The kinetics of prokaryotic gene expression has been modelled by the Monte Carlo computer simulation algorithm of Gillespie, which allowed the study of random fluctuations in the number of protein molecules during gene expression. The model, when applied to the simulation of LacZ gene expression, is in good agreement with experimental data. The influence of the frequencies of transcription and translation initiation on random fluctuations in gene expression has been studied in a number of simulations in which promoter and ribosome binding site effectiveness has been changed in the range of values reported for various prokaryotic genes. We show that the genes expressed from strong promoters produce the protein evenly, with a rate that does not vary significantly among cells. The genes with very weak promoters express the protein in "bursts" occurring at random time intervals. Therefore, if the low level of gene expression results from the low frequency of transcription initiation, huge fluctuations arise. In contrast, the protein can be produced with a low and uniform rate if the gene has a strong promoter and a slow rate of ribosome binding (a weak ribosome binding site). The implications of these findings for the expression of regulatory proteins are discussed.Stochastic fluctuations in gene expression have drawn the attention of several research groups. It has been postulated (1, 2) and observed (3) that proteins are produced in short "bursts" occurring at random time intervals rather than in a continuos manner. This expression pattern arises from the fact that elementary processes such as polymerase binding and open complex formation involve small number of molecules and therefore show a wide distribution of reaction times. The fluctuations in a number of protein molecules resulting from stochastic gene expression are of special importance if the concentration of the protein constitutes the message that regulates expression of another gene. In this case, one may expect that the activation pattern of the regulated gene is also random, to some extent. The stochastic nature of gene expression and other biochemical processes involving small numbers of molecules may explain the variations observed in isogenic populations of bacterial cells. Examples are individual chemotactic responses (4), the distribution of generation times observed in Escherichia coli cells (5), and the individual cell responses observed during induction of lactose (6) and arabinose (7) operons at subsaturating inducer concentrations. Stochastic effects have also been observed in engineered genetic networks in E. coli (8). Taking into account the stochastic phenomena described above, it is clear that the cell must contain various mechanisms that ensure deterministic regulation of cellular processes. The check points in eukaryotic cell cycle regulation (9) are examples of such a mechanism.Computer simulations implementing various Monte Carlo algorithms proved to be useful in studying stochastic processes in biochemical reaction networks. This i...

The LysR-type transcriptional regulators (LTTRs) comprise the largest family of prokaryotic transcription factors. These proteins are composed of an N-terminal DNA binding domain (DBD) and a C-terminal cofactor binding domain. To date, no structure of the DBD has been solved. According to the SUPERFAMILY and MODBASE databases, a reliable homology model of LTTR DBDs may be built using the structure of the Escherichia coli ModE transcription factor, containing a winged helix- turn-helix (HTH) motif, as a template. The remote, but statistically significant, sequence similarity between ModE and LTTR DBDs and an alignment generated using SUPERFAMILY and MODBASE methods was independently confirmed by alignment of sequence profiles representing ModE and LTTR family DBDs. Using the crystal structure of the E.coli OxyR C-terminal domain and the DBD alignments we constructed a structural model of the full-length dimer of this LTTR family member and used it to investigate the mode of protein-DNA interaction. We also applied the model to interpret, in a structural context, the results of numerous biochemical studies of mutated LTTRs. A comparison of the LTTR DBD model with the structures of other HTH proteins also provides insights into the interaction of LTTRs with the C-terminal domain of the RNA polymerase alpha subunit.

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The Crt1 (RFX1) protein in Saccharomyces cerevisiae is an effector of the DNA damage checkpoint pathway. It recognizes a 13-bp cis-regulatory element in the 5 -untranslated region (5 -UTR) of the ribonucleotide reductase genes RNR2, RNR3, and RNR4; the HUG1 gene; and itself. We calculated the weight matrix representing the Crt1p binding site motif according to analysis of the 5 -UTR sequences of the genes that are under its regulation. We subsequently searched the 5 -UTR sequences of all the genes in the yeast genome for the occurrence of this motif. The motif was found in regulatory regions of 30 genes. A statistical analysis showed that it is unlikely that a random gene cluster contains the motif conserved as well as the Crt1p binding site. Analysis of microarray data provided supporting evidence for five putative Crt1p targets: FSH3, YLR345W, UBC5, NDE2, and NTH2. We used reverse transcription-PCR to compare the expression levels of these genes in wild-type and crt1⌬ strains. Our results indicated that FSH3, YLR345W, and NTH2 are indeed under the regulation of Crt1p. Sequence analysis of the FSH3p indicated that this protein may be involved in folate metabolism either by carrying serine hydrolase activity required for the novel metabolic pathway involving dihydrofolate reductase (DHFR) or by directly interacting with the DHFR enzyme. We postulate that Crt1p may influence deoxyribonucleotide synthesis not only by regulating expression of the RNR genes but also by modulating DHFR activity. FSH3p shares significant sequence similarity with the product of the human tumor suppressor gene OVCA2. YLR345Wp and NTH2p are enzymes involved in the central metabolism under stress conditions.

SummaryCysB is a LysR-type transcriptional regulator (LTTR) controlling the expression of numerous genes involved in bacterial sulphur assimilation via cysteine biosynthesis. Our previous mutational analysis of CysB identified several residues within the N-terminal domain crucial for DNA-binding function. Here, we focus on the functional significance of CysB residues localized in the turn between the a a a a 2 and a a a a 3 helices forming an N-terminal helix-turn-helix motif. On the basis of the characteristics of alanine-substituted mutants, we propose that CysB residues Y27, T28 and S29, lying in this turn region, comprise an 'activating region' (AR) that is crucial for positive control of the cysP promoter, but not for DNA binding and inducer response activities of CysB. Using a library of alanine substitutions in the C-terminal domain of the RNAP a a a a subunit ( a a a a -CTD), we identify several residues in a a a a -CTD that are important for CysB-dependent transcription from the cysP promoter. After probing potential protein-protein contacts in vivo with a LexA-based two-hybrid system, we propose that the '273 determinant' on a a a a -CTD, including residues K271 and E273, represents a target for interaction with CysB at the cysP promoter.