in vivo , the biologically active form of dna in prokaryotes is negatively supercoiled . the amount of superhelical stress imposed on the dna is determined by the levels of competing dna topoisomerase enzyme activities , and by local events such as protein binding or dna transcription ( 13 ) . transient changes in the level of global dna supercoiling have been observed with several types of environmental stress , including heat shock , cold shock , ph changes , osmotic shifts , transitions from aerobiosis to anaerobiosis and starvation ( 1,2 ) . along with these changes in stress level , the expression patterns of the bacteria involved were observed to be dramatically altered ( 46 ) . reactions occurring on the dna template , including transcription and replication , also affect the local level of supercoiling . when rna polymerase threads through the dna template , it pushes a wave of positive supercoils ahead , and leaves a trail of negative supercoils behind ( 3,7 ) . one way in which negative superhelicity can influence regulation is through the destabilizing effect it has on the double helix at susceptible locations within the sequence . destabilization by even a few kilocalories , far less than would be required to open the duplex , can have a profound effect on the ability of a regulatory molecule to unpair the dna , as is required for the initiation of transcription or replication . in this manner experiments have shown that stress - induced duplex destabilization plays essential roles in the transcriptional regulation of several genes ( 810 ) . we have developed computational methods that evaluate the patterns of stress - induced dna duplex destabilization ( sidd ) in dna sequences ( 11,12 ) . these analyses predict the locations where the dna duplex becomes susceptible to separation when under superhelical stress . all conformational and thermodynamic parameters are given their experimentally measured values , so there are no free parameters in these analyses . despite this , their results are in quantitative agreement with experiments in all cases where experimental information is available . when the entire escherichia coli genome is analyzed in this way , the sites that are predicted to be easily stress - destabilized are found not to be distributed at random . instead , these sidd sites are highly enriched in those intergenic regions that are known or inferred to contain promoters , and occur infrequently in coding regions ( 13 ) . both components of this pattern have very high statistical significances . the frequency of sidd sites in intergenic regions separating convergent open reading frames ( orfs ) , which are inferred not to contain promoters , are consistent with random . a similar pattern of sidd sites avoiding coding regions and being enriched in intergenic regions was noted in yeast , although there the strongest sidd sites were in the terminal flanks of genes , not in their promoters ( 14 ) . our most recent studies also indicate that those genes in e.coli whose promoters have strong sidd sites are clustered in certain functional groups such as transcription regulators , transport and membrane proteins . it is interesting that many known supercoil - responsive genes and environmental stress - responsive genes have highly destabilized sites in their upstream 5 flanks . sidd sites have been shown to be important functional elements in regulating transcriptional initiation , transcriptional termination and other biological activities . in e.coli , activation of both the ilvpg and leuv promoters are mediated by similar mechanisms involving a binding - induced translocation of superhelical tension from a sidd site to the promoter ( 8,9 ) . this translocated superhelical tension facilitates the formation of the open initiation complex by unwinding the dna duplex in the promoter region . in humans , the initiation of transcription of the c - myc gene is regulated by the binding of fbp to a highly destabilized sidd site ( 15 ) . sidd sites also have been implicated in transcriptional termination and chromosomal matrix attachment in yeast ( 16 ) . these and other results show that sidd is an essential component of regulatory mechanisms for a variety of biological activities . it is important to understand that sidd properties are not simply reflections of the underlying thermal stability of the sequences involved . stresses couple together the destabilization behaviors of all base pairs that experience them this leads to much more complex , interactive behaviors than that occur with thermal melting . [ see figures 1 and 2 of ref ( 17 ) . ] here we describe the database we are compiling of the sidd profiles of microbial genomes . accessible over the web at , it gives users an overview of the sidd sites in their selected genome , and their positions relative to the annotated genes . this information will facilitate the identification of regulatory elements , such as promoter - containing regions , in the genomic sequence . in addition , the original sidd profiles ( raw data and graphs ) can be visualized and made available for downloading . the refseq sequences of the analyzed microbial genomes were downloaded from the nih microbial website . in all cases the protein gene products are classified into functional categories according to the information in the clusters of orthologous groups ( cog ) database ( 18 ) . our research group has developed three algorithmic strategies to evaluate the equilibrium distribution of states of destabilization of a short dna sequence in response to negative superhelicity ( 12,19,20 ) . these methods can calculate the probability of opening of each base pair in the sequence . one algorithm also calculates the incremental free energy g(x ) needed to guarantee opening of the base pair at position x. this can be done for each base pair in the sequence . strongly destabilized sites require little or no extra free energy to open , so their values of g(x ) are near zero . sites that remain virtually as stable as they would be in relaxed conditions ( which is the majority of the genome ) have g(x ) near 10 kcal / mol . partially destabilized sites these methods have been extended recently to enable the analysis of long dna sequences , and successfully applied to the complete genome of e.coli ( 13,17 ) . ( for detailed information on the algorithms and the methods for analyzing their results , please refer to the cited publications . ) the sidd analysis of complete microbial genomes has been semi - automated on a 38 node apple cluster . all sidd profiles were calculated at superhelical density  = lk / lk0 = 0.06 , a moderate physiological value . the results from the calculations were manually reviewed for integrity , then their global characteristics were analyzed by a set of perl scripts and c++ programs . the results were directly channeled to a postgres database for storage , visualization and further analysis . as of the present ( september 8 , 2005 ) there are 134 analyzed microbial genomes in this database , 118 from bacteria and 16 from archaea . we update the database whenever the sidd analysis of another fully sequenced genome is completed , so the number of analyzed genomes will rise in the future . for each analyzed genome each sidd site in the graph is a set of contiguous base pairs for all of which g(x ) < 8 kcal / mol . these sidd sites were binned into disjoint sets according to the minimum value gm that g(x ) attains within them . the lowest bin is determined by gm  0 , and the other bins contain the sidd sites satisfying i1 < gm  i for i = 1 ,  , 6 . a color map scheme is used to represent these binned sidd sites . the sidd sites in all the fully analyzed bacterial genomes have a similar pattern of distribution to that reported previously for the e.coli genome ( 13 ) . strong destabilization preferentially occurs in the intergenic regions separating divergently ( div ) or tandemly ( tan ) transcribed orfs , while avoiding coding regions . destabilization in intergenic regions separating convergently transcribing orfs ( con ) , which may be inferred not to contain promoters , is consistent with random . this trend is clearly demonstrated in figure 2 , which summarizes data from the analysis of sidd locations in 42 bacterial genomes . for each genome in the siddbase database we provide a table summarizing the number of sidd sites at each level of destabilization , and the number of these that occur in the three types of intergenic regions div , tan and con . systematic analysis is underway to compare the sidd properties of different strains of the same species , between different phylogenetic groups of the same kingdom and between different kingdoms . one also can display detailed sidd information for any specific region of interest , as shown in figure 3 . these requests can be made by clicking on a region of the circular map , or by specifying the site either by identifying an annotated gene it contains or by its chromosomal location . the figure displayed is a plot of the oriented genes in a 10 kb window centered on the requested position , together with the locations of the sidd sites in the region . the genes are labeled , their orientations are shown by arrowheads , and they are color coded according to their cog classification . x. ) the end of an arrowhead corresponds to the stop codon position of a gene . the sidd sites are shown as colored bars , coded according to their gm values , and displayed below the line showing the annotated genes . the graph of the sidd profile of a 5 kb long region centered on a sidd site can be viewed by clicking on the color bar corresponding to that site . while the sidd calculation for an entire bacterial genome is time consuming , calculations for short dna sequences ( viz 5 kb ) can be executed efficiently . we have provided a website where users can calculate sidd profiles of short sequences of interest to them . there one can set some of the calculation parameters , including the assumed superhelix density . it should be noted that the results calculated from the web server may not necessarily be identical as the ones displayed on this database , even when the sequences and the parameters are the same . the sidd profile of a dna segment in this database was calculated in its native global genomic context , while the results from the web server calculation were not . the current database only contains sidd profiles of complete genomes from prokaryotes and archaea . in the future we also will deposit the results of sidd analyses for eukaryotic genomes . initially this will be yeast , at least one complete chromosome from each fully sequenced eukaryote , and the encode regions of the human genome . we intend eventually to include the sidd profiles of the complete genomes of all fully sequenced model organisms . we will also provide sidd profiles of specific prokaryotic genomes at several superhelical densities . we will add further functionalities to the database as these are developed , including sidd - based ( or sidd - assisted ) promoter predictions . we will continue to analyze more microbial genomes as their sequences are completed , and we will periodically update our analyses in response to significant changes in ncbi refseq sequences . the genes are plotted in the inner circle , color coded according to their cog classifications as shown in the gene color map . the sidd sites are shown in the outer circle , color coded according to their minimum sidd energy as shown in the sidd color map . the ratio of the observed number of sidd sites to the number expected if they were located at random . this ratio has been calculated for sidd sites that overlap intergenic regions whose flanking orfs are in any of three orientations ( div , divergent ; con , convergent ; and tan , tandem ) , and also for those that occur within coding regions . these results were calculated from the sidd profiles of 42 bacterial genomes that were chosen to represent the phylogenetic diversity of sequenced genomes and the range of at / gc ratios . the x - axis is the sidd level ; the y - axis is the ratio of predicted sidd sites found in the regions to the expected number of such sites if they were located at random . this shows that the pattern reported previously in e.coli k12 occurs throughout the sequenced prokaryotes . this view is obtained from the window of figure 1 by clicking on a gene , or by entering a gene name or chromosomal location into the appropriate field . the genes are annotated , and the sidd sites are displayed as colored bars belowthe line . clicking on a sidd color bar gives an annotated sidd profile centered on that region , as shown .
prokaryotic genomic dna is generally negatively supercoiled in vivo . 
 many regulatory processes , including the initiation of transcription , are known to depend on the superhelical state of the dna substrate . 
 the stresses induced within dna by negative superhelicity can destabilize the dna duplex at specific sites . 
 various experiments have either shown or suggested that stress - induced dna duplex destabilization ( sidd ) is involved in specific regulatory mechanisms governing a variety of biological processes . 
 we have developed methods to evaluate the sidd properties of dna sequences , including complete chromosomes . 
 this analysis predicts the locations where the duplex becomes destabilized under superhelical stress . 
 previous studies have shown that the sidd - susceptible sites predicted in this way occur at rates much higher than expected at random in transcriptional regulatory regions , and much lower than expected in coding regions . 
 analysis of the sidd profiles of 42 bacterial genomes chosen for their diversity confirms this pattern . 
 predictions of sidd sites have been used to identify potential genomic regulatory regions , and suggest both possible regulatory mechanisms involving stress - induced destabilization and experimental tests of these mechanisms . 
 here we describe the siddbase database which enables users to retrieve and visualize the results of sidd analyses of completely sequenced prokaryotic and archaeal genomes , together with their annotations . 
 siddbase is available at .