BACKGROUND
being stationary organisms that are unable to move, plants represent a unique biological system that is highly adaptive to environmental stresses.
the adaptation mechanisms of plants to stresses also involve coordinated adjustments of a large array of metabolic networks.
among those are metabolic networks containing amino acids as intermediate metabolites, which can either be incorporated into proteins, accumulate to high levels in response to specific cues, such as proline accumulation in response to salt stress  <cit> , or serve as precursors for a large array of metabolites with multiple functions.
some of the metabolic networks of amino acids possess several competing branches, each leading to the synthesis of one or more amino acids and their downstream metabolites.
two of the most important branched metabolic networks of amino acids are the asp-family network and the aromatic amino acids  network .
these two networks also possess significant nutritional value because humans and much of their farm animals cannot synthesize the amino acids produced by them and therefore depend on plants as their nutritional supplements  <cit> .
astep numbers represent enzymatic steps described in fig.
<dig> and additional file  <dig>
batg represents the common locus number using tair nomenclature.
cprobeset represents specific identifiers according to affymetrix ath <dig> microarray.
dhighly coordinated genes
the asp-family network, which classically includes the amino acids lys, thr, met and ile , is a central regulator of plant growth not only because its amino acids are essential for protein synthesis.
met is a metabolic precursor for multiple fundamental cellular processes  <cit> , while thr, through its conversion into ile, participates plant pathogen interactions  <cit>  and cellular energy production  <cit> .
thr is also catabolized by two thr aldolase isozymes into gly, which is closely associated with photorespiration  <cit> .
lys biosynthesis and catabolism was also shown to be associated with plant pathogen interactions as well as with the production of the stress associated hormone salicylic acid  <cit> .
the aaa metabolic network leads to the synthesis of trp, phe and tyr, which are further used as precursors for various hormones, cell wall components and a large array of multifunctional secondary metabolites  <cit> .
using a bioinformatics approach based on publicly available microarray results, we have recently demonstrated evidence supporting the presence of principal transcriptional programs of amino acid metabolism in response to abiotic stresses  <cit> .
strikingly, these responses were most profoundly associated with changes in expression of genes encoding the catabolic enzymes of the amino acids with only minor changes in mrna levels of genes encoding the biosynthesis enzymes  <cit> .
this phenomenon in which genes encoding only a fraction of the enzymes within a given metabolic pathway are altered in response to a given cue is in sharp contrast to microorganisms in which the expression of all genes of a given metabolic pathway is generally altered in response to a given cue  <cit> .
this major conceptual difference is likely because highly dividing microorganisms face extensive dilution of their enzyme concentrations through the frequent cell divisions, while cells of higher organisms relatively infrequently divide in the short time scales of environmental changes.
in addition, higher organisms often have more than one gene encoding a given enzyme, and therefore transcriptionally regulate only a fraction of the genes encoding isozymes in different tissues or in response to different cues.
this fact adds another damnation of complexity when analyzing transcription results of higher organisms.
notably, arabidopsis plants specifically adjust the expression of genes encoding different catabolic enzymes of amino acids in response to different stresses  <cit> .
this implies that bioinformatics approach aiming to elucidate interactions of different branched networks of amino acid metabolism in plants under multiple growth conditions is a challenging issue because different branches are likely subjected to dynamically changing patterns of coordinated regulation.
under some conditions, such as optimal growth conditions, all branches are expected to operate efficiently to allow the synthesis of amino acid for incorporation into proteins.
under other biological perturbations, such as exposure to specific stress conditions, fluxes are expected to increase in some branches on the expense of others to allow optimal metabolic adjustments  <cit> .
therefore genes encoding enzymes of specific branches within a given amino acid metabolic network are expected to be both positively correlated under some biological perturbations, while negatively correlated or not correlated at all under other biological perturbations.
as a consequence, genes encoding enzymes of specific branches within a given metabolic network are also expected to be both positively correlated, negatively correlated or non-correlated with other genome-wide genes under different biological perturbations.
therefore, commonly used correlation methodologies are not suited to elucidate transcriptional network interactions of amino acid metabolic pathways because they are unable to resolve positive from negative correlations within a wide range of biological perturbations.
to overcome this limitation, we have developed in the present report a novel principal approach, termed "gene coordination" allowing the elucidation of groups of genes whose expression is coordinated by both positive and negative correlations in response to different sets of biological perturbations.
we also used this novel approach to elucidate differential genome-wide interactions of two central amino acid metabolic networks, namely the asp-family and aaa metabolic networks,.
our results expose novel principal transcriptional regulatory aspects of each of these networks and also show that they differentially interact with genome-wide genes in plant growth and response to the environment.
RESULTS
selection of genes associated with the asp-family and aaa metabolic networks and sources of publicly available microarray experiments
the aim of this research was to discover novel network interactions associated with two central metabolic networks of amino acids, namely the asp-family network and the aaa network .
the asp-family network includes the amino acids lys, thr and met, ile and gly whose synthesis initiates from asp, and in which one pathway leads to lys metabolism , a second pathway leads to thr synthesis and its further conversion into ile and gly , and the third pathway leads to met metabolism .
the aaa network, whose synthesis initiates from chorismate, includes three pathways; one leading to trp metabolism , while the second and third pathways lead to phe and tyr metabolism.
since the phe and tyr pathways contain altogether only few enzymatic steps , from which one is common to both pathways, we therefore treated them as a single pathway.
in both the asp-family and aaa networks, we focused on genes encoding biosynthetic enzymes as well as enzymes catalyzing the first catabolic steps of the amino acids.
our definition of catabolism included the breakdown of the amino acid into carbon, nitrogen and energy-associated molecules as well as the utilization of the amino acids for the synthesis of other special metabolites, such as secondary metabolites.
the selection of the entire set of genes associated with these two networks was as previously described  <cit> .
the functional annotation of the genes in this list was based on a combinatorial analysis of information form tair , aracyc  and literature review.
the list of enzymes and the genes encoding them, which were used in this study, are detailed in table  <dig>  some of the genes studied in this report are indistinguishable in the ath <dig> affymetrix chip and are monitored by a common probeset as indicated in table  <dig>  for simplicity, we will refer in the following to these probesets as genes rather than probesets.
our bioinformatics approach was based on analyzing a selected set of experiments in the publicly available arabidopsis microarray data available through the nasc database .
yet, since we were interested to elucidate programs of transcriptional regulation, we focused only on relatively short time responses  of genes, belonging to the asp-family and aaa metabolic networks, to different biological cues.
in addition, in experiments where a mutant genotype was analyzed in comparison to a control genotype, we considered these lines as two distinct genotypes.
these guidelines enabled us to extract  <dig> different short-term biological perturbations, which were enforced on many different genotypes.
it is important to emphasize that in cases in which multiple time points were analyzed in an individual experiment, each time point was used as an independent biological perturbation.
this was done due to the fact that the response of different genes in different time scales  may play a significant regulatory role in the adjustment of metabolic channelling as was suggested in our previous report  <cit> .
since different branches in branched metabolic networks lead to the synthesis of different metabolites with distinct functions, it is expected that the different branches should possess significant regulatory gene expression flexibilities to either be positively or negatively correlated in response to different cues .
hence, pearson correlation analysis is not suitable to discover associations between such genes over large sets of different experiments.
to overcome this, we developed a novel bioinformatics approach, termed "gene coordination".
the principal difference between gene correlation  and gene coordination is that gene coordination allows the identification of both statistically significant negative and positive coordinations of expression between pairs of genes over a set of multiple biological perturbations.
in short, this novel measure assigns two distinct values between each pair of genes:  a positive coordination, which is the number of biological perturbations in which both genes of a given gene pair are either up-regulated or down-regulated together in a statistical significant manner, compared to non-treated controls; and  a negative coordination which is the number of biological perturbations in which one gene of the same gene pair is up-regulated while the other is down-regulated in a statistical significant manner, compared to non-treated controls.
in contrast to pearson correlation, which is usually calculated using the absolute value of each hybridization experiment and when calculated based on expression differences ignores the statistical significance of the differences in each biological perturbation, the gene coordination measure is always based on expression differences and the statistical significance of the difference in each biological perturbation is always taken into account.
it is important to mention that since the calculation of gene coordination is strongly based on the selection of the different biological perturbations, it is essential to identify the relevant biological perturbations for each biological question.
detailed explanation of this novel measure and the statistical model that was used to analyze it are described in the methods section.
the power of our novel gene coordination measure is exemplified in fig.
<dig>  panel a illustrates the relationships between the correlation and coordination of expression of the lkr/sdh gene of lysine catabolism with each one of the other arabidopsis genes , based on our entire dataset of  <dig> different biological perturbations.
this relationship is depicted by two dotes, one with a blue color and the second with a red color.
the two dotes possess identical correlation values over the entire dataset of  <dig> biological perturbations  because they belong to the same pair of genes.
yet, they possess two different coordination values, one showing negative coordination, which is contributed by a selected set of biological perturbations , while the other showing positive coordination that is contributed by a different set of biological perturbations  .
panels b-d of fig.
<dig> illustrate the expression relationship between the lkr/sdh gene and three representative genes over the entire dataset of  <dig> biological perturbations.
each dot represents data associated with a specific biological perturbation that was obtained from analysis of at least four different microarray chips and thus allows performing a significance test.
r value of the pearson correlation coefficient is also indicated within each panel.
panel b illustrates a case in which there is no correlation between the pair of genes across the entire depicted set of biological perturbations, but there is a significant number of biological perturbations that contribute both to negative and positive coordinations between these two genes .
panel c illustrates a case in which there is a positive correlation of expression between a pair of genes across the entire depicted set of biological perturbations, but a significant number of biological perturbations contribute to a negative coordination between these two genes .
panel d illustrates an opposite case in which there is a negative correlation of expression between a pair of genes across the entire depicted set of biological perturbations, but a significant number of biological perturbations contribute to a positive coordination between these two genes .
hence, genes whose expression shows statistically significant negative or positive coordination under depicted set of biological perturbations  were defined as "highly coordinated genes" .
identification of highly coordinated genes  within the asp-family and aaa networks
to identify the hcgs within each network, we used a coordination matrix  in which the upper right triangle shows positive coordination and the lower left triangle shows negative coordination .
it is important to note that in such a coordination matrix, the red or the blue squares existing for each genes pair are derived from responses to different biological perturbations.
panels a and c in fig.
<dig> depict respectively the coordination matrixes of the entire set of genes within the asp-family and aaa metabolic networks.
notably, only a selected group of genes within each of these two networks showed either high negative  and/or high positive  coordination of expression in which higher intensity of the colors signifies higher number of biological perturbations in which negative or positive co-regulation were observed.
in order to identify the hcgs within each network, we used a background model for the evaluation of the negative and positive coordination in each network, assuming no coordination, and considered genes to be hcgs if their observed coordination was higher by more then six standard deviations from the coordination that was estimated by our background model .
based on these criteria, we selected  <dig> and  <dig> hcgs within the asp-family and the aaa networks, respectively .
it is clear from these two panels that in each network, the hcgs are divided into two distinct groups of genes in which there is a positive coordination between the genes within each hcgs group and a negative coordination between the genes of the different hcgs groups.
in the asp-family network, one hcgs group includes exclusively catabolic genes, namely tha <dig> , bcat <dig> , mgl  and lkr/sdh  , and from here on will be referred to as the "catabolic group".
the second group in the asp-family network includes almost entirely genes encoding enzymes of met biosynthesis and catabolism towards sam and various glucosinolates, and therefore from here on will be referred to as the "met metabolism group".
in specific, this group includes  genes encoding biosynthetic enzymes, namely, the bifunctional ak/hsdh <dig> isozyme plus one or more monofunctional ak isozymes catalyzing the first step of the asp-family network , cgs <dig>  and dapd ; and  genes encoding catabolic enzymes, namely, sams <dig> , bcat <dig>  as well as bcat <dig>  mam <dig> and maml  .
in the aaa network, one hcgs group includes  <dig> genes containing both biosynthetic and catabolic genes, while the second hcgs group includes only two genes .
since the expression patterns of the aaa genes showed that the first group also possesses isozymic genes of pal and igps, which are expressed under conditions that pal <dig> and igps are repressed , we decided to exclude this group from further analyses.
the first group, which will be referred to from here on as the sole "aaa group" of the aaa network, includes the following genes: the trp biosynthesis genes asa <dig>  asb, tsa <dig>  tsb1/ <dig> and one of the igps genes; the trp catabolic gene cyp79b <dig>  the phe biosynthesis gene pd, the phe catabolic genes pal <dig> and pal <dig> and the tyr catabolic gene tat <dig> .
effects of specific biological perturbations on the patterns of expression of the hcgs of the asp-family network
to identify the patterns of response of the hcgs of the asp-family network to specific biological perturbations, we selected from the  <dig> short-term biological perturbations of the nasc database all biological perturbations in which expression of at least one of the hcgs of this network was increased or decreased by more then four folds.
this stringent filter was used to make sure that we are analyzing only relevant perturbations.
in experiments containing time course exposure to a given cue, each time point was considered separately.
fig.
<dig> lists the specific biological perturbations obeying the above rule , as well as their effect on the expression of each of the hcgs of the asp-family network  and the euclidian distance between the specific biological perturbations .
in this dendogram, the larger the separation between two biological perturbations, the larger is the extent of their differential effects on the hcgs of the asp-family network.
in addition, an artificial biological perturbation of growing in the dark in the presence of sucrose also had a significant effect on the asp-family network .
the magnitudes of the expression response of the different hcgs to the different abiotic and biotic stresses varied between the different stresses and the time course of each stress, being generally higher at later periods of exposure to the stresses .
however, the hcgs could be clearly classified into two principal groups, matching the earlier "met metabolism" and "catabolic" hcgs groups with the opposite responses, the first  being repressed , while the second  being induced  by the stresses.
notably, the artificial biological perturbation of dark plus added sucrose on plants with suppression and over expression of myb <dig>  had a significantly different effect on the asp-family genes repressing the expression of the genes belonging to the catabolic group , while inducing the expression of genes belonging to the met metabolism group .
this artificial biological perturbation seems to increase the biosynthetic fluxes and reduce much of the catabolic fluxes of the asp-family network and may signify an override of the sucrose signal over the dark signal to promote growth and protein synthesis.
effects of specific biological perturbations on the patterns of expression of the hcgs of the aaa network
next, we identified the patterns of response of the hcgs of the aaa network to the  <dig> short-term biological perturbations of the nasc database in an identical manner to that used for the asp-family network .
fig.
<dig> lists the specific biological perturbations , as well as their effect on the expression of each of the hcgs of the aaa network  and the euclidian distance between the specific biological perturbations .
also in the case of the aaa network, most of the biological perturbations influencing the expression of aaa genes included biotic and abiotic stresses .
the magnitude of the expression responses of the different hcgs to the different abiotic and biotic stresses varied between the different stresses and the time course of each stress .
interestingly, as opposed to the asp-family network , the artificial biological perturbation of adding sucrose in the dark was inseparable from other stresses in its effect on the aaa network , implying that the hypothetical override of sucrose over dark is network dependent.
interactive coordination of expression of the hcgs from the asp-family and aaa metabolic networks
next, we examined the cross-network coordination between the hcgs of the asp-family and aaa networks, based on the same  <dig> short-term biological perturbations.
the respective negative and positive coordination matrixes between the hcgs of the asp-family and aaa networks are shown in fig.
<dig>  notably, most of the hcgs of the two networks exhibited both a considerable cross-network negative coordination  as well as a considerable cross-network positive coordination  between them under different biological perturbations.
this implies that some cues trigger a coordinated opposite transcriptional regulation of the two networks , while other cues trigger a coordinated similar transcriptional stimulation or repression of the two networks .
it is important to notice that this behavior, of both negative and positive coordination patterns, observed between the hcgs of both networks, is conceptually different from the behavior that was observed within the hcgs of each network where all pairs of genes were either positively or negatively coordinated and therefore were respectfully assigned to the same or to different groups.
interactive influence of different biological perturbations on the asp-family and aaa metabolic networks
taking into account the central importance of the asp-family and aaa metabolic networks in plant growth, it was also interesting to examine the extent of interactive effects of different cues  on the operation of the asp-family and aaa networks.
to address this, we plotted the calculated euclidian distance between all possible pairs of cues, which significantly alter the expression of at list one of the hcgs in either networks , in respect to the magnitude of their differential effects on the entire hcgs of each of the networks .
the pairs of cues  ranged from pairs having highly similar magnitudes of differential effects  to pairs having progressively increasing differential magnitudes of effects on one of the network while having progressively decreasing differential magnitudes of effects on the second network .
we were particularly interested in the black dots within the blue and red circles  because they represent pairs of cues having a similar effect on one of the networks, while a differential effect on the second network.
these in fact signify cues that are differentially recognized by the plant in respect to the operation of the asp-family and aaa metabolic networks .
the entire set of biological perturbations pairs which meet the above criteria can be divided in to two groups:  biological perturbations pairs in which both biological perturbations affect one of the networks, while only one of them affects the other network: and  biological perturbations pairs in which both biological perturbations affect both networks, but having similar effects on one of the networks, while differential effects on the other network.
identification of genome-wide genes whose expression is coordinated with the expression of the hcgs of the asp-family and aaa networks in response to the different cues
we also used the gene coordination principle to identify cross-interactions between the hcgs of the asp-family and aaa networks and other functionally annotated genome-wide genes in order to elucidate the association between the different hcgs groups and specific biological processes.
to address this, we selected only genome-wide genes that are either positively or negatively coordinated with all of the genes within each one of the three groups of hcgs .
this created six groups of genome-wide genes as follows:   <dig> and  <dig> genome-wide genes whose expression is positively and negatively coordinated, respectively, with the met metabolism group:   <dig> and  <dig> genome-wide genes whose expression is positively and negatively coordinated, respectively, with the catabolic group; and   <dig> and  <dig> genome-wide genes whose expression is positively and negatively coordinated, respectively, with the aaa group.
the entire lists of these genes are shown in additional file  <dig>  these genome-wide groups of genes were then classified, using the publicly available gene ontology  annotation  into distinct groups based on their link to biological processes, searching for significant enrichments of specific biological processes that are associated with the different hcgs groups.
the entire list of biological processes showing a significant enrichment for each one of the six groups of genome-wide genes is presented in table  <dig>  in general, the met metabolism group of the asp-family network was positively coordinated with genes controlling growth-promoting processes, such as nucleosome assembly ribosome biogenesis, translation and biosynthetic processes, while it was negatively coordinated mostly with stress-associated processes, such as the stress-associated hormones jasmonic acid, salicylic acid and aba as well as trehalose metabolism.
the catabolic group of the asp-family pathway was positively coordinated with various stress-associated process, which only partially overlap with the stress-associated processes that are negatively coordinated with the met metabolism group of hcgs of this network.
in addition, the catabolic group was negatively coordinated with various growth promoting processes, which was only partially overlap with the growth promoting processes positively coordinated with the met metabolism group of the same network .
hence, the met metabolism and the catabolic groups of the asp-family network partially negatively interact with each other in respect to their cooperation with other genome-wide genes associated with various physiological processes.
the aaa group of hcgs of the aaa network was essentially positively coordinated with genome-wide genes associated with various stresses as well as the production of phenylpropanoids, including the biosynthesis of the cell wall phenylpropanoid lignin, while it was essentially negatively coordinated with various growth-promoting processes, such as water transport, photosynthesis and various biosynthetic processes.
notably, there was a relatively small overlap between the biological processes linked to the asp-family and aaa networks .
discussion
gene coordination: a new bioinformatics approach to discover genes whose expression pattern exhibits both negative and positive interactions under different biological conditions
pearson correction is a common bioinformatics approach to search for genes with harmonized expression patterns over a wide range of biological conditions.
yet, in some biological networks, such as networks of amino acid metabolism, some metabolites can serve as substrates to multiple metabolic pathways, leading to the synthesis of different metabolites with differential functions.
due to a potential biological need to channel a given branch point metabolite to different pathways under given growth conditions or to two or more pathways together under other growth conditions, it is expected that expression of given genes encoding enzymes of different pathways may be both positively correlated under some biological perturbations while negatively correlated or not correlated at all under other biological perturbations.
in the present report we describe the development of "gene coordination" as a novel bioinformatics approach to address this issue.
this approach takes advantage on the ability to detect positive and negative coordination patterns between gene pairs under multiple biological perturbations by comparing changes in the intensities of expression signals of treatment versus control in several repeated experiments for each biological perturbation.
genes whose expression is either negatively or positively coordinated in a statistical significant manner under a selected set of biological perturbations are defined as highly coordinated genes .
using the asp-family and aaa metabolic networks of amino acid metabolism as model systems, we also provide evidence indicating that hcgs are central regulatory genes within specific biological networks, as evident from their tight negatively or positively coordinated expression with other genome-wide genes under different biological perturbations.
moreover, our results showing high positive coordination with no negative coordination among hcgs of the same group and high negative coordination with no positive coordination between hcgs of different groups within the same network imply that our gene coordination approach can identify hcgs groups and networks without any prior experimental knowledge for their existence.
the asp-family network is principally regulated by two negatively coordinated transcriptional programs of its hcgs
our results exposing two negatively coordinated groups of hcgs within the asp-family network imply that this network is regulated by two opposing transcription programs, namely, when the first program is active the second is repressed and vice versa.
the enzymatic steps controlled by the hcgs belonging to these two programs are depicted by blue and red arrows in additional file  <dig>  the first transcription program  includes coordinated expression of genes controlling:  the entry point into this network ;  the conversion of asp into lys  and met ;  catabolism of met via sam into multiple growth-associated metabolites  <cit> ; and  catabolism met into multiple glucosinolates .
the second transcription program  includes coordinated expression of genes encoding the catabolic enzymes lkr/sdh , tha- <dig>  and mgl .
each of these two opposing transcription programs also contains a gene encoding a distinct isozyme controlling ile catabolism into energy production .
the biological significance of this observation is still not clear.
notably, even though the asp-family network also leads to the synthesis of thr and ile, genes encoding enzymes of these two branches are not included in the group of hcgs that participate in the transcriptional regulation of this network .
yet, the last enzyme of thr biosynthesis, namely thr synthase, is regulated by a post-transcriptional control , implying that the principal transcription programs exposed in this report operate in concert with other post-transcriptional programs and covers all branches of the asp-family network .
concerted transcriptional and post-transcriptional controls of the asp-family network
previous studies showed that the asp-family network is regulated by multiple post-transcriptional controls including:  feedback inhibition of the different ak isozymes, controlling the entry point into this network, by thr, lys and sam, feedback inhibition of homoserine dehydrogenase by thr, feedback inhibition of thr deaminase by ile and feedback inhibition of dihydrodipicolinate synthase by lys   <cit> ;  post-transcriptional inhibition of the mrna level of cgs, the central regulatory enzyme of met biosynthesis, by sam via a highly complex post-transcriptional regulation  <cit> ;  stimulation of the activity of thr synthase, the terminal enzyme of thr biosynthesis by sam  <cit> ; and  regulation of lkr/sdh activity by protein phosphorylation  <cit> .
our present results thus add another dimension to the above extensive regulatory programs, implying that the asp-family network is also regulated by two opposing transcription programs encoding either the "catabolic" or the "met biosynthesis" groups of hcgs.
the participation of the dapd gene of lys biosynthesis in the hcgs comprising the biosynthesis program is also particularly interesting, taking into account that a mutation in this enzyme was recently found to play an important regulatory role in the response of arabidopsis plants to pseudomonas infection, apparently via modulating the regulation of the biotic stress-associated hormone salicylic acid  <cit> .
interaction of the asp-family network with genome-wide genes
our study showed that the met metabolism and catabolic groups of hcgs of the asp-family network exhibit:  positive coordinated expression patterns with  <dig> and  <dig> genome-wide genes, respectively; and  negative coordinated expression patterns with other  <dig> and  <dig> genome wide genes, respectively .
division of these genome-wide genes into functional groups implied the following:  the biosynthesis program of the asp-family network  is positively associated with genome-wide growth promoting process , while negatively associated with genome-wide stress-associated process ; and  the catabolic program  of the asp-family pathways is positively associated with genome-wide stress-associated programs  and negatively associates with genome-wide growth associated processes .
thus, our results suggest that:  active growth under favorable growth conditions essentially triggers the biosynthesis of the asp-family amino acids for their incorporation into proteins and also for the catabolism of met via sam towards the synthesis of growth promoting hormones as well for donation of methyl groups for dna replication and for the synthesis of a large array of growth-associated metabolites; and  exposure to stress conditions stimulates rapid metabolic switches within the asp-family pathway, shifting fluxes from the met branch, to the lys and thr branches on route towards their catabolism into other metabolites, such as glu and acetyl coa , ile-mediated energy production  and gly production , which are apparently needed to support metabolic adaptation to stress conditions.
it is also interesting to note that in the met metabolism group of the asp-family network, the ratio between the number of genome-wide genes that are significantly positively coordinated to those that were significantly negatively coordinated is much higher than in the catabolic group of the asp-family network as well as in the aaa group of the aaa network .
we hypothesize that this reflects the centrality of the met metabolism group of the asp-family network in the physiology of plant growth under favorable, non-stress conditions, an hypothesis that is also in accord with extensive previous literature  <cit> .
these observations also support the notion that gene expression networks in plants  operate in a modular fashion through interactions of multiple modules, which in the present report are represented by the three hcgs groups of the asp-family and aaa networks.
we also assume that under the majority of growth conditions, most of the modules are relatively inactive, an assumption that is supported by the observation that in most arrays, about half of the genes are not express .
the outcome of such an assumption is that most modules are expected to be much more often negatively coordinated rather than positively coordinated with other modules, while only central modules, such as the met metabolism module, which are needed in a wide range of growth conditions, will deviate in respect to their more profound operation.
the aaa network is principally regulated by a single transcriptional program of its hcgs
our results imply that the regulation of the aaa network is principally significantly simpler than that of the asp-family network, including only a single dominant transcription program of  <dig> hcgs.
this transcription program comprises genes controlling the first catabolic steps of phe, tyr and trp and also genes controlling biosynthetic enzymes of trp .
these genes are principally stimulated in response to biotic and abiotic stresses, but the combinations of specific genes within this group of hcgs vary between the different stress conditions.
responses to biotic stresses and also relatively early responses  to several abiotic stresses, such as uv-b, stimulate the expression of most of the hcgs of the aaa network, while stimulation of only different combinations of the catabolic genes of the different amino acids of this network is principally needed during the late response to various abiotic stresses.
as depicted in table  <dig>  the functions of the genome-wide genes exhibiting positive coordinated expression patterns with the hcgs of the aaa network essentially include:  negative regulation of programmed cell death;  facilitation of production of secondary metabolites derived from the aromatic amino acids for various physiological needs, including lignin production for cell wall biosynthesis; and  defence against various biotic and abiotic stresses.
the genome-wide genes exhibiting negative coordinated expression patterns with the hcgs of the aaa network generally function in various processes associated with plant growth under favourable growth conditions.
regulatory transcriptional interaction between the asp-family and aaa metabolic networks
the considerable variation in euclidian distance between many pairs of biological perturbations  when calculated based on their effects on the hcgs of the asp-family and aaa metabolic networks  has two major implications.
the first is that some biological perturbations affect one, but not the second network.
for example, both uv-b stress after one hour in shoots and drought stress after one hour in roots stimulate only mildly if at all the hcgs of the asp-family network , while stimulating much stronger the hcgs of the aaa network .
yet, these uv-b and drought stresses seems to differentially affect the aaa network, the first stimulating phe and trp catabolism by up regulating pal <dig>  pd and cyp79b <dig> and down regulating the tat <dig> gene of tyr catabolism, while the second stimulate only tyr catabolism by up regulating tat <dig> .
the second implication is that some biological perturbations affect both networks, but having different effects on each one of them.
for example, uv-b stress after six hours in shoots and low light for  <dig> h hours in petioles similarly shift the conversion of met into glucosinolates towards energy biosynthesis by repressing mam <dig>  maml and bcat <dig> of glucosinolates biosynthesis and up regulating mgl and bcat <dig> of ile-derived energy biosynthesis.
yet these same stresses have differential effect on the aaa network, the first  highly stimulates trp synthesis and catabolism  by up regulation of most of the relevant hcgs, while the second  suppresses the aaa network probably as results of a lower growth rate.
an opposite situation is observed in the response to wounding after  <dig> hours in shoots and the response to salt stress after  <dig> hours in roots.
both of these stresses promote tyr catabolism in the aaa network by strongly up regulating tat <dig> expression, but having differential effects on the asp-family network with wounding affecting promoting the catabolism of thr, lys and ile , while salt seems to shut down the entire network by down regulating the entire set of biosynthetic hcgs.
CONCLUSIONS
in the present report, we have developed a novel gene coordination approach, which enables the simultaneous identification of positive and negative expression relationships between genes over a wide range of biological perturbations.
this approach is particularly important in cases where both positive and negative expression relationships are expected as in genes controlling competing branches in metabolic networks.
this approach was central to the identification of hcgs with the asp-family and aaa metabolic networks of arabidopsis plants and is likely also to enable the identification of hcgs in other complex biological networks of higher organisms in which only genes encoding a small fraction of the enzymatic steps play a key regulatory role.
notably, our gene coordination approach also revealed that pairs of environmental cues can have a similar effect on one network, while having a differential effect on another network.
this implies that when plants are exposed to two or more simultaneous stresses, there may be an override of one stress over the other in its effect on one network, but not the other.
our present report also provides an approach to elucidate such complex relationships.

 being stationary organisms that are unable to move, plants represent a unique biological system that is highly adaptive to environmental stresses. the adaptation mechanisms of plants to stresses also involve coordinated adjustments of a large array of metabolic networks. among those are metabolic networks containing amino acids as intermediate metabolites, which can either be incorporated into proteins, accumulate to high levels in response to specific cues, such as proline accumulation in response to salt stress, or serve as precursors for a large array of metabolites with multiple functions. some of the metabolic networks of amino acids possess several competing branches, each leading to the synthesis of one or more amino acids and their downstream metabolites. two of the most important branched metabolic networks of amino acids are the asp-family network and the aromatic amino acids network. these two networks also possess significant nutritional value because humans and much of their farm animals cannot synthesize the amino acids produced by them and therefore depend on plants as their nutritional supplements. astep numbers represent enzymatic steps described in fig. and additional file batg represents the common locus number using tair nomenclature. cprobeset represents specific identifiers according to affymetrix ath microarray. dhighly coordinated genes the asp-family network, which classically includes the amino acids lys, thr, met and ile, is a central regulator of plant growth not only because its amino acids are essential for protein synthesis. met is a metabolic precursor for multiple fundamental cellular processes, while thr, through its conversion into ile, participates plant pathogen interactions and cellular energy production. thr is also catabolized by two thr aldolase isozymes into gly, which is closely associated with photorespiration. lys biosynthesis and catabolism was also shown to be associated with plant pathogen interactions as well as with the production of the stress associated hormone salicylic acid. the aaa metabolic network leads to the synthesis of trp, phe and tyr, which are further used as precursors for various hormones, cell wall components and a large array of multifunctional secondary metabolites. using a bioinformatics approach based on publicly available microarray results, we have recently demonstrated evidence supporting the presence of principal transcriptional programs of amino acid metabolism in response to abiotic stresses. strikingly, these responses were most profoundly associated with changes in expression of genes encoding the catabolic enzymes of the amino acids with only minor changes in mrna levels of genes encoding the biosynthesis enzymes. this phenomenon in which genes encoding only a fraction of the enzymes within a given metabolic pathway are altered in response to a given cue is in sharp contrast to microorganisms in which the expression of all genes of a given metabolic pathway is generally altered in response to a given cue. this major conceptual difference is likely because highly dividing microorganisms face extensive dilution of their enzyme concentrations through the frequent cell divisions, while cells of higher organisms relatively infrequently divide in the short time scales of environmental changes. in addition, higher organisms often have more than one gene encoding a given enzyme, and therefore transcriptionally regulate only a fraction of the genes encoding isozymes in different tissues or in response to different cues. this fact adds another damnation of complexity when analyzing transcription results of higher organisms. notably, arabidopsis plants specifically adjust the expression of genes encoding different catabolic enzymes of amino acids in response to different stresses. this implies that bioinformatics approach aiming to elucidate interactions of different branched networks of amino acid metabolism in plants under multiple growth conditions is a challenging issue because different branches are likely subjected to dynamically changing patterns of coordinated regulation. under some conditions, such as optimal growth conditions, all branches are expected to operate efficiently to allow the synthesis of amino acid for incorporation into proteins. under other biological perturbations, such as exposure to specific stress conditions, fluxes are expected to increase in some branches on the expense of others to allow optimal metabolic adjustments. therefore genes encoding enzymes of specific branches within a given amino acid metabolic network are expected to be both positively correlated under some biological perturbations, while negatively correlated or not correlated at all under other biological perturbations. as a consequence, genes encoding enzymes of specific branches within a given metabolic network are also expected to be both positively correlated, negatively correlated or non-correlated with other genome-wide genes under different biological perturbations. therefore, commonly used correlation methodologies are not suited to elucidate transcriptional network interactions of amino acid metabolic pathways because they are unable to resolve positive from negative correlations within a wide range of biological perturbations. to overcome this limitation, we have developed in the present report a novel principal approach, termed "gene coordination" allowing the elucidation of groups of genes whose expression is coordinated by both positive and negative correlations in response to different sets of biological perturbations. we also used this novel approach to elucidate differential genome-wide interactions of two central amino acid metabolic networks, namely the asp-family and aaa metabolic networks,. our results expose novel principal transcriptional regulatory aspects of each of these networks and also show that they differentially interact with genome-wide genes in plant growth and response to the environment.  selection of genes associated with the asp-family and aaa metabolic networks and sources of publicly available microarray experiments the aim of this research was to discover novel network interactions associated with two central metabolic networks of amino acids, namely the asp-family network and the aaa network. the asp-family network includes the amino acids lys, thr and met, ile and gly whose synthesis initiates from asp, and in which one pathway leads to lys metabolism, a second pathway leads to thr synthesis and its further conversion into ile and gly, and the third pathway leads to met metabolism. the aaa network, whose synthesis initiates from chorismate, includes three pathways; one leading to trp metabolism, while the second and third pathways lead to phe and tyr metabolism. since the phe and tyr pathways contain altogether only few enzymatic steps, from which one is common to both pathways, we therefore treated them as a single pathway. in both the asp-family and aaa networks, we focused on genes encoding biosynthetic enzymes as well as enzymes catalyzing the first catabolic steps of the amino acids. our definition of catabolism included the breakdown of the amino acid into carbon, nitrogen and energy-associated molecules as well as the utilization of the amino acids for the synthesis of other special metabolites, such as secondary metabolites. the selection of the entire set of genes associated with these two networks was as previously described. the functional annotation of the genes in this list was based on a combinatorial analysis of information form tair, aracyc and literature review. the list of enzymes and the genes encoding them, which were used in this study, are detailed in table some of the genes studied in this report are indistinguishable in the ath affymetrix chip and are monitored by a common probeset as indicated in table for simplicity, we will refer in the following to these probesets as genes rather than probesets. our bioinformatics approach was based on analyzing a selected set of experiments in the publicly available arabidopsis microarray data available through the nasc database. yet, since we were interested to elucidate programs of transcriptional regulation, we focused only on relatively short time responses of genes, belonging to the asp-family and aaa metabolic networks, to different biological cues. in addition, in experiments where a mutant genotype was analyzed in comparison to a control genotype, we considered these lines as two distinct genotypes. these guidelines enabled us to extract different short-term biological perturbations, which were enforced on many different genotypes. it is important to emphasize that in cases in which multiple time points were analyzed in an individual experiment, each time point was used as an independent biological perturbation. this was done due to the fact that the response of different genes in different time scales may play a significant regulatory role in the adjustment of metabolic channelling as was suggested in our previous report. since different branches in branched metabolic networks lead to the synthesis of different metabolites with distinct functions, it is expected that the different branches should possess significant regulatory gene expression flexibilities to either be positively or negatively correlated in response to different cues. hence, pearson correlation analysis is not suitable to discover associations between such genes over large sets of different experiments. to overcome this, we developed a novel bioinformatics approach, termed "gene coordination". the principal difference between gene correlation and gene coordination is that gene coordination allows the identification of both statistically significant negative and positive coordinations of expression between pairs of genes over a set of multiple biological perturbations. in short, this novel measure assigns two distinct values between each pair of genes: a positive coordination, which is the number of biological perturbations in which both genes of a given gene pair are either up-regulated or down-regulated together in a statistical significant manner, compared to non-treated controls; and a negative coordination which is the number of biological perturbations in which one gene of the same gene pair is up-regulated while the other is down-regulated in a statistical significant manner, compared to non-treated controls. in contrast to pearson correlation, which is usually calculated using the absolute value of each hybridization experiment and when calculated based on expression differences ignores the statistical significance of the differences in each biological perturbation, the gene coordination measure is always based on expression differences and the statistical significance of the difference in each biological perturbation is always taken into account. it is important to mention that since the calculation of gene coordination is strongly based on the selection of the different biological perturbations, it is essential to identify the relevant biological perturbations for each biological question. detailed explanation of this novel measure and the statistical model that was used to analyze it are described in the methods section. the power of our novel gene coordination measure is exemplified in fig. panel a illustrates the relationships between the correlation and coordination of expression of the lkr/sdh gene of lysine catabolism with each one of the other arabidopsis genes, based on our entire dataset of different biological perturbations. this relationship is depicted by two dotes, one with a blue color and the second with a red color. the two dotes possess identical correlation values over the entire dataset of biological perturbations because they belong to the same pair of genes. yet, they possess two different coordination values, one showing negative coordination, which is contributed by a selected set of biological perturbations, while the other showing positive coordination that is contributed by a different set of biological perturbations. panels b-d of fig. illustrate the expression relationship between the lkr/sdh gene and three representative genes over the entire dataset of biological perturbations. each dot represents data associated with a specific biological perturbation that was obtained from analysis of at least four different microarray chips and thus allows performing a significance test. r value of the pearson correlation coefficient is also indicated within each panel. panel b illustrates a case in which there is no correlation between the pair of genes across the entire depicted set of biological perturbations, but there is a significant number of biological perturbations that contribute both to negative and positive coordinations between these two genes. panel c illustrates a case in which there is a positive correlation of expression between a pair of genes across the entire depicted set of biological perturbations, but a significant number of biological perturbations contribute to a negative coordination between these two genes. panel d illustrates an opposite case in which there is a negative correlation of expression between a pair of genes across the entire depicted set of biological perturbations, but a significant number of biological perturbations contribute to a positive coordination between these two genes. hence, genes whose expression shows statistically significant negative or positive coordination under depicted set of biological perturbations were defined as "highly coordinated genes". identification of highly coordinated genes within the asp-family and aaa networks to identify the hcgs within each network, we used a coordination matrix in which the upper right triangle shows positive coordination and the lower left triangle shows negative coordination. it is important to note that in such a coordination matrix, the red or the blue squares existing for each genes pair are derived from responses to different biological perturbations. panels a and c in fig. depict respectively the coordination matrixes of the entire set of genes within the asp-family and aaa metabolic networks. notably, only a selected group of genes within each of these two networks showed either high negative and/or high positive coordination of expression in which higher intensity of the colors signifies higher number of biological perturbations in which negative or positive co-regulation were observed. in order to identify the hcgs within each network, we used a background model for the evaluation of the negative and positive coordination in each network, assuming no coordination, and considered genes to be hcgs if their observed coordination was higher by more then six standard deviations from the coordination that was estimated by our background model. based on these criteria, we selected and hcgs within the asp-family and the aaa networks, respectively. it is clear from these two panels that in each network, the hcgs are divided into two distinct groups of genes in which there is a positive coordination between the genes within each hcgs group and a negative coordination between the genes of the different hcgs groups. in the asp-family network, one hcgs group includes exclusively catabolic genes, namely tha, bcat, mgl and lkr/sdh, and from here on will be referred to as the "catabolic group". the second group in the asp-family network includes almost entirely genes encoding enzymes of met biosynthesis and catabolism towards sam and various glucosinolates, and therefore from here on will be referred to as the "met metabolism group". in specific, this group includes genes encoding biosynthetic enzymes, namely, the bifunctional ak/hsdh isozyme plus one or more monofunctional ak isozymes catalyzing the first step of the asp-family network, cgs and dapd; and genes encoding catabolic enzymes, namely, sams, bcat as well as bcat mam and maml. in the aaa network, one hcgs group includes genes containing both biosynthetic and catabolic genes, while the second hcgs group includes only two genes. since the expression patterns of the aaa genes showed that the first group also possesses isozymic genes of pal and igps, which are expressed under conditions that pal and igps are repressed, we decided to exclude this group from further analyses. the first group, which will be referred to from here on as the sole "aaa group" of the aaa network, includes the following genes: the trp biosynthesis genes asa asb, tsa tsb1/ and one of the igps genes; the trp catabolic gene cyp79b the phe biosynthesis gene pd, the phe catabolic genes pal and pal and the tyr catabolic gene tat. effects of specific biological perturbations on the patterns of expression of the hcgs of the asp-family network to identify the patterns of response of the hcgs of the asp-family network to specific biological perturbations, we selected from the short-term biological perturbations of the nasc database all biological perturbations in which expression of at least one of the hcgs of this network was increased or decreased by more then four folds. this stringent filter was used to make sure that we are analyzing only relevant perturbations. in experiments containing time course exposure to a given cue, each time point was considered separately. fig. lists the specific biological perturbations obeying the above rule, as well as their effect on the expression of each of the hcgs of the asp-family network and the euclidian distance between the specific biological perturbations. in this dendogram, the larger the separation between two biological perturbations, the larger is the extent of their differential effects on the hcgs of the asp-family network. in addition, an artificial biological perturbation of growing in the dark in the presence of sucrose also had a significant effect on the asp-family network. the magnitudes of the expression response of the different hcgs to the different abiotic and biotic stresses varied between the different stresses and the time course of each stress, being generally higher at later periods of exposure to the stresses. however, the hcgs could be clearly classified into two principal groups, matching the earlier "met metabolism" and "catabolic" hcgs groups with the opposite responses, the first being repressed, while the second being induced by the stresses. notably, the artificial biological perturbation of dark plus added sucrose on plants with suppression and over expression of myb had a significantly different effect on the asp-family genes repressing the expression of the genes belonging to the catabolic group, while inducing the expression of genes belonging to the met metabolism group. this artificial biological perturbation seems to increase the biosynthetic fluxes and reduce much of the catabolic fluxes of the asp-family network and may signify an override of the sucrose signal over the dark signal to promote growth and protein synthesis. effects of specific biological perturbations on the patterns of expression of the hcgs of the aaa network next, we identified the patterns of response of the hcgs of the aaa network to the short-term biological perturbations of the nasc database in an identical manner to that used for the asp-family network. fig. lists the specific biological perturbations, as well as their effect on the expression of each of the hcgs of the aaa network and the euclidian distance between the specific biological perturbations. also in the case of the aaa network, most of the biological perturbations influencing the expression of aaa genes included biotic and abiotic stresses. the magnitude of the expression responses of the different hcgs to the different abiotic and biotic stresses varied between the different stresses and the time course of each stress. interestingly, as opposed to the asp-family network, the artificial biological perturbation of adding sucrose in the dark was inseparable from other stresses in its effect on the aaa network, implying that the hypothetical override of sucrose over dark is network dependent. interactive coordination of expression of the hcgs from the asp-family and aaa metabolic networks next, we examined the cross-network coordination between the hcgs of the asp-family and aaa networks, based on the same short-term biological perturbations. the respective negative and positive coordination matrixes between the hcgs of the asp-family and aaa networks are shown in fig. notably, most of the hcgs of the two networks exhibited both a considerable cross-network negative coordination as well as a considerable cross-network positive coordination between them under different biological perturbations. this implies that some cues trigger a coordinated opposite transcriptional regulation of the two networks, while other cues trigger a coordinated similar transcriptional stimulation or repression of the two networks. it is important to notice that this behavior, of both negative and positive coordination patterns, observed between the hcgs of both networks, is conceptually different from the behavior that was observed within the hcgs of each network where all pairs of genes were either positively or negatively coordinated and therefore were respectfully assigned to the same or to different groups. interactive influence of different biological perturbations on the asp-family and aaa metabolic networks taking into account the central importance of the asp-family and aaa metabolic networks in plant growth, it was also interesting to examine the extent of interactive effects of different cues on the operation of the asp-family and aaa networks. to address this, we plotted the calculated euclidian distance between all possible pairs of cues, which significantly alter the expression of at list one of the hcgs in either networks, in respect to the magnitude of their differential effects on the entire hcgs of each of the networks. the pairs of cues ranged from pairs having highly similar magnitudes of differential effects to pairs having progressively increasing differential magnitudes of effects on one of the network while having progressively decreasing differential magnitudes of effects on the second network. we were particularly interested in the black dots within the blue and red circles because they represent pairs of cues having a similar effect on one of the networks, while a differential effect on the second network. these in fact signify cues that are differentially recognized by the plant in respect to the operation of the asp-family and aaa metabolic networks. the entire set of biological perturbations pairs which meet the above criteria can be divided in to two groups: biological perturbations pairs in which both biological perturbations affect one of the networks, while only one of them affects the other network: and biological perturbations pairs in which both biological perturbations affect both networks, but having similar effects on one of the networks, while differential effects on the other network. identification of genome-wide genes whose expression is coordinated with the expression of the hcgs of the asp-family and aaa networks in response to the different cues we also used the gene coordination principle to identify cross-interactions between the hcgs of the asp-family and aaa networks and other functionally annotated genome-wide genes in order to elucidate the association between the different hcgs groups and specific biological processes. to address this, we selected only genome-wide genes that are either positively or negatively coordinated with all of the genes within each one of the three groups of hcgs. this created six groups of genome-wide genes as follows: and genome-wide genes whose expression is positively and negatively coordinated, respectively, with the met metabolism group: and genome-wide genes whose expression is positively and negatively coordinated, respectively, with the catabolic group; and and genome-wide genes whose expression is positively and negatively coordinated, respectively, with the aaa group. the entire lists of these genes are shown in additional file these genome-wide groups of genes were then classified, using the publicly available gene ontology annotation into distinct groups based on their link to biological processes, searching for significant enrichments of specific biological processes that are associated with the different hcgs groups. the entire list of biological processes showing a significant enrichment for each one of the six groups of genome-wide genes is presented in table in general, the met metabolism group of the asp-family network was positively coordinated with genes controlling growth-promoting processes, such as nucleosome assembly ribosome biogenesis, translation and biosynthetic processes, while it was negatively coordinated mostly with stress-associated processes, such as the stress-associated hormones jasmonic acid, salicylic acid and aba as well as trehalose metabolism. the catabolic group of the asp-family pathway was positively coordinated with various stress-associated process, which only partially overlap with the stress-associated processes that are negatively coordinated with the met metabolism group of hcgs of this network. in addition, the catabolic group was negatively coordinated with various growth promoting processes, which was only partially overlap with the growth promoting processes positively coordinated with the met metabolism group of the same network. hence, the met metabolism and the catabolic groups of the asp-family network partially negatively interact with each other in respect to their cooperation with other genome-wide genes associated with various physiological processes. the aaa group of hcgs of the aaa network was essentially positively coordinated with genome-wide genes associated with various stresses as well as the production of phenylpropanoids, including the biosynthesis of the cell wall phenylpropanoid lignin, while it was essentially negatively coordinated with various growth-promoting processes, such as water transport, photosynthesis and various biosynthetic processes. notably, there was a relatively small overlap between the biological processes linked to the asp-family and aaa networks. discussion gene coordination: a new bioinformatics approach to discover genes whose expression pattern exhibits both negative and positive interactions under different biological conditions pearson correction is a common bioinformatics approach to search for genes with harmonized expression patterns over a wide range of biological conditions. yet, in some biological networks, such as networks of amino acid metabolism, some metabolites can serve as substrates to multiple metabolic pathways, leading to the synthesis of different metabolites with differential functions. due to a potential biological need to channel a given branch point metabolite to different pathways under given growth conditions or to two or more pathways together under other growth conditions, it is expected that expression of given genes encoding enzymes of different pathways may be both positively correlated under some biological perturbations while negatively correlated or not correlated at all under other biological perturbations. in the present report we describe the development of "gene coordination" as a novel bioinformatics approach to address this issue. this approach takes advantage on the ability to detect positive and negative coordination patterns between gene pairs under multiple biological perturbations by comparing changes in the intensities of expression signals of treatment versus control in several repeated experiments for each biological perturbation. genes whose expression is either negatively or positively coordinated in a statistical significant manner under a selected set of biological perturbations are defined as highly coordinated genes. using the asp-family and aaa metabolic networks of amino acid metabolism as model systems, we also provide evidence indicating that hcgs are central regulatory genes within specific biological networks, as evident from their tight negatively or positively coordinated expression with other genome-wide genes under different biological perturbations. moreover, our results showing high positive coordination with no negative coordination among hcgs of the same group and high negative coordination with no positive coordination between hcgs of different groups within the same network imply that our gene coordination approach can identify hcgs groups and networks without any prior experimental knowledge for their existence. the asp-family network is principally regulated by two negatively coordinated transcriptional programs of its hcgs our results exposing two negatively coordinated groups of hcgs within the asp-family network imply that this network is regulated by two opposing transcription programs, namely, when the first program is active the second is repressed and vice versa. the enzymatic steps controlled by the hcgs belonging to these two programs are depicted by blue and red arrows in additional file the first transcription program includes coordinated expression of genes controlling: the entry point into this network; the conversion of asp into lys and met; catabolism of met via sam into multiple growth-associated metabolites; and catabolism met into multiple glucosinolates. the second transcription program includes coordinated expression of genes encoding the catabolic enzymes lkr/sdh, tha- and mgl. each of these two opposing transcription programs also contains a gene encoding a distinct isozyme controlling ile catabolism into energy production. the biological significance of this observation is still not clear. notably, even though the asp-family network also leads to the synthesis of thr and ile, genes encoding enzymes of these two branches are not included in the group of hcgs that participate in the transcriptional regulation of this network. yet, the last enzyme of thr biosynthesis, namely thr synthase, is regulated by a post-transcriptional control, implying that the principal transcription programs exposed in this report operate in concert with other post-transcriptional programs and covers all branches of the asp-family network. concerted transcriptional and post-transcriptional controls of the asp-family network previous studies showed that the asp-family network is regulated by multiple post-transcriptional controls including: feedback inhibition of the different ak isozymes, controlling the entry point into this network, by thr, lys and sam, feedback inhibition of homoserine dehydrogenase by thr, feedback inhibition of thr deaminase by ile and feedback inhibition of dihydrodipicolinate synthase by lys; post-transcriptional inhibition of the mrna level of cgs, the central regulatory enzyme of met biosynthesis, by sam via a highly complex post-transcriptional regulation; stimulation of the activity of thr synthase, the terminal enzyme of thr biosynthesis by sam; and regulation of lkr/sdh activity by protein phosphorylation. our present results thus add another dimension to the above extensive regulatory programs, implying that the asp-family network is also regulated by two opposing transcription programs encoding either the "catabolic" or the "met biosynthesis" groups of hcgs. the participation of the dapd gene of lys biosynthesis in the hcgs comprising the biosynthesis program is also particularly interesting, taking into account that a mutation in this enzyme was recently found to play an important regulatory role in the response of arabidopsis plants to pseudomonas infection, apparently via modulating the regulation of the biotic stress-associated hormone salicylic acid. interaction of the asp-family network with genome-wide genes our study showed that the met metabolism and catabolic groups of hcgs of the asp-family network exhibit: positive coordinated expression patterns with and genome-wide genes, respectively; and negative coordinated expression patterns with other and genome wide genes, respectively. division of these genome-wide genes into functional groups implied the following: the biosynthesis program of the asp-family network is positively associated with genome-wide growth promoting process, while negatively associated with genome-wide stress-associated process; and the catabolic program of the asp-family pathways is positively associated with genome-wide stress-associated programs and negatively associates with genome-wide growth associated processes. thus, our results suggest that: active growth under favorable growth conditions essentially triggers the biosynthesis of the asp-family amino acids for their incorporation into proteins and also for the catabolism of met via sam towards the synthesis of growth promoting hormones as well for donation of methyl groups for dna replication and for the synthesis of a large array of growth-associated metabolites; and exposure to stress conditions stimulates rapid metabolic switches within the asp-family pathway, shifting fluxes from the met branch, to the lys and thr branches on route towards their catabolism into other metabolites, such as glu and acetyl coa, ile-mediated energy production and gly production, which are apparently needed to support metabolic adaptation to stress conditions. it is also interesting to note that in the met metabolism group of the asp-family network, the ratio between the number of genome-wide genes that are significantly positively coordinated to those that were significantly negatively coordinated is much higher than in the catabolic group of the asp-family network as well as in the aaa group of the aaa network. we hypothesize that this reflects the centrality of the met metabolism group of the asp-family network in the physiology of plant growth under favorable, non-stress conditions, an hypothesis that is also in accord with extensive previous literature. these observations also support the notion that gene expression networks in plants operate in a modular fashion through interactions of multiple modules, which in the present report are represented by the three hcgs groups of the asp-family and aaa networks. we also assume that under the majority of growth conditions, most of the modules are relatively inactive, an assumption that is supported by the observation that in most arrays, about half of the genes are not express. the outcome of such an assumption is that most modules are expected to be much more often negatively coordinated rather than positively coordinated with other modules, while only central modules, such as the met metabolism module, which are needed in a wide range of growth conditions, will deviate in respect to their more profound operation. the aaa network is principally regulated by a single transcriptional program of its hcgs our results imply that the regulation of the aaa network is principally significantly simpler than that of the asp-family network, including only a single dominant transcription program of hcgs. this transcription program comprises genes controlling the first catabolic steps of phe, tyr and trp and also genes controlling biosynthetic enzymes of trp. these genes are principally stimulated in response to biotic and abiotic stresses, but the combinations of specific genes within this group of hcgs vary between the different stress conditions. responses to biotic stresses and also relatively early responses to several abiotic stresses, such as uv-b, stimulate the expression of most of the hcgs of the aaa network, while stimulation of only different combinations of the catabolic genes of the different amino acids of this network is principally needed during the late response to various abiotic stresses. as depicted in table the functions of the genome-wide genes exhibiting positive coordinated expression patterns with the hcgs of the aaa network essentially include: negative regulation of programmed cell death; facilitation of production of secondary metabolites derived from the aromatic amino acids for various physiological needs, including lignin production for cell wall biosynthesis; and defence against various biotic and abiotic stresses. the genome-wide genes exhibiting negative coordinated expression patterns with the hcgs of the aaa network generally function in various processes associated with plant growth under favourable growth conditions. regulatory transcriptional interaction between the asp-family and aaa metabolic networks the considerable variation in euclidian distance between many pairs of biological perturbations when calculated based on their effects on the hcgs of the asp-family and aaa metabolic networks has two major implications. the first is that some biological perturbations affect one, but not the second network. for example, both uv-b stress after one hour in shoots and drought stress after one hour in roots stimulate only mildly if at all the hcgs of the asp-family network, while stimulating much stronger the hcgs of the aaa network. yet, these uv-b and drought stresses seems to differentially affect the aaa network, the first stimulating phe and trp catabolism by up regulating pal pd and cyp79b and down regulating the tat gene of tyr catabolism, while the second stimulate only tyr catabolism by up regulating tat. the second implication is that some biological perturbations affect both networks, but having different effects on each one of them. for example, uv-b stress after six hours in shoots and low light for h hours in petioles similarly shift the conversion of met into glucosinolates towards energy biosynthesis by repressing mam maml and bcat of glucosinolates biosynthesis and up regulating mgl and bcat of ile-derived energy biosynthesis. yet these same stresses have differential effect on the aaa network, the first highly stimulates trp synthesis and catabolism by up regulation of most of the relevant hcgs, while the second suppresses the aaa network probably as results of a lower growth rate. an opposite situation is observed in the response to wounding after hours in shoots and the response to salt stress after hours in roots. both of these stresses promote tyr catabolism in the aaa network by strongly up regulating tat expression, but having differential effects on the asp-family network with wounding affecting promoting the catabolism of thr, lys and ile, while salt seems to shut down the entire network by down regulating the entire set of biosynthetic hcgs.  in the present report, we have developed a novel gene coordination approach, which enables the simultaneous identification of positive and negative expression relationships between genes over a wide range of biological perturbations. this approach is particularly important in cases where both positive and negative expression relationships are expected as in genes controlling competing branches in metabolic networks. this approach was central to the identification of hcgs with the asp-family and aaa metabolic networks of arabidopsis plants and is likely also to enable the identification of hcgs in other complex biological networks of higher organisms in which only genes encoding a small fraction of the enzymatic steps play a key regulatory role. notably, our gene coordination approach also revealed that pairs of environmental cues can have a similar effect on one network, while having a differential effect on another network. this implies that when plants are exposed to two or more simultaneous stresses, there may be an override of one stress over the other in its effect on one network, but not the other. our present report also provides an approach to elucidate such complex relationships. 
in the present report, we developed a novel "gene coordination" bioinformatics approach and use it to elucidate adjustable transcriptional interactions of two branched amino acid metabolic networks in plants in response to environmental stresses, using publicly available microarray results. using our "gene coordination" approach, we have identified in arabidopsis plants two oppositely regulated groups of "highly coordinated" genes within the branched asp-family network of arabidopsis plants, which metabolizes the amino acids lys, met, thr, ile and gly, as well as a single group of "highly coordinated" genes within the branched aromatic amino acid metabolic network, which metabolizes the amino acids trp, phe and tyr. we also provide evidence implying that these highly coordinated genes are central to impose intra- and inter-network interactions between the asp-family and aromatic amino acid metabolic networks as well as differential system interactions with other growth promoting and stress-associated genome-wide genes. our novel gene coordination elucidates that branched amino acid metabolic networks in plants are regulated by specific groups of highly coordinated genes that possess adjustable intra-network, inter-network and genome-wide transcriptional interactions. such adjustments need particular coordination in branched metabolic networks in which a given metabolite can be converted into multiple other metabolites via different enzymatic chains.
 being sessile organisms, plants should adjust their metabolism to dynamic changes in their environment. such adjustments need particular coordination in branched metabolic networks in which a given metabolite can be converted into multiple other metabolites via different enzymatic chains. in the present report, we developed a novel "gene coordination" bioinformatics approach and use it to elucidate adjustable transcriptional interactions of two branched amino acid metabolic networks in plants in response to environmental stresses, using publicly available microarray results.  using our "gene coordination" approach, we have identified in arabidopsis plants two oppositely regulated groups of "highly coordinated" genes within the branched asp-family network of arabidopsis plants, which metabolizes the amino acids lys, met, thr, ile and gly, as well as a single group of "highly coordinated" genes within the branched aromatic amino acid metabolic network, which metabolizes the amino acids trp, phe and tyr. these genes possess highly coordinated adjustable negative and positive expression responses to various stress cues, which apparently regulate adjustable metabolic shifts between competing branches of these networks. we also provide evidence implying that these highly coordinated genes are central to impose intra- and inter-network interactions between the asp-family and aromatic amino acid metabolic networks as well as differential system interactions with other growth promoting and stress-associated genome-wide genes.  our novel gene coordination elucidates that branched amino acid metabolic networks in plants are regulated by specific groups of highly coordinated genes that possess adjustable intra-network, inter-network and genome-wide transcriptional interactions. we also hypothesize that such transcriptional interactions enable regulatory metabolic adjustments needed for adaptation to the stresses. 