Arabidopsis MLO2 is a negative regulator of sensitivity to extracellular reactive oxygen species

The atmospheric pollutant ozone (O₃ ) is a strong oxidant that causes extracellular reactive oxygen species (ROS) formation, has significant ecological relevance, and is used here as a non-invasive ROS inducer to study plant signalling. Previous genetic screens identified several mutants exhibiting enhanced O₃ sensitivity, but few with enhanced tolerance. We found that loss-of-function mutants in Arabidopsis MLO2, a gene implicated in susceptibility to powdery mildew disease, exhibit enhanced dose-dependent tolerance to O₃ and extracellular ROS, but a normal response to intracellular ROS. This phenotype is increased in a mlo2 mlo6 mlo12 triple mutant, reminiscent of the genetic redundancy of MLO genes in powdery mildew resistance. Stomatal assays revealed that enhanced O₃ tolerance in mlo2 mutants is not caused by altered stomatal conductance. We explored modulation of the mlo2-associated O₃ tolerance, powdery mildew resistance, and early senescence phenotypes by genetic epistasis analysis, involving mutants with known effects on ROS sensitivity or antifungal defence. Mining of publicly accessible microarray data suggests that these MLO proteins regulate accumulation of abiotic stress response transcripts, and transcript accumulation of MLO2 itself is O₃ responsive. In summary, our data reveal MLO2 as a novel negative regulator in plant ROS responses, which links biotic and abiotic stress response pathways.

DynOmics to identify delays and co-expression patterns across time course experiments

Dynamic changes in biological systems can be captured by measuring molecular expression from different levels (e.g., genes and proteins) across time. Integration of such data aims to identify molecules that show similar expression changes over time; such molecules may be co-regulated and thus involved in similar biological processes. Combining data sources presents a systematic approach to study molecular behaviour. It can compensate for missing data in one source, and can reduce false positives when multiple sources highlight the same pathways. However, integrative approaches must accommodate the challenges inherent in ‘omics’ data, including high-dimensionality, noise, and timing differences in expression. As current methods for identification of co-expression cannot cope with this level of complexity, we developed a novel algorithm called DynOmics. DynOmics is based on the fast Fourier transform, from which the difference in expression initiation between trajectories can be estimated. This delay can then be used to realign the trajectories and identify those which show a high degree of correlation. Through extensive simulations, we demonstrate that DynOmics is efficient and accurate compared to existing approaches. We consider two case studies highlighting its application, identifying regulatory relationships across ‘omics’ data within an organism and for comparative gene expression analysis across organisms.

Retrieving relevant time-course experiments: a study on Arabidopsis microarrays

Understanding time-course regulation of genes in response to a stimulus is a major concern in current systems biology. The problem is usually approached by computational methods to model the gene behaviour or its networked interactions with the others by a set of latent parameters. The model parameters can be estimated through a meta-analysis of available data obtained from other relevant experiments. The key question here is how to find the relevant experiments which are potentially useful in analysing current data. In this study, the authors address this problem in the context of time-course gene expression experiments from an information retrieval perspective. To this end, they introduce a computational framework that takes a time-course experiment as a query and reports a list of relevant experiments retrieved from a given repository. These retrieved experiments can then be used to associate the environmental factors of query experiment with the findings previously reported. The model is tested using a set of time-course Arabidopsis microarrays. The experimental results show that relevant experiments can be successfully retrieved based on content similarity.

Photosystem II Repair and Plant Immunity: Lessons Learned from Arabidopsis Mutant Lacking the THYLAKOID LUMEN PROTEIN 18.3

Chloroplasts play an important role in the cellular sensing of abiotic and biotic stress. Signals originating from photosynthetic light reactions, in the form of redox and pH changes, accumulation of reactive oxygen and electrophile species or stromal metabolites are of key importance in chloroplast retrograde signaling. These signals initiate plant acclimation responses to both abiotic and biotic stresses. To reveal the molecular responses activated by rapid fluctuations in growth light intensity, gene expression analysis was performed with Arabidopsis thaliana wild type and the tlp18.3 mutant plants, the latter showing a stunted growth phenotype under fluctuating light conditions (Biochem. J, 406, 415-425). Expression pattern of genes encoding components of the photosynthetic electron transfer chain did not differ between fluctuating and constant light conditions, neither in wild type nor in tlp18.3 plants, and the composition of the thylakoid membrane protein complexes likewise remained unchanged. Nevertheless, the fluctuating light conditions repressed in wild-type plants a broad spectrum of genes involved in immune responses, which likely resulted from shade-avoidance responses and their intermixing with hormonal signaling. On the contrary, in the tlp18.3 mutant plants there was an imperfect repression of defense-related transcripts upon growth under fluctuating light, possibly by signals originating from minor malfunction of the photosystem II (PSII) repair cycle, which directly or indirectly modulated the transcript abundances of genes related to light perception via phytochromes. Consequently, a strong allocation of resources to defense reactions in the tlp18.3 mutant plants presumably results in the stunted growth phenotype under fluctuating light.

Modelling-based experiment retrieval: a case study with gene expression clustering

MOTIVATION

Public and private repositories of experimental data are growing to sizes that require dedicated methods for finding relevant data. To improve on the state of the art of keyword searches from annotations, methods for content-based retrieval have been proposed. In the context of gene expression experiments, most methods retrieve gene expression profiles, requiring each experiment to be expressed as a single profile, typically of case versus control. A more general, recently suggested alternative is to retrieve experiments whose models are good for modelling the query dataset. However, for very noisy and high-dimensional query data, this retrieval criterion turns out to be very noisy as well.

RESULTS

We propose doing retrieval using a denoised model of the query dataset, instead of the original noisy dataset itself. To this end, we introduce a general probabilistic framework, where each experiment is modelled separately and the retrieval is done by finding related models. For retrieval of gene expression experiments, we use a probabilistic model called product partition model, which induces a clustering of genes that show similar expression patterns across a number of samples. The suggested metric for retrieval using clusterings is the normalized information distance. Empirical results finally suggest that inference for the full probabilistic model can be approximated with good performance using computationally faster heuristic clustering approaches (e.g. k-means). The method is highly scalable and straightforward to apply to construct a general-purpose gene expression experiment retrieval method.

AVAILABILITY AND IMPLEMENTATION

The method can be implemented using standard clustering algorithms and normalized information distance, available in many statistical software packages.

CONTACT

paul.blomstedt@aalto.fi or samuel.kaski@aalto.fi

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integration of photosynthesis, development and stress as an opportunity for plant biology

With the tremendous progress of the past decades, molecular plant science is becoming more unified than ever. We now have the exciting opportunity to further connect subdisciplines and understand plants as whole organisms, as will be required to efficiently utilize them in natural and agricultural systems to meet human needs. The subfields of photosynthesis, plant developmental biology and plant stress are used as examples to discuss how plant science can become better integrated. The challenges, strategies and rich opportunities for the integration of the plant sciences are discussed. In recent years, more and more overlap between various subdisciplines has been inadvertently discovered including tradeoffs that may occur in plants engineered for biotechnological applications. Already important, bioinformatics and computational modelling will become even more central to structuring and understanding the ever growing amounts of data. The process of integrating and overlapping fields in plant biology research is advancing, but plant science will benefit from dedicating more effort and urgency to reach across its boundaries.

Large-Scale Phenomics Identifies Primary and Fine-Tuning Roles for CRKs in Responses Related to Oxidative Stress

Cysteine-rich receptor-like kinases (CRKs) are transmembrane proteins characterized by the presence of two domains of unknown function 26 (DUF26) in their ectodomain. The CRKs form one of the largest groups of receptor-like protein kinases in plants, but their biological functions have so far remained largely uncharacterized. We conducted a large-scale phenotyping approach of a nearly complete crk T-DNA insertion line collection showing that CRKs control important aspects of plant development and stress adaptation in response to biotic and abiotic stimuli in a non-redundant fashion. In particular, the analysis of reactive oxygen species (ROS)-related stress responses, such as regulation of the stomatal aperture, suggests that CRKs participate in ROS/redox signalling and sensing. CRKs play general and fine-tuning roles in the regulation of stomatal closure induced by microbial and abiotic cues. Despite their great number and high similarity, large-scale phenotyping identified specific functions in diverse processes for many CRKs and indicated that CRK2 and CRK5 play predominant roles in growth regulation and stress adaptation, respectively. As a whole, the CRKs contribute to specificity in ROS signalling. Individual CRKs control distinct responses in an antagonistic fashion suggesting future potential for using CRKs in genetic approaches to improve plant performance and stress tolerance.

Retrieving relevant experiments: The case of microRNA microarrays

Content-based retrieval of biological experiments in large public repositories is a recent challenge in computational biology and bioinformatics. The task is, in general, to search in a database using a query-by-example without any experimental meta-data annotation. Here, we consider a more specific problem that seeks a solution for retrieving relevant microRNA experiments from microarray repositories. A computational framework is proposed with this objective. The framework adapts a normal-uniform mixture model for identifying differentially expressed microRNAs in microarray profiling experiments. A rank-based thresholding scheme is offered to binarize real-valued experiment fingerprints based on differential expression. An effective similarity metric is introduced to compare categorical fingerprints, which in turn infers the relevance between two experiments. Two different views of experimental relevance are evaluated, one for disease association and another for embryonic germ layer, to discern the retrieval ability of the proposed model. To the best of our knowledge, the experiment retrieval task is investigated for the first time in the context of microRNA microarrays.

Apoplastic and chloroplastic redox signaling networks in plant stress responses

SIGNIFICANCE

Interplay among apoplastic and chloroplastic redox signaling networks is emerging as a key mechanism in plant stress responses.

RECENT ADVANCES

Recent research has revealed components involved in apoplastic and chloroplastic redox signaling. Also, the sequence of events from stress perception, activation of apoplastic reactive oxygen species (ROS) burst through NADPH oxidases, cytoplasmic and chloroplastic Ca(2+)-transients, and organellar redox signals to physiological responses is starting to emerge. Moreover, a functional overlap between light acclimation and plant immunity in photosynthetically active tissues has been demonstrated.

CRITICAL ISSUES

Any deviations from the basal cellular redox balance may induce acclimation responses that continuously readjust cellular functions. However, diversion of resources to stress responses may lead to attenuation of growth, and exaggeration of defensive reactions may thus be detrimental to the plant. The ultimate outcome of acclimation responses must therefore be tightly controlled by the redox signaling networks between organellar and apoplastic signaling systems.

FUTURE DIRECTIONS

Two major questions still remain to be solved: the sensory mechanism for ROS and the components involved in relaying the signals from the apoplast to the chloroplast. A comprehensive view of regulatory networks will facilitate the understanding on how environmental factors affect the production of phytonutrients and biomass in plants. Translation of such information from model plants to crop species will be at the cutting edge of research in the near future. These challenges give a frame for future studies on ROS and redox regulation of stress acclimation in photosynthetic organisms.

Apoplastic and chloroplastic redox signaling networks in plant stress responses

SIGNIFICANCE

Interplay among apoplastic and chloroplastic redox signaling networks is emerging as a key mechanism in plant stress responses.

RECENT ADVANCES

Recent research has revealed components involved in apoplastic and chloroplastic redox signaling. Also, the sequence of events from stress perception, activation of apoplastic reactive oxygen species (ROS) burst through NADPH oxidases, cytoplasmic and chloroplastic Ca(2+)-transients, and organellar redox signals to physiological responses is starting to emerge. Moreover, a functional overlap between light acclimation and plant immunity in photosynthetically active tissues has been demonstrated.

CRITICAL ISSUES

Any deviations from the basal cellular redox balance may induce acclimation responses that continuously readjust cellular functions. However, diversion of resources to stress responses may lead to attenuation of growth, and exaggeration of defensive reactions may thus be detrimental to the plant. The ultimate outcome of acclimation responses must therefore be tightly controlled by the redox signaling networks between organellar and apoplastic signaling systems.

FUTURE DIRECTIONS

Two major questions still remain to be solved: the sensory mechanism for ROS and the components involved in relaying the signals from the apoplast to the chloroplast. A comprehensive view of regulatory networks will facilitate the understanding on how environmental factors affect the production of phytonutrients and biomass in plants. Translation of such information from model plants to crop species will be at the cutting edge of research in the near future. These challenges give a frame for future studies on ROS and redox regulation of stress acclimation in photosynthetic organisms.

STIFDB2: an updated version of plant stress-responsive transcription factor database with additional stress signals, stress-responsive transcription factor binding sites and stress-responsive genes in Arabidopsis and rice

Understanding the principles of abiotic and biotic stress responses, tolerance and adaptation remains important in plant physiology research to develop better varieties of crop plants. Better understanding of plant stress response mechanisms and application of knowledge derived from integrated experimental and bioinformatics approaches are gaining importance. Earlier, we showed that compiling a database of stress-responsive transcription factors and their corresponding target binding sites in the form of Hidden Markov models at promoter, untranslated and upstream regions of stress-up-regulated genes from expression analysis can help in elucidating various aspects of the stress response in Arabidopsis. In addition to the extensive content in the first version, STIFDB2 is now updated with 15 stress signals, 31 transcription factors and 5,984 stress-responsive genes from three species (Arabidopsis thaliana, Oryza sativa subsp. japonica and Oryza sativa subsp. indica). We have employed an integrated biocuration and genomic data mining approach to characterize the data set of transcription factors and consensus binding sites from literature mining and stress-responsive genes from the Gene Expression Omnibus. STIFDB2 currently has 38,798 associations of stress signals, stress-responsive genes and transcription factor binding sites predicted using the Stress-responsive Transcription Factor (STIF) algorithm, along with various functional annotation data. As a unique plant stress regulatory genomics data platform, STIFDB2 can be utilized for targeted as well as high-throughput experimental and computational studies to unravel principles of the stress regulome in dicots and gramineae. STIFDB2 is available from the URL: http://caps.ncbs.res.in/stifdb2.