The association of poised genes with transcription factories may contribute to rapid transcriptional activation in response to stimuli and to silencing when genes are located at the interior of their chromosome territories. +S2p−) factories prior to activation and localized at the CT interior. Shortly after induction, the uPA locus is found associated with active (S5p+S2p+) factories and loops out from its CT. However, the levels of gene association with poised or active transcription factories, before and after activation, are independent of locus positioning relative to its CT. RNA-FISH analyses show that, after activation, the uPA gene is transcribed with the same frequency at each CT position. Unexpectedly, prior to activation, the uPA loci internal to the CT are seldom transcriptionally active, while the smaller number of uPA loci found outside their CT are transcribed as frequently as after induction. The association of inducible genes with poised transcription factories prior to activation is likely to contribute to the rapid and robust induction of gene expression in response to external stimuli, whereas gene positioning at the CT interior may be important to reinforce silencing mechanisms prior to induction.The position of genes in the interphase nucleus and their association with functional landmarks correlate with active and/or silent states of expression. Gene activation can induce chromatin looping from chromosome territories (CTs) and is thought to require de novo association with transcription factories. We identify two types of factory: “poised transcription factories,” containing RNA polymerase II phosphorylated on Ser5, but not Ser2, residues, which differ from “active factories” associated with phosphorylation on both residues. Using the urokinase-type plasminogen activator (uPA) gene as a model system, we find that this inducible gene is predominantly associated with poised . Recent genome-wide mapping of RNA polymerase II has identified its presence at many genes poised for activation, raising the possibility that such genes might associate with poised transcription factories. Using an inducible mammalian gene, urokinase-type plasminogen activator (uPA), and a system in which this gene is poised for expression, we show that uPA associates with poised transcription factories prior to activation. Gene activation induces two independent events: repositioning towards the exterior of its chromosome territory and association with active transcription factories. Surprisingly, genes inside the interior of the chromosome territory prior to activation are less likely to be actively transcribed, suggesting that positioning at the territory interior has a role in gene silencing. The spatial folding of chromatin within the mammalian cell nucleus, from the level of whole chromosomes down to single genomic regions, is thought to contribute to the expression status of genes Although CTs do not represent general barriers to the transcriptional machinery 1-Ser2-Pro3-Thr4-Ser5-Pro6-Ser7, and phosphorylation on Ser5 residues (S5p) is associated with transcription initiation and priming, whereas phosphorylation on Ser2 (S2p) correlates with transcriptional elongation Complex phosphorylation events at the C-terminal domain (CTD) of the largest subunit of RNAP correlate with initiation and elongation steps of the transcription cycle and are crucial for chromatin remodelling and RNA processing To investigate whether primed genes are associated with discrete RNAP sites enriched in RNAP-S5p and the functional relevance of large-scale gene repositioning in promoting associations with the transcription machinery during gene activation, we investigated the expression levels, epigenetic status, nuclear position, and association with RNAP factories of an inducible gene, the urokinase-type plasminogen activator , before and after activation. We use antibodies that specifically detect different phosphorylated forms of RNAP to investigate the association of the inducible uPA gene with transcription factories. Prior to induction, most uPA alleles are positioned inside their CT and extensively associated with RNAP sites marked by S5p. Transcriptional activation leads to looping out of the uPA locus from its CT, and increased association with active transcription factories marked by both S5p and S2p. However, the extent of gene association with factories, before and after activation, is independent of the uPA position relative to its CT. Unexpectedly, we find that the majority of uPA genes which are positioned at the CT interior prior to activation are seldom transcribed, in comparison with the few uPA genes located outside the CT which are active with the same frequency as the fully induced uPA genes.The uPA gene encodes a serine protease that promotes cell motility, and its overexpression is known to correlate with cancer malignancies and tumor invasion z axis We first investigated whether transcriptional induction of the uPA gene was associated with large-scale repositioning relative to its CT, using a whole chromosome 10 probe together with a BAC probe containing the uPA locus . We perfn = 166 loci) and relocates to the exterior upon activation  but not the elongating (S2p) form of RNAP at the promoter and enhancer regions of the uPA gene prior to induction , demonstn = 165 loci; n = 170 loci; χ2 test, p<0.0001; +S2p−, transcription factories.Previous studies describing the presence of RNAP at the promoters of paused or poised genes did not investigate a possible association with transcription factories marked specifically by the S5p modification 3n = 68 loci), a significantly lower number than the experimental value of 87%±9% for the uPA locus . In contrast, the association of randomly positioned signals with S2p was 39%±5% (n = 69 loci), similar to the experimental value of 31%±5%  of standard confocal microscopes. This is particularly important when analysing highly abundant structures such as transcription factories which can exist at densities of 20/µmn = 183), while maintaining an association with RNAP-S5p , consistent with the MN-ChIP results. The approximately 2-fold increase in association with RNAP-S2p from 31% to 72%, before and after TPA treatment, respectively, was highly statistically significant . Evaluation of simulated uPA loci positioned at random coordinates in the same experimental images showed that the increased association of the uPA locus with S2p observed after activation (72%) cannot be explained by random processes, as the frequency of association of simulated loci remained at 38%±2%  both before and after activation . Analysis of spliced transcripts of CAMK2G and VCL confirms their active state prior to TPA induction and demonstrates similar effects upon activation (unpublished). Interestingly, low levels of uPA primary transcripts sensitive to α-amanitin treatment are detected prior to activation , whereas the association with S2p sites prior to induction can be (pS2p/−TPA = 0.62).Similar analyses of uPA gene association with S5p and S2p sites using a fosmid probe  confirms2 test, p = 0.26). Simultaneous detection of fosmid and BAC probes in combination with S2p detection . The increase in association of uPA loci with active factories marked by S2p after TPA is statistically significant (p<0.0001), but the effect of TPA on the level of association is the same across all positions relative to the CT . These results show that the association of the uPA, CAMK2G, and VCL genes with RNAP-S2p occurs independently of CT position. A recent analysis of gene activation induced by the insertion of a strong (ß-globin) enhancer in a gene rich-region also showed no effect on the frequency of locus association with active transcription factories at different positions relative to the CT Hoxb locus, a small preferential association of Hoxb1 and flanking genes with active transcription factories is observed outside the CT upon retinoic acid treatment Hox genes.To investigate whether the large-scale chromatin movements that accompany TPA induction of the uPA gene had an effect on the association of the flanking genes, CAMK2G and VCL, with active (S2p) factories, we performed triple labelling cryoFISH experiments for chromosome 10, the CAMK2G, or VCL loci detected with fosmid probes and active (S2p) factories . We findp = 0.74; n = 100). These results differ from the murine Igf2bp1 and Cbx1 genes, flanking the Hoxb cluster, which are also transcriptionally active at all CT positions, independently of Hoxb induction, but are preferentially active outside the CT Hoxb1 transcripts did not allow a similar analysis of allelic transcription upon induction Finally, to investigate whether the CT position of the uPA gene has an influence on its transcriptional activity, we labelled the uPA gene, chromosome 10, and uPA transcripts simultaneously . We usedp = 0.0001; n = 103), whereas the smaller proportion of uPA loci not located at the preferred internal CT position is transcribed at the same frequency as upon TPA induction  RNAP modifications, as expected in the active state. Although the correlation between looping out of the CT and the change in RNAP configuration suggested that the external position might favour transcriptional activation, triple-labelling experiments showed that the position of the uPA locus relative to its CT and the association with poised or active transcription factories are independent events. RNA-FISH experiments confirm that after TPA induction both external and internal positions of the uPA gene, with respect to its CT, are equally competent for transcription. However, positioning of the uPA locus inside the CT, before activation, may help control the levels of transcription, as uPA genes that are found outside of the CT before TPA treatment are more likely to be transcribed  preferentially positioned at the interior of its CT; (b) in a poised state, characterized by open chromatin configuration and the presence of RNAP-S5p at regulatory regions; and (c) preferentially associated with poised, S5pnscribed .Our findings reinforce the idea that the interior of CTs is not repressive for the association of genes with transcription machinery, suggesting that large-scale chromatin movements are unlikely to be necessary for genes to find transcription factories, although they may influence the extent of association for specific subsets of genes. This study expands current models of gene regulation by showing that silent genes can be associated with poised transcription factories and that factory association and gene position relative to the CT can be independent factors. Our results are also compatible with the notion that poised transcription factories represent a sub-population of specialized sites that may allow primed genes to respond rapidly and efficiently to specific activation signals.A detailed description of the experimental procedures is given in HepG2 cells were cultured in the absence or presence of 100 ng/ml TPA (Sigma) for the indicated times as previously described Chromatin cross-linking, MNase digestion, and immunoprecipitation were performed as described previously http://www.singerlab.org/protocols). See uPA protein expression was detected with specific rabbit antiserum antibodies. For high-resolution imaging using cryoFISH, ultrathin cryosections (∼140–150 nm thick) were immunolabelled and/or labelled by fluorescence in situ hybridization (FISH) essentially as described before 2 test, logistic regression analysis, ANOVA, Student t-test, or Mann-Whitney U test. See Images were acquired by confocal microscopy and analysed quantitatively. Statistical analyses were performed using χFigure S1H3K9me2 histone modification is present at H19 gene promoter, but not the uPA gene promoter. Cross-linked, sonicated chromatin from ±TPA-treated HepG2 cells was digested with MN for 50 min before immunoprecipitation with antibodies that recognize lysine 9 dimethylated histone H3 (H3K9me2), associated with closed chromatin. Control (“unrelated”) antibodies were polyclonal anti-uPAR antibodies. Immunoprecipitated DNA was amplified using primers spanning the 5′ portion of the imprinted H19 gene and the uP fragment of the uPA gene (see scheme in (0.72 MB TIF)Click here for additional data file.Figure S2Characterization of antibodies against different phosphorylated forms of RNAP.  Reactivity of different RNAP antibodies against hyper- (IIO) and hypophosphorylated (IIA) forms of the largest subunit of RNAP (RPB1) was assessed by Western blotting using total protein extracts from HepG2 cells treated for 1 h in the absence (A) or presence (B) of 1 µM flavopiridol, a specific inhibitor of CDK9, the Ser2 kinase. Both IIO and IIA bands are detected by antibody N-20 (A), raised against the amino-terminus of RPB1, which binds independently of phosphorylation. Antibodies against S5p (4H8 and H14) or S2p (H5) only detect the IIO band . Treatment of Western blots with alkaline phosphatase  prior to immunolabelling reveals the specificity of 4H8, H14, and H5 antibodies for phosphorylated epitopes, and has no effect on the binding of an antibody to the N terminus of RPB1. The specificity of H5 antibodies to the S2p modification is shown by loss of binding in flavopiridol-treated samples (B). Binding of 4H8 and H14 antibodies to IIO band is insensitive to flavopiridol treatment in these conditions, consistent with their specificity for the Ser5 modification (S5p) catalyzed by CDK7, as previously shown (B and wn B and . Protein(8.10 MB TIF)Click here for additional data file.Figure S3Frequency of association of simulated uPA loci with RNAP-S5p and RNAP-S2p sites. (A) Diagram of the genomic location of the uPA gene and the regions covered by the BAC  and fosmid  probes used for FISH experiments. Arrows indicate the 5′-3′ transcription direction.  To analyse the frequency of association of a simulated uPA locus positioned at random coordinates with RNAP-S5p or -S2p sites, we generated a new image containing the original experimental S5p  or S2p (images unpublished) distribution, and the experimental uPA signal , and an additional, simulated uPA signal with the same number of pixels, but positioned at random nucleopasmic coordinates . This analysis was performed for both BAC (B) and fosmid (D) experiments presented in nBAC,S5p = 68 and 62; nBAC,S2p = 69 and 75; nfosmid,S5p = 47 and 40; nfosmid,S2p = 50 and 46, for − and +TPA, respectively.(8.58 MB TIF)Click here for additional data file.Figure S4The uPA gene loops out of its chromatin domain. (A) Diagram illustrating the genomic location of the uPA gene and the regions covered by the BAC  and fosmid  probes used for FISH experiments. Arrows indicate the 5′-3′ transcription direction. (B) The association of BAC and fosmid signals (arrowhead) relative to RNAP-S2p sites (green) was determined simultaneously by immuno-cryoFISH before (unpublished image) and after (B) TPA activation for 3 h, using digoxigenin-labelled BAC (blue) and rhodamine-labelled fosmid (red) probes. High magnification images show examples of the co-association of both BAC- and fosmid-uPA signals with S2p sites (top) or the association of fosmid-uPA signal, but not the BAC signal with S2p sites (bottom). Nucleic acids were counterstained with DAPI (inset). Bar: 2 µm. (C) Frequency of the association of BAC or fosmid signals with S2p sites is similar between probes . Error bars are standard deviations from two replicate experiments. (D) Fosmid signals (red) can loop out of BAC foci (green). Arrowheads indicate the position of BAC and fosmid signals. Insets show higher magnification images. Nucleic acids were counterstained with TOTO-3 (blue). Bar: 2 µm. Frequency of co-localisation of BAC foci with fosmid-uPA signals show that 15%–20% of uPA alleles detected with the fosmid probe loop out from the BAC signals. The difference between the levels of fosmid looping ±TPA was not statistically significant .(6.78 MB TIF)Click here for additional data file.Figure S5Control experiments for cryo-RNA-FISH. (A–D) Cryosections (∼150 nm thick) of HepG2 cells were hybridised with Cyanine3 labelled uPA oligonucleotide probes before (A) and after (B–D) TPA activation. Inspection of nucleoplasmic regions identifies frequent uPA-RNA signals in TPA-treated cells . Pre-incubation of sections with RNase A (C) or omission of oligonucleotide probes (D) abolishes most uPA-RNA signals within the nucleoplasm, demonstrating its specificity. Nucleic acids were counterstained with TOTO-3 (red). Bars: 2 µm.(8.38 MB TIF)Click here for additional data file.Figure S6Detection of the uPA gene with a fosmid probe recapitulates the CT looping and position-independent association with S5p and S2p factories observed with the BAC probe. (A) The position of the uPA locus  relative to the chromosome 10 territory  was determined in HepG2 cells, before and after TPA activation for 3 h, by cryoFISH using a whole chromosome 10 paint and a digoxigenin-labelled uPA fosmid probe. The positions of uPA loci were scored as “inside,” “inner-edge,” “edge,” “outer-edge,” and “outside” relative to its CT as in n = 234 loci), and relocates to the exterior upon activation . (B) The proportion of uPA loci detected using the fosmid probe, which associate with RNAP-S5p before and after TPA activation, was calculated at each CT position  as for the BAC probe . Overall no effect of TPA treatment on the association of the uPA gene with S5p was detected . Association of uPA loci detected with the fosmid probe with S2p sites before and after activation is also independent of its position relative to the CT . This same analysis also detected an increased association of uPA gene with S2p sites upon activation .AC probe . Associa(5.63 MB TIF)Click here for additional data file.Figure S7uPA-flanking genes, CAMK2G and VCL, associate with S2p factories independently of CT position or TPA activation. The association of CAMK2G or VCL loci with RNAP-S2p were determined relative to the chromosome 10 territory (CT10) in HepG2 cells, before and after TPA activation (3 h), by cryoFISH using a whole chromosome 10 paint and digoxigenin-labelled CAMK2G and VCL fosmid probes. (A) Images represent examples of CAMK2G loci  that co-localise with RNAP-S2p (green) inside (left) or outside (right) of CT10 (blue). Nucleic acids were counterstained with DAPI (insets). Bar: 2 µm. (B) The proportion of CAMK2G or VCL loci, which associate with RNAP-S2p, was determined at each CT position , before and after TPA activation. Association of either gene with S2p is independent of their position relative to the CT and to TPA treatment.(5.98 MB TIF)Click here for additional data file.Figure S8Examples of classification criteria for the association of uPA loci with RNAP-S5p and RNAP-S2p sites. The position of the uPA locus (red) with S5p and S2p sites (green) was determined by immuno-cryoFISH using a rhodamine-labelled BAC probe containing the uPA locus and antibodies specific for RNAP phosphorylated at residues S5 or S2 of the CTD. Associated uPA loci co-localise with S5p or S2p sites if signals overlap by at least a single pixel, whereas separated sites do not show overlap of the two signals and include loci that may touch an RNAP site without signal overlap.(4.11 MB TIF)Click here for additional data file.Table S1MN-ChIP primers. List of primers used in MN-ChIP analyses in 5′ to 3′ orientation.(0.06 MB DOC)Click here for additional data file.Text S1Supplementary information.(0.10 MB DOC)Click here for additional data file.


In this study, we show that the intS gene is tightly regulated by its own product as well as by the TorI RDF protein. In silico analysis revealed that overlap of the attL region with the integrase promoter is widely encountered in prophages present in prokaryotic genomes, suggesting a general occurrence of negatively autoregulated integrase genes. The prediction that these integrase genes are negatively autoregulated was biologically assessed by studying the regulation of several integrase genes from two different Escherichia coli strains. Our results suggest that the majority of tRNA-associated integrase genes in prokaryotic genomes could be autoregulated and that this might be correlated with the recombination efficiency as in KplE1. The consequences of this unprecedented regulation for excisive recombination are discussed.Temperate phages have the ability to maintain their genome in their host, a process called lysogeny. For most, passive replication of the phage genome relies on integration into the host's chromosome and becoming a prophage. Prophages remain silent in the absence of stress and replicate passively within their host genome. However, when stressful conditions occur, a prophage excises itself and resumes the viral cycle. Integration and excision of phage genomes are mediated by regulated site-specific recombination catalyzed by tyrosine and serine recombinases. In the KplE1 prophage, site-specific recombination is mediated by the IntS integrase and the TorI recombination directionality factor (RDF). We previously described a sub-family of temperate phages that is characterized by an unusual organization of the recombination module. Consequently, the  Temperate bacteriophages are widespread bacterial viruses that have the ability to replicate passively in their hosts as long as no stressful conditions are encountered, a process called lysogeny. Prophage-encoded genes may benefit the host in several ways such as providing resistance to antibiotics, increased pathogenicity, or increased fitness. Most temperate phages insert their genome into the host's chromosome by site-specific recombination. After prophage induction, usually under stressful conditions, the excisive recombination constitutes a key step toward productive phage development. In this paper, we study the regulation of integrase genes that encode the enzyme required for integrative as well as excisive recombination. We noticed that for prophages inserted in or near tRNA genes the orientation of the integrase gene relative to the tRNA is crucial for its regulation. Temperate bacteriophages are characterized by their ability to maintain their genome into the host, a process called lysogeny. Most temperate phages integrate their genome into the host's chromosome, becoming prophages. Alternatively, circularized phage genomes are maintained as episomes. Once integrated, the now so-called prophage is stable and replicates passively with its host genome. This situation can continue as long as outside conditions do not become threatening for the host, and therefore for the virus. Prophages are indeed able to detect many stressful signals, such as DNA damage, excessive heat or pressure attP on the phage genome and attB on the bacterial chromosome leading to the formation of the recombined halves attL and attR at the junctions between the bacterial chromosome and the integrated phage genome . None of these ORFs seems to encode a repressor consistent with the finding that KplE1 is not SOS-inducible . Despite the small remnant genome, the KplE1 prophage can be excised in vivoattL and attR recombination regions E. coli strains K1 RS218 and TD2158, respectively, and Sf6, which infects Shigella flexneri, as well as in prophages present in E. coli strains APEC-O1 and UTI89 in vivo independently of prophage induction since the CI regulator module is missing in KplE1. Directionality of the site-specific recombination has been studied using KplE1 DNA substrates as well as HK620 substrates and requires the RDF protein TorI to direct the recombination reaction towards excision intS gene relative to the attL region  located distal to the int gene. Thus, lower amounts of Int are made, and Xis production is not affected by this element The KplE1 prophage  is a defective prophage integrated into the coli K12 . The proL region . Indeed,mination . The difintS promoter that overlaps the attL recombination region  that contains a sc101 replication origin, which leads to a low copy number (3 to 4 copies in the logarithmic growth phase) of the plasmid in vivo to avoid titration of the regulators attL region (positions 2464344 to 2464630 on the E. coli chromosome) in the pUA66 vector in order to measure pattL-gfp expression in various genetic backgrounds. Primer extension was used to control that transcription initiation occurred at the same site in this construct rather than in the chromosome  is also present in the gfp gene.The romosome , lane 3.attL-gfp wild-type fusion was expressed at a high level in the absence of IntS (6368±914 Units) and was repressed in the presence of IntS (1270±208 Units), leading to a repression ratio of ∼5 when the control ratio of placZ-gfp expression was close to 1 in the same conditions. This ratio of ∼5 is in complete agreement with the values we obtained by measuring intS expression from the chromosomal gene with quantitative RT-PCR We measured the fusion expression with two different methods: direct fluorescence measurement , which gattL (intS expression. As indicated in intS background led to a strong decrease in expression of the pattL-gfp(wt) fusion (compare 6368±914 with 1201±370 units). Taken together, these results show that intS expression is under the negative control of both TorI and IntS.Looking at the recombination protein binding sites identified on attL , it was attL region contains five TorI binding sites organized in two blocks ) with a repression ratio of 5.4 , TorI was no longer able to repress the expression of the fusion, meaning that at least one of these sites was important for repression. We thus measured the effect of each site independently. If the mutation of site I3 had little effect on the repression ratio (4.7), the mutations of sites I4 and I5 led to expression of the fusion independent of the presence of TorI . These two sites are the closest to the −35 sequence and are therefore appropriate candidates for mediating TorI repressor activity. We observed increased basal expression of the fusion  when the I5 site was mutated. This effect is probably due to the change in the nucleotides adjacent to the −35 sequence that results in a promoter-up phenotype.The o of 5.4 . In contP' sites, blue symbols in P' sites the conserved motif TAAA present in all P' sites was changed into its complement ATTT. Interestingly, none of the individual mutations led to derepression of the fusion; indeed, in all cases , the repression ratio ranged from 4.0 to 5.2 (P'1 site's influence was more difficult to study since it overlapped with the −10 sequence (attL-gfp(P'1*)). Additional constructs were made to avoid this effect on the promoter activity; however, any change we made that altered IntS binding also affected promoter activity (attL-gfp(P'1-A and B)), and in the case the latter was not affected (pattL-gfp(P'1-C)), neither was the down regulation of intS. In a control experiment, we mutated the core site, which is the binding site for the catalytic domain of the integrase, and this construct showed an unaltered repression phenotype  and increasing concentrations of IntS (0.02 to 6.7 µM). The attP product was quantified by Q-PCR and the efficiency of the reaction was calculated as the percentage of substrates transformed into products. As the concentration of IntS increased, the efficiency of the reaction increased until a maximum level of ∼80% was achieved for an IntS concentration around 1 µM (One could ask about the “und 1 µM . Howeverin vivo. Strain LCB6005 contains a Km resistance cassette in the tail fiber encoding gene (tfaS) of the KplE1 prophage, thus allowing an in vivo excision assay to be performed without any effect on the site-specific recombination process. This strain was transformed with the pJFi plasmid that contains the torI gene under the control of an IPTG inducible promoter as well as with the pBAD33 vector containing or not the intS gene under the control of an arabinose inducible promoter (pBADintS). Colonies were counted after the different cultures induced with IPTG were plated on LB medium containing ampicillin or kanamycin , whereas KmR colonies originate from cells that have kept the tfaS::kan marker, and thus the KplE1 prophage. As shown before torI from a multicopy plasmid (pJFi) is sufficient to promote excisive recombination. Indeed, in the strain containing the low copy vector alone (pBAD33), the maximal level of excision was achieved in the presence of TorI as revealed by a high ApR/KmR ratio  are adjacent to a tRNA gene. These couples of tRNA-integrase genes  constitute the primary data set used in this study , SIT (Same orientation and I precedes T), OC (Opposite and Convergent orientation) and OD (Opposite and Divergent orientation). We then analyzed the distribution of the InTr copy-number per organism  occur relatively rarely  in the analyzed genomes. Therefore, the high occurrence of STI and OC shapes within the prokaryotes may highlight the functional importance of these shapes in microbial organisms.To address the general relevance of the negative autoregulation of the is study . InTr shr shapes : STI  and selC-intL, 2 OC shapes argU-intD (MG1655) and thrW-intH (EDL933) and 1 OD ptwF-intF (MG1655). Of these integrase genes, 3 are predicted to be autoregulated , and 2 should not exhibit autoregulation (intD and intH). To avoid the influence of the chromosomal copies of MG1655 integrase genes, we transformed both kinds of plasmids (the empty vector and the integrase encoding vector) in the appropriate deletion mutant, and when applicable, we used the MG1655 mutant for the EDL933 equivalent. As indicated in tac promoter, indicating that the leak of the promoter allowed sufficient IntF production to produce a negative effect on the fusion expression. In contrast, the pPintL-gfp fusion was only down-regulated by a factor of 4 in the exponential growth phase, and this occurred in the presence of 0.1 mM of IPTG. Thus, the level of IntL required to lead to a negative effect on the fusion expression is probably higher than that necessary for the IntF integrase. One possible explanation is that integrase genes from E. coli MG1655 interfere with the downregulation of EDL933 genes. This hypothesis is strengthened by the fact that the regulatory ratios measured with the pPintC fusion were higher in an intS background than in a WT MG1655 background (data not shown). Together, these results supported the in silico prediction that STI and OD shape associated integrase genes should be negatively autoregulated. However, this prediction could be associated with promoter and recombination region sequence analysis to ensure that the two overlap.To validate the In temperate phages, site-specific recombination is a highly regulated process; indeed, both the activity and integrase gene expression are controlled. Little is known about integrase gene expression in general, except for the lambda phage integrase for which extensive studies have been available for almost 40 years. Integrase gene expression has been detected in natural environment samples induced with mitomycin C, which promotes productive growth. Therefore, integrase gene expression is used as a marker of (pro)phage presence LP and IP). Under lytic conditions, the int gene is transcribed together with the xis gene from the LP promoter due to the antitermination role of the N protein int gene is expressed from the lysogenic transcript, and the RDF is the first gene on the lytic transcript intS promoter, according to its orientation, overlaps with the attL region, where recombination proteins, including IntS itself, bind. We measured intS transcription during the E. coli exponential growth phase, and as expected, the intS transcript could be detected by RT-QPCR at the different time points of the growth phages, the RDF protein may directly control the appropriate integrase/RDF ratio through negative regulation of the integrase gene. Several lines of evidence support this statement; in particular, we showed in previous papers that the chromosomal intS gene was transcribed at a low level during the exponential growth phase torI gene from a multicopy plasmid was sufficient to promote in vivo excision The second component of TorI RDF . As mentTorI RDF . It is tH) in Staphylococcus aureus participates in maintaining prophages by controlling integrase expression to ensure that more integrase than excisionase is made thus avoiding undesired excision xis transcription is strictly repressed by CI in the lambda prophage during lysogeny, one could imagine that transcriptional leakage is possible; thus, a moderate expression of the int gene could maintain the right balance of Int/Xis during lysogeny.The narrow optimum Int concentration for recombination is probably the consequence of the strict stoechiometry required for the correct assembly of the intasome intS integrase gene, we performed a large-scale study of tRNA inserted prophages on complete prokaryotic genomes. The first step consisted of identifying of the InTr shapes. Current computational methods  detect prophages in genomes by identifying possible essential proteins such as integrases, a region containing proteins similar to those occurring in prophages, or by dinucleotide relative abundance difference (DRAD) a priori, based on the presence of the essential integrase gene. Moreover, our procedure can likely identify complete integrated elements and defective prophage regions encountered within prokaryotic genomes as long as they contain an integrase gene. The obtained data combined with tRNA searches gave 92.6% of STI InTr shapes in which the integrases have only a «Phage integrase» domain, and therefore, this procedure avoids many false positive results. Thus, without any a priori on the data, the most frequently observed STI shapes were with proteins likely to be similar to IntS, indicating a clear tRNA sublocation preference with this integrase subfamily. Several genome analysis studies showed that a vast majority of prophages are inserted in or adjacent to tRNA genes attB sequence is in a tRNA or tmRNA and that some of the prophages are flanked by tRNA genes. A bias was also noted for the selenocysteinyl tRNA (tRNA SelC), tRNA Arg, tRNA Met, and tRNA Ala genes  exhibited a promoter that overlapped with the attL recombination region (STI and OD shapes). As a consequence, and given the results we obtained with the intS promoter, we were able to predict that these genes may undergo negative autoregulation, which was confirmed in vivo for several genes phages is widespread among the tRNA inserted prophages. The fact that the attL region overlaps the integrase promoter has several consequences: (i) the integrase gene is likely down-regulated by itself and the RDF, as long as the recombination protein and the RNA polymerase binding sites overlap sufficiently, (ii) the transcription of the integrase and RDF genes are uncoupled, and (iii) the regulatory switch that permits prophage excision relies on RDF gene expression. Full understanding of prophage excision control will require focusing on the expression of the RDF genes that are uncoupled to the integrase gene transcription.The regulatory switch leading to the controlled expression of the integrase and RDF proteins that allows the excision of the lambda prophage and therefore permits productive growth to resume has long been the paradigm for all temperate phages −1), chloramphenicol (25 µg mL−1), kanamycin (25 µg mL−1) or IPTG (0.1–1 mM) were added.Bacterial strains and plasmids are listed in lacIZ) tfaS::KanR (JW5383), intS::KanR (JW2345), intD::KanR (JW0525) and intF::KanR (JW0275) markers kan gene was then removed from strains LCB6006, LCB6035 and LCB6036 by using the pCP20 plasmid intS, KanS), LCB6037 , LCB6038 . Strains are described in Strains LCB6005, LCB6006, LCB6035 and LCB6036 are derivatives of ENZ1734 , and strain LCB1019 (ΔKplE1) containing pattL-gfp were hybridized with a primer complementary to the positions +40 to +64 relative to the ATG of intS (attL-ter). attL-ter was 32P labeled by using [γ32P]ATP and T4 polynucleotide kinase (Biolabs). A total of 12 µg of ARNs and 4 ng of labeled primer were incubated together with 200 units of Superscript III reverse transcriptase (Invitrogen) for 50 minutes at 50°C, followed by 10 minutes at 70°C to inactivate the enzyme. The sequencing ladder was PCR amplified with the same labeled primer and 5′ primer hybridizing to positions −196 to −173 relative to the ATG of intS (attL-Kpn). The sequencing reaction was performed using the Thermo Sequenase Cycle Sequencing Kit (USB Corporation). Extension and sequencing products were separated onto a 6 M urea 8% acrylamide (19∶1) gel.Total RNAs extracted from strains MC4100 and LCB1024  carrying plasmids pJFi and pBAD33 (control) or pJFi and pBintS were grown in LB medium supplemented by increasing amounts of arabinose as indicated in 600 reached 0.5 units (0.5×109 cells mL−1), IPTG (1 mM) was added and the culture resumed for 2 h at 37°C under agitation. Culture dilutions were prepared and plated onto rich medium containing either ampicillin (pJFi) or kanamycin (tfaS::kan). Numeration of the colonies plated on both antibiotics was performed and the ratio of ampicillin-resistant/kanamycin-resistant (ApR/KnR) colonies was calculated. This value is close to one when the excision rate is low and the tfaS::kan marker is present, and increases when excision efficiency increases and the cells no longer contain the KplE1 prophage. The values represent the average of at least three independent determinations. The IntS relative amount in crude extracts was analyzed after 12% SDS-PAGE with Western blot using a polyclonal IntS antiserum.Strain LCB6005 (KanattL (attL-SpeI/attL-KpnI primers) and attR (attR-XbaI/attR-IHF2 primers) in buffer containing 30 mM Tris-HCl (pH 7.6), 10 mM spermidine, 5 mM EDTA, 1 mg.mL−1 bovine serum albumin, 34 mM KCl and 5% glycerol. IHF (0.25 µM) and TorI (1.6 µM) were added in all samples in the presence of a range of IntS concentrations (0.02 to 8 µM). The reactions were carried out in optimized conditions: 37°C for 1 h. The best efficiency was obtained for IntS concentrations ranging from 0.8 to 1.2 µM, leading to an IHF:IntS:TorI protein ratio of 1∶4∶6.Purified IHF, IntS and TorI were used in all experiments. All reaction mixtures (25 µl) included 32 nM of linear attP formed during in vitro excision assays was quantified by real-time PCR, using a known concentration of PCR amplified attP as a reference standard. The real-time PCR quantifications were performed with an Eppendorf Mastercycler ep realplex instrument and the SYBR Premix Ex Taq (TaKaRa) according to the manufacturer specifications. Serial dilutions of each in vitro reaction were mixed with 1.5 µM of primers and 6 µL of master mix in a 14 µL final volume. The primer pair used to quantify attP was attR-IHF2/attL-SpeI. PCR parameters were as follows: one cycle at 95°C for 2 min followed by 40 cycles at 95°C for 5 s, 55°C for 15 s and 72°C for 10 s. Excision efficiency was calculated as the percentage of the initial substrate (32 nM) transformed into product.The abundance of 600 and fluorescence measurements were performed using the Infinit M200 instrument (Tecan) and the Tecan i-control 1.3 application . The value of blank (0.25X M9 or LB) was withdrawn and normalized fluorescence intensities (emission at 521 nm/A600) were calculated. The values represent the averages of at least four independent measurements. Microscopic analysis was performed using an automated and inverted epifluorescence microscope TE2000-E-PFS  and adequate filters . Images were recorded with a CoolSNAP HQ 2  and a 40x/0.75 DLL “Plan-Apochromat” or a 100x/1.4 DLL objective; image analysis was conducted with MetaMorph 7.5 software (Molecular Devices). For each cell preparation, a total of 25 images were taken randomly on different optical fields, and the average intensity of each cell was calculated (GFP fluorescence was measured on whole cells after an overnight aerobic growth at 37°C in LB medium supplemented by IPTG (0.1–1 mM) for TorI and/or integrase induction . The pJFlculated .ftp:/ftp.ncbi.nih.gov/genomes/Bacteria/) and constitute the primary data source. To identify integrase promoters overlapping the integration site, the analysis was restricted to prophage insertion targeted to tRNA sites. The HMMER-3 package int and E. coli intS as reference seed proteins) in the complete genomes. The presence of one of these functional domains  organisms available in December 2009 were downloaded from the NCBI ftp site /pJF119EH (0), LCB6007/pJFi (+TorI) or ENZ1734 (wt)/pJF119EH (+IntS) strains were transformed with pUA66-gfp  and pattL-gfp . After an overnight aerobic growth in the presence of 1 mM of IPTG for torI induction, the average fluorescence of the bacteria was calculated (see the Expression of the  see the . Populat(0.22 MB TIF)Click here for additional data file.Figure S2InTr insertion biases with respect to the tRNA codon. For each tRNA, the InTr tRNA codon bias was computed as Obs/All where Obs, is the proportion of InTr tRNA codon shapes over the total number of InTr shapes and All is the proportion of the same InTr shape codon over the total number of tRNA codons in the 561 organisms. Threshold ratios for positive and negative biases are set to (0.16 MB TIF)Click here for additional data file.Table S1A detailed description of all tRNA associated integrase genes present in prokaryotic genomes that constitute the primary data set used in this study.(0.49 MB XLS)Click here for additional data file.Table S2Obs/Exp where Obs is the proportion of specific InTr shapes (over the 1273 InTr shapes) and Exp, the proportion of the same tRNA out of the overall tRNA in 561 genomes. If the ratio Obs/Exp is <1, the bias becomes -Exp/Obs. Note that Pseudo, Sup and Undef tRNAs  were removed from our data. %AR, is the proportion of predicted autoregulated InTr shapes. Note that in four cases, the InTr shapes were found within the plasmids eg. 2 in Silici bacter_TM140 , 1 in Ralstonia eutropha JM134  and 1 in Burkholderia phymatum STM 185 .The integrase insertion bias in close proximity of each tRNA was calculated as (0.05 MB DOC)Click here for additional data file.Table S3InTr tRNA codon bias was computed as Obs/All, where Obs is the proportion of InTr tRNA codon shapes over the total number of InTr shapes and All is the proportion of the same InTr shape codon over the total number of tRNA codons in the 561 organisms. Threshold ratios for positive and negative biases are InTr shapes). <10–4, less than 0.0001. Negative and positive biases are marked by (−) and (+), respectively.For each tRNA, the (0.05 MB DOC)Click here for additional data file.In silico analysis of tRNA associated integrase genes in prokaryotic genomes. The supporting text contains a detailed analysis of tRNA associated genes in prokaryotic genomes.(0.39 MB DOCX)Click here for additional data file.


Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands. Riboswitches are RNA-based components that integrate ligand binding and gene regulation to dynamically respond to molecular signals within cells. Natural riboswitches are employed to regulate metabolism and other cellular processes, while synthetic riboswitches have been constructed to expand the sensory and regulatory capabilities exhibited in nature. Characterization studies have revealed that sequence modifications can tune properties of the riboswitch response curve, which links ligand concentration to expression levels. Tunability is critical when matching component properties to the regulatory demands of biological systems; however, the characterization of riboswitch tuning strategies is complicated by the integration of numerous regulatory mechanisms and various processes, such as RNA folding and turnover, that impact riboswitch performance. To develop a generalized framework for examining quantitative aspects of riboswitch tuning, we modeled the kinetics of riboswitch function operating under common regulatory mechanisms. Our results reveal that riboswitch performance is primarily dictated by the competition between reversible and mechanism-specific irreversible rate constants. We demonstrate that practical system restrictions can significantly alter the requirements for riboswitch performance, necessitating a variety of tuning strategies. We developed design principles to guide the construction of synthetic riboswitches and a quantitative framework from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands. The breadth of function exhibited by biological systems provides a foundation from which to develop solutions to global challenges including sustainability, renewable energy production, material synthesis, and medical advancement. Underlying these systems-level functions are regulatory components that evaluate molecular information in the extracellular and intracellular environments and ultimately translate that information into phenotypic responses over varying time scales. The properties of individual regulatory components and genetic networks composed of these components are tuned to control critical functions, including survival in fluctuating environments glmS ribozyme in vitroRiboswitches are RNA-based regulatory components that mediate ligand control of gene expression. Natural riboswitches have been identified in all three kingdoms of life 50) 50) for one type of regulatory mechanism. However, advancing the characterization or design of new riboswitches requires a general quantitative framework that applies broadly to different regulatory mechanisms. Due to the link between RNA secondary structure and function and the relative ease with which RNA molecules can be modeled, riboswitches present an interesting class of regulatory components through which researchers can examine links between physical composition, tuned component response properties, and resulting systems-level behavior.Natural and synthetic riboswitches have been demonstrated to be highly tunable regulatory components. Targeted nucleotide changes in synthetic riboswitches can shift the response curve In this study, we employed mathematical modeling to explore how the dynamics of riboswitch function dictate its performance, where performance is evaluated based on the response curve quantitatively linking ligand concentration and protein levels. To draw general conclusions regarding riboswitch performance, we considered three representative regulatory mechanisms: transcriptional termination, translational repression, and mRNA destabilization. Parameter space for all three mechanisms was surveyed in order to understand the relationship between model parameters and riboswitch performance. Our results show that the competition between reversible and mechanism-specific irreversible rate constants primarily dictates riboswitch performance and response curve tuning properties. Complete dominance of irreversible rate constants renders a riboswitch non-functional, although ligand binding during transcription can rescue riboswitch performance. Our results also demonstrate that placing an upper limit on the ligand concentration alters the observed tuning properties such that a maximum dynamic range exists for intermediate conformational partitioning. Model predictions are supported by published experimental data and new data obtained through the modification of a synthetic riboswitch. We provide a set of design principles for the construction of synthetic riboswitches based on our modeling results. In addition, our results lend insights into the inherent flexibility and potential biological relevance of tuning of natural riboswitches.We started with a detailed molecular description of riboswitch function  that accfA) or B (kfB) to reflect transcriptional folding. Transcription is broken into discrete steps that represent different sequence lengths. Each step determines the extent of conformational switching , the ability to bind and release ligand , and the rate of progression to the next step (kE). For transcriptional termination, riboswitches effectively choose between termination  and extension  after transcription of the terminator stem. To ensure that both conformations make the decision with the same frequency, we set the sum of termination and extension rate constants for each conformation equal to a single parameter kM:PA, kPB) or undergo degradation . A single constant is assigned when the rate constants are equal between conformations . Values for the rate constants can vary widely depending on the organism and regulatory mechanism (We assigned a rate constant to each mechanistic step in the models to yield a detailed relationship between ligand concentration (L) and protein levels (P). In all models, transcriptional initiation produces a partial-length riboswitch in either conformation A  defined as the difference between high and low protein levels, basal protein levels (P(L = 0)), and ligand-saturating protein levels (P(L→∞)). While the dynamic range can be alternatively defined as the ratio of high and low protein levels, we selected the difference definition based on the mathematical symmetry between the equations representing ON and OFF behaviors  or conformation B (kfB). This simplification excludes ligand binding during transcription, which has been demonstrated for natural riboswitches functioning through transcriptional termination Transcription can be considered as a discrete multistep process . The con50, and basal and ligand-saturating levels—for riboswitches functioning through each regulatory mechanism (1 = k1′/k1) and the ligand association constant (K2 = k2/k2′). K1 reflects the relative stability of conformation A and is present in all performance descriptor expressions. K2 reflects the affinity between the aptamer and its cognate ligand and is only present in the expression for EC50.We first derived expressions for the performance descriptors—dynamic range, ECechanism . From th1 and K2 reflect reversible conformational switching and ligand association, the core processes of riboswitch function. These processes are opposed by irreversible events that deplete the abundance of both conformations: mRNA degradation for translational repression and mRNA destabilization, and the riboswitch's decision to terminate or extend for transcriptional termination. The ratio between the rate constants for irreversible and reversible events is prevalent in all expressions for the performance descriptors , transcriptional termination (kM), and mRNA degradation (kdMA and kdMB).For all regulatory mechanisms, Kcriptors . This ra1 and γ2. The first regime occurs when both reversible rate constants dominate , the second begins when either of the reversible rate constants is balanced with the associated irreversible rate constant (either γ1 or γ2 is less than one), and the third begins when the irreversible rate constant kiA dominates over k1 (γ1 converge to zero). Each regime is generally determined by the competition between reversible and irreversible rate constants. We next evaluated the tuning properties of each regime for all regulatory mechanisms.Three operating regimes can be defined based on the ratio of reversible and irreversible rate constants within γ1 = γ2 = 1), a riboswitch molecule can sample both conformations and bind and unbind ligand many times before the irreversible event occurs. We define this regime as ‘thermodynamically-driven’ in accord with previous uses of this term in the study of natural riboswitches For dominating reversible rate constants (γ1), the aptamer association constant (K2), mRNA degradation rate constants , and representative regulatory activities of conformations A (KA) and B (KB):A and KB depend on the selected regulatory mechanism and are provided in In the thermodynamically-driven regime, riboswitch function is captured for the three regulatory mechanisms by a general molecular description . The ass1 stabilizes conformation A, resulting in more riboswitch molecules adopting this conformation. Since conformation A has lower regulatory activity for ON behavior (KA<KB), basal levels decrease. Concomitantly, EC50 increases as higher ligand concentrations are required to offset the decreased abundance of conformation B. Increasing K2 reduces EC50 as expected when aptamer affinity is modulated. However, K2 has no effect on dynamic range and ligand-saturating levels since we assumed sufficient ligand can be added to saturate the response curve. Previous mutational studies of two synthetic riboswitches f) and protein decay (kdP) affect both basal levels and dynamic range by modulating the steady-state mRNA and protein levels.Parameter variation has a unique effect on the response curve for both ON  and OFF 1) improves the dynamic range to an upper limit set by the regulatory activities  and mRNA degradation rate constants  associated with each conformation , less partitioning toward conformation A (lower K1) is required to separate basal and ligand-saturating levels, whereas more partitioning toward conformation A (higher K1) is required when conformation B degrades faster . As a result, thermodynamically-driven riboswitches functioning through mRNA destabilization require more (OFF behavior) or less (ON behavior) partitioning toward conformation A to achieve a larger dynamic range. In contrast, riboswitches functioning through translational repression and transcriptional termination display similar trends in dynamic range as a function of conformational partitioning for ON and OFF behaviors as the degradation rate constants are the same for each conformation.Stabilizing conformation A . Therefore, although stabilizing conformation A (increasing K1) can improve the dynamic range, excessive stabilization can be detrimental due to the increase in EC50. As a result, tuning strategies based on increasing K1 require higher ligand concentrations to access the improved dynamic range. The ratio of the mRNA degradation rate constants in the expression for EC50 offsets the modified dependence of the dynamic range on K1 for riboswitches functioning through mRNA destabilization. Therefore, riboswitches functioning through any of the regulatory mechanisms exhibit the same trade-off between EC50 and dynamic range.EC1 or γ2 is between zero and one). We call this regime the ‘kinetically-driven’ regime in accord with uses of this term in the study of natural riboswitches 1 is coupled to K1 and kfA while γ2 is coupled to K2, both γ1 and γ2 are anticipated to have a significant impact on the response curve and impart several tuning properties distinct to this regime. We initially use riboswitches functioning through transcriptional termination to highlight two of these tuning properties  increases, riboswitch molecules become trapped in a given conformation after transcriptional folding or conformational switching as reflected in γ1. This effect reduces the dynamic range (f), translation (kP), and mRNA (kdM) and protein (kdP) degradation. However, such changes also increase basal levels.First, irreversible rate constants modulate all performance descriptors, often at a cost to riboswitch performance. As the rate constant for terminator stem formation  and ligand release (k2′) . Therefore, the relative values of k1 and k2′ must be known to predict the effect of modulating the irreversible rate constant on EC50.γse (k2′) . IncreasfB/kf = 0), riboswitch molecules must have sufficient time to switch between conformations to maintain activity. Therefore, the dynamic range declines as kM approaches and surpasses k1. In contrast, when transcriptional folding is biased toward conformation B (kfB/kf = 1), riboswitch molecules must switch to conformation A before the irreversible event occurs. In this case, kM must exceed the sum 2k1+k1′ to reduce the dynamic range. As a result, biasing transcriptional folding toward conformation B in the kinetically-driven regime increases the dynamic range.Second, biased transcriptional folding can modulate the relationship between irreversible rate constants and the dynamic range . When trdMA, kdMB) are responsible for both the irreversible event and the steady-state basal and ligand-saturating levels, resulting in complex tuning properties (dMA (ON behavior) or kdMB (OFF behavior) initially improves the dynamic range by separating the steady-state basal and ligand-saturating levels. However, the impact of larger values of kdMA and kdMB depends on riboswitch behavior. For ON behavior, if a riboswitch predominantly folds into conformation A during transcription (kfB/kf = 0), then values of kdMA in excess of k1 diminish the dynamic range as conformation A is degraded before it can switch conformations. However, if a riboswitch predominantly folds into conformation B during transcription (kfB/kf = 1), then the dynamic range plateaus as each molecule either binds ligand or irreversibly switches to conformation A. In contrast, transcriptional folding has a negligible impact on the relationship between the dynamic range and kdMB for OFF behavior, since molecules that adopt conformation A will switch to conformation B before undergoing degradation. Furthermore, as observed for the thermodynamically-driven regime, more partitioning toward conformation A (higher K1) is required to counteract the influence of kdMB on mRNA steady-state levels. Increasing kdMB eventually dominates basal levels when partitioning is maintained, leading to a loss in the dynamic range . In this regime, ligand has a negligible effect on performance. The fast time scales of terminator stem formation and mRNA cleavage may drive riboswitches functioning through these regulatory mechanisms into this regime.Higher irreversible rate constants require increased ligand concentrations to achieve a diminishing change in protein levels. We define the ‘non-functional’ regime as one in which riboswitches are effectively trapped in the conformation formed during transcriptional folding  when γ2 approaches 0. As a potential solution, studies of natural riboswitches have suggested that ligand binding during transcription can preserve EC50fB/kf = 1) prior to polymerase extension (kE) through the gene regulatory element responsible for the irreversible event.Our analysis of the kinetically-driven regime revealed that performance can be preserved by biasing transcriptional folding toward conformation B and ensuring that kM) occurs much faster than ligand release (k2′) and the progression from conformation A to B (k1) to limit consideration to non-functional riboswitches. Under these assumptions, the dynamic range is dependent on the ratio of read-through efficiencies for conformations A (kMA/kM) and B (kMB/kM), the progression from conformation B to A (k1′), and the rate of terminator stem formation (kM). The dynamic range is maximized when conformational progression occurs much faster than terminator stem formation  and the time necessary to transcribe the sequences required for the formation of conformation A (kE) have a significant impact on the value of EC50  without impacting the dynamic range. In contrast, the EC50 of a thermodynamically-driven riboswitch approaches the aptamer dissociation constant as conformation B is stabilized, resulting in a concomitant decrease in the dynamic range  was calculated according to protein levels at L = 0 and L'.In our analyses thus far, we assumed that the maximum ligand concentration always saturates the response curve. However, studies of synthetic riboswitches have demonstrated that the response curve may not be saturated by the accessible upper limit in ligand concentration  due to v50  in the presence of theophylline 1) affects both EC50 and basal levels  A, KB). Additional mutants were examined that are predicted to entirely favor either conformation A (mA) or conformation B (mB) to establish the regulatory activity of either conformation. Riboswitch performance was evaluated by measuring β-Galactosidase levels over a range of theophylline concentrations.We examined two model predictions that could not be supported with available experimental data for cis-acting riboswitches: (1) solely modulating conformational partitioning se curve . We moduce m1–4; . Mutant max = 15,600 MU) (50 approached 0.5 mM (L'/2) for increased stabilization of conformation A  , and EC5mation A . Dynamicmation A . The datm empty; . Our preWhile our modeling efforts focused on translational repression, transcriptional termination, and mRNA destabilization, the predicted tuning trends generally apply to riboswitches utilizing other regulatory mechanisms. For example, riboswitches that function through alternative splicing mechanisms The competition between reversible and irreversible rate constants establishes three operating regimes with distinct tuning properties. Therefore, measuring the reversible and irreversible rate constants is critical when predicting the impact of parameter modulation on the response curve. While well-established methods allow measurement of the rates of mRNA degradation and ligand binding and release, measuring the rates of RNA folding and conformational inter-conversion is currently an active area of research. New technologies are emerging that allow the measurement of kinetic folding rates: site-specific incorporation of aminopurines 1 for a riboswitch sequence 1, k1′) in silico to identify riboswitches with tuned conformational partitioning according to model predictions. Mutations that impact other parameters, such as mutations to the RBS sequence that affect regulatory activity, can also be screened in silico to evaluate the impact on secondary structure and conformational partitioning. However, these algorithms are often inaccurate when predicting RNA folding in vivo, requiring modified approaches An alternative approach to measuring conformational switching relies on parameter predictions with RNA folding algorithms. Most algorithms calculate the free energy of individual conformations and can be used to estimate the value of KSynthetic riboswitches can be divided into two categories based on the intended application: inducible regulators and autonomous regulators. The applicable category depends on the identity and source of the detected ligand and requires distinct approaches to riboswitch design. We provide the following design principles assembled from our modeling results to guide the design of synthetic riboswitches as inducible or autonomous regulatory systems.1) will generally increase the dynamic range, although such strategies require higher ligand concentrations to modulate protein levels. The rates of events separate from core riboswitch processes, such as transcription, translation, and protein decay, can be modulated to increase the dynamic range difference at the expense of increased basal levels.The desired properties of inducible regulatory systems include large dynamic ranges, low basal expression levels, and titratable control over expression levels. Selecting an effective regulatory mechanism is critical since numerous factors reduce the dynamic range, such as conformational partitioning, dominating irreversible rates, upper limits to ligand concentration, and reduced gene regulatory efficiencies from the incorporation of other riboswitch elements 1′) will allow kinetically-driven and non-functional riboswitches to exploit ligand binding during transcription, thereby decreasing the amount of ligand required to induce gene expression.The selected regulatory mechanism will likely dictate the values of the irreversible rate constants and thus the operating regime. In support of this, studies on natural riboswitches have suggested a consistent pairing between translational repression and the thermodynamically-driven regime 1) that achieve a suboptimal maximum dynamic range. An alternative strategy is the design of non-functional riboswitches that bind ligand during transcription, which can respond to ligand at lower concentrations without sacrificing the dynamic range.In many practical applications, system restrictions will limit the accessible range of the response curve . Such liGenes often exist in regulatory networks that dictate cellular phenotype such that complex relationships exist between the expression levels of individual genes and systems-level functions. To effectively regulate these genes with synthetic riboswitches, a variety of tuning strategies must be employed to tune the response curve to operate within system restrictions. The properties of the regulated gene, its integration into a biological network, and the ultimate systems-level functions must be considered. One can envision an application-specific regulatory niche that defines the acceptable ranges of basal and maximum-ligand expression levels for proper system performance . For exaThe engineering of synthetic riboswitches that act as autonomous regulatory systems presents an even greater design challenge. Here, the upper and lower ligand concentrations that the system fluctuates between establish the accessible section of the response curve such that the regulatory niche is further restricted . For exa50 value to meet the performance requirements. Aptamer affinity (K2), conformational partitioning (K1), and the irreversible rates associated with the gene regulatory mechanism can be modulated to increase EC50. However, rational modulation of aptamer affinity is restrictive since most mutations effectively abolish ligand binding, while the method and ease of modulating irreversible rates depend on the regulatory mechanism. Modulating conformational partitioning is an attractive approach since simple base-pairing interactions principally establish each conformation. However, conformational partitioning also impacts basal levels and the dynamic range, such that other parameters may need to be modulated to compensate for any undesired changes. Thus, the effective design of synthetic riboswitches requires knowledge of the relationship between riboswitch sequence and model parameters and may require the coordinated modulation of multiple parameters to meet application-specific performance requirements.Many parameters can potentially be modulated to tune the response curve. However, current practical considerations favor the modulation of a subset of these parameters in the laboratory. As one example, a given riboswitch may require a higher ECThe relationship between riboswitch sequence and model parameters depends in part on the composition framework used in the riboswitch design. A synthetic riboswitch can be designed such that parameters map to individual domains Bacillus subtilis demonstrated that these riboswitches exhibit a diverse range of values for basal expression levels, EC50, and dynamic range Natural riboswitches primarily serve as key autonomous regulators of diverse metabolic processes Understanding the extent to which natural riboswitches are tuned to their regulatory niches will provide insights into riboswitch utilization and the underlying principles of genetic regulatory control. Similar to the tuning of synthetic riboswitches to match their intended regulatory niche, investigating the extent and biological relevance of natural riboswitch tuning requires knowledge of the functional properties of the regulated genes and their contribution to cellular fitness. Furthermore, the typical ligand concentration range encountered in the intracellular environment designates the operational section of the response curve, such that determining this range is critical to advancing our understanding of natural riboswitch tuning within regulatory niches.The composition of a natural riboswitch dictates the relationship between its sequence and model parameters. One way to gain insights into this relationship is investigating sequence deviations between natural riboswitches in the same organism or different organisms that recognize the same ligand and employ the same regulatory mechanism. Using the response curve as a basis of comparison, these mutations may be neutral or shift the response curve in line with modulation of single or multiple parameters. Identifying which parameters are modulated will provide insights into how accessible each parameter is to random point mutations and how evolution effectively tunes the response curve through parameter modulation. Advances in our understanding of the biological utilization of natural riboswitches will enable researchers to better define regulatory niches in a biological system and more effectively design synthetic riboswitches to match these niches. Beyond riboswitch design and implementation, insights into the fine-tuning of natural regulatory components and networks will enable the construction of biological networks that reliably control systems-level functions.50), basal protein levels (P(L = 0)), and maximum-ligand protein levels (P(L→L' or ∞)).All modeling assumptions and methods are fully described in tac1 promoter and the downstream Tn10-β-Galactosidase fusion gene. Mutant sequences were cloned into the unique KpnI and HindIII restriction sites located directly upstream of the riboswitch and approximately 200 nucleotides into the fusion gene coding region. Primers harboring mutant sequences (Escherichia coli strain DH10B. Assembled plasmid constructs were verified by sequencing (Laragen). All molecular biology reagents and enzymes were obtained from New England Biolabs.pSAL8.3 served as the base plasmid for all experimental studies equences  and a 5′E. coli DH10B cells harboring the pSAL8.3 plasmid mutants based on modifications to previously described protocols 2HPO4, 20 mM KCl, 2 mM MgSO4, 0.6 mg/ml CTAB, 0.4 mg/ml sodium deoxycholate, and 5.4 µl/ml β-mercaptoethanol) and mixed at room temperature for approximately 10 min. In a fresh 96-well microplate, 25 µl of the lysed culture was mixed with 150 µl substrate solution . ONPG hydrolysis was stopped with the addition of 75 µl 1 M Na2CO3 when a faint yellow color was observed. Absorbance at 420 nm was then measured on the fluorescence plate reader and protein levels were calculated in Miller Units (MU):β-Galactosidase assays were conducted using Figure S1E. Once the full riboswitch sequence is transcribed, the riboswitch is susceptible to the regulatory mechanism that controls protein (P) production. Green arrows designate mRNA synthesis with biased transcriptional folding, red arrows designate species degradation, and blue arrows designate translation that is proportional to mRNA levels. Under transcriptional termination (B), riboswitches effectively choose between termination to form a truncated product (T) and extension to form the full-length mRNA (M). To ensure both conformations make the decision with the same frequency, we designated a rate constant kM equal to the sum of the rate constants for extension and termination for either conformation (kM = kMA+kTA = kMB+kTB). We assumed that the riboswitch sequence immediately prior to termination or extension cannot undergo degradation.Detailed molecular description of riboswitch function. Molecular descriptions shown for riboswitches functioning through (A) translational repression, (B) transcriptional termination, and (C) mRNA destabilization. All riboswitches can reversibly switch between conformations A and B that display different regulatory activities or different rates of degradation. Conformation B contains a formed aptamer that can reversibly bind ligand (L). Transcription is represented as two discrete steps designated by the subscripts I and II, although the model can be altered to include more or less steps. Riboswitches at each step may switch between conformations or reversibly bind ligand depending on the transcribed sequence. The lag between steps is captured by the rate constant k(3.60 MB TIF)Click here for additional data file.Figure S21 is the conformational partitioning constant (k1′/k1) and K2 is the aptamer association constant (k2/k2′). (A) K1 affects both basal levels and EC50. (B) K2 only affects EC50. (C) Biased conformational partitioning toward B maximizes the dynamic range at the cost of an increased EC50. Parameter values for red response curves are identical to those reported in A = 10−2/s; KB = 10−3/s.Thermodynamically-driven riboswitches exhibiting OFF behavior display similar tuning properties to riboswitches exhibiting ON behavior. K(2.01 MB TIF)Click here for additional data file.Figure S3A and KB affects the maximum dynamic range (η) for ON and OFF behaviors. KA and KB can be independently modulated for riboswitches functioning through translational repression and transcriptional termination. Parameter values for red curve in (A): KA = 10−3/s; KB = 10−2/s; kf = 6*10−12 M/s; kdP = 10−3/s; kdMA = kdMB = 10−3/s. Both dynamic range and its dependence on K1 change when irreversible rates are modulated, showing different trends for (B) ON and (C) OFF behaviors. The degradation rate constants kdMA and kdMB impact steady-state mRNA levels, thereby influencing the dynamic range. Parameter values for red curves in (B) and (C): KA = KB = 1.4*10−2/s; kf = 6*10−12 M/s; kdP = 10−3/s; kdMA = 6*10−3/s and kdMB = 10−3/s for ON behavior; kdMA = 10−3/s and kdMB = 6*10−3/s for OFF behavior.The mechanism-specific regulatory activities dictate differential tuning properties for thermodynamically-driven riboswitches. (A) Modulation of K(1.78 MB TIF)Click here for additional data file.Figure S450  display different dependencies on the dominant mRNA degradation rate constant for ON  and OFF  behaviors. Biased transcriptional folding significantly affects riboswitches displaying ON behavior. Riboswitches displaying OFF behavior show a negligible dependence on transcriptional folding  for the selected parameter values. Parameter values: k1 = 5*10−3; k1′ = 2*10−1; k2 = 106/M*s; k2′ = 10−3/s; kP = 10−3/s; kf = 10−11 M/s; kdP = 10−3/s; kdMA = 10−4/s for OFF behavior; kdMB = 10−4/s for ON behavior.Distinction between tuning properties for ON and OFF behaviors for riboswitches functioning through mRNA destabilization. Dynamic range  and EC(1.78 MB TIF)Click here for additional data file.Figure S5D, A) and ratio  when subjected to a ligand concentration upper limit (L'). In the absence of a ligand concentration upper limit, the dynamic range converges on a maximum (ηmax). The optimum value of the conformational partitioning constant (K1) is higher for the dynamic range ratio as the ratio favors lower basal levels. Increasing the aptamer association constant (K2) or L' improve the suboptimal dynamic range maximum. Parameter values for the red curves are identical to those reported in 1 value for the dynamic range ratio as compared to the dynamic range difference. β-Galactosidase levels are reported in Miller Units (MU). Data represent independent measurements of triplicate samples, where the standard error was below 5% of each mean value.The dynamic range difference and ratio exhibit qualitatively similar tuning properties. Model predictions for the dynamic range difference (η(2.25 MB TIF)Click here for additional data file.Table S15′-AATAGGTACC-[Seq]-TGCGAACTC-3′ and 5′-CGACGGGATCGATCCCCCC-3′, where [Seq] is the designated sequence in the table.Sequence variants of pSAL8.3 and associated β-Galactosidase levels reported in Miller Units (MU). Database # is included for plasmid requests. The start codon is shown in green and point mutations are shown in blue. To generate each variant, the 5′ end of the β-Galactosidase coding region was amplified and cloned into KpnI/HindIII of pSAL8.3 using primers (0.09 MB PDF)Click here for additional data file.Text S1Alternative definitions for dynamic range.(0.04 MB DOC)Click here for additional data file.Text S2Derivation of mathematical models.(0.22 MB DOC)Click here for additional data file.


Tas3-derived ta-siRNAs define the adaxial side of the leaf by restricting the expression domain of miRNA miR166, which in turn demarcates the abaxial side of leaves by restricting the expression of adaxial determinants. To investigate the regulatory mechanisms that allow for the precise spatiotemporal accumulation of these polarizing small RNAs, we used laser-microdissection coupled to RT-PCR to determine the expression profiles of their precursor transcripts within the maize shoot apex. Our data reveal that the pattern of mature miR166 accumulation results, in part, from intricate transcriptional regulation of its precursor loci and that only a subset of mir166 family members contribute to the establishment of leaf polarity. We show that miR390, an upstream determinant in leaf polarity whose activity triggers tas3 ta-siRNA biogenesis, accumulates adaxially in leaves. The polar expression of miR390 is established and maintained independent of the ta-siRNA pathway. The comparison of small RNA localization data with the expression profiles of precursor transcripts suggests that miR166 and miR390 accumulation is also regulated at the level of biogenesis and/or stability. Furthermore, mir390 precursors accumulate exclusively within the epidermal layer of the incipient leaf, whereas mature miR390 accumulates in sub-epidermal layers as well. Regulation of miR390 biogenesis, stability, or even discrete trafficking of miR390 from the epidermis to underlying cell layers provide possible mechanisms that define the extent of miR390 accumulation within the incipient leaf, which patterns this small field of cells into adaxial and abaxial domains via the production of tas3-derived ta-siRNAs.MicroRNAs (miRNAs) and  meristem, at the plant's growing tip. Each newly formed leaf becomes polarized and develops distinct adaxial (top) and abaxial (bottom) sides. The establishment of adaxial–abaxial polarity requires a complex genetic network, including miRNAs and trans-acting siRNAs. We used a focused laser to microdissect regions of the shoot apical meristem and developing leaves of maize to analyze the expression profiles of the small RNA precursor molecules. By comparing these expression profiles to the accumulation patterns of the mature small RNAs, we show that precursor genes are subject to tissue-specific regulation and exhibit diverse expression patterns during leaf development. Our findings suggest that mechanisms exist to regulate the biogenesis, stability, and possibly even the intercellular movement of small RNAs. Such regulation should be considered when designing artificial miRNAs and has implications for the roles miRNAs play during plant and animal development.Small RNAs regulate many key developmental processes. Consistent with a prominent role in development, miRNAs exhibit complex and distinctive expression patterns. In this study, we identify regulatory mechanisms that allow for the precise spatial accumulation of developmentally important small RNAs in plants. Plants generate new leaves throughout their lifetime. These arise on the flank of a specialized stem cell niche, termed  Loss-of-function mutations in leafbladeless1 (lbl1) that disrupt ta-siRNA biogenesis give rise to an abaxialized leaf phenotype and loss of hd-zipIII expression, demonstrating that the ta-siRNA pathway is necessary for specifying adaxial fate in maize tas3-derived ta-siRNA species conserved between maize and Arabidopsis, accumulate on the adaxial side of incipient and developing leaf primordia, where they act to spatially restrict the expression domains of abaxial determinants. This includes, although indirectly, miR166, which is expressed ectopically in lbl1 leaf primordia and accumulates in both the adaxial and abaxial domains tas3-derived ta-siRNAs and miR166, which divide the small field of cells of the incipient primordium into adaxial and abaxial domains.MiRNA miR166 promotes abaxial/ventral fate in developing primordia by restricting the expression of class III homeodomain leucine zipper (HD-ZIPIII) transcription factors, which are necessary and sufficient to specify adaxial/dorsal fate tas) transcripts enter into an RNA-DEPENDENT RNA POLYMERASE6 (RDR6) and LEAFBLADELESS1/SUPRESSOR OF GENE SILENCING3 (LBL1/SGS3)-dependent pathway and are processed by DICER-LIKE4 (DCL4) into phased, 21 nucleotide ta-siRNAs TAS3 precursor family are processed using a subspecialized pathway dependent on miR390 activity. MiR390 forms a specialized RISC with AGO7/ZIP, the activity of which is required to recognize the 5′ and cleave the 3′ miR390 target sites of TAS3A precursor transcripts in Arabidopsis to produce TAS3-derived ta-siRNAs The functional importance of tasiR-ARF and miR166 activity in specifying the adaxial and abaxial domains of the leaf suggests mechanisms exist to maintain the accuracy of their spatiotemporal localization. However, even though our knowledge regarding small RNA biogenesis and function has increased significantly, and the detailed expression patterns of several mature miRNAs have been described mir) families, in which multiple mir genes produce identical mature miRNA species Post-transcriptional mechanisms that operate at the level of biogenesis could modulate the spatiotemporal localization of small RNAs, perhaps through the limited availability of necessary biogenesis factors, as has been proposed for animals tas3 ta-siRNA pathway in the maize SAM. The comparison of mature small RNA in situ localization data with the expression profiles of precursor transcripts, as determined using laser-microdissected domains, indicates that the accumulation pattern of mature miR166 results from the co-operative activities of multiple mir gene family members and is further regulated at the level of biogenesis and/or stability. Furthermore, we show that the polarized expression of miR390, an upstream component in leaf polarity, is established and maintained independently of the ta-siRNA pathway. The discrete adaxial accumulation of miR390 in the incipient leaf is regulated at the post-transcriptional level and might possibly result from limited mobility of mature miR390 over the span of a few cells.Here, we employ laser-microdissection (LM) to investigate the complex regulatory mechanisms that allow for the precise spatial accumulation of miR166 and small RNAs in the mir166 loci, mir166a through mir166i, which have the potential to produce identical mature miR166 species (miRbase release 10.1). To determine which family members contribute to the spatiotemporal expression pattern of mature miR166 in vegetative tissues, we investigated mir166 gene expression in hand-dissected apices containing the SAM and four to five leaf primordia. Precursor transcripts of all nine mir166 genes accumulate in vegetative apices  is expressed in all tissue samples tested rough sheath1 (rs1) transcripts are limited to those domains that include the subtending regions of leaves kanadi2 (kan2), the expression of kan1 demarks cells in the developing young leaf primordia As an initial analysis, we investigated the expression of a subset of ize apex . Cells wize apex . The expmir166 family members are expressed in every tissue sample analyzed, each mir166 gene tested exhibits a unique expression profile . To identify which tas3 family members contribute to the localized accumulation of tasiR-ARFs in the incipient leaf, we analyzed the expression of tas3a-d precursors in the SAM. Unlike the mir166 genes, all four tas3 family members are expressed within and below the incipient leaf and thus likely contribute redundantly to the establishment of leaf polarity . The two mir390 precursors, referred to hereafter as mir390a and mir390b  in the L1 layer and knotted1 (kn1) in the L2 layer  and extended using maize EST and genome sequence databases (http://magi.plantgenomics.iastate.edu and http://www.maizesequence.org). The mir390a precursor has been described previously mir390b were assembled using the above-mentioned databases, and the BAC accession number for mir390b is AC197125. The maize genome contains at least five dcl genes; two most similar to Arabidopsis DCL3 and one each most similar to DCL1, DCL2, and DCL4 (http://www.chromdb.org). The BAC accession number for dcl1 is AC191256. The maize SERRATE homologs have been described previously mir390a and mir390b precursors were predicted using RNAfold.Sequences corresponding to the Total RNA was extracted from vegetative apices including the SAM and four to five leaf primordia and from immature ears (0.5–1 cm) using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. DNaseI-treated RNA was converted into first-strand cDNA and amplified by PCR according to standard protocols. Primer sequences used in this study are listed in lbl1-rgd1 seedlings were pretreated and hybridized as previously described rld2 probe, comprising nucleotides 625–1677 of the coding sequence, was used at a concentration of 0.5 ng/µL/kb as described Tissue sections prepared from the shoot apices of two-week-old wild-type or Shoot apices from two-week old wild-type seedlings were dissected and immediately fixed in pure, ice-cold acetone. Acetone was gradually replaced with xylene and subsequently paraplast. Cells of interest were captured from 10 µm tissue sections using a PALM MicroBeam system. Detailed embedding and LM protocols have been described previously Figure S1mir166 family members in maize vegetative apices and female inflorescence tissues. (A) RT-PCR amplification of mir166a - i precursor transcripts on total RNA isolated from hand-dissected vegetative apices and female inflorescences (∼0.5–1 cm) shows that all nine mir166 genes are expressed in both tissues. The loading control tubulin6 (tub6) and -RT controls are shown. (B) Cartoon representing a mir166 precursor transcript with the miRNA* (blue) and mature miRNA (red) shown. Gene specific primers (arrows) were designed downstream of the stem-loop as indicated.Expression analyses of (0.15 MB JPG)Click here for additional data file.Figure S2tas3 genes are expressed broadly throughout the maize shoot apical meristem. Cells were captured by laser-microdissection from the tip of the SAM (5), the incipient leaf (6) and below the incipient leaf (7) as depicted in tas3a - tas3d precursors are expressed broadly throughout the SAM, and only tas3a does not appear to be expressed in the tip of the SAM.(0.07 MB JPG)Click here for additional data file.Figure S3mir390a (A) and mir390b (B) precursor stem-loops. Blue lines mark the mature miR390 sequence.Diagrams showing the sequences and secondary structure of the (0.17 MB JPG)Click here for additional data file.Figure S4Arabidopsis (At), rice (Os) and maize (Zm) DICER-LIKE proteins. Four sub-groups comprising DCL1, DCL2, DCL3 and DCL4 homologs are distinguished within the phylogenetic tree. The phylogram was generated as a consensus of 1000 bootstrap replicates by the neighbor joining method using the MEGA2 software. The scale bar indicates the relative frequency of changes along the branches. At least five dcl genes have been identified in maize; two most similar to Arabidopsis DCL3 and one each most similar to DCL1, DCL2, and DCL4. Protein sequences were retrieved from the chromatin database (http://www.chromdb.org). (B) ZmDCL1 (bold in A) contains conserved domains characteristic of the DCL proteins belonging to the Arabidopsis DCL1 sub-group. Protein domains were predicted using Pfam (http://pfam.wustl.edu/).Phylogenetic analysis of DICER-LIKE (DCL) proteins from maize, rice and Arabidopsis identifies a single conserved maize DCL1 protein. (A) Un-rooted phylogram of (0.28 MB JPG)Click here for additional data file.Table S1Sequences of primers used in this study.(0.05 MB DOC)Click here for additional data file.