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Multi-drug combination therapy carries significant promise for pharmacological intervention, primarily better efficacy with less toxicity and fewer side effects. However, the field lacks methodology to assess synergistic or antagonistic interactions for drugs with non-traditional dose response curves. Specifically, our goal was to assess small-molecule modulators of antioxidant response element (ARE)-driven gene expression, which is largely regulated by the Nrf2 transcription factor. Known as Nrf2 activators, this class of compounds upregulates a battery of cytoprotective genes and shows significant promise for prevention of numerous chronic diseases. For example, sulforaphane sourced from broccoli sprouts is the subject of over 70 clinical trials. Nrf2 activators generally have non-traditional dose response curves that are hormetic, or U-shaped. We introduce a method based on the principles of Loewe Additivity to assess synergism and antagonism for two compounds in combination. This method, termed Dose-Equivalence/Zero Interaction (DE/ZI), can be used with traditional Hill-slope response curves, and it also can assess interactions for compounds with non-traditional curves, using a nearest-neighbor approach. Using a Monte-Carlo method, DE/ZI generates a measure of synergy or antagonism for each dosing pair with an associated error and p-value, resulting in a 3D response surface. For the assessed Nrf2 activators, sulforaphane and di-tert-butylhydroquinone, this approach revealed synergistic interactions at higher dosing concentrations consistently across data sets and potential antagonistic interactions at lower concentrations. DE/ZI eliminates the need to determine the best fit equation for a given data set and values experimentally-derived results over formulated fits.

Stress inducing molecules affect both the mean behavior of bacterial growth and also variations in the growth. While the mechanisms that cause changes in the mean behavior are well understood, little is known about changes in the variation of the population. A true understanding of how organisms respond to stress must include an understanding of the mechanisms and purposes of changes in variation and the distribution not directly related to changes in the mean of the population. We have explored the results of combinatorial treatments using EDTA, copper sulfate, hydrogen peroxide, and hydrochloric acid as stress inducing molecules on bacterial colony formation and area on LB-agar plates. Three different combinations of X-gal and IPTG were used to create different background conditions. Some treatments alter the variation and/or the distribution of the area without having a significant effect on the mean, others affect the mean without altering the distribution, and yet others affect distribution and the mean.

Small molecule Nrf2/ARE pathway activators show promise to preventchronic disease conditions, given their role in mitigating oxidative and electrophilic stress. We find that the efficacy and potency of the clinically-studied electrophilic Nrf2/ARE activator sulforaphane are enhanced by 12.5 µM 2,5-di-tert-butyl hydroquinone (dtBHQ), a reactive oxygen species-generating diphenol. Because the maximum efficacy of sulforaphane is increased, the compounds are acting in a synergistic manner. The issue that arises is how to quantitate the extent of the synergistic interaction. Synergy is defined by a response greater than the predicted additive response. We investigated whether the commonly used dose-effect models, including Highest Single Agent, Response Additivity, and Bliss Independence, as well as the curve-based models, e.g. Loewe Additivity and the Chou-Talalay method, could be applied to sulforaphane and dtBHQ data sets to predict the additive response. Nrf2-targeted activators, including sulforaphane, do not exhibit a traditional Hill-slope dose-response curve, but rather a hormetic dose-response, with a U-shape. We show that, given the sulforaphane curve shape, published methods of determining the predictive additive effect are not appropriate. Therefore, we propose a model to assess synergistic interactions that can be applied to any curve shape. This method, termed dose-equivalence/zero-interaction (DE/ZI), is based on the principles of Loewe Additivity, in which additivity is determined not by adding the effects of doses of drug A and drug B, but by adding the dose of A and the equivalent dose of B and calculating the predicted effect. DE/ZI differs from Loewe Additivy in that DE/ZI releases the constraint that interpolation off curve A and curve B must give the same predicted additive result. DE/ZI generates a FoldSynergy value with error, based on a Monte Carlo simulation. DE/ZI allows drug combinations to be assessed for synergy or antagonism, even for compounds that do not fit to a traditional Hill-slope model.

For most proteins, multiple sequence alignments are a viable method to identify functionally and structurally important amino acids, but for most organisms, there is a subset of proteins that are unique or found in a few closely related organisms. For these proteins, it is not possible to produce sequence alignments that are useful in identifying functionally or structurally important amino acids. We have investigated the relationship between amino acid conservation and five factors (the amino acid's identity, N-terminal neighbor, C-terminal neighbor, the local hydropathy of surrounding amino acids, and the local expected net charge of the surrounding amino acids based on the primary sequence) in Escherichia coli proteins. For four of the factors examined (all but the amino acid's identity), there is a significant relationship with conservation for some of the standard 20 amino acids. Using the combination of all five factors, we show that it is possible to calculate a score based on the primary sequences of a subset of E. coli proteins that has statistically significant predictive value with respect to predicting conserved amino acids in other E. coli proteins and Saccharomyces cerevisiae proteins. As these five variables show significant relationships with conservation, we have termed them conservation factors.

The Arabidopsis thaliana AtNRT2.1 gene, which encodes a NO(3)(-) transporter involved in high-affinity uptake by the roots, is a molecular target of several mechanisms responsible for the regulation of root NO(3)(-) acquisition by the N status of the plant. All levels of AtNRT2.1 expression (promoter activity, transcript level, protein accumulation, transport activity) are coordinately up-regulated in the presence of NO(3)(-), and repressed by downstream N metabolites. Transgenic plants expressing the GUS reporter gene under the control of upstream sequences of AtNRT2.1 have been studied to identify elements targeted by these two regulatory mechanisms. A 150 bp sequence located upstream of the TATA box that is required for both stimulation by NO(3)(-) and repression by N metabolites of the promoter has been identified. This sequence is able to confer these two regulations to a minimal promoter. Split-root experiments indicate that the stimulation of the chimaeric promoter by NO(3)(-) occurs only at the local level, whereas its repression by N metabolites is mediated by a systemic signal spread to the whole plant. The activity of the cis-acting 150 bp element is also regulated by sucrose supply to the roots, suggesting a possible interaction between N and C signalling within this short region. Accordingly, multiple motifs potentially involved in regulations by N and/or C status are identified within this sequence by bioinformatic approaches. This is the first report of such a cis-acting element in higher plants.

ThiI is an enzyme common to the biosynthetic pathways leading to both thiamin and 4-thiouridine in tRNA. Comparison of the ThiI sequence with protein sequences in the data bases revealed that the Escherichia coli enzyme contains a C-terminal extension displaying sequence similarity to the sulfurtransferase rhodanese. Cys-456 of ThiI aligns with the active site cysteine residue of rhodanese that transiently forms a persulfide during catalysis. We investigated the functional importance of this sequence similarity and discovered that, like rhodanese, ThiI catalyzes the transfer of sulfur from thiosulfate to cyanide. Mutation of Cys-456 to alanine impairs this sulfurtransferase activity, and the C456A ThiI is incapable of supporting generation of 4-thiouridine in tRNA both in vitro and in vivo. We therefore conclude that Cys-456 of ThiI is critical for activity and propose that Cys-456 transiently forms a persulfide during catalysis. To accommodate this hypothesis, we propose a general mechanism for sulfur transfer in which the terminal sulfur of the persulfide first acts as a nucleophile and is then transferred as an equivalent of S(2-) rather than S(0).

All organisms modify the bases of their RNA after transcription. Relatively little is known about the functions that these chemical alterations serve and, with very few exceptions, even less has been established regarding the enzymology involved. One modified base of known function is 4-thiouridine at position 8 of certain bacterial tRNAs, which serves as a photosensor for near-UV light. A gene involved in the conversion of uridine at position 8 into 4-thiouridine has been identified by genetic screening and its role in 4-thiouridine generation has been confirmed biochemically. This same gene, thiI , has recently been shown to play a role in thiamin biosynthesis. The purification and characteristics of the purified protein are also reported.

Understanding how the biological connectivity of genes and gene products affects evolution is an important aspect of understanding evolution. Genes encoding enzymes are frequently used to carry out such analyses. Interestingly, studies have shown that connectivity in the metabolic networks in parasitic protists, including Plasmodium falciparum and Trypanosoma brucei, have been substantially altered as compared to free living eukaryotes, such as Saccharomyces cerevisiae. Herein, we have determined K(a) values, which are a measure of the non-synonymous substitution rate, and used them to examine the differences between the evolution of genes in T. brucei, P. falciparum, S. cerevisiae, and Schizosaccharomyces pombe. All four organisms share similar traits with respect to the evolution of genes encoding metabolic enzymes. First, genes encoding metabolic enzymes have lower K(a) values than genes encoding non-metabolic proteins. In addition, perturbations of the metabolic network appear to have limited affects on the genes encoding enzymes near the perturbation. In most cases, there is a negative relationship between connectivity in the metabolic network of the gene product and the K(a) value for the gene, i.e. examining how much constraint there is on gene evolution when it is connected to many other genes. In addition, we find that the K(a) values of orthologs encoding for metabolic enzymes in each organism are significantly correlated, indicating similar patterns of non-synonymous substitutions. In total, our results indicate that the evolution of genes encoding metabolic enzymes do not tend to be greatly affected by changes in the metabolic network.

Analysis of the Arabidopsis thaliana, Saccharomyces cerevisiae, Mus musculus, Escherichia coli, Bacillus subtilis, Thermoplasma acidophilum, and Sulfolobus tokodaii genomes demonstrate that many amino acid biases occur at the N- and C-termini of proteins, a statistically significant number of these biases are evolutionarily conserved, and these biases occur in amino acids beyond the first and last five amino acids. Analyses designed to shed light on the mechanism causing amino acid biases suggest that in at least some cases the bias is caused by forces acting at the nucleic acid level. It is also demonstrated that in E. coli functionally related proteins show similar biases at the N- and C-termini suggesting that the mechanisms causing the biases are complex and in some cases are related to function.

Transcription by RNA polymerase II in trypanosomes deviates from the standard eukaryotic paradigm. Genes are transcribed polycistronically and subsequently cleaved into functional mRNAs, requiring trans splicing of a capped 39-nucleotide leader RNA derived from a short transcript, the spliced leader (SL) RNA. The only identified trypanosome RNA polymerase II promoter is that of the SL RNA gene. We have previously shown that transcription of SL RNA requires divergent trypanosome homologs of RNA polymerase II, TATA binding protein, and the small nuclear RNA (snRNA)-activating protein complex. In other eukaryotes, TFIIB is an additional key component of transcription for both mRNAs and polymerase II-dependent snRNAs. We have identified a divergent homolog of the usually highly conserved basal transcription factor, TFIIB, from the pathogenic parasite Trypanosoma brucei. T. brucei TFIIB (TbTFIIB) interacted directly with the trypanosome TATA binding protein and RNA polymerase II, confirming its identity. Functionally, in vitro transcription studies demonstrated that TbTFIIB is indispensable in SL RNA gene transcription. RNA interference (RNAi) studies corroborated the essential nature of TbTFIIB, as depletion of this protein led to growth arrest of parasites. Furthermore, nuclear extracts prepared from parasites depleted of TbTFIIB, after the induction of RNAi, required recombinant TbTFIIB to support spliced leader transcription. The information gleaned from TbTFIIB studies furthers our understanding of SL RNA gene transcription and the elusive overall transcriptional processes in trypanosomes.

Systems biology requires mathematical tools not only to analyse large genomic datasets, but also to explore large experimental spaces in a systematic yet economical way. We demonstrate that two-factor combinatorial design (CD), shown to be useful in software testing, can be used to design a small set of experiments that would allow biologists to explore larger experimental spaces. Further, the results of an initial set of experiments can be used to seed further 'Adaptive' CD experimental designs. As a proof of principle, we demonstrate the usefulness of this Adaptive CD approach by analysing data from the effects of six binary inputs on the regulation of genes in the N-assimilation pathway of Arabidopsis. This CD approach identified the more important regulatory signals previously discovered by traditional experiments using far fewer experiments, and also identified examples of input interactions previously unknown. Tests using simulated data show that Adaptive CD suffers from fewer false positives than traditional experimental designs in determining decisive inputs, and succeeds far more often than traditional or random experimental designs in determining when genes are regulated by input interactions. We conclude that Adaptive CD offers an economical framework for discovering dominant inputs and interactions that affect different aspects of genomic outputs and organismal responses.

The enzyme ThiI is common to the biosynthetic pathways leading to both thiamin and 4-thiouridine in tRNA. We earlier noted the presence of a motif shared with sulfurtransferases, and we reported that the cysteine residue (Cys-456 of Escherichia coli ThiI) found in this motif is essential for activity (Palenchar, P. M., Buck, C. J., Cheng, H., Larson, T. J., and Mueller, E. G. (2000) J. Biol. Chem. 275, 8283–8286). In light of that finding and the report of the involvement of the protein IscS in the reaction (Kambampati, R., and Lauhon, C. T. (1999) Biochemistry 38, 16561–16568), we proposed two mechanisms for the sulfur transfer mediated by ThiI, and both suggested possible involvement of the thiol group of another cysteine residue in ThiI. We have now substituted each of the cysteine residues with alanine and characterized the effect on activity in vivo and in vitro. Cys-108 and Cys-202 were converted to alanine with no significant effect on ThiI activity, and C207A ThiI was only mildly impaired. Substitution of Cys-344, the only cysteine residue conserved among all sequenced ThiI, resulted in the loss of function in vivo and a 2700-fold reduction in activity measured in vitro. We also examined the possibility that ThiI contains an iron-sulfur cluster or disulfide bonds in the resting state, and we found no evidence to support the presence of either species. We propose that Cys-344 forms a disulfide bond with Cys-456 during turnover, and we present evidence that a disulfide bond can form between these two residues in native ThiI and that disulfide bonds do form in ThiI during turnover. We also discuss the relevance of these findings to the biosynthesis of thiamin and iron-sulfur clusters.

The gene thiI encodes a protein (ThiI) that plays a role in the transfer of sulfur from cysteine to both thiamin and 4-thiouridine, but the reaction catalyzed by ThiI remains undetermined. Based upon sequence alignments, ThiI shares a unique "P-loop" motif with the PPi synthetase family, four enzymes that catalyze adenylation and subsequent substitution of carbonyl oxygens. To test whether or not this motif is critical for ThiI function, the Asp in the motif was converted to Ala (D189A), and a screen for in vivo 4-thiouridine production revealed the altered enzyme to be inactive. Further scrutiny of sequence data and the crystal structures of two members of the PPi synthetase family implicated Lys321 in the proposed adenylation function of ThiI, and the critical nature of Lys321 has been demonstrated by site-directed mutagenesis and genetic screening. Our results, then, indicate that ThiI catalyzes the adenylation of a substrate at the expense of ATP, a narrowing of possible reactions that provides a strong new basis for deducing the early steps in the transfer of sulfur from cysteine to both thiamin and 4-thiouridine.

In support of the key features of sulfur transfer in the proposed mechanisms of 4-thiouridine generation, the enzyme ThiI can turn over only once in the absence of reductants of disulfide bonds, and Cys-456 of ThiI receives the sulfur transferred from the persulfide group of the sulfurtransferase IscS.

Light and carbon are two essential signals influencing plant growth and development. Little is known about how carbon and light signaling pathways intersect or influence one another to affect gene expression. Microarrays are used to investigate carbon and light signaling interactions at a genome-wide level in Arabidopsis thaliana. A classification system, 'InterAct Class', is used to classify genes on the basis of their expression profiles. InterAct classes and the genes within them are placed into theoretical models describing interactions between carbon and light signaling. Within InterAct classes there are genes regulated by carbon (201 genes), light (77 genes) or through carbon and light interactions (1,247 genes). We determined whether genes involved in specific biological processes are over-represented in the population of genes regulated by carbon and/or light signaling. Of 29 primary functional categories identified by the Munich Information Center for Protein Sequences, five show over-representation of genes regulated by carbon and/or light. Metabolism has the highest representation of genes regulated by carbon and light interactions and includes the secondary functional categories of carbon-containing-compound/carbohydrate metabolism, amino-acid metabolism, lipid metabolism, fatty-acid metabolism and isoprenoid metabolism. Genes that share a similar InterAct class expression profile and are involved in the same biological process are used to identify putative cis elements possibly involved in responses to both carbon and light signals. The work presented here represents a method to organize and classify microarray datasets, enabling one to investigate signaling interactions and to identify putative cis elements in silico through the analysis of genes that share a similar expression profile and biological function.

Background Cycads are ancient seed plants (living fossils) with origins in the Paleozoic. Cycads are sometimes considered a 'missing link' as they exhibit characteristics intermediate between vascular non-seed plants and the more derived seed plants. Cycads have also been implicated as the source of 'Guam's dementia', possibly due to the production of S(+)-beta-methyl-alpha, beta-diaminopropionic acid (BMAA), which is an agonist of animal glutamate receptors.

Microarray analysis and the 'InterAct class' method were used to study interactions between carbon and nitrogen signaling in Arabidopsis., Background Carbon and nitrogen are two signals that influence plant growth and development. It is known that carbon- and nitrogen-signaling pathways influence one another to affect gene expression, but little is known about which genes are regulated by interactions between carbon and nitrogen signaling or the mechanisms by which the different pathways interact. Results Microarray analysis was used to study global changes in mRNA levels due to carbon and nitrogen in Arabidopsis thaliana. An informatic analysis using InterAct Class enabled us to classify genes on the basis of their responses to carbon or nitrogen treatments. This analysis provides in vivo evidence supporting the hypothesis that plants have a carbon/nitrogen (CN)-sensing/regulatory mechanism, as we have identified over 300 genes whose response to combined CN treatment is different from that expected from expression values due to carbon and nitrogen treatments separately. Metabolism, energy and protein synthesis were found to be significantly affected by interactions between carbon and nitrogen signaling. Identified putative cis-acting regulatory elements involved in mediating CN-responsive gene expression suggest multiple mechanisms for CN responsiveness. One mechanism invokes the existence of a single CN-responsive cis element, while another invokes the existence of cis elements that promote nitrogen-responsive gene expression only when present in combination with a carbon-responsive cis element. Conclusion This study has allowed us to identify genes and processes regulated by interactions between carbon and nitrogen signaling and take a first step in uncovering how carbon- and nitrogen-signaling pathways interact to regulate transcription.