BACKGROUND
cyanobacteria, which have been model organisms since the early 70s of the past century  <cit> , are a widespread group of photoautotrophic microorganisms, which originated, evolved, and diversified early in earth's history  <cit> .
it is commonly accepted that cyanobacteria played a crucial role in the precambrian phase by contributing oxygen to the atmosphere  <cit> .
all cyanobacteria combine the ability to perform an oxygenic photosynthesis  with typical prokaryotic features, like performing anoxygenic photosynthesis by using hydrogen sulfide  as the electron donor or fixing atmospheric dinitrogen  into ammonia .
relevance of this phylum covers from evolutionary studies  <cit>  to biotechnological applications, including biofuel production  <cit> .
synechocystis sp.
pcc <dig> is a cyanobacterium that is considered as a good candidate for developing a photo-biological cell factory towards production of a variety of molecules of socio-economic interest, with co <dig>  as carbon source and light  as energy source  <cit> .
the diversity of potential applications in this sense is broad.
works have been published on heterologous production of metabolites such as isoprene  <cit> , poly-beta-hydroxybutyrate  <cit> , biofuels  <cit>  and bio-hydrogen  <cit>  - an energy vector of global interest  <cit> .
synechocystis sp.
pcc <dig> is capable of growing under three different growth conditions as marked by the utilized carbon source   <cit> .
this causes that three distinct modes of operation are interweaved over the same metabolic network, viz., i) photoautotrophy, where energy comes from light and carbon from co2; ii) heterotrophy, where energy and carbon source is a saccharide, for instance glucose; and, iii) mixotrophy, a combination of the above two, where light is present as well as a combination of two carbon sources: glucose and co <dig>  reconstruction of a genome-scale metabolic model for this model photo-synthetic bacterium is one of the main goals of the current study.
genome-scale metabolic network reconstruction is, in essence, a systematic assembly and organization of all the reactions which build up the metabolism of a given organism; and has been of great interest in the post-genomic era.
the variety of applications of such a metabolic model  <cit>  includes the possibility of assessing projects for the production and optimization of an added value metabolite.
if a model is formulated properly, it is expected to allow simulating environmental and genetic perturbations in the metabolic network.
thus, together with appropriate constraints, a metabolic model would partially represent a virtual organism - an in silico model that allows probing possible flux distributions inside the cell under different environmental conditions and for a given genetic make-up.
towards this end, a variety of tools/algorithms are available  <cit> , including flux balance analysis   <cit> , minimization of metabolic adjustments   <cit> , regulatory on-off minimization   <cit>  and metabolic control analysis   <cit> .
synechocystis sp.
pcc <dig> genome was sequenced, annotated and made publicly available in  <dig>  <cit>  and has been the target of some metabolic modeling effort, especially for central carbon metabolic reconstructions  <cit> .
the work from yang et al  <cit>  focused on a metabolic model of glycolysis, tricarboxylic acid cycle and pentose phosphate pathway that was simulated under heterotrophic and mixotrophic conditions.
shastri and morgan  <cit>  studied a metabolic model with the same pathways under autotrophic conditions and compared their results to the ones from yang et al.
these two works considered one lumped reaction for the photosynthesis of the system.
more recently, an uncurated reaction list with a biomass composition represented by central carbon metabolites has been published  <cit> .
this model, however, is not suitable for simulations due to lack of proper biomass equation, lumped nature of some key reactions and missing reactions.
the large quantity of information featured in public databases, like details about genomes  <cit> , pathways  <cit> , enzymes  <cit>  or proteins  <cit>  can be used from different databases to gather all published data for one specific organism.
however, the lack of quality must be considered as a major drawback of some of the databases: false positives, false negatives as well as wrongly annotated objects may hinder efforts of collecting accurate data  <cit> .
consequently, manual reconstruction by detailed inspection of each and every reaction, biomass equation based on metabolic building blocks , consistency and integrity of the network is a pre-requisite for creating a high quality and useful metabolic model  <cit> .
the current study presents such manually curated reconstruction for synechocystis sp.
pcc <dig> and demonstrates some of its potential applications.
the present model features a detailed biomass equation which encompasses all the building blocks that are needed for a flux distribution simulation that reflects observed phenotype.
no lumped reactions are present and photosynthesis is described as a set of  <dig> reactions, thus enabling the tracing of the corresponding fluxes.
furthermore, different analyses are performed by using this metabolic reconstruction, including reaction knock-out simulations, flux variability analysis and identification of transcriptional regulatory hotspots.
overall, isyn <dig> is a valuable tool towards the development of a photo-biological production platform.
the model will also contribute to the existing set of genome-scale models with a virtue of being one of the first stoichiometric models that account for photosynthesis.
RESULTS
genome-scale metabolic network reconstruction
a complete literature examination, including databases, biochemistry textbooks and the annotated genome sequence, was needed in order to extract the current state of the art on known metabolic reactions within the metabolic network of synechocystis sp.
pcc <dig>  for a thorough overview of the process of metabolic model reconstruction, refer to very instructive work by forster et al  <cit>  as well as review by feist et al  <cit> .
in detail, the reconstruction started with the annotation and genomic sequence files of synechocystis sp.
pcc <dig>  <cit> .
these files were used with pathway tools software  <cit>  in order to build a database of all the genes, proteins and metabolites presents in the organism.
the list of reactions was then retrieved from pathway tools; ec numbers and stoichiometry of the reactions were checked and verified with the help of the enzyme nomenclature database  <cit>  and kegg pathway database  <cit> .
reactions were elementally balanced except for protons, so that chemical conversions were coherent.
in some of the reactions present in these databases, metabolites were reported in a non-specific form .
this is insufficient for metabolic model simulation and, so, corresponding organism-specific metabolites had to be identified  <cit> .
additionally, in a large number of reactions cofactors were not completely clarified: an enzyme being capable of using nadh or nadph or both.
in the latter, two reactions were included in the reconstructed metabolic network.
determination of reversibility of the reactions was assisted by specific enzyme databases, like brenda  <cit> .
if no conclusive evidence was reported, reactions were set to be reversible.
in the reconstruction of the metabolic model, many reactions  were found to be necessary for the production of the monomers, precursors or building blocks, that are considered in the biomass equation but which have no corresponding enzyme coding gene assigned.
in consequence, many genes that were not annotated before should be considered, as they code for enzymes that should be present to allow the formation of biomass.
for instance, enzymes malyl-coa lyase and isocitrate lyase were not allocated in the annotation of the genome albeit their activities have been measured  <cit>  and their presence is necessary to complete the glyoxylate shunt; consequently, they were included in the model.
the product of this reconstruction process was a set of reactions that encompass all the known metabolite conversions that take place in synechocystis sp.
pcc <dig>  the resulting network, isyn <dig>  consists of  <dig> metabolic reactions and  <dig> metabolites .
a total of  <dig> genes were included, to which  <dig> reactions were assigned ; the difference between the number of genes and assigned reactions is due to the presence of considerable number of protein complexes  and isoenzymes.
reactions with no cognate genes are also present in isyn <dig>   <dig> passive transport reactions and  <dig> chemical conversions  were included.
additionally, a total of  <dig> reactions were included on the basis of biochemical evidence or physiological considerations, but currently with no annotated open reading frame .
isyn <dig> genome-scale metabolic model is available in additional file  <dig> .
isyn <dig> spans all the biologically relevant flux nodes in the synechocystis metabolism.
pyruvate, phosphoenolpyruvate , 3-phosphoglycerate, erythrose-4-phosphate and 2-oxoglutarate are main flux nodes for amino acids biosynthesis.
acetyl-coa is an important flux node for fatty acids production, with high relevance for metabolic engineering towards biofuel production.
biosynthesis of nucleic acids comes from different metabolites, namely, ribose-5-phosphate, 5-phospho-beta-d-ribosyl-amine, l-histidine and l-glutamine.
moreover, with the information publicly available on databases, we can conclude that synechocystis sp.
pcc <dig> bears an incomplete tricarboxylic acid cycle , as it lacks 2-ketoglutarate dehydrogenase .
it has been published that glyoxylate shunt completes this cycle  <cit> , permitting the recycling of tca metabolites.
alternatively, aspartate transaminase  can interconvert 2-ketoglutarate and oxaloacetate, thus bridging the gap of 2-ketoglutarate dehydrogenase, but short-circuiting tca cycle.
from the network topology perspective, isyn <dig> displays the connectivity distribution pattern similar to that of the other microbial genome-scale networks, e.g.
yeast  <cit>  and escherichia coli  <cit>  .
while most of the metabolites have few connections, few metabolites are involved in very many reactions and are often referred to as metabolic hubs.
homeostasis of such highly connected metabolites will affect globally the metabolic phenotype  and therefore of interest for studying the organization of regulatory mechanisms on the genome-wide scale.
most connected metabolites include those related to energy harvesting , a key metabolite in the porphyrin and chlorophyll metabolism , a couple of amino acids and its precursors  and a key metabolite in the lipid biosynthesis pathway .
high connectivity of these metabolites hints to their potential central role in the re/adjustments of fluxes following environmental changes/perturbations.
in order to discover the corresponding regulatory mechanisms, additional studies should be done - e.g.
putative regulatory sequence motifs associated with the neighbors of these highly connected metabolites  <cit> .
furthermore, most connected metabolites with filtered cofactors can be found in additional file  <dig>
simulations of the three metabolic modes
isyn <dig>  together with appropriate physiological constraints, was used as a stoichiometric simulation model by using fba algorithm  <cit> .
the fba model simulates steady state behavior by enforcing mass balances constraints for the all metabolic intermediates .
biomass synthesis, a theoretical abstraction for cellular growth, is considered as a drain of some of these intermediates, i.e.
building blocks, into a general biomass component.
different studies have reported that the simulation results do not usually vary drastically when using a common biomass equation for different growth condition  <cit> .
nevertheless, experimental efforts should be directed at the depiction of the best precursors and composition that could characterize, at least, the three main growth modes, viz., autotrophy, heterotrophy and mixotrophy, in the scope of recent results  <cit> .
due to the lack of such data, the present work uses one single biomass equation in the simulations of all three metabolic states .
presence of photosynthesis allows isyn <dig> to "grow" under the all three metabolic states : carbon dioxide and light , sugars , carbon dioxide, light and sugars .
biomass composition description with references where the information was retrieved from.
all this building blocks with their respective stoichiometric coefficient is converted into one gram of dry cell weight.
biomass equation is reaction biomass in additional files  <dig> and  <dig>
growth under pure heterotrophy, or dark heterotrophy  is a subject under study  <cit> , being the regular experimental design to give a short light pulse prior to the pure heterotrophic phase .
nevertheless, the theoretical flux distribution under heterotrophic conditions is interesting by itself - especially in comparison with the flux distribution in a light-fed energy metabolism.
moreover, fluxes in the heterotrophy mode may help in obtaining insight into the variations under the mixotrophic condition, which is of high relevance for industrial applications  <cit> .
all fba simulations were carried out under the appropriate constraints so as to match an autotrophic specific growth rate of  <dig>  h- <dig>  this growth rate corresponds to a light input of  <dig>  me gdw- <dig> h- <dig> and to a net carbon flux of  <dig>  mmol gdw- <dig> h- <dig> into the cell, with hco3- and co <dig> as carbon sources.
for the sake of comparison across the different conditions, uptake rates for the corresponding carbon sources were matched based on normalization per number of carbon atoms .
results of the subsequent fba simulations for the three different growth conditions are presented in the following.
some of the reactions that are physiologically relevant for each of the conditions are summarized in table  <dig> and figure  <dig>  flux values for the rest of the reactions, including the upper and lower bounds are provided in additional file  <dig>
reaction
units in mmol gdw- <dig> h- <dig>   <dig> .
<dig> a, glucokinase, is the reaction that phosphorylates beta-d-glucose upon entrance in the cell, marking the start of the glycolysis.
the flux direction changes can be seen in reaction  <dig> .
<dig> , fumarate hydratase, from tca cycle and  <dig> .
<dig> , ribose-5-phosphate isomerase, from the pentose phosphate pathway.
_uq and _ <dig> .
<dig>  are reactions that reduce uqh <dig> from photosystem ii or nadh oxidation, respectively, causing a pumping of protons to the thylakoid.
_ <dig> .
<dig>  is the atp synthase that forms atp shuttling protons from the thylakoid to the cytosol.
<dig> .
<dig> , acetate-coa ligase, is the reaction that generates acetyl-coa from acetate and coenzyme a, that would be a major flux hub in an ethanol-producing strain, standing as the first step of fermentation.
heterotrophy
heterotrophy was simulated by considering glucose as the sole carbon source with uptake rate of  <dig>  mmol gdw- <dig> h- <dig>  entering the system through glcp glucose transporter .
with the purpose of having a pure heterotrophic state, photon uptake rate was constrained to 0; this caused photosynthesis fluxes to be shut down.
in this case, glucose will be the source for the formation of carbon backbones for the building blocks of the cell, depicted in the biomass equation.
the glycolytic and the oxidative mode of the pentose phosphate pathway were found to be active.
oxidative pentose phosphate pathway is the major pathway for glucose catabolism as was reported in reference  <cit> .
pep carboxylase  is the main anaplerotic flux to the tca cycle.
carbon fixation efficiency is around 60%, the rest being released in the form of co <dig>  as reported in our previous work  <cit> .
in contrast to dark heterotrophy, if a light-activated heterotrophy simulation is run, light enters the system and rubisco enzyme is active , fixing all the co <dig> that was released in dark heterotrophy, boosting carbon efficiency to a theoretical 100%.
in this case, global flux distribution as well as flux ranges resemble that of autotrophy more than that of the dark heterotrophy.
carbon skeletons are still produced through glycolysis and nadh is reduced along the glycolysis, pyruvate metabolism and tca cycle.
on the other hand, pentose phosphate pathway has shifted to the reductive mode due to rubisco activation and the corresponding flux is increased in magnitude.
carbon fixation happens at the rubisco level, thereby assimilating the co <dig> produced by the glucose metabolism, and the production of atp and nadph through photosynthesis relieves the oxidative phosphorylation from draining nadph to generate atp.
autotrophy
photoautotrophy was initially simulated considering an illumination of  <dig>  me m- <dig> s- <dig>  assuming that the mass of a typical synechocystis sp.
pcc <dig> cell is  <dig>  pg  <cit>  and its radius is  <dig>  μm  <cit> , we estimated that the theoretical maximum illumination is  <dig>  me gdw- <dig> h- <dig>  an additional optimization step was performed in order to estimate physiologically meaningful photon uptake values that are closer to the experimental measurements  <cit> .
first, carbon uptake rate was found that resulted in a specific growth rate of  <dig>  h- <dig>  while the light intake was unconstrained.
next, the growth rate was constrained to this value and the second optimization problem was solved where light uptake was minimized.
this minimization resulted in photon uptake for photosystem i  and photosystem ii  being  <dig>  me gdw- <dig> h- <dig>  carbon sources used in simulating photoautotrophy conditions were carbon dioxide and carbonic acid, and its entrance to the system was mediated by rubisco  and carbonic anhydrase  respectively.
as isyn <dig> biomass equation encompasses all essential metabolite precursors, these will be the sinks of our network, while photons, carbon dioxide and/or carbonic acid will be the sources.
thus autotrophic fluxes will flow in the gluconeogenic direction and through the calvin cycle, which is the reductive mode of the pentose phosphate pathway.
pep carboxylase is the main anaplerotic flux to the tca cycle and glyoxylate shunt is inactive.
mixotrophy
photons, carbon dioxide and glucose are independent feed fluxes in this simulation.
these fluxes entered the system through the same reactions as described for the previous growth modes.
carbon source presents, in this case, one more degree of freedom than in the rest of the conditions.
in order to keep a comparative criterion across conditions, we normalized co <dig> and glucose inputs to the same carbon uptake flux as in the case of the autotrophy and the heterotrophy.
photon uptake rates were also normalized in a similar manner to match the autotrophic state.
having the same metabolic sinks as the two previous modes and the sources from the both of them, it is logical to think that the resulting flux distribution will be a mixture of the autotrophic and heterotrophic simulations.
indeed, we observed that the mixotrophic flux distribution lies in-between the previous two states, being a bit closer to the heterotrophy.
glycolysis is present and glyoxylate is shut down; an active photosynthesis is present, oxidative phosphorylation is less stressed than in heterotrophy as the energy can be produced from the photon uptake; and calvin cycle is active, as carbon sources are co <dig> and glucose.
flux variability analysis
flux balance analysis presented above guarantees to find the optimal objective function value .
however, the predicted intra-cellular flux distribution is not necessarily unique due to the presence of multiple pathways that are equivalent in terms of their overall stoichiometry.
thus, often the system exhibits multiple optimal solutions and further elucidation requires additional constraints based on experimental evidences .
alternatively, physiological insight can be still obtained by studying the variability at each flux node given the objective function value - a procedure referred to as flux variability analysis.
in order to gain insight into the flux changes underlying the changes in the synechocystis metabolism due to availability of light, we have compared the autotrophic growth with the other two by using flux variability analysis .
interestingly, autotrophy permits an overall broader flux landscape than heterotrophy .
on the other hand autotrophic flux ranges are in general narrower than the mixotrophic ranges.
figure  <dig> and table  <dig> depict some of the physiologically relevant reactions for which the feasible flux range differs across conditions.
these include glucokinase from glycolysis, fumarate hydratase from tca cycle, ribose-5-phosphate isomerase from pentose phosphate pathway, nadh dehydrogenase from oxidative phosphorylation or photosystem ii oxidation.
these reactions mark the key nodes in the metabolism network that must be appropriately regulated in order to adapt in response to the available energy/carbon source.
mechanisms underlying such changes will be of particular interest not only for biotechnological applications but also from the biological point of view.
as a glimpse of the detailed flux distributions in each of the studied growth conditions, additional file  <dig> describes fluxes in the pyruvate metabolism.
gene/reaction knock-out analysis
the comprehensive set of reconstructed biochemical equations of isyn <dig> and fba simulations enabled us to further analyze the characteristics and potential of the synechocystis metabolic network.
this can be oriented towards the study of the reactions  that are necessary for the growth, or to in silico metabolic engineering for identification of targets for maximization of a given metabolite of socio-economic interest.
essential genes
isyn <dig> network consists of  <dig> metabolites and  <dig> reactions.
among these,  <dig> genes  were found to be necessary for the formation of the biomass under the mixotrophic growth conditions by using fba and moma algorithms.
this set of genes can be divided in to two categories: i) essential genes, deletion of which completely inhibits biomass growth : and ii) genes deletion of which causes a reduced growth rate .
the set of  <dig> essential genes can be understood as the core of the metabolism, as deleting them would produce an unviable organism.
the results based on moma algorithm essentially tally these numbers:  <dig> essential genes, 35% of the total, and  <dig> that cause a reduced growth rate, 5% of the total, .
interestingly, if we compare the proportion of the essential genes under fba simulation in the metabolic networks of e. coli   <cit>  and saccharomyces cerevisiae   <cit>  with isyn <dig>  we find that synechocystis has a significantly larger fraction of metabolic genes whose deletion obliterates biomass formation .
one possible explanation for the difference in the relative proportion of essential genes in these three organisms would be an incomplete/incorrect annotation of the genome of synechocystis sp.
pcc <dig>  for example, if only one of the isoenzymes corresponding to a reaction is annotated, the corresponding in silico knock-out will result in a false negative prediction.
it is important to note that the computational predictions of gene essentiality based on fba are highly dependent on the growth medium used for the simulations.
thus, the comparison across different species may not be straight-forward.
moreover, it is also possible that the natural growth conditions of synechocystis may have dictated selection for a relatively high proportion of essential genes.
such hypotheses need careful consideration of several factors and are beyond the scope of this work.
production of value-added compounds
synechocystis sp.
pcc <dig> is considered as a candidate photobiological production platform - it can potentially produce molecules of interest by using co <dig> and light  <cit> .
to this end, isyn <dig> can be used to perform simulations, not only for assessing the feasibility of producing a given compound, but also to identify potential metabolic engineering targets towards improved productivity.
for example, fba simulations can help in estimating maximum theoretical yields for the products/intermediates of interest.
a product of obvious interest is hydrogen.
in our previous work  <cit> , we have estimated maximum theoretical hydrogen production values that are far from the current state of experimental reports.
in silico studies can direct the efforts and counsel the scientists towards a hydrogen producing cyanobacteria that could be of impact.
isyn <dig> predicts, in autotrophic conditions, a theoretical h <dig> evolution rate of  <dig>  mmol gdw- <dig> h- <dig> obliterating biomass growth.
else, the stoichiometry permits the evolution of  <dig>  mmol gdw- <dig> h- <dig> of hydrogen with a biomass growth of 10% of the wild type .
succinate is an important metabolite for its biotechnological applications as well as for being a metabolite that bridges the tca cycle with the electron transfer chain.
as an example of the usefulness of the present metabolic model we have designed an in silico metabolic engineering strategy to improve the production of succinate.
the underlying idea is to design a succinate over-producing metabolic network , whereas the intracellular fluxes are distributed so as to maximize the biological objective function   <cit> .
to this end, optgene algorithm  <cit>  was used together with minimization of metabolic adjustment   <cit>  as a biological objective function.
moma has been reported to provide better description of flux distributions in mutants or under un-natural growth conditions as opposed to fba.
a design objective function which copes with the metabolite of interest, succinate, has been determined maintaining the biological objective function as the biomass formation.
optgene simulations for single, double and triple knock-out strategies were performed to obtain solutions with improved succinate production, but without drastically diminishing the biomass production.
we used mixotrophic conditions, for which wild type optimal growth rate was  <dig>  mmol gdw- <dig> h- <dig>  the best single knock-out was found to be the mutant of pyruvate kinase  that has a succinate evolution of  <dig>  mmol gdw- <dig> h- <dig> with a growth rate of  <dig>  mmol gdw- <dig> h- <dig>  blocking this reaction, preventing pyruvate and phosphoenolpyruvate from using gtp and gdp would drive a high increase in succinate production.
the flux between pyruvate and phosphoenolpyruvate can still be accomplished with reactions  <dig> .
<dig> a and  <dig> .
<dig> , but using atp and adp as cofactors.
double deletion did not improve the results from the single knock-out strain, evolving the same succinate production with the same growth rate.
the best triple knock-out was found to be the combination of pyruvate kinase , fructose-bisphosphate aldolase  and succinate dehydrogenase .
this simulated strain has a succinate evolution of  <dig>  mmol gdw- <dig> h- <dig> with a growth rate of  <dig>  mmol gdw- <dig> h- <dig>  this design combines the blocking of the oxidation of succinate on the electron chain transfer through succinate dehydrogenase with the prevention of using gtp between pyruvate and phosphoenolpyruvate and the lack of an aldolase needed in the reductive mode of the pentose phosphate pathway.
this leads to a situation where flux is directed to tca cycle in order to meet with an overproduction of succinate.
these studies on knock-outs are reaction centered, even though the in vivo knock-out building will ultimately be through gene manipulations.
this is the reason underlying the fact that we found  <dig> .
<dig> c knock-out as the best result.
this design would hint at the idea of selection of a mutated pyruvate kinase protein specific for atp cofactor.
this may be difficult to achieve on the bench, but has high biotechnological expectations.
isyn <dig> as a data integration scaffold
apart from the flux simulations, another important problem in the field of metabolic systems biology that can be addressed by using reconstructed genome-scale models is the integration of the different genome-wide bio-molecular abundance datasets, i.e.
omics datasets, such as transcriptome and metabolome.
an example of algorithms for carrying out such an integrative analysis through the use of genome-scale metabolic networks is reporter features  <cit> .
reporter algorithm allows integration of omics data with bio-molecular interaction networks, thereby allowing identification of cellular regulatory focal points , for instance reporter metabolites as regulatory hubs in the metabolic network.
in this work, reporter features software was used to integrate transcriptional information over the reconstructed synechocystis sp.
pcc <dig> network allowing us to infer regulatory principles underlying metabolic flux changes following shifts in growth mode.
in particular, we analyzed the data from a work  <cit>  that reports the transcriptional changes caused in synechocystis sp.
pcc <dig> by shifts from darkness to illumination conditions and back.
as it can be understood from the rationale beneath the metabolic capabilities of this cyanobacterium, the presence or absence of light drives big changes in the flux distribution through the network, as discussed in the previous sections.
we have focused our study on the relationship between the transcription of synechocystis sp.
pcc <dig> genes and the reactions of the metabolic network.
associations between genes and reactions were identified, listing all the genes that performed or were involved in a specific reaction.
with this information and the metabolic model, reporter features analysis was carried out.
in brief, the analysis helped to identify metabolites around which the transcriptional changes are significantly concentrated.
these metabolites are termed reporter metabolites as they represent key regulatory nodes in the network.
gill et al  <cit>  designed the experiment so that synechocystis was grown to mid-exponential phase .
then, the lights were extinguished and rna samples were taken after  <dig> h in the dark .
illumination was then turned back on for  <dig> min , followed immediately by an additional  <dig> min in the dark .
we were interested in two aspects of this study: i) to identify metabolites around which regulation is centered during the light regime transitions; and ii) to find the metabolic genes that were collectively significantly co-regulated across these transitions  <cit> .the analysis was divided in three parts: an analysis of the data arrays from the whole experimental profile , an analysis of the shift from darkness to a light environment  and from light back to dark .
for a study of the overall genome and its light regulation, refer to gill et al  <cit> .
in this study, as the relationship between the metabolism and this regulation was investigated, genes with no direct relationship to a metabolic reaction were not considered.
distributions of the genes across kegg orthologies related to the metabolism altered with the light shift are depicted in table  <dig>
biosynthesis of secondary
biosynthesis of polyketides
all time points
when all seven arrays were used, reporter metabolites were found to be quite scattered across the metabolism spanning several metabolic pathways, and thus offering a global view of the transcriptional response in the metabolic network .
presence of some amino acids , nucleic acids and its precursors , carbon metabolism metabolites , lipids precursors , cofactors  and photosynthesis metabolites  pictures a scenario of a global regulation throughout the different metabolic pathways.
reporter metabolites for each set of arrays analysed with reporter features software.
by using the metabolic sub-network search algorithm, we found  <dig> genes that have their expression changed across the arrays and that have a relationship with the metabolites of isyn <dig> network.
furthermore,  <dig> genes were identified that are strongly co-regulated all along the profile of the experiment .
this set of genes is characterized in two groups.
the first set consists of the genes from photosynthesis  and oxidative phosphorylation .
the second set is representative of a variety of genes from different pathways such as amino acid metabolism , carbohydrate metabolism , nucleotide metabolism , nitrogen metabolism  and metabolism of cofactors  that globally regulates the entire metabolic network .
it can be expected that an experimental design like the one we have based our work on, which combines a shift from dark to light with a shift back to darkness, will encompass an important part of the regulatory changes the cell is undergoing in its natural habitat.
in a glucose-deficient environment, the presence or absence of light is the main condition around which the synechocystis metabolism gravitates  <cit> .
indeed, one of the co-regulated sets consists of the genes coding for the proteins that work on, and around, the thylakoid membrane, let it be photosynthesis or oxidative phosphorylation genes.
dark to light
next, we considered the arrays that represent the shift from darkness to light, the first three arrays .
reporter metabolites were found to be largely within the nucleotide and amino acid metabolism .
some cofactors were also identified as regulation hubs like tetrahydrofolate, thioredoxin and adenosylcobinamide.
sub-network search yielded set of  <dig> genes that have their expression changed across the first three arrays and that are related with isyn <dig> reactions.
furthermore,  <dig> genes were identified that are strongly co-regulated across the three arrays .
this set of genes cover photosynthesis , oxidative phosphorylation , amino acid metabolism , carbohydrate metabolism , nucleotide metabolism  and metabolism of cofactors .
this set of data arrays are indeed a good example of a cell's metabolic machinery starting up.
after a  <dig> hour period in darkness where cell density did not change , light enters the system and the cell starts to synthesize new bio-molecules, mostly nucleotides so it can copy its genetic material and amino acids to build up proteins.
light to dark
finally, we considered the arrays that represent the shift from light to dark, data from " <dig> minutes of light" array to " <dig> minutes of dark" array.
similar to the previous case study, reporter metabolites were found to be focused on the nucleotide and amino acid metabolism .
additionally, the presence of metabolite a  <dig> -alpha-d-glucan_n and its cognate a  <dig> -alpha-d-glucan_n <dig> also stands out as they are involved in carbon reserves catabolism and anabolism.
with the help of the sub-network search,  <dig> genes were identified as being significantly co-regulated across those three arrays .
this set comprises of the genes from photosynthesis , oxidative phosphorylation , amino acid metabolism , carbohydrate metabolism , nucleotide metabolism  and metabolism of cofactors .
this last set of data array is a scenario where metabolism is being shut down, as a consequence of the darkness and lack of carbohydrate source.
without light, photosynthesis is blocked and carbon fixation is nearly obliterated.
cells strive to build up carbon reserves  and oxidative phosphorylation is the main energy pathway that remains present.
regulation is centered on the energy metabolism shift , withholding amino acids and nucleotide precursors and keeping the cofactors available in a low-profile metabolism.
CONCLUSIONS
we have successfully reconstructed a genome-scale metabolic network for synechocystis sp.
pcc <dig>  called isyn <dig>  which allows simulating production of all the metabolic precursors of the organism.
the metabolic reconstruction represents an up-to-date database that encompasses all knowledge available in public databases, scientific publications and textbooks on the metabolism of this cyanobacterium.
from the annotation publicly available, our metabolic network includes  <dig> metabolic reactions and  <dig> metabolites, as well as the information from  <dig> genes that have some relationship with the metabolic reactions.
this model is the most complete and comprehensive work for synechocystis sp.
pcc <dig> to date, which has its potential as the photosynthetic model organism.
interestingly, the reconstruction identified  <dig> reactions that should be present in the metabolism but with no cognate gene discovered yet; this should direct experimental work at the discovery of these genes.
topological characteristics of the network resemble those of other reconstructed microbial metabolic networks and thus provide an additional input for the analysis of their structural and organizational properties from evolutionary perspective.
applicability of isyn <dig> metabolic model was demonstrated by using a variety of computational analyses.
flux balance analysis was applied in order to simulate the three physiologically important growth conditions of cyanobacteria, viz., heterotrophic, mixotrophic and autotrophic.
our metabolic model was capable of simulating the production of the monomers or building blocks that build up the cells, in the range that is in agreement with the reported growth experiments.
our photosynthetic metabolic model includes all of the central metabolic pathways that previous works  <cit>  considered.
regarding the parts from our model that overlap with the previous works , the predictions for the flux directionality changes following light shift match between those models and isyn <dig>  in fact, isyn <dig> expands the flux study to all the pathways described in the synechocystis sp.
pcc <dig> genome annotation.
further work should be directed at the definition of a detailed and descriptive biomass cell composition, so as to have a better representation of the biomass equation for simulation purposes.
single reaction/gene knock-out simulations revealed  <dig> genes that are essential for the survival.
bearing in mind the distance from the efforts taken in the annotation of the genome of the bacteria and yeast models to that of the cyanobacterium, our study shows that synechocystis sp.
pcc <dig> has a larger fraction of genes that are essential for producing biomass, as opposed to escherichia coli and saccharomyces cerevisiae.
further investigation of the causes for this difference will be of definite interest in understanding the genome annotation and/or the evolution of the metabolic network of synechocystis.
evaluation of the theoretical potential of this organism to produce hydrogen was assessed, in support of the efforts directed to this direction from several groups and scientific council initiatives.
present hydrogen production projects are far from the theoretical potential, but efforts in this field can trigger a very significant increase of the present hydrogen evolution rates in synechocystis sp.
pcc <dig> or other photobiological production platforms candidates, e.g.
chlamydomonas reinhardtii, nostoc punctiforme and synechococcus species.
suitability of the presented model for performing in silico metabolic engineering analysis was demonstrated by using optgene software framework.
furthermore, we also show that isyn <dig> can be used as a scaffold to integrate network-wide omics data.
as a case study, we identified key reporter metabolites around which regulation during light shifts is organized, as well as gene sub-networks that were co-regulated across the light conditions.
altogether, the genome-scale metabolic network of synechocystis sp.
pcc <dig>  will be a valuable tool for the applied and fundamental research of synechocystis sp.
pcc <dig>  as well as for the broad field of metabolic systems biology.
isyn <dig> represents an important step for the integration of tools and knowledge from different disciplines towards development of photo-biological cell factories.

 cyanobacteria, which have been model organisms since the early 70s of the past century, are a widespread group of photoautotrophic microorganisms, which originated, evolved, and diversified early in earth's history. it is commonly accepted that cyanobacteria played a crucial role in the precambrian phase by contributing oxygen to the atmosphere. all cyanobacteria combine the ability to perform an oxygenic photosynthesis with typical prokaryotic features, like performing anoxygenic photosynthesis by using hydrogen sulfide as the electron donor or fixing atmospheric dinitrogen into ammonia. relevance of this phylum covers from evolutionary studies to biotechnological applications, including biofuel production. synechocystis sp. pcc is a cyanobacterium that is considered as a good candidate for developing a photo-biological cell factory towards production of a variety of molecules of socio-economic interest, with co as carbon source and light as energy source. the diversity of potential applications in this sense is broad. works have been published on heterologous production of metabolites such as isoprene, poly-beta-hydroxybutyrate, biofuels and bio-hydrogen - an energy vector of global interest. synechocystis sp. pcc is capable of growing under three different growth conditions as marked by the utilized carbon source. this causes that three distinct modes of operation are interweaved over the same metabolic network, viz., i) photoautotrophy, where energy comes from light and carbon from co2; ii) heterotrophy, where energy and carbon source is a saccharide, for instance glucose; and, iii) mixotrophy, a combination of the above two, where light is present as well as a combination of two carbon sources: glucose and co reconstruction of a genome-scale metabolic model for this model photo-synthetic bacterium is one of the main goals of the current study. genome-scale metabolic network reconstruction is, in essence, a systematic assembly and organization of all the reactions which build up the metabolism of a given organism; and has been of great interest in the post-genomic era. the variety of applications of such a metabolic model includes the possibility of assessing projects for the production and optimization of an added value metabolite. if a model is formulated properly, it is expected to allow simulating environmental and genetic perturbations in the metabolic network. thus, together with appropriate constraints, a metabolic model would partially represent a virtual organism - an in silico model that allows probing possible flux distributions inside the cell under different environmental conditions and for a given genetic make-up. towards this end, a variety of tools/algorithms are available, including flux balance analysis, minimization of metabolic adjustments, regulatory on-off minimization and metabolic control analysis. synechocystis sp. pcc genome was sequenced, annotated and made publicly available in and has been the target of some metabolic modeling effort, especially for central carbon metabolic reconstructions. the work from yang et al focused on a metabolic model of glycolysis, tricarboxylic acid cycle and pentose phosphate pathway that was simulated under heterotrophic and mixotrophic conditions. shastri and morgan studied a metabolic model with the same pathways under autotrophic conditions and compared their results to the ones from yang et al. these two works considered one lumped reaction for the photosynthesis of the system. more recently, an uncurated reaction list with a biomass composition represented by central carbon metabolites has been published. this model, however, is not suitable for simulations due to lack of proper biomass equation, lumped nature of some key reactions and missing reactions. the large quantity of information featured in public databases, like details about genomes, pathways, enzymes or proteins can be used from different databases to gather all published data for one specific organism. however, the lack of quality must be considered as a major drawback of some of the databases: false positives, false negatives as well as wrongly annotated objects may hinder efforts of collecting accurate data. consequently, manual reconstruction by detailed inspection of each and every reaction, biomass equation based on metabolic building blocks, consistency and integrity of the network is a pre-requisite for creating a high quality and useful metabolic model. the current study presents such manually curated reconstruction for synechocystis sp. pcc and demonstrates some of its potential applications. the present model features a detailed biomass equation which encompasses all the building blocks that are needed for a flux distribution simulation that reflects observed phenotype. no lumped reactions are present and photosynthesis is described as a set of reactions, thus enabling the tracing of the corresponding fluxes. furthermore, different analyses are performed by using this metabolic reconstruction, including reaction knock-out simulations, flux variability analysis and identification of transcriptional regulatory hotspots. overall, isyn is a valuable tool towards the development of a photo-biological production platform. the model will also contribute to the existing set of genome-scale models with a virtue of being one of the first stoichiometric models that account for photosynthesis.  genome-scale metabolic network reconstruction a complete literature examination, including databases, biochemistry textbooks and the annotated genome sequence, was needed in order to extract the current state of the art on known metabolic reactions within the metabolic network of synechocystis sp. pcc for a thorough overview of the process of metabolic model reconstruction, refer to very instructive work by forster et al as well as review by feist et al. in detail, the reconstruction started with the annotation and genomic sequence files of synechocystis sp. pcc. these files were used with pathway tools software in order to build a database of all the genes, proteins and metabolites presents in the organism. the list of reactions was then retrieved from pathway tools; ec numbers and stoichiometry of the reactions were checked and verified with the help of the enzyme nomenclature database and kegg pathway database. reactions were elementally balanced except for protons, so that chemical conversions were coherent. in some of the reactions present in these databases, metabolites were reported in a non-specific form. this is insufficient for metabolic model simulation and, so, corresponding organism-specific metabolites had to be identified. additionally, in a large number of reactions cofactors were not completely clarified: an enzyme being capable of using nadh or nadph or both. in the latter, two reactions were included in the reconstructed metabolic network. determination of reversibility of the reactions was assisted by specific enzyme databases, like brenda. if no conclusive evidence was reported, reactions were set to be reversible. in the reconstruction of the metabolic model, many reactions were found to be necessary for the production of the monomers, precursors or building blocks, that are considered in the biomass equation but which have no corresponding enzyme coding gene assigned. in consequence, many genes that were not annotated before should be considered, as they code for enzymes that should be present to allow the formation of biomass. for instance, enzymes malyl-coa lyase and isocitrate lyase were not allocated in the annotation of the genome albeit their activities have been measured and their presence is necessary to complete the glyoxylate shunt; consequently, they were included in the model. the product of this reconstruction process was a set of reactions that encompass all the known metabolite conversions that take place in synechocystis sp. pcc the resulting network, isyn consists of metabolic reactions and metabolites. a total of genes were included, to which reactions were assigned; the difference between the number of genes and assigned reactions is due to the presence of considerable number of protein complexes and isoenzymes. reactions with no cognate genes are also present in isyn passive transport reactions and chemical conversions were included. additionally, a total of reactions were included on the basis of biochemical evidence or physiological considerations, but currently with no annotated open reading frame. isyn genome-scale metabolic model is available in additional file. isyn spans all the biologically relevant flux nodes in the synechocystis metabolism. pyruvate, phosphoenolpyruvate, 3-phosphoglycerate, erythrose-4-phosphate and 2-oxoglutarate are main flux nodes for amino acids biosynthesis. acetyl-coa is an important flux node for fatty acids production, with high relevance for metabolic engineering towards biofuel production. biosynthesis of nucleic acids comes from different metabolites, namely, ribose-5-phosphate, 5-phospho-beta-d-ribosyl-amine, l-histidine and l-glutamine. moreover, with the information publicly available on databases, we can conclude that synechocystis sp. pcc bears an incomplete tricarboxylic acid cycle, as it lacks 2-ketoglutarate dehydrogenase. it has been published that glyoxylate shunt completes this cycle, permitting the recycling of tca metabolites. alternatively, aspartate transaminase can interconvert 2-ketoglutarate and oxaloacetate, thus bridging the gap of 2-ketoglutarate dehydrogenase, but short-circuiting tca cycle. from the network topology perspective, isyn displays the connectivity distribution pattern similar to that of the other microbial genome-scale networks, e.g. yeast and escherichia coli. while most of the metabolites have few connections, few metabolites are involved in very many reactions and are often referred to as metabolic hubs. homeostasis of such highly connected metabolites will affect globally the metabolic phenotype and therefore of interest for studying the organization of regulatory mechanisms on the genome-wide scale. most connected metabolites include those related to energy harvesting, a key metabolite in the porphyrin and chlorophyll metabolism, a couple of amino acids and its precursors and a key metabolite in the lipid biosynthesis pathway. high connectivity of these metabolites hints to their potential central role in the re/adjustments of fluxes following environmental changes/perturbations. in order to discover the corresponding regulatory mechanisms, additional studies should be done - e.g. putative regulatory sequence motifs associated with the neighbors of these highly connected metabolites. furthermore, most connected metabolites with filtered cofactors can be found in additional file simulations of the three metabolic modes isyn together with appropriate physiological constraints, was used as a stoichiometric simulation model by using fba algorithm. the fba model simulates steady state behavior by enforcing mass balances constraints for the all metabolic intermediates. biomass synthesis, a theoretical abstraction for cellular growth, is considered as a drain of some of these intermediates, i.e. building blocks, into a general biomass component. different studies have reported that the simulation results do not usually vary drastically when using a common biomass equation for different growth condition. nevertheless, experimental efforts should be directed at the depiction of the best precursors and composition that could characterize, at least, the three main growth modes, viz., autotrophy, heterotrophy and mixotrophy, in the scope of recent results. due to the lack of such data, the present work uses one single biomass equation in the simulations of all three metabolic states. presence of photosynthesis allows isyn to "grow" under the all three metabolic states: carbon dioxide and light, sugars, carbon dioxide, light and sugars. biomass composition description with references where the information was retrieved from. all this building blocks with their respective stoichiometric coefficient is converted into one gram of dry cell weight. biomass equation is reaction biomass in additional files and growth under pure heterotrophy, or dark heterotrophy is a subject under study, being the regular experimental design to give a short light pulse prior to the pure heterotrophic phase. nevertheless, the theoretical flux distribution under heterotrophic conditions is interesting by itself - especially in comparison with the flux distribution in a light-fed energy metabolism. moreover, fluxes in the heterotrophy mode may help in obtaining insight into the variations under the mixotrophic condition, which is of high relevance for industrial applications. all fba simulations were carried out under the appropriate constraints so as to match an autotrophic specific growth rate of h- this growth rate corresponds to a light input of me gdw- h- and to a net carbon flux of mmol gdw- h- into the cell, with hco3- and co as carbon sources. for the sake of comparison across the different conditions, uptake rates for the corresponding carbon sources were matched based on normalization per number of carbon atoms. results of the subsequent fba simulations for the three different growth conditions are presented in the following. some of the reactions that are physiologically relevant for each of the conditions are summarized in table and figure flux values for the rest of the reactions, including the upper and lower bounds are provided in additional file reaction units in mmol gdw- h-. a, glucokinase, is the reaction that phosphorylates beta-d-glucose upon entrance in the cell, marking the start of the glycolysis. the flux direction changes can be seen in reaction., fumarate hydratase, from tca cycle and., ribose-5-phosphate isomerase, from the pentose phosphate pathway. _uq and _. are reactions that reduce uqh from photosystem ii or nadh oxidation, respectively, causing a pumping of protons to the thylakoid. _. is the atp synthase that forms atp shuttling protons from the thylakoid to the cytosol.., acetate-coa ligase, is the reaction that generates acetyl-coa from acetate and coenzyme a, that would be a major flux hub in an ethanol-producing strain, standing as the first step of fermentation. heterotrophy heterotrophy was simulated by considering glucose as the sole carbon source with uptake rate of mmol gdw- h- entering the system through glcp glucose transporter. with the purpose of having a pure heterotrophic state, photon uptake rate was constrained to 0; this caused photosynthesis fluxes to be shut down. in this case, glucose will be the source for the formation of carbon backbones for the building blocks of the cell, depicted in the biomass equation. the glycolytic and the oxidative mode of the pentose phosphate pathway were found to be active. oxidative pentose phosphate pathway is the major pathway for glucose catabolism as was reported in reference. pep carboxylase is the main anaplerotic flux to the tca cycle. carbon fixation efficiency is around 60%, the rest being released in the form of co as reported in our previous work. in contrast to dark heterotrophy, if a light-activated heterotrophy simulation is run, light enters the system and rubisco enzyme is active, fixing all the co that was released in dark heterotrophy, boosting carbon efficiency to a theoretical 100%. in this case, global flux distribution as well as flux ranges resemble that of autotrophy more than that of the dark heterotrophy. carbon skeletons are still produced through glycolysis and nadh is reduced along the glycolysis, pyruvate metabolism and tca cycle. on the other hand, pentose phosphate pathway has shifted to the reductive mode due to rubisco activation and the corresponding flux is increased in magnitude. carbon fixation happens at the rubisco level, thereby assimilating the co produced by the glucose metabolism, and the production of atp and nadph through photosynthesis relieves the oxidative phosphorylation from draining nadph to generate atp. autotrophy photoautotrophy was initially simulated considering an illumination of me m- s- assuming that the mass of a typical synechocystis sp. pcc cell is pg and its radius is μm, we estimated that the theoretical maximum illumination is me gdw- h- an additional optimization step was performed in order to estimate physiologically meaningful photon uptake values that are closer to the experimental measurements. first, carbon uptake rate was found that resulted in a specific growth rate of h- while the light intake was unconstrained. next, the growth rate was constrained to this value and the second optimization problem was solved where light uptake was minimized. this minimization resulted in photon uptake for photosystem i and photosystem ii being me gdw- h- carbon sources used in simulating photoautotrophy conditions were carbon dioxide and carbonic acid, and its entrance to the system was mediated by rubisco and carbonic anhydrase respectively. as isyn biomass equation encompasses all essential metabolite precursors, these will be the sinks of our network, while photons, carbon dioxide and/or carbonic acid will be the sources. thus autotrophic fluxes will flow in the gluconeogenic direction and through the calvin cycle, which is the reductive mode of the pentose phosphate pathway. pep carboxylase is the main anaplerotic flux to the tca cycle and glyoxylate shunt is inactive. mixotrophy photons, carbon dioxide and glucose are independent feed fluxes in this simulation. these fluxes entered the system through the same reactions as described for the previous growth modes. carbon source presents, in this case, one more degree of freedom than in the rest of the conditions. in order to keep a comparative criterion across conditions, we normalized co and glucose inputs to the same carbon uptake flux as in the case of the autotrophy and the heterotrophy. photon uptake rates were also normalized in a similar manner to match the autotrophic state. having the same metabolic sinks as the two previous modes and the sources from the both of them, it is logical to think that the resulting flux distribution will be a mixture of the autotrophic and heterotrophic simulations. indeed, we observed that the mixotrophic flux distribution lies in-between the previous two states, being a bit closer to the heterotrophy. glycolysis is present and glyoxylate is shut down; an active photosynthesis is present, oxidative phosphorylation is less stressed than in heterotrophy as the energy can be produced from the photon uptake; and calvin cycle is active, as carbon sources are co and glucose. flux variability analysis flux balance analysis presented above guarantees to find the optimal objective function value. however, the predicted intra-cellular flux distribution is not necessarily unique due to the presence of multiple pathways that are equivalent in terms of their overall stoichiometry. thus, often the system exhibits multiple optimal solutions and further elucidation requires additional constraints based on experimental evidences. alternatively, physiological insight can be still obtained by studying the variability at each flux node given the objective function value - a procedure referred to as flux variability analysis. in order to gain insight into the flux changes underlying the changes in the synechocystis metabolism due to availability of light, we have compared the autotrophic growth with the other two by using flux variability analysis. interestingly, autotrophy permits an overall broader flux landscape than heterotrophy. on the other hand autotrophic flux ranges are in general narrower than the mixotrophic ranges. figure and table depict some of the physiologically relevant reactions for which the feasible flux range differs across conditions. these include glucokinase from glycolysis, fumarate hydratase from tca cycle, ribose-5-phosphate isomerase from pentose phosphate pathway, nadh dehydrogenase from oxidative phosphorylation or photosystem ii oxidation. these reactions mark the key nodes in the metabolism network that must be appropriately regulated in order to adapt in response to the available energy/carbon source. mechanisms underlying such changes will be of particular interest not only for biotechnological applications but also from the biological point of view. as a glimpse of the detailed flux distributions in each of the studied growth conditions, additional file describes fluxes in the pyruvate metabolism. gene/reaction knock-out analysis the comprehensive set of reconstructed biochemical equations of isyn and fba simulations enabled us to further analyze the characteristics and potential of the synechocystis metabolic network. this can be oriented towards the study of the reactions that are necessary for the growth, or to in silico metabolic engineering for identification of targets for maximization of a given metabolite of socio-economic interest. essential genes isyn network consists of metabolites and reactions. among these, genes were found to be necessary for the formation of the biomass under the mixotrophic growth conditions by using fba and moma algorithms. this set of genes can be divided in to two categories: i) essential genes, deletion of which completely inhibits biomass growth: and ii) genes deletion of which causes a reduced growth rate. the set of essential genes can be understood as the core of the metabolism, as deleting them would produce an unviable organism. the results based on moma algorithm essentially tally these numbers: essential genes, 35% of the total, and that cause a reduced growth rate, 5% of the total,. interestingly, if we compare the proportion of the essential genes under fba simulation in the metabolic networks of e. coli and saccharomyces cerevisiae with isyn we find that synechocystis has a significantly larger fraction of metabolic genes whose deletion obliterates biomass formation. one possible explanation for the difference in the relative proportion of essential genes in these three organisms would be an incomplete/incorrect annotation of the genome of synechocystis sp. pcc for example, if only one of the isoenzymes corresponding to a reaction is annotated, the corresponding in silico knock-out will result in a false negative prediction. it is important to note that the computational predictions of gene essentiality based on fba are highly dependent on the growth medium used for the simulations. thus, the comparison across different species may not be straight-forward. moreover, it is also possible that the natural growth conditions of synechocystis may have dictated selection for a relatively high proportion of essential genes. such hypotheses need careful consideration of several factors and are beyond the scope of this work. production of value-added compounds synechocystis sp. pcc is considered as a candidate photobiological production platform - it can potentially produce molecules of interest by using co and light. to this end, isyn can be used to perform simulations, not only for assessing the feasibility of producing a given compound, but also to identify potential metabolic engineering targets towards improved productivity. for example, fba simulations can help in estimating maximum theoretical yields for the products/intermediates of interest. a product of obvious interest is hydrogen. in our previous work, we have estimated maximum theoretical hydrogen production values that are far from the current state of experimental reports. in silico studies can direct the efforts and counsel the scientists towards a hydrogen producing cyanobacteria that could be of impact. isyn predicts, in autotrophic conditions, a theoretical h evolution rate of mmol gdw- h- obliterating biomass growth. else, the stoichiometry permits the evolution of mmol gdw- h- of hydrogen with a biomass growth of 10% of the wild type. succinate is an important metabolite for its biotechnological applications as well as for being a metabolite that bridges the tca cycle with the electron transfer chain. as an example of the usefulness of the present metabolic model we have designed an in silico metabolic engineering strategy to improve the production of succinate. the underlying idea is to design a succinate over-producing metabolic network, whereas the intracellular fluxes are distributed so as to maximize the biological objective function. to this end, optgene algorithm was used together with minimization of metabolic adjustment as a biological objective function. moma has been reported to provide better description of flux distributions in mutants or under un-natural growth conditions as opposed to fba. a design objective function which copes with the metabolite of interest, succinate, has been determined maintaining the biological objective function as the biomass formation. optgene simulations for single, double and triple knock-out strategies were performed to obtain solutions with improved succinate production, but without drastically diminishing the biomass production. we used mixotrophic conditions, for which wild type optimal growth rate was mmol gdw- h- the best single knock-out was found to be the mutant of pyruvate kinase that has a succinate evolution of mmol gdw- h- with a growth rate of mmol gdw- h- blocking this reaction, preventing pyruvate and phosphoenolpyruvate from using gtp and gdp would drive a high increase in succinate production. the flux between pyruvate and phosphoenolpyruvate can still be accomplished with reactions. a and., but using atp and adp as cofactors. double deletion did not improve the results from the single knock-out strain, evolving the same succinate production with the same growth rate. the best triple knock-out was found to be the combination of pyruvate kinase, fructose-bisphosphate aldolase and succinate dehydrogenase. this simulated strain has a succinate evolution of mmol gdw- h- with a growth rate of mmol gdw- h- this design combines the blocking of the oxidation of succinate on the electron chain transfer through succinate dehydrogenase with the prevention of using gtp between pyruvate and phosphoenolpyruvate and the lack of an aldolase needed in the reductive mode of the pentose phosphate pathway. this leads to a situation where flux is directed to tca cycle in order to meet with an overproduction of succinate. these studies on knock-outs are reaction centered, even though the in vivo knock-out building will ultimately be through gene manipulations. this is the reason underlying the fact that we found. c knock-out as the best result. this design would hint at the idea of selection of a mutated pyruvate kinase protein specific for atp cofactor. this may be difficult to achieve on the bench, but has high biotechnological expectations. isyn as a data integration scaffold apart from the flux simulations, another important problem in the field of metabolic systems biology that can be addressed by using reconstructed genome-scale models is the integration of the different genome-wide bio-molecular abundance datasets, i.e. omics datasets, such as transcriptome and metabolome. an example of algorithms for carrying out such an integrative analysis through the use of genome-scale metabolic networks is reporter features. reporter algorithm allows integration of omics data with bio-molecular interaction networks, thereby allowing identification of cellular regulatory focal points, for instance reporter metabolites as regulatory hubs in the metabolic network. in this work, reporter features software was used to integrate transcriptional information over the reconstructed synechocystis sp. pcc network allowing us to infer regulatory principles underlying metabolic flux changes following shifts in growth mode. in particular, we analyzed the data from a work that reports the transcriptional changes caused in synechocystis sp. pcc by shifts from darkness to illumination conditions and back. as it can be understood from the rationale beneath the metabolic capabilities of this cyanobacterium, the presence or absence of light drives big changes in the flux distribution through the network, as discussed in the previous sections. we have focused our study on the relationship between the transcription of synechocystis sp. pcc genes and the reactions of the metabolic network. associations between genes and reactions were identified, listing all the genes that performed or were involved in a specific reaction. with this information and the metabolic model, reporter features analysis was carried out. in brief, the analysis helped to identify metabolites around which the transcriptional changes are significantly concentrated. these metabolites are termed reporter metabolites as they represent key regulatory nodes in the network. gill et al designed the experiment so that synechocystis was grown to mid-exponential phase. then, the lights were extinguished and rna samples were taken after h in the dark. illumination was then turned back on for min, followed immediately by an additional min in the dark. we were interested in two aspects of this study: i) to identify metabolites around which regulation is centered during the light regime transitions; and ii) to find the metabolic genes that were collectively significantly co-regulated across these transitions.the analysis was divided in three parts: an analysis of the data arrays from the whole experimental profile, an analysis of the shift from darkness to a light environment and from light back to dark. for a study of the overall genome and its light regulation, refer to gill et al. in this study, as the relationship between the metabolism and this regulation was investigated, genes with no direct relationship to a metabolic reaction were not considered. distributions of the genes across kegg orthologies related to the metabolism altered with the light shift are depicted in table biosynthesis of secondary biosynthesis of polyketides all time points when all seven arrays were used, reporter metabolites were found to be quite scattered across the metabolism spanning several metabolic pathways, and thus offering a global view of the transcriptional response in the metabolic network. presence of some amino acids, nucleic acids and its precursors, carbon metabolism metabolites, lipids precursors, cofactors and photosynthesis metabolites pictures a scenario of a global regulation throughout the different metabolic pathways. reporter metabolites for each set of arrays analysed with reporter features software. by using the metabolic sub-network search algorithm, we found genes that have their expression changed across the arrays and that have a relationship with the metabolites of isyn network. furthermore, genes were identified that are strongly co-regulated all along the profile of the experiment. this set of genes is characterized in two groups. the first set consists of the genes from photosynthesis and oxidative phosphorylation. the second set is representative of a variety of genes from different pathways such as amino acid metabolism, carbohydrate metabolism, nucleotide metabolism, nitrogen metabolism and metabolism of cofactors that globally regulates the entire metabolic network. it can be expected that an experimental design like the one we have based our work on, which combines a shift from dark to light with a shift back to darkness, will encompass an important part of the regulatory changes the cell is undergoing in its natural habitat. in a glucose-deficient environment, the presence or absence of light is the main condition around which the synechocystis metabolism gravitates. indeed, one of the co-regulated sets consists of the genes coding for the proteins that work on, and around, the thylakoid membrane, let it be photosynthesis or oxidative phosphorylation genes. dark to light next, we considered the arrays that represent the shift from darkness to light, the first three arrays. reporter metabolites were found to be largely within the nucleotide and amino acid metabolism. some cofactors were also identified as regulation hubs like tetrahydrofolate, thioredoxin and adenosylcobinamide. sub-network search yielded set of genes that have their expression changed across the first three arrays and that are related with isyn reactions. furthermore, genes were identified that are strongly co-regulated across the three arrays. this set of genes cover photosynthesis, oxidative phosphorylation, amino acid metabolism, carbohydrate metabolism, nucleotide metabolism and metabolism of cofactors. this set of data arrays are indeed a good example of a cell's metabolic machinery starting up. after a hour period in darkness where cell density did not change, light enters the system and the cell starts to synthesize new bio-molecules, mostly nucleotides so it can copy its genetic material and amino acids to build up proteins. light to dark finally, we considered the arrays that represent the shift from light to dark, data from " minutes of light" array to " minutes of dark" array. similar to the previous case study, reporter metabolites were found to be focused on the nucleotide and amino acid metabolism. additionally, the presence of metabolite a -alpha-d-glucan_n and its cognate a -alpha-d-glucan_n also stands out as they are involved in carbon reserves catabolism and anabolism. with the help of the sub-network search, genes were identified as being significantly co-regulated across those three arrays. this set comprises of the genes from photosynthesis, oxidative phosphorylation, amino acid metabolism, carbohydrate metabolism, nucleotide metabolism and metabolism of cofactors. this last set of data array is a scenario where metabolism is being shut down, as a consequence of the darkness and lack of carbohydrate source. without light, photosynthesis is blocked and carbon fixation is nearly obliterated. cells strive to build up carbon reserves and oxidative phosphorylation is the main energy pathway that remains present. regulation is centered on the energy metabolism shift, withholding amino acids and nucleotide precursors and keeping the cofactors available in a low-profile metabolism.  we have successfully reconstructed a genome-scale metabolic network for synechocystis sp. pcc called isyn which allows simulating production of all the metabolic precursors of the organism. the metabolic reconstruction represents an up-to-date database that encompasses all knowledge available in public databases, scientific publications and textbooks on the metabolism of this cyanobacterium. from the annotation publicly available, our metabolic network includes metabolic reactions and metabolites, as well as the information from genes that have some relationship with the metabolic reactions. this model is the most complete and comprehensive work for synechocystis sp. pcc to date, which has its potential as the photosynthetic model organism. interestingly, the reconstruction identified reactions that should be present in the metabolism but with no cognate gene discovered yet; this should direct experimental work at the discovery of these genes. topological characteristics of the network resemble those of other reconstructed microbial metabolic networks and thus provide an additional input for the analysis of their structural and organizational properties from evolutionary perspective. applicability of isyn metabolic model was demonstrated by using a variety of computational analyses. flux balance analysis was applied in order to simulate the three physiologically important growth conditions of cyanobacteria, viz., heterotrophic, mixotrophic and autotrophic. our metabolic model was capable of simulating the production of the monomers or building blocks that build up the cells, in the range that is in agreement with the reported growth experiments. our photosynthetic metabolic model includes all of the central metabolic pathways that previous works considered. regarding the parts from our model that overlap with the previous works, the predictions for the flux directionality changes following light shift match between those models and isyn in fact, isyn expands the flux study to all the pathways described in the synechocystis sp. pcc genome annotation. further work should be directed at the definition of a detailed and descriptive biomass cell composition, so as to have a better representation of the biomass equation for simulation purposes. single reaction/gene knock-out simulations revealed genes that are essential for the survival. bearing in mind the distance from the efforts taken in the annotation of the genome of the bacteria and yeast models to that of the cyanobacterium, our study shows that synechocystis sp. pcc has a larger fraction of genes that are essential for producing biomass, as opposed to escherichia coli and saccharomyces cerevisiae. further investigation of the causes for this difference will be of definite interest in understanding the genome annotation and/or the evolution of the metabolic network of synechocystis. evaluation of the theoretical potential of this organism to produce hydrogen was assessed, in support of the efforts directed to this direction from several groups and scientific council initiatives. present hydrogen production projects are far from the theoretical potential, but efforts in this field can trigger a very significant increase of the present hydrogen evolution rates in synechocystis sp. pcc or other photobiological production platforms candidates, e.g. chlamydomonas reinhardtii, nostoc punctiforme and synechococcus species. suitability of the presented model for performing in silico metabolic engineering analysis was demonstrated by using optgene software framework. furthermore, we also show that isyn can be used as a scaffold to integrate network-wide omics data. as a case study, we identified key reporter metabolites around which regulation during light shifts is organized, as well as gene sub-networks that were co-regulated across the light conditions. altogether, the genome-scale metabolic network of synechocystis sp. pcc will be a valuable tool for the applied and fundamental research of synechocystis sp. pcc as well as for the broad field of metabolic systems biology. isyn represents an important step for the integration of tools and knowledge from different disciplines towards development of photo-biological cell factories. 
gene essentiality and hydrogen production potential have also been assessed. pcc it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the synechocystis metabolic network. pcc and through in silico metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. the model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. in order to enable efficient use of metabolic potential of synechocystis sp. we report the most comprehensive metabolic model of synechocystis sp. we demonstrate applicability of isyn for stoichiometric analysis by simulating three physiologically relevant growth conditions of synechocystis sp.
 synechocystis sp. pcc is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using co and light as carbon and energy source, respectively. in order to enable efficient use of metabolic potential of synechocystis sp. pcc it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the synechocystis metabolic network.  we report the most comprehensive metabolic model of synechocystis sp. pcc available, isyn which includes reactions, associated with genes, and metabolites. the model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. we demonstrate applicability of isyn for stoichiometric analysis by simulating three physiologically relevant growth conditions of synechocystis sp. pcc and through in silico metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. gene essentiality and hydrogen production potential have also been assessed. furthermore, isyn was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes.  isyn provides a platform for facilitating the development of cyanobacteria as microbial cell factories. 