Fine-Tuning Tomato Agronomic Properties by Computational Genome Redesign
[['Considering a cell as a DNA-based molecular factory [1] and applying principles drawn from industrial engineering provides new approaches to optimize cellular performance ( Figure S1 ) .', 'This approach adopts the new philosophy implemented nowadays by large industries that is known as Lean Manufacturing ( LM ) .', 'LM consists in the implementation of standards based on elimination of bottlenecks and processes without mark-up and minimization of pathways and excessive costs .', 'This approach can be applied to the emerging fields of systems and synthetic biology , and allows translating engineering concepts into biotechnology [2]–[4] .', 'Our main goal is to optimize the phenotypic response of a natural plant biofactory , exemplified here by the edible tomato fruit , by using a combined experimental and computational synthetic biology approach .', 'The approach involves re-designing the fruit factory from within; i . e . , by modeling and identifying the important genes and intermediates for a given trait of agronomical interest .', 'Previous works have considered modeling the global metabolism [5] , transcription [6]–[11] or the integration of both in microbial organisms [12]–[14] from the point of view of systems biology .', 'Many groups , using a re-designing strategy that is characteristic of synthetic biology , have implemented genome-scale re-designs and explorations of the gene knockout landscape both in prokaryotes [15]–[17] and eukaryotes [18] .', 'More recent reports have tackled the prediction of phenotypes from metabolic data based on statistical models for microbes [12] and plants [18]–[20] .', 'The next logical and desirable development should consist in modeling phenotypes of interest in a complex organism from metabolic and gene expression data .', 'For that purpose we have chosen tomato: a model plant for fleshy fruit -this being a natural biofactory of nutrients and healthy compounds , and a plant of agronomic interest with well-developed genetics and genomics ( http://solgenomics . net ) and with extensive work on metadata analysis [21]–[23] .', 'We have assumed that at least in part the genetic program of the fruit at the ripe stage should have an impact on the metabolite content and also in other high order fruit traits .', 'In this study , we have used omic data that have been experimentally obtained by means of transcriptomics , metabolomics and phenomics for a large number of recombinant inbred lines ( RILs ) derived from a cross of Solanum lycopersicum×S .', 'pimpinellifolium .', 'Following the LM approach , we have developed here a novel in silico optimization method that extensively explores single and multiple genetic perturbations to render a series of desired tomato phenotypes; i . e . , show agronomical properties of biotechnological interest .', 'Recently , large efforts in genome-scale modeling have been reported [24] , [25] ( e . g . , genome wide selection methods ) .', 'Herein , techniques based on reverse engineering were applied to a large set of experimental omics data to obtain a kinetic model based on ordinary differential equations ( ODEs ) that describe the steady state concentration of mRNAs .', 'This model has the advantage of quantitatively characterizing the kinetic parameters describing molecular interactions that are essential for simulating the genetic perturbations involved in redesigning genomes .', 'Hence , this model describes the fruit metabolic profile from gene expression data for an autonomous subset of genes with potential effect on transcription regulation .', 'By capturing relationships between metabolic profiles and high-throughput phenomic data , our model was extended to predict changes in agronomic properties that would be produced by specific changes in genetic expression ( Figure S2 ) .', 'Finally , in order to close the design cycle imposed by LM , the genetic modifications suggested by our computational approach were experimentally verified .', 'This was done by demonstrating the predicted ability of the in silico modified fruit genomes to reproduce the correlations between metabolites empirically found in the fruit .', 'We propose that the principles and practices learned from these engineering success cases can help to formulate a model to guide the design of new organisms with biotechnological applications .'], ['We have extended our recently developed inference methodology , InferGene [7] , to obtain a gene regulatory model coupled to metabolism that allows us analyzing optimality in terms of specified agronomic and organoleptic properties of the tomato fruit ( Figure 1 ) .', 'For this , we have taken advantage of an experimentally characterized subset of the metabolome of 169 tomato RILs , which includes the accumulation levels of 67 metabolites in the fruit and that contribute to the flavor ( sugars , acids and some volatiles ) , aroma ( volatiles ) and other quality traits ( such as color and healthy carotenoids and vitamins ) .', 'Moreover , we have also used the information on transcript levels from fruits for a subset of the 50 RILs analyzed at the metabolic level , to select 5592 non-redundant genes that were consistently expressed in those fruit samples ( see Methods ) .', 'Transcriptomic and metabolomic data from these 50 RILs were normalized by the LOWESS method [26] and used to construct a model that predicts components of the fruit quality metabolome from transcriptome data; i . e . , level of a given metabolite is effectively determined by the expression of a minimal set of genes .', 'The size of the space of possible gene-predictors was reduced in one order of magnitude by using a CLR method ( Dataset S1 ) .', 'After that , LASSO method was used to find a minimal set of potential predictor genes for each metabolite; subsequently , multiple regressions were obtained to estimate the effective kinetic parameters of a linear model based on ODEs that integrates transcription and metabolism processes in steady state ( Figure 2 ) [7] .', 'Values were used as optimal threshold in order to limit the number of possible gene-metabolite interactions and minimize the distance between the predicted and measured metabolic profiles over the training set in terms of average Pearson correlations ( blue bars in Figure 2C; r\u200a=\u200a0 . 85 , 167 d . f . , ) .', 'Hence , on average , each metabolite required 18 genes for explaining its behavior , thus a total of 959 genes was required to describe our tomato fruit metabolome .', 'This subset of genes constitutes the effective transcription network .', 'We performed a 5-fold cross-validation test to rule out dependence of the testing set , this reducing the metabolite average prediction ( red bars in Figure 2C; r\u200a=\u200a0 . 42 , 167 d . f . , p\u200a=\u200a0 . 067 with a mean false positive rate ( FPR ) of 14% and a 56% mean positive predictive value ( PPV ) of predictors ( bootstrap test , and , respectively ) .', 'The next step was to construct an effective gene regulatory model able to predict autonomously the transcriptional processes that , by means of the model previously described , would generate a quantitative metabolic response .', 'In this way changes at the transcriptional level resulting from the proposed genetic perturbations could be translated and predicted effectively into metabolic changes .', 'For doing that , we used the microarray data obtained from fruits of 50 of the RILs to infer a network of gene-gene interactions .', 'The CLR method provided the first sets ( ) of predictor genes for each gene considered .', 'Afterwards , LASSO method reduced the number of regulations per gene to a scale-free space following a power-law with exponent ( ) and an average of 26 interactions per gene .', 'High values of similarity between the predicted and measured gene expression ( blue bars in Figure 2D ) were computed for the whole training set ( , 48 d . f . , ) while for a 5-fold cross validation the average similarity ( red bars in Figure 2D ) was r\u200a=\u200a0 . 59 ( 48 d . f . , ) with a mean FPR of the 25% and a 63%mean PPV of predictors ( bootstrap test , and , respectively ) .', 'We addressed the question of whether the agronomic/phenotypic properties of the tomato fruit could be determined by their metabolite composition .', 'For that , we studied the relationship between agronomic properties and metabolic composition across 169 tomato RILs .', 'We applied LASSO method to select a set of metabolites that may act as predictors for each agronomic property ( Dataset S1 ) .', 'Our model included 47 metabolites observing considerably high Pearson correlations between the measured and predicted phenotypic responses over the 169 RILs for number of fruits per plant and fruit harvested across two different seasons , ( Figure 2A; r\u200a=\u200a0 . 62 and r\u200a=\u200a0 . 73 respectively , 167 d . f . , in both cases ) .', 'A reduction to r\u200a=\u200a0 . 46 ( 167 d . f . , ) and r\u200a=\u200a0 . 62 ( 167 d . f . , ) in the median correlation was computed in a 10-fold cross validation , with 84% mean PPV in both cases ( bootstrap test , ) , and mean FPR of 33% and 35% ( bootstrap test , in both cases ) , respectively .', 'Average fruit weight and pH required as many as 44 metabolites as potential predictors with high reliability levels .', 'Reliability was assessed by comparing the corresponding predicted and measured values for the 169 RILs ( Figure 2A; r\u200a=\u200a0 . 85 and r\u200a=\u200a0 . 80 , 167 d . f . , in both cases ) .', 'A 10-fold validation only reduced those similarities to r\u200a=\u200a0 . 73 and r\u200a=\u200a0 . 63 ( 167 d . f . , in both cases ) , with mean FPRs of 37% and 22% ( bootstrap test , and , respectively ) , and mean PPVs of 81% and 88% ( bootstrap test , and ) , respectively .', 'Additionally , to test how the metabolome contributed to an accurate prediction of tomato phenotype , we studied the relationship between agronomic properties and gene expression of the core of 959 genes across the 50 tomato RILs [27] .', 'Note that we select this reduced set of genes as a core of potential predictors to avoid model over-fitting due to the low number of RILs with the transcript levels measured .', 'Imposing the same criteria that was used to select metabolites as predictors , we observed that similarities between predicted and measured values of number of fruits per plant and harvested fruits increased ( r\u200a=\u200a0 . 80 and r\u200a=\u200a0 . 81 , 48 d . f . , in both cases ) while average of fruit weight and pH decreased ( r\u200a=\u200a0 . 79 and r\u200a=\u200a0 . 73 , 48 d . f . , in both cases ) ( see dashed line in Figure S3A–B ) .', 'Moreover , relaxing the threshold ( ) to include possible interactions agronomic variable-genes in the LASSO method , surprisingly similarities for all agronomic variables highly decreased ( r<0 . 65 , 48 d . f . , ; see Figure S3C–D ) .', 'Hence , we illustrated an alternative way to described accurately phenotypic properties of tomato fruit by using gene expression profile of the reduced set of RILs .', 'Next , to test the specificity of the inferred model parameters , we perturbed the target phenotypic profile for each RIL adding different levels of noise .', 'Figure 2B shows the distance between predicted and measured values ( green points ) and mean correlations for different noise levels .', 'A similar approach was performed by using the metabolic and gene expression profiles ( red and blue points , respectively ) .', 'Correlations with significance levels higher than the indicated above were not considered in the cross-validations .', 'In addition , we estimated a very low mean error in predicting the agronomic properties across the training set ( , see Methods ) .', 'Here , our main goal is to redesign the genome of tomato to generate an engineered surrogate that , if viable , would be easier to study and of greater potential biotechnological interest .', 'Our design approach was inspired by the practice of in silico optimization over a predictive global model .', 'Our next step was to test the possibility of improving agronomical properties of interest .', 'We tested several scoring functions that fall into two global types: on the one hand , agronomical variables measured experimentally such as the number of fruits harvested per plant , the average fruit weight or its pH; and on the other hand , more complex fruit attributes that could be defined according to some of the components of the metabolic profile and are related to organoleptic properties of the fruit .', 'In this later case , we first evaluated as proof of concept: fruit acceptability according to criteria based on acidity and sugars [28] , quality as defined by the contribution of specific volatiles to aroma and by a reported [28] panel assessments of the tomato fruit and consequently on organoleptic acceptance .', 'For this latter case we assumed a strong influence of a set of metabolites to be either maximized ( -ionone , -damascenone , 2-phenylethanol and benzaldehyde ) or minimized ( methyl salicylate , guaiacol , hexanal , 1-penten-3-one and ( E ) -2-hexenal ) using balanced weighting factors to account for their positive or negative contribution to quality .', 'Moreover , all single metabolites were also optimized in single target analyses .', 'Finally , a bi-objective function that included a high trade-off was proposed to optimize fruit quality and its production .', 'As a first approach , we re-engineered tomato genome by perturbing independently the 959 genes included in the model , then we re-computed the scoring functions for all RILs enumerating all single knockouts and finally , all gene over-expression models were obtained .', 'Hence , mimicking the optimization patterns typical from LM , the landscape of desired agronomic properties of tomato fruit was exhaustively explored perturbing its effective transcriptional regulatory network ( TRN ) with single-gene alterations .', 'Figure 3A shows the improvement of two of the agronomic properties mentioned above ( fruit acceptability and quality vs production ) as result of single gene perturbations according to our model .', 'The success of the approach is shown by the efficiency function obtained for each transcriptional perturbation computed and which is defined by the normalized ratio between the agronomic property obtained for the re-engineered TRN and that for the wild-type TRN .', 'Both agronomic properties and efficiencies in the case of single-perturbations were computed for each of the 169 RILs , resulting in a high variability between the lineages for all knockouts and over-expressed gene re-engineered TRN cases .', 'We corroborated that there is a highly significant linear correlation ( , for fruit acceptability and quality vs production ) between the average value of the improved agronomic properties and the efficiencies reached across the set of RILs for all transcriptional perturbations .', 'Both gene knockout and over-expression models resulted in similar linear regression slopes when considering acceptability and quality vs production together ( 0 . 05 and 0 . 24 , respectively , Figure 3A ) .', 'In addition , we also explored the possibility of tuning a given agronomic property towards a defined value , as it is desired for some biotechnological applications ( see Text S1 ) ; achieving also in this case high efficiency values ( Figure S4 and Tables S1 and S2 ) .', 'After this , we ranked the list of knockout/over-expressed genes of the TRN according to two criteria directed to maximize:', '( i ) the mean efficiency across all lineages in the case of goals such as acceptability and quality vs production; and', '( ii ) the average of the maximum agronomic property reached by all possible TRN reconfigurations in the case of fruit quality ( Dataset S2 ) .', 'Specifically , Table 1 shows the top 5 genes proposed for knockouts or over-expressed depending on the fitness evaluated .', 'Fruit acceptability could be improved to 2 . 91% or 8 . 84% using gene knockout ( i . e . , LE24K20 ) or over-expression ( i . e . , LE13M10 ) in all lineages , respectively .', 'By contrast , quality was highly increased achieving improvement ratios of 43 . 34% by gene knockout ( i . e . , LE24K20 ) and 227 . 31% by over-expression of LE15D07 .', 'Finally , taking into account not only the quality but also fruit production , ratios decreased to 15 . 32% ( i . e . , LE13F23 ) and 35 . 94% ( i . e . , LE14B20 ) using the two types of perturbations , respectively .', 'Notice that all these rates of improvement were achieved in the lineages that provided maximum fitness in the wild-type TRN .', 'Lineages exhibited variability in their resistance to be optimized and this resistance changed with each target agronomic property .', 'Figure 3B shows a strong linear dependence between the level of the agronomic property in the wild-type TRN and the average level of the agronomic properties resulting from all single perturbations in the TRN for each RIL ( linear regression slope in the range 0 . 99–1 . 12 and , ) .', 'Interestingly , we observed that the effect of predicting agronomic properties under genetic perturbations was not dependent on the lineage selected .', 'This provided a high level of robustness when we selected the lineages to implement experimentally re-designed TRN .', 'We computed the average number of single-gene perturbations to overcome an efficiency threshold given in the 169 RILs and the average probability of selecting the same gene-perturbation commonly for the whole set of RILs .', 'The right panel in Figure 3C shows that only a few gene knockouts were able to improve fruit acceptability with a high probability in all lineages whereas , on the other hand , tens of gene knockouts could be proposed for increasing fruit quality and for the quality and production .', 'On the other hand , the left panel in Figure 3C allowed re-asserting that re-engineering the TRN by gene over-expression could result in higher increments in the agronomic properties and with a higher density of suggested perturbations across the RILs .', 'The next step in our study was to propose new genome re-designs including multiple perturbations .', 'To do this , we sampled widely the landscape of the acceptability , quality and quality vs production of tomato fruits by introducing two-gene perturbations either by knockouts and over-expressions ( Dataset S3 ) .', 'Figure 4A shows the median efficiencies reached by two-gene transcriptional perturbations based on knockouts and over-expression in order to improve the agronomic properties defined as multiple-objective .', 'As expected , we corroborated that multiple perturbations , located in different pathways ( Table 2 ) , could improve the agronomic properties significantly better than single perturbations .', 'Table 2 lists the best gene-pairs to be used in perturbations that maximize such agronomic properties of the fruit .', 'Figure 4B shows the average number of single gene perturbations that are able to overcome a given efficiency threshold for the top 5 RILs when ranked for single perturbations as well as the average probability of selecting the same multiple-perturbation commonly in a set of RILs .', 'After generating our predictive model for the TRN and metabolism of tomato fruit , we use it to automatically design tomato genomes with extreme alterations for each of the 56 volatile compounds by introducing a set of genetic perturbations .', 'We compared sets of genetic perturbations for all pairs of volatile compounds and then inferred their levels of correlations ( see Methods ) .', 'Hence , these predicted correlations were compared to the levels of correlations obtained from the experimental values for each volatile pair that often reflects their belonging or not to the same metabolic/regulatory pathway or to be or not structurally related .', 'Figure 4C–4F shows the predictive power of our model to determine correlations between all the volatile compounds .', 'Interestingly , selecting a correlation cut-off between 0 . 5 and 0 . 8 we obtained high performance -scores ( see Methods section ) ranging between 0 . 32 and 0 . 91 ( Figure 4D ) for gene knockouts and between 0 . 31 and 0 . 80 when model selected genes by over-expression ( Figure 4F ) .', 'Notice that only pairs of experimental volatile compounds with were considered .', 'Predictions decreased when we incorporated all pairs of compounds ( Figure 4E–4F ) indicating that our model captured high correlations observed experimentally with more precision .', 'Figure S5 shows the dendograms of the volatile compound obtained from the correlation of experimentally obtained volatiles levels and the dendograms obtained using as distance between volatile compounds the number of common genetic perturbations proposed by the model .', 'We observed that perturbations proposed by gene over-expression were pivotal to predict computationally significant distances between volatile compounds ( Mantel test: r\u200a=\u200a0 . 54 , 1540 d . f . , ) thus providing high support to our model .', 'By contrast , predicted perturbations based on gene knockout could only identify a small fraction of the entire dendogram ( Mantel test: r\u200a=\u200a0 . 38 , 1540 d . f . , ) .', 'To give further support to our model we constructed experimentally two inbred lines ( ILs ) derived from another interspecific cross whose transcriptome and metabolome were also experimentally measured .', 'Parents of these ILs are a different cultivar of tomato M82 and a S . pennelli accession and therefore represent a completely different set of gene alleles from those in RILs used to construct the model .', 'These ILs can be used as independent and useful test case to evaluate the validity of the model .', 'We corroborated that a significant set of genetic perturbations suggested by computational design to optimize the phenotype observed were identified as genes differentially altered in the target phenotype ( Text S1 and , Figure S6 ) .'], ['LM is a methodology that is being implemented by large industries to optimize their production .', 'In the process of decision making applied to the redesign of production systems , firstly , engineers evaluate systematically the addition or elimination of resources in each of the participating single processes; afterwards , multiple changes are considered trying to achieve maximum quality and production [29] .', 'Translating this engineering approach to a cellular molecular factory and identifying the basic functional elements has allowed us to develop a design methodology that optimizes the genome , resulting in a more desirable phenotypic properties .', 'In addition , by mimicking the methodology from LM we have provided a first robust optimization to redesign an optimal genetic network based on the systemic exploration of the effects of a large number of single gene knockout and over-expression genotypes; then , a second multiple-optimization of random paths allowed improving substantially the desired agronomical properties .', 'The success of this approach indicates that despite the existence of molecular interactions , the model is able to overcome this limitation and results in a good predictor .', 'We have proposed several re-engineered genomes that improve desired agronomic properties of the fruit by targeting single or multiple genetic modifications .', 'It has been previously reported that single under-/over-expressed of certain genes may affect fruit quality traits , being these key genes involved in the biosynthesis of a product of fruit metabolism or to a general ripening regulators ( i . e . , carotenoids [30] ) .', 'We have explored single perturbations by gene knockout or over-expression and our results indicated that a significantly better fine-tuning could be obtained by using over-expression approaches .', 'We observed that improvement ratios could reach even more than 4-fold the wild-type value of most of phenotypes desired by designing genomes with only two genetic perturbations ( Figure 4A and Table 2 ) .', 'The magnitude of the predicted change sometimes may appear low but an improvement in a quantitative trait , if consistent and predictable , maybe economically important .', 'Indeed , a good combination of high yield with even slightly increased solid solids content is a major breeding goal for processing tomatoes that it is difficult to be achieved [31] because of polygenic nature and pleiotropic relationships of both traits [32] .', 'Although it is not the objective of this paper , it does not escape our attention that some of the perturbations proposed are consistent with the biological processes associated to the trait and therefore the model could be used to reveal the molecular underpinnings of quality traits ( see experimental evidences of each gene perturbation proposed by the model in the Dataset S4 ) .', 'For instance the role of YABBY ( a gene proposed by our model to affect quality ) in controlling fruit size probably through the auxin pathway and the effect of auxin in altering fruit growth and ripening has been previously reported [33] , [34] .', 'Similarly the importance of phytoene desaturase to affect carotenoids and carotenoid derived volatiles has been reported [35] .', 'Most of the genes proposed by the models however are new , therefore opening new avenues of research either by targeting in transgenic plants , identification of mutants in those genes by TILLING [36] or by TAL engineering [37] , as well as to be used as an additional guide during plant breeding .', 'In principle these modifications are to be implemented in red fruit or around red fruit stage either genetically or by the use of external elicitors ( physical or chemical ) and our model provides roadmap for those approaches .', 'Our methodology takes advantage of our ability to predict variations in fruit cell phenotype based on changes in the transcriptome .', 'The linear relationships shown in Figure 3 ( A , C , and D ) guarantees that by optimizing our effective transcriptomic , metabolic or phenotypic fitness we are also optimizing the phenotype measured experimentally of the tomato fruits .', 'While it is true that complex multi-organ organism such as tomato rely on the coordination and transport of multiple signals and nutrients from different parts of the plants to achieve the final phenotype , and this is especially true for the fruit [19] , [38] , it not less true that the most important part of the fruit characteristics at ripening depends basically on the fruit program before around the ripening stage [39] , [40] .', 'The ability to target redesign crops for enhanced content of metabolites of interest has been experimentally achieved in a number of cases ( for instance vitamins C [41] and E [42] ) using transgenic approaches and the information of bottlenecks or limiting steps for the biochemical pathways of the compounds of interest .', 'The most dramatic examples of this have been introducing the new trait in a genetic background with very low value for it ( i . e . , golden rice [43] ) using ectopic expression of one or several foreign genes .', 'The use of natural genetic variability in combination with our nonbiased ( hypothesis-free ) modeling approach allows us to identify new candidate genes as potential targets to engineer the plant ( although the biotechnological use of more active orthologs from other organisms is not discarded in our approach ) .', 'The existence of regulatory networks connecting primary and secondary metabolism in plants should also be taken into consideration in future attempts to metabolically engineer the various classes of plant secondary metabolites [44] .', 'It is interesting that known genes in the biosynthesis path often do not co-localize with quantitative trait locus for the metabolites in the path [35] indicating that there is ample of opportunities to be explored for metabolite and quality improvement , and our model fits nicely in this gap .'], ['The construction of the tomato RILs used in this study has been described elsewhere [45] .', 'Triplicate samples of red ripe fruits ( each representing at least 5 fruit ) from each of 169 RILs were harvested and analyzed for volatile compounds as described in [46] .', 'For method validation , red ripe fruits from five ILs with a different genetic background [47] were used .', 'Transcript profile datasets ( 11876×3×50 data points ) were obtained from triplicate fruit samples of 50 selected RILs using TOM2 microarray , as previously reported [48] .', 'Data sets corresponding to the rest of metabolites and phenomic data were obtained as in [46] from triplicate samples of the 169 RILs .', 'To decrease experimental variability , the same fruits representing each RIL were homogenized and divided in different aliquot samples for the different metabolite or transcript profiling techniques .', 'Before use all transcriptomic , metabolomic and phenomic data were normalized and transformed to log-scale .', 'The ILs used for model validation have been described previously [21] .', 'An effective linear model based on ODEs each providing the steady states of tomato fruit mRNA was used to describe transcriptional gene regulations [7] .', 'Thus , the mRNA steady state from the gene , , is given by , where represents the regulatory effect that gene has on gene .', 'Each gene expression value is contained in a range interval defined by the minimum and maximum value of all its experimental measurements obtained from the subset of 50 RILs used for transcript profiling .', 'is a tunable parameter that decreases the gene expression range to improve the predictive capacity of the presented model under genetic predictions .', 'The dynamics of metabolic profile was computed by , where is the steady-state concentration from the metabolite , is the regulatory strength that gene has on metabolite .', 'Hence , agronomic variables ( ) were predicted by means of a linear combination of the metabolic profile , , where is the regulatory effect that metabolite has on agronomic variable .', ', and are the perturbation terms that allow to calibrate gene expression , metabolic profiles and predicted agronomic properties , respectively , for all RILs .', 'Notice that degradation coefficients of genes and metabolites ( , respectively ) scaled time conveniently and that we assumed the model in steady state ( and ) .', 'Our global model consists of three blocks of algebraic equations covering respectively from gene expression , through metabolic profile until agronomic properties , and in all three cases the same methodology was applied .', 'The inference procedure consisted of two nested steps .', 'Firstly , the network connectivity was inferred by using the InferGene algorithm [7] .', 'This method uses mutual information with a local significance value ( z-score computation ) to obtain the effective regulations .', 'Hence , the potential interaction between a predictor and a target is z-scored , constituting an estimator of the likelihood of mutual information .', 'Subsequently , we selected a z-score threshold for a predictor cutoff .', 'In a second step , LASSO method was used to avoid over-fitting and to estimate the kinetic parameters of each effective model .', 'Notice that the 8 . 7% of the selected genes in the TRN were annotated as TFs and 16 . 2% as encoding enzymatic activities and , in neither case , they were over-represented since both the tomato genome and the whole array contain similar fractions of TFs ( 8 . 8% ) and enzymes ( 17 . 1% ) .', 'For the construction of the effective TRN model and its later integration with the metabolism , we used steady-state mRNA expression profiles derived from RILs transcriptionally and metabolically characterized .', 'The dataset contains pre-processed expression data from 50×3\u200a=\u200a150 hybridization experiments using an array with 11876 probe sets spotted , and data for levels of 67 metabolites that were quantified over the same sample set .', 'For this study , we only considered the 5592 genes whose expression values could be consistently found in more than 80% of the microarrays .', 'We found 1057 TFs and 1962 genes with enzymatic activity after searching for the motifs transcription regulator and enzyme activity respectively in the functionally annotated tomato genome ( Tom2 ) .', 'Moreover , all 169 RILs ( including the previous 50 ones ) for which we had metabolite and phenotype data were used to train a linear model able to predict agronomic properties of the fruit from potentially predictor m
['Introduction', 'Results', 'Discussion', 'Materials and Methods']
['Considering cells as biofactories , we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing .', 'We have applied reverse engineering computational methods to transcriptomic , metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes .', 'Based on predicted metabolic profiles , a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence .', 'Inspired in a synthetic biology approach , the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties .', 'The method was validated by the ability of the proposed genomes , engineered for modified desired agronomic traits , to recapitulate experimental correlations between associated metabolites .']
['Considering cells as biofactories , we aimed to optimize their internal processes by using existing design principles acquired from engineering .', 'Herein , we present a synthetic biology approach based on experimental and computational methodology that integrates genomic , transcriptomic , metabolomic and phenomic data to formulate a kinetic and constraint based model of tomato agronomic and fruit quality characteristics .', 'The model has been used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with improved biotechnological properties .', 'The methodology was validated by the ability of the proposed engineered genomes with modified desired agronomic traits , to recapitulate correlations between associated metabolites that are found experimentally in a number of examples .']
['systems biology', 'synthetic biology', 'biology', 'computational biology', 'molecular biology', 'genetics and genomics']