simultaneous changes in transcript levels are candidates of common transcriptional regulation. Combining numerous different experiments in data matrices allows ruling out outliers and conditional changes of transcript levels. CSB.DB was queried for transcriptional co-responses with the BR-signalling components BRI1 and BAK1: 301 out of 9694 genes represented in the nasc0271 database showed co-responses with both genes. As expected, these genes comprised pathway-involved genes (e.g. 72 BR-induced genes), because the BRI1 and BAK1 proteins are required for BR-responses. But transcript co-response takes the analysis a step further compared with direct approaches because BR-related non BR-responsive genes were identified. Insights into networks and the functional context of genes are provided, because factors determining expression patterns are reflected in correlations. Our findings demonstrate that transcript co-response analysis presents a valuable resource to uncover common regulatory patterns of genes. Different data matrices in CSB.DB allow examination of specific biological questions. All matrices are publicly available through CSB.DB. This work presents one possible roadmap to use the CSB.DB resources.

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

BACKGROUND: Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. RESULTS: Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. CONCLUSION: PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.