Zoran Nikoloski

On Modularity Clustering

Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, particularly in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomerative approach.

PlaNet: Combined Sequence and Expression Comparisons across Plant Networks Derived from Seven Species

Genes that are similarly expressed, or coexpressed, are often involved in related biological processes. Such coexpressed relationships also appear to be conserved across species. The PlaNet platform enables comparative analysis of genome-wide coexpression networks across seven plant species, thus enabling prediction of gene function and elucidation of the identity of functional homologs. The model organism Arabidopsis thaliana is readily used in basic research due to resource availability and relative speed of data acquisition. A major goal is to transfer acquired knowledge from Arabidopsis to crop species. However, the identification of functional equivalents of well-characterized Arabidopsis genes in other plants is a nontrivial task. It is well documented that transcriptionally coordinated genes tend to be functionally related and that such relationships may be conserved across different species and even kingdoms. To exploit such relationships, we constructed whole-genome coexpression networks for Arabidopsis and six important plant crop species. The interactive networks, clustered using the HCCA algorithm, are provided under the banner PlaNet (http://aranet.mpimp-golm.mpg.de). We implemented a comparative network algorithm that estimates similarities between network structures. Thus, the platform can be used to swiftly infer similar coexpressed network vicinities within and across species and can predict the identity of functional homologs. We exemplify this using the PSA-D and chalcone synthase-related gene networks. Finally, we assessed how ontology terms are transcriptionally connected in the seven species and provide the corresponding MapMan term coexpression networks. The data support the contention that this platform will considerably improve transfer of knowledge generated in Arabidopsis to valuable crop species.

Metabolic Fluxes in an Illuminated Arabidopsis Rosette

Kinetic flux profiling has been extensively used in unicellular bacterial systems to study primary metabolism. We present a framework for its use in estimating photosynthetic fluxes in land plants. The resulting flux estimates are benchmarked against published flux estimates. Photosynthesis is the basis for life, and its optimization is a key biotechnological aim given the problems of population explosion and environmental deterioration. We describe a method to resolve intracellular fluxes in intact Arabidopsis thaliana rosettes based on time-dependent labeling patterns in the metabolome. Plants photosynthesizing under limiting irradiance and ambient CO2 in a custom-built chamber were transferred into a 13CO2-enriched environment. The isotope labeling patterns of 40 metabolites were obtained using liquid or gas chromatography coupled to mass spectrometry. Labeling kinetics revealed striking differences between metabolites. At a qualitative level, they matched expectations in terms of pathway topology and stoichiometry, but some unexpected features point to the complexity of subcellular and cellular compartmentation. To achieve quantitative insights, the data set was used for estimating fluxes in the framework of kinetic flux profiling. We benchmarked flux estimates to four classically determined flux signatures of photosynthesis and assessed the robustness of the estimates with respect to different features of the underlying metabolic model and the time-resolved data set.

Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues

The tricarboxylic acid (TCA) cycle is a crucial component of respiratory metabolism in both photosynthetic and heterotrophic plant organs. All of the major genes of the tomato TCA cycle have been cloned recently, allowing the generation of a suite of transgenic plants in which the majority of the enzymes in the pathway are progressively decreased. Investigations of these plants have provided an almost complete view of the distribution of control in this important pathway. Our studies suggest that citrate synthase, aconitase, isocitrate dehydrogenase, succinyl CoA ligase, succinate dehydrogenase, fumarase and malate dehydrogenase have control coefficients flux for respiration of -0.4, 0.964, -0.123, 0.0008, 0.289, 0.601 and 1.76, respectively; while 2-oxoglutarate dehydrogenase is estimated to have a control coefficient of 0.786 in potato tubers. These results thus indicate that the control of this pathway is distributed among malate dehydrogenase, aconitase, fumarase, succinate dehydrogenase and 2-oxoglutarate dehydrogenase. The unusual distribution of control estimated here is consistent with specific non-cyclic flux mode and cytosolic bypasses that operate in illuminated leaves. These observations are discussed in the context of known regulatory properties of the enzymes and some illustrative examples of how the pathway responds to environmental change are given.

Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits

Genome-wide association sheds light on the genetic architecture of metabolic traits underlying fruit quality in tomato. Genome-wide association studies have been successful in identifying genes involved in polygenic traits and are valuable for crop improvement. Tomato (Solanum lycopersicum) is a major crop and is highly appreciated worldwide for its health value. We used a core collection of 163 tomato accessions composed of S. lycopersicum, S. lycopersicum var cerasiforme, and Solanum pimpinellifolium to map loci controlling variation in fruit metabolites. Fruits were phenotyped for a broad range of metabolites, including amino acids, sugars, and ascorbate. In parallel, the accessions were genotyped with 5,995 single-nucleotide polymorphism markers spread over the whole genome. Genome-wide association analysis was conducted on a large set of metabolic traits that were stable over 2 years using a multilocus mixed model as a general method for mapping complex traits in structured populations and applied to tomato. We detected a total of 44 loci that were significantly associated with a total of 19 traits, including sucrose, ascorbate, malate, and citrate levels. These results not only provide a list of candidate loci to be functionally validated but also a powerful analytical approach for finding genetic variants that can be directly used for crop improvement and deciphering the genetic architecture of complex traits.

Integrative Comparative Analyses of Transcript and Metabolite Profiles from Pepper and Tomato Ripening and Development Stages Uncovers Species-Specific Patterns of Network Regulatory Behavior

Integrative comparative analyses of transcript and metabolite levels from climacteric and nonclimacteric fruits can be employed to unravel the similarities and differences of the underlying regulatory processes. To this end, we conducted combined gas chromatography-mass spectrometry and heterologous microarray hybridization assays in tomato (Solanum lycopersicum; climacteric) and pepper (Capsicum chilense; nonclimacteric) fruits across development and ripening. Computational methods from multivariate and network-based analyses successfully revealed the difference between the covariance structures of the integrated data sets. Moreover, our results suggest that both fruits have similar ethylene-mediated signaling components; however, their regulation is different and may reflect altered ethylene sensitivity or regulators other than ethylene in pepper. Genes involved in ethylene biosynthesis were not induced in pepper fruits. Nevertheless, genes downstream of ethylene perception such as cell wall metabolism genes, carotenoid biosynthesis genes, and the never-ripe receptor were clearly induced in pepper as in tomato fruit. While signaling sensitivity or actual signals may differ between climacteric and nonclimacteric fruit, the evidence described here suggests that activation of a common set of ripening genes influences metabolic traits. Also, a coordinate regulation of transcripts and the accumulation of key organic acids, including malate, citrate, dehydroascorbate, and threonate, in pepper fruit were observed. Therefore, the integrated analysis allows us to uncover additional information for the comprehensive understanding of biological events relevant to metabolic regulation during climacteric and nonclimacteric fruit development.

Metabolite profiling and network analysis reveal coordinated changes in grapevine water stress response

BackgroundGrapevine metabolism in response to water deficit was studied in two cultivars, Shiraz and Cabernet Sauvignon, which were shown to have different hydraulic behaviors (Hochberg et al. Physiol. Plant. 147:443–453, 2012).ResultsProgressive water deficit was found to effect changes in leaf water potentials accompanied by metabolic changes. In both cultivars, but more intensively in Shiraz than Cabernet Sauvignon, water deficit caused a shift to higher osmolality and lower C/N ratios, the latter of which was also reflected in marked increases in amino acids, e.g., Pro, Val, Leu, Thr and Trp, reductions of most organic acids, and changes in the phenylpropanoid pathway. PCA analysis showed that changes in primary metabolism were mostly associated with water stress, while diversification of specialized metabolism was mostly linked to the cultivars. In the phloem sap, drought was characterized by higher ABA concentration and major changes in benzoate levels coinciding with lower stomatal conductance and suberinization of vascular bundles. Enhanced suberin biosynthesis in Shiraz was reflected by the higher abundance of sap hydroxybenzoate derivatives. Correlation-based network analysis revealed that compared to Cabernet Sauvignon, Shiraz had considerably larger and highly coordinated stress-related changes, reflected in its increased metabolic network connectivity under stress. Network analysis also highlighted the structural role of major stress related metabolites, e.g., Pro, quercetin and ascorbate, which drastically altered their connectedness in the Shiraz network under water deficit.ConclusionsTaken together, the results showed that Vitis vinifera cultivars possess a common metabolic response to water deficit. Central metabolism, and specifically N metabolism, plays a significant role in stress response in vine. At the cultivar level, Cabernet Sauvignon was characterized by milder metabolic perturbations, likely due to a tighter regulation of stomata upon stress induction. Network analysis was successfully implemented to characterize plant stress molecular response and to identify metabolites with a significant structural and biological role in vine stress response.

Metabolic Profiling of a Mapping Population Exposes New Insights in the Regulation of Seed Metabolism and Seed, Fruit, and Plant Relations

To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping.

Metabolic variation between japonica and indica rice cultivars as revealed by non-targeted metabolomics

Seed metabolites are critically important both for plant development and human nutrition; however, the natural variation in their levels remains poorly characterized. Here we profiled 121 metabolites in mature seeds of a wide panel Oryza sativa japonica and indica cultivars, revealing correlations between the metabolic phenotype and geographic origin of the rice seeds. Moreover, japonica and indica subspecies differed significantly not only in the relative abundances of metabolites but also in their corresponding metabolic association networks. These findings provide important insights into metabolic adaptation in rice subgroups, bridging the gap between genome and phenome, and facilitating the identification of genetic control of metabolic properties that can serve as a basis for the future improvement of rice quality via metabolic engineering.

Identification and Mode of Inheritance of Quantitative Trait Loci for Secondary Metabolite Abundance in Tomato

Metabolite QTL for secondary metabolism in a Solanum pennelli introgression line population show different modes of inheritance and network properties linking the traits. A large-scale metabolic quantitative trait loci (mQTL) analysis was performed on the well-characterized Solanum pennellii introgression lines to investigate the genomic regions associated with secondary metabolism in tomato fruit pericarp. In total, 679 mQTLs were detected across the 76 introgression lines. Heritability analyses revealed that mQTLs of secondary metabolism were less affected by environment than mQTLs of primary metabolism. Network analysis allowed us to assess the interconnectivity of primary and secondary metabolism as well as to compare and contrast their respective associations with morphological traits. Additionally, we applied a recently established real-time quantitative PCR platform to gain insight into transcriptional control mechanisms of a subset of the mQTLs, including those for hydroxycinnamates, acyl-sugar, naringenin chalcone, and a range of glycoalkaloids. Intriguingly, many of these compounds displayed a dominant-negative mode of inheritance, which is contrary to the conventional wisdom that secondary metabolite contents decreased on domestication. We additionally performed an exemplary evaluation of two candidate genes for glycolalkaloid mQTLs via the use of virus-induced gene silencing. The combined data of this study were compared with previous results on primary metabolism obtained from the same material and to other studies of natural variance of secondary metabolism.