Plastic gene expression in a reef coral

Microarray analysis reveals transcriptional plasticity in the reef building coral Acropora millepora.
Bay L, Ulstrup K, Nielsen H, Jarmer H, Goffard N, Willis B, Miller D, VAN Oppen M.
Mol Ecol. 2009 Jul;18(14):3062-75.

We investigated variation in transcript abundance in the scleractinian coral, Acropora millepora, within and between populations characteristically exposed to different turbidity regimes and hence different levels of light and suspended particulate matter. We examined phenotypic plasticity by comparing levels of gene expression between source populations and following 10 days of acclimatization to a laboratory environment. Analyses of variance revealed that 0.05% of genes were differentially expressed between source populations, 1.32% following translocation into a common laboratory and 0.07% in the interaction (source population-dependent responses to translocation). Functional analyses identified an over-representation of differentially expressed genes associated with metabolism and fluorescence categories (primarily downregulated), and environmental information processing (primarily upregulated) following translocation to a lower light and turbidity environment. Such metabolic downregulation may indicate nonoxidative stress, hibernation or caloric restriction associated with the changed environmental conditions. Green fluorescent protein-related genes were the most differentially expressed and were exclusively downregulated; however, green fluorescent protein levels remained unchanged following translocation. Photophysiological responses of corals from both locations were characterized by a decline when introduced to the common laboratory environment but remained healthy (F(v)/F(m) > 0.6). Declines in total lipid content following translocation were the greatest for inshore corals, suggesting that turbid water corals have a strong reliance on heterotrophic feeding.

PathExpress update

The enzyme neighbourhood method of associating gene-expression data with metabolic pathways
Goffard N, Frickey T, Weiller G.
Nucleic Acids Res. 2009 Jul 1;37(Web Server issue):W335-9.

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/.

An Ecological Microarray Study of Coral Bleaching

Seneca F, Foret S, Goffard N, Smith C, Grasso L, Hayward D, Saint R, van Oppen M, Ball E, Miller D.

In: 11th International Coral Reef Symposium. Fort Lauderdale (USA); 2008. In: 11th Pacific Science Inter-congress: PSI 20009. Tahiti (French Polynesia); 2009

Reef building corals live close to their upper thermal tolerance limit and prolonged exposure to temperatures exceeding 31°C induces coral bleaching – the expulsion of Symbiodinium sp. which is often the first step toward mass mortality. Current projections suggest that average tropical ocean temperatures could warm by 1-3°C by the end of this century, so unless corals have the capacity for adaptation to anthropogenically induced climate change, those species that survive are likely to undergo dramatic shifts in distribution patterns. To investigate coral stress responses at a fundamental level we used microarrays of approximately 17,000 expressed sequence tags (ESTs) from the hermatypic coral Acropora millepora to attempt to identify genes responsible for individual fitness and the capacity to survive. Bleaching responses have traditionally been investigated largely by sub jecting corals to acute thermal stress in vitro.
Our approach has focussed on several coral colonies growing in a single bay that have been sampled in situ through a natural bleaching episode and the subsequent recovery period. During the sampling period, water temperature was continuously monitored (at 15 min intervals) and symbiont density recorded at monthly intervals as a measure of bleaching status. Individual colonies differed dramatically in their overall responses to similar environmental conditions – the extent of reduction of symbiont density varied considerably and, whereas some colonies recovered after the summer period, others died. Microarray experiments on a subset of colonies, which showed similar patterns of symbiont loss, identified a large number of genes with expression significantly correlated to decreases in symbiont density. The implications of these experiments in terms of understanding the mechanisms by which corals respond during bleaching episodes will be discussed.

Bioinformatics applied to infectious diseases

Goffard N

In: 11th Pacific Science Inter-congress – PSI 2009, Tahiti (French Polynesia); 2009

To face up to the threat of emerging infectious disease, one of the major challenge is to understand the molecular
mechanisms of pathogenesis, host immunity, environmental adaptation in pathogens and drug resistance. The objective is to facilitate the development of therapeutics, diagnostics and vaccines to combat the diseases. With the recent advances in high-throughput experimental technologies, bioinformatics has an essential role in deciphering the vast amount of data generated and in organizing information gathered from traditional biology. Applied to the study of infectious diseases, bioinformatics permits a gene survey of related biological sequences, which consists of molecular characterisation, structure prediction, phylogenetic analysis and regulatory motif prediction. Bioinformatics has also become an integral part of the investigation of the biological complexity of host-pathogen interactions. For example, the increasing number of genome sequences available in public databases, produced by novel sequencing technologies, not only enhances studies of biodiversity and molecular epidemiology but also allows to explore the dynamic processes of co-evolution in host-pathogen systems. During the last decade, a variety of other experimental systems have been developed allowing bioinformatics analysis at the genome scale giving insights into host responses against pathogens such as microarrays for transcriptional or protein expression profiling, genetic screening systems like the yeast-two-hybrid system used to identify pairwise protein interactions and novel mass spectrometry approaches. The integration of system-wide approaches, including transcriptomics, metabolomics, proteomics and high- throughput techniques, increases understanding of the fundamental mechanisms leading to the development of innovative strategies to deal effectively against infectious diseases.

Legume Seed Proteomic

The proteome of seed development in the model legume Lotus japonicus
Dam S, Laursen BS, Ornfelt JH, Jochimsen B, Stærfeldt HH, Friis C, Nielsen K, Goffard N, Besenbacher S, Krusell L, Sato S, Tabata S, Thogersen IB, Enghild JJ, Stougaard J.
Plant Physiol. 2009 Mar;149(3):1325-40.

We have characterized the development of seeds in the model legume Lotus japonicus. Like soybean and pea, Lotus develops straight seed pods and each pod contains approximately 20 seeds that reach maturity within 40 days. Histological sections show the characteristic three developmental phases of legume seeds and the presence of embryo, endosperm and seed coat in desiccated seeds. Furthermore, protein, oil, starch, phytic acid, and ash contents were determined and this indicates that the composition of mature Lotus seed is more similar to soybean than pea. In a first attempt to determine the seed proteome both a 2-D PAGE approach and a GeLC-MS/MS approach were used. Globulins were analyzed by 2-D PAGE and five legumins, LLP1-5, and two convicilins, LCP1-2, were identified by MALDI Q-TOF mass spectrometry. For two distinct developmental phases, seed filling and desiccation, a GeLC-MS/MS approach was used, and 665 and 181 unique proteins corresponding to gene accession numbers were identified for the two phases respectively. All the proteome data including the experimental data and MS spectra peaks were collected in a database that is available to the scientific community via a web-interface. This database establishes the basis for relating physiology, biochemistry and regulation of seed development in Lotus. Together with a new a web-interface collecting all protein identifications for Lotus, Medicago, and soybean seed proteomes, this database is a valuable resource for comparative seed proteomics and pathway analysis within and beyond the legume family.

Genome-wide transcriptional analysis of super-embryogenic M. truncatula explant cultures

Imin N, Goffard N, Nizamidin M, Rolfe BG.

BMC Plant Biol (2008) vol. 8 (1) pp. 110

BACKGROUND: The Medicago truncatula (M. truncatula) line 2HA has a 500-fold greater capacity to regenerate plants in culture by somatic embryogenesis than its wild type progenitor Jemalong. To understand the molecular basis for the regeneration capacity of this super-embryogenic line 2HA, using Affymetrix GeneChip(R), we have compared transcriptomes of explant leaf cultures of these two lines that were grown on media containing the auxin NAA (1-naphthaleneacetic acid) and the cytokinin BAP (6-benzylaminopurine) for two weeks, an early time point for tissue culture proliferation.
RESULTS: Using Affymetrix GeneChip(R), GCRMA normalisation and statistical analysis, we have showed that more than 196 and 49 probes were significantly (p<0.05) up- or down-regulated respectively more than 2 fold in expression. We have utilised GeneBins, a database for classifying gene expression data to distinguish differentially displayed pathways among these two cultures which showed changes in number of biochemical pathways including carbon and flavonoid biosynthesis, phytohormone biosynthesis and signalling. The up-regulated genes in the embryogenic 2HA culture included nodulins, transporters, regulatory genes, embryogenesis related arabinogalactans and genes involved in redox homeostasis, the transition from vegetative growth to reproductive growth and cytokinin signalling. Down-regulated genes included protease inhibitors, wound-induced proteins, and genes involved in biosynthesis and signalling of phytohormones auxin, gibberellin and ethylene. These changes indicate essential differences between the super-embryogenic line 2HA and Jemalong not only in many aspects of biochemical pathways but also in their response to auxin and cytokinin. To validate the GeneChip results, we used quantitative real-time RT-PCR to examine the expression of the genes up-regulated in 2HA such as transposase, RNA-directed DNA polymerase, regulator of chromosome condensation, RESPONSE REGULATOR 10, AGAMOUS-LIKE 20, flower promoting factor 1, nodulin 3, fasciclin and lipoxygenase, and a down-regulated gene ETHYLENE INSENSITIVE 3, all of which positively correlated with the microarray data.
CONCLUSION: We have described the differences in transcriptomes between the M. truncatula super-embryogenic line 2HA and its non-embryogenic progenitor Jemalong at an early time point. This data will facilitate the mapping of regulatory and metabolic networks involved in the gaining totipotency and regeneration capacity in M. truncatula and provides candidates for functional analysis.

Exploring the Enzyme Neighbourhood to interpret gene expression data

Goffard N, Frickey T, Imin N, Weiller G.

In: German Conference on Bioinformatics: GCB 2008. Dresden (Germany); 2008.

Post-genomic data analysis represents a new challenge to link and interpret the vast amount of raw data obtained with transcriptomic or proteomic techniques in the context of metabolic pathways. We propose a new strategy with the help of a metabolic network graph to extend PathExpress, a web-based tool to interpret gene expression data, without being restricted to predefined pathways. We defined the Enzyme Neighbourhood as groups of linked enzymes, corresponding to a sub-network, to explore the metabolic network in order to identify the most relevant sub-networks affected in gene expression experiments.

Transcriptional profiling of Medicago truncatula meristematic root cells

Holmes P, Goffard N, Weiller GF, Rolfe BG, Imin N.

BMC Plant Biol (2008) vol. 8 (1) pp. 21

BACKGROUND: The root apical meristem of crop and model legume Medicago truncatula is a significantly different stem cell system to that of the widely studied model plant species Arabidopsis thaliana. In this study we used the Affymetrix Medicago GeneChipA(R) to compare the transcriptomes of meristem and non-meristematic root to identify root meristem specific candidate genes.
RESULTS: Using mRNA from root meristem and non-meristem we were able to identify 324 and 363 transcripts differentially expressed from the two regions. With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots.
CONCLUSIONS: This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array. This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

Bioinformatic analysis of the CLE signaling peptide family

Oelkers K, Goffard N, Weiller GF, Gresshoff PM, Mathesius U, Frickey T.

BMC Plant Biol (2008) vol. 8 pp. 1

BACKGROUND: Plants encode a large number of leucine-rich repeat receptor-like kinases. Legumes encode several LRR-RLK linked to the process of root nodule formation, the ligands of which are unknown. To identify ligands for these receptors, we used a combination of profile hidden Markov models and position-specific iterative BLAST, allowing us to detect new members of the CLV3/ESR (CLE) protein family from publicly available sequence databases.
RESULTS: We identified 114 new members of the CLE protein family from various plant species, as well as five protein sequences containing multiple CLE domains. We were able to cluster the CLE domain proteins into 13 distinct groups based on their pairwise similarities in the primary CLE motif. In addition, we identified secondary motifs that coincide with our sequence clusters. The groupings based on the CLE motifs correlate with known biological functions of CLE signaling peptides and are analogous to groupings based on phylogenetic analysis and ectopic overexpression studies. We tested the biological function of two of the predicted CLE signaling peptides in the legume Medicago truncatula. These peptides inhibit the activity of the root apical and lateral root meristems in a manner consistent with our functional predictions based on other CLE signaling peptides clustering in the same groups.
CONCLUSION: Our analysis provides an identification and classification of a large number of novel potential CLE signaling peptides. The additional motifs we found could lead to future discovery of recognition sites for processing peptidases as well as predictions for receptor binding specificity.

Identifying components of complexes

Goffard N, Weiller G.

Methods Mol Biol (2008) vol. 453 pp. 257-65

Identifying and analyzing components of complexes is essential to understand the activities and organization of the cell. Moreover, it provides additional information on the possible function of proteins involved in these complexes. Two bioinformatics approaches are usually used for this purpose. The first is based on the identification, by clustering algorithms, of full or densely connected sub-graphs in protein-protein interaction networks derived from experimental sources that might represent complexes. The second approach consists of the integration of genomic and proteomic data by using Bayesian networks or decision trees. This approach is based on the hypothesis that proteins involved in a complex usually share common properties.