Single-molecule tracking of the transcription cycle by sub-second RNA detection
Transcription is the first , and frequently the most regulated step in the flow of genetic information from DNA to protein . Transcription is a dynamic , multi-step process in which RNA polymerase ( RNAP ) ( i ) binds to the promoter to form the closed complex ( RPc ) ; ( ii ) melts the promoter to form the open complex ( RPo ) ; ( iii ) performs several abortive cycles of synthesis and release of short 2–12 nt RNA products as the initial transcribing complex ( RPitc ) ; ( iv ) escapes the promoter; ( v ) undergoes some promoter-proximal pausing; ( vi ) forms an elongating complex ( RDe ) whose processivity can either be interrupted by more pauses or stimulated by trailing RNAPs and elongation factors; and , finally ( vii ) terminates at the end of the transcription unit ( reviewed in DeHaseth et al . , 1998; Murakami and Darst , 2003; Cheung and Cramer , 2012 ) . Due to the low copy number of genes in a cell ( usually one in prokaryotes and two in eukaryotes ) , molecular fluctuations at any of the above steps may cause large cell-to-cell variability in the amount of the final RNA transcript produced in populations of otherwise genetically identical cells grown under identical conditions , and thus can affect gene expression , and cell physiology ( Ogawa , 1993; Raj and Van Oudenaarden , 2009; Yamanaka , 2009; Gupta et al . , 2011; Lionnet and Singer , 2012 ) . Therefore , understanding how molecular fluctuations at different steps of the transcription cycle alter transcriptional outcomes is required to dissect the mechanism of gene regulation . Single-molecule techniques are ideally suited to directly monitor molecular fluctuations in multi-step reactions in real-time , without averaging out their inherent stochasticity ( Weiss , 1999 ) , and have provided important insights into the dynamics of transcription , unattainable by conventional ensemble methods ( Bai et al . , 2006 ) . For instance , single-molecule assays based on optical nanomanipulation have revealed pausing and backtracking of RDe ( Neuman et al . , 2003; Shaevitz et al . , 2003; Galburt et al . , 2007 ) and measured the force and the torque generated by RDe ( Wang et al . , 1998; Ma et al . , 2013 ) . Methods based on magnetic nanomanipulation and single-molecule fluorescence resonance energy transfer have probed conformational changes in DNA and RNAP within RPo , and RPitc ( Kapanidis et al . , 2006; Revyakin et al . , 2006; Tang et al . , 2009; Chakraborty et al . , 2012; Robb et al . , 2013 ) . Finally , single-molecule localization studies have probed the dynamics of the initial promoter search by RNAP ( Wang et al . , 2012; Friedman et al . , 2013 ) . However , most current single-molecule methods focus on only one step of transcription , and are not well suited to relate protein-DNA complex assembly and dynamics during multiple stages of the transcription cycle to RNA production . In addition , most methods do not measure RNA production directly , but rather infer it from changes in DNA conformation or movement of RNAP along the DNA . Most recently , single-molecule tracking of key protein-DNA interactions coupled with detection of the RNA production has been demonstrated in the bacterial ( Friedman and Gelles , 2012 ) and human transcription systems ( Revyakin et al . , 2012 ) . The former study achieved time resolution for RNA detection on the order of ∼10 s , and thus provided a dynamic , quantitative view of the full transcription cycle of bacterial RNAP . However , time scales of many events in transcription are on the order of ∼1 s , particularly under physiological conditions ( for instance , the residence time of transcription factors on DNA ( reviewed in Hager et al . , 2009 ) , the rate of initiation and promoter clearance by RNAPs ( Revyakin et al . , 2006; Tang et al . , 2009 ) , and the expected time delay between cooperatively elongating RNAPs molecules ( Epshtein and Nudler , 2003 ) ) . Thus , a real-time method for nascent transcript detection at ∼1 s time scales would significantly enhance our ability to dissect the dynamics of the transcription process , and to correlate stochastic fluctuations at different steps with transcriptional outcomes . Currently , the most sensitive and specific methods for detecting RNA transcripts continue to rely on complementary nucleic acid hybridization . However , oligonucleotide probes typically hybridize several orders of magnitude slower than diffusion under physiological conditions ( effective rate constant kon less than 105 M−1 s−1 , [Chan et al . , 1995 and references therein] ) and , as a result , do not permit real-time nascent RNA detection with common single-molecule setups , such as total internal reflection fluorescence ( TIRF ) microscopy . Here we present a fast fluorescence in situ hybridization method ( fastFISH ) to detect synthesis of nascent RNA transcripts at sub-second time resolution , at the single-molecule level . The method takes advantage of our finding that single-stranded nucleic acid probes with sequences comprised of just three of the four bases ( A , U and C for RNA probes , and A , T , and G for the complementary DNA targets ) are intrinsically unstructured and , as a result , hybridize at exceptionally fast rates ( ∼107 M−1s−1 ) without compromising sequence specificity . As a proof of concept , we applied fastFISH to probe the production of nascent RNA transcripts by the speedy bacteriophage T7 RNA Polymerase ( T7 RNAP ) in vitro . Furthermore , by using fastFISH in combination with fluorescently labeled RNAP , we dissected the full T7 RNAP transcription cycle ( promoter binding , promoter escape , elongation , and termination ) . FastFISH can be used to study transcription by multi-subunit prokaryotic and eukaryotic RNA polymerases at the level of stochastic molecular interactions . The rules for generating fastFISH probe-target pairs can also be used for gene silencing , gene profiling and bottom-up assembly of nucleic acid nanostructures ( Rothemund , 2006 ) .
To achieve real-time nascent RNA detection , we set out to find a general rule for designing RNA-probe pairs that hybridize at the fastest possible rates . Hybridization of two single-stranded nucleic acid fragments requires unfolding of the fragments into unstructured coils , which then anneal to form an intermolecular base paired helix ( Lima et al . , 1992 and references therein ) . In support of this notion , nucleic acid probes with less stable secondary structures show faster hybridization rates to complementary nucleic acid targets ( Lima et al . , 1992; Kushon et al . , 2001; Wang and Drlica , 2004; Gao et al . , 2006; Yilmaz et al . , 2006 ) . Likewise , decreasing the length of hairpins in conventional molecular beacons increases their hybridization rates ( Tsourkas et al . , 2003 ) . Thus , we reasoned that intrinsically unstructured nucleic acid oligonucleotide pairs of optimal lengths should have the fastest hybridization kinetics under physiological conditions without compromising specificity . To systematically examine the propensity of RNA sequences to form base-paired secondary structures , we used the nucleic acid structure prediction tool Mfold ( Zuker , 2003 ) to calculate the free energy of self-folding , ΔG37°C , of randomly selected short RNA sequences ( N = 338 , 417 ) . We chose RNA sequence with length of 19 nt and GC content between 0 . 4 and 0 . 6 as representative of a typical oligonucleotide primer . We found that ΔG37°C values were mostly negative and widely distributed ( −1 . 7 ± 1 . 7 kCal mol−1 ) , indicating that an average random 19-mer RNA sequence is mostly structured ( Figure 1A ) . Next , we closely examined a subset of 19-mer RNA sequences that had positive ΔG37°C ( >+2 kCal mol−1 , N = 2 , 768 , <1% of the total pool of random sequences ) , and found that these mostly unstructured sequences were composed predominantly of only three bases A , U , and C ( ∼84% had only 2 G residues or less , significantly less than the 4 . 75 G residues expected on average , Figure 1—figure supplement 1 ) . The bias towards the lower G-content in the unstructured sequences was not surprising , because guanine is the most potent in base-paring interactions: it forms a triple hydrogen bond with cytosine and a wobble pair with uracil . We then calculated ΔG37°C for randomly picked 19-mers composed of only A , U , and C ( N = 99 , 777 , GC content between 0 . 4 and 0 . 6 , Figure 1A ) , and found that these AUC-sequences had mostly positive ΔG37°C , with a much narrower distribution ( +2 . 5 ± 0 . 6 kCal mol−1 , Figure 1A ) . Analysis of other three-base-derived RNA sequences ( AUG , CAG , CUG ) indicated that AUC-sequences were unique in their largely positive ΔG37°C ( Figure 1A ) . Calculation of ΔG37°C for random DNA 19-mers ( that could be used as complementary probes for RNA targets ) indicated that ATG-based and ATC-based DNA 19-mers were also significantly less structured than their four-base counterparts ( Figure 1A ) . Therefore , we hypothesized that the use of the AUC alphabet for RNA targets , and ATG alphabet for DNA probes should allow the fastest annealing reactions under physiological temperature of 37°C . 10 . 7554/eLife . 01775 . 003Figure 1 . Design of fastFISH probe-target pairs . ( A ) Probability distribution of Mfold-calculated free energies of self-folding of randomly selected , single-stranded 19-mer RNA ( left ) and DNA ( right ) oligonucleotides , composed of three or four bases . Results of analysis of three independent sets are shown as ‘+’ , ‘x’ , and ‘○’ . About 100 , 000 three-letter sequences , and about 300 , 000 four-letter sequences were analyzed in each set . ( B ) Lempel–Ziv complexity analysis of three-letter 19-mer oligonucleotides ( one set of ∼100 , 000 AUC sequences ) , four-letter 19-mer oligonucleotides ( one set of ∼300 , 000 AUGC sequences ) , and all tiling 19-mers from the exome of the human chromosome 22 . ( C ) Single-molecule measurements of hybridization rates of fastFISH probe-target pairs , and the effect of G-residues in the targets on the rates . Left: schematic of experiment . Cy3-labeled 90-base RNA oligonucleotides containing a single target sequence were immobilized on a glass surface through a biotin moiety at the 3′ end . Atto633-labeled DNA probes were injected into the imaging flow cell , and their hybridization was detected using TIRF/CoSMoS to obtain the probe arrival time Twait . Right: table of RNA target sequences , Mfold-calculated free energies of self-folding of RNA targets ( ΔGtarget ) , DNA probes ( ΔGprobe ) , combined energies of targets and probes , and on-rates calculated based on probe Twait and concentrations . ( D ) Self-quenching approach to reduce fluorescence background from unbound DNA probes in TIRF imaging of probe-target hybridization . Left: schematic of experiment . A quencher ( e . g . , Iowa Black FQ ) is placed on one end of a DNA probe , and a fluorophore ( e . g . , Cy3 ) is placed on the opposite end of the DNA probe . The short persistence length of single-stranded DNA ( lo ∼0 . 8 nm , Smith et al . , 1996; Dessinges et al . , 2002 ) enables quenching of Cy3 . Upon hybridization to the target , the distance between Cy3 and Iowa Black FQ increases due to the larger lo ∼50 nm of the DNA-RNA duplex , leading to an increase of Cy3 fluorescence . Middle: representative TIRF image and a corresponding three-dimensional plot of target-hybridized F1 probes acquired in the presence of unbound , self-quenched F1 probe at 100 nM . Right: same set of molecules imaged in the presence of unbound , unquenched F1 probe at 100 nM . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 00310 . 7554/eLife . 01775 . 004Figure 1—figure supplement 1 . Sample sequences of the unstructured 19-mer RNA oligos . Representative sequences of randomly picked 19-mer 4-base RNA oligonucleotides with free energy of self-hybridization ΔG37°C of 2 kCal mol-1 or higher ( 2 , 768 sequences total , selected from a pool of 339 , 612 randomly picked sequences ) are shown . First column: RNA sequence; second column: Mfold-calculated ΔG37°C; third column: number of G residues in the sequence . The histogram is the probability distribution of the number of G residues per sequence . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 00410 . 7554/eLife . 01775 . 005Figure 1—figure supplement 2 . Single-molecule measurements of fastFISH probe-target hybridization rates using TIRF/CoSMoS . ( A ) Representative real-time video montage of binding of an F1 probe molecule to a location in which an F1 target molecule has been previously registered ( region of interest 5 × 5 pixels ) . The video frame in which binding of F1 probe occurred is shown with an arrow . ( B ) Fluorescence time trace corresponding to the montage in Panel A . ( C ) Probability distribution of F1 probe binding times fit to a single exponential function to determine the mean binding time Twait . ( D ) Summary of single-molecule measurements of probe-target hybridization rates for probes F1 and F2 , and F2 target variants containing 1 , 2 , 3 , and 4 G residues , at the probe concentrations shown . Mean binding time Twait was estimated by fitting the probability distributions to a single exponential function . Goodness of fitting is evident from the consistency among the values of Twait , <Twait> , and the standard deviation of dwell times , σ . The last column shows the calculated concentrations of respective probes required to achieve mean Twait of 1 s in a real-time nascent RNA detection experiment . Concentrations of self-quenched probes above 1000 nM , and unquenched probes above 100 nM , are generally incompatible with single-molecule imaging . Fit error for Twait is given for 95% confidence intervals , and error of the mean was calculated as σ/√ ( Nmolecules ) . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 00510 . 7554/eLife . 01775 . 006Figure 1—figure supplement 3 . Reduction of fluorescence background of free fastFISH probes by self-quenching: additional representative images . ( A ) Top: self-quenched F1 probe ( Cy3 dye at the 5′ end and Iowa Black FQ quencher at the 3′ end ) . Middle: representative images of signals from self-quenched F1 probe molecules hybridized to surface-immobilized RNA targets , in the presence of free Cy3-F1-FQ probe at 100 nM and 1 μM concentrations . Bottom: same images shown as three-dimensional plots . ( B ) Same set of molecules as in ( A ) , but in the presence of free Cy3-F1 containing no quencher at 10 nM and 100 nM concentrations . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 006 To ensure that the use of the three-base alphabet did not compromise the specificity of probe-target hybridization , we calculated the textual complexity of randomly picked three-letter 19-mers using the algorithm of Lempel and Ziv ( Ziv and Lempel , 1976; Kaspar and Schuster , 1987; Orlov and Potapov , 2004 ) . This algorithm , commonly used in lossless data compression programs , calculates the minimal number of operations required to reconstruct a sequence of symbols by copying and inserting segments of an existing sub-sequence . Thus , nucleic acid sequences that contain repetitive elements would have a lower LZ complexity ( and would be less specific in hybridization ) ( Wright and Church , 2002 ) . We found that three-letter 19-mer sequences had complexity indices of 8 . 1 ± 0 . 8 ( N = 99 , 777 ) , while four-letter 19-mers had complexity indices of 9 . 3 ± 0 . 8 ( N = 338 , 417 , Figure 1B ) . As a comparative reference , we calculated complexity indices for tiling 19-mers in all exons of human chromosome 22 to be 8 . 9 ± 1 . 0 ( Figure 1B ) . Importantly , a significant fraction of three-letter 19-mers ( ∼31% ) had complexity indices of 9 and higher , which matched or exceeded the average complexity of human exons . These calculations indicate that a significant fraction of the random probe sequences composed of only three bases nevertheless retain sequence complexity and specificity that match their physiological , four-base derived counterparts . We applied the AUC rule and the complexity filter to generate two candidate probe-target pairs ( referred to as F1 and F2 ) . The calculated ΔG37°C for the F1 and F2 pairs were +1 . 5 and +2 . 2 kCal mol−1 , respectively , for the AUC-based RNA targets , and +1 . 0 and +0 . 9 kcal mol−1 for their ATG-based complementary DNA probes ( Figure 1C ) , suggesting that the pairs are mostly unstructured and likely to be fast-hybridizing . Indeed , the F1 and F2 probes annealed to their surface-immobilized RNA targets at exceptionally fast rates—6 × 106 M−1s−1 and 4 × 106 M−1s−1 , respectively , as measured by TIRF-based Colocalization Single-Molecule Spectroscopy ( CoSMoS , Friedman et al . , 2006 ) ( Figure 1C , Figure 1—figure supplement 2 ) . These on-rates were at least 100-fold faster than typical four-base nucleic acid probes of similar lengths reported in literature ( Lima et al . , 1992; Kushon et al . , 2001; Wang and Drlica , 2004; Friedman et al . , 2006; Gao et al . , 2006; Yilmaz et al . , 2006 ) . Consistent with the AUC rule , introducing back one or more G residues into the F2 RNA target sequence decreased the rate of its hybridization to the complementary DNA probe ( 10-fold reduction for one G residue and 300-fold reduction for four G residues ) , which correlated with the progressively lower free energies of self-folding ( Figure 1C , Figure 1—figure supplement 2D ) . We conclude that the target sequences designed using the AUC rule , combined with the complexity filter , achieved our goal of generating superior hybridization kinetics for fast transcript detection . Although the F1 and F2 probes were exceptionally fast , detection of RNA on the sub-second time scales would require the use of fluorescent probe concentrations above 100 nM ( Figure 1—figure supplement 2D ) . Such concentrations are generally incompatible with common single-molecule detection setups such as TIRF microscopy , due to high fluorescence background from the freely diffusing , unbound probe molecules . We overcame this problem by attaching a quencher to the single-stranded probe at the end opposite of the fluorophore ( Marras et al . , 2002 ) . This self-quenching strategy enabled the use of free probes at concentrations up to 1 μM ( Figure 1D , Figure 1—figure supplement 3 ) . We believe that , in the absence of the secondary structure , the self-quenching effect was likely mediated by random polymer motion and/or contact quenching ( Johansson et al . , 2002; Marras et al . , 2002 ) . We refer to our method for fast nucleic acid detection using unstructured , sequence specific , self-quenched fluorescent probes as ‘fastFISH’ . To demonstrate that fastFISH can detect nascent transcripts in real time at single-molecule resolution , we used the bacteriophage T7 RNAP . This single-subunit RNAP is an excellent test case for fastFISH: at physiological temperature ( 37°C ) it initiates transcripts at an effective rate of at least 1 s−1 ( Martin and Coleman , 1987 ) , and elongates transcripts at ∼240 nt s−1 ( Golomb and Chamberlin , 1974; Bonner et al . , 1994 ) . As a model template , we used a fluorescently labeled linear DNA fragment containing the consensus promoter for T7 RNAP ( Milligan et al . , 1987 ) and the F1 target sequence ( positioned between +28 and +46 from the transcription start site , +1 ) , and ending at +295 . We surface-immobilized the Cy3-labeled DNA via a biotin moiety attached to the upstream end of the template ( position −75 ) ( Figure 2A ) . In this configuration , RNAP molecules were expected to initiate transcription at the promoter , elongate the nascent RNA in the direction away from the surface , and run off the free , untethered template end at +295 , together with their nascent RNA products . 10 . 7554/eLife . 01775 . 007Figure 2 . Real-time single-molecule detection of transcription by T7 RNAP using fastFISH . ( A ) Schematic of experiment . DNA templates containing a single consensus promoter for T7 RNAP ( +1 ) , or a single null mutant promoter ( cross ) , were immobilized on a surface , with the promoter directing transcription towards the free end ( +295 ) . The templates contained the F1 fastFISH target sequence downstream from the promoter ( from +28 to +46 ) which was expected to become available for hybridization in the nascent RNA after the RNAP active site reaches position +60 . ( B ) Co-localization analysis of F1 probe-DNA interactions in a representative experiment . Left: wild type promoter . Right: mutant promoter . ( C ) and ( D ) Same as panels ( A ) and ( B ) , but for the F2 target and probe . The templates contained the F2 fastFISH target sequence ( from +181 to +199 ) which was expected to become available for hybridization in the nascent RNA after the RNAP active site reaches position +213 . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 007 We supplied unlabeled RNAP , NTPs and the fluorescent , self-quenched F1 probe to the imaging flow-cell , and monitored the interactions of the F1 probe with the DNA loci by TIRF/CoSMoS ( Friedman et al . , 2006; Revyakin et al . , 2012 ) . We reasoned that the F1 target sequence in the nascent RNA would become available for hybridization once the active site of elongating RNAP ( RDe ) reaches position +60 ( taking into account the ∼14 bases of nascent RNA protected by RNAP [Huang and Sousa , 2000] ) . The RDe complex would then remain on the DNA until it runs off at +295 . At the expected average RNAP elongation rate of 240 nt s−1 , the F1 probe would have a brief ∼1 s window of opportunity to ‘catch’ the nascent transcript at the DNA molecule of origin . Probe hybridization to the RNA product would then be observed as a fluorescent spot co-localizing with the DNA locus . Figure 2B shows the co-localization analysis of probe-DNA interactions in a typical single-molecule fastFISH experiment . This analysis counts all DNA molecules that co-localized with a probe ‘spot’ for more than five cumulative frames ( at 0 . 4 s/frame ) during the incubation ( ∼15 min ) , and plots the Δx , Δy displacements between the probe and DNA molecules as a two-dimensional histogram ( Revyakin et al . , 2012 ) . Specific probe-DNA interactions were observed , as indicated by a prominent peak at position ( 0 , 0 ) of the co-localization histogram . In a typical experiment , 10–30% of DNA templates in a field of view co-localized with a probe . This apparent incomplete template utilization was not due to inefficient probe hybridization ( see Figure 4 and ‘Discussion’ ) , but , instead , was likely limited by the accessibility of the DNA template due to surface interference . No probe-DNA interactions were observed in a control experiment with a DNA template containing a null mutant promoter ( Raskin et al . , 1993 ) , indicating that the co-localization was due to promoter-specific transcription . We also performed real-time single-molecule transcription experiments using the other unstructured probe , F2 , and obtained nearly identical DNA-probe co-localization results ( Figure 2C–D ) . Taken together , these findings suggest that fastFISH can detect production of nascent transcripts in real-time . To measure the efficiency of real-time detection of nascent transcripts by fastFISH , we needed a reference to define the start and end of each productive single-molecule transcription event . We reasoned that monitoring the interactions between RNAP molecules and the DNA templates during promoter binding and run-off can serve this purpose . Therefore , we fluorescently labeled RNAP with Cy5 using HaloTag ( Figure 3—figure supplement 1 ) , supplied Cy5-RNAP and NTPs to an imaging flow cell containing immobilized DNA templates , and monitored Cy5-RNAP interactions with the DNA molecules ( Figure 3 ) . We observed transient RNAP binding events that lasted between 0 . 08 and 8 s , and were promoter-specific ( Figure 3B–D ) . The events were comprised of two distinct populations: short-lived events whose dwell times fit well to a single exponential distribution ( mean dwell time T0 ∼0 . 14 s ) ; and a long-lived , bell-shaped population skewed towards long-lived events ( peak dwell time T1 ∼1 . 7 s ) . The durations of observed interactions were not limited by the lifetime of the Cy5 label before photobleaching ( Figure 3—figure supplement 2 ) . We interpret the short-lived , stochastic interactions to be promoter-specific but non-productive RPc and RPo , because no interactions were observed with templates containing a null promoter sequence ( at frame rates of 12 . 5 Hz , Figure 3B ) and similar short-lived interactions were observed in the absence of NTPs ( single exponential T0 ∼0 . 3 s , Figure 3D ) . 10 . 7554/eLife . 01775 . 008Figure 3 . Single-molecule dynamics of T7 RNAP-DNA interactions . ( A ) Schematic of experiment . ( B ) Co-localization analysis of RNAP-DNA interactions . Left: null promoter DNA template in the presence of NTPs . Center: wild type promoter DNA template in the presence of NTPs . Right: wild type promoter DNA template in the absence of NTPs . ( C ) Representative data . Top: video montages of RNAP interactions with template containing consensus promoter for a 5 × 5 pixel region of interest centered at a single , photobleached DNA molecule ( 1 pixel = 200 nm , imaged at 12 . 5 Hz ) . Bottom: fluorescence time traces corresponding to the montages shown on top . Baseline of zero intensity indicates no binding . Left: experiment carried out in the presence of NTPs . Right: experiment carried out in the absence of NTPs . Yellow arrows indicate the first frames of RNAP binding events . ( D ) Dwell time probability distributions of RNAP-DNA binding events . Left: experiment carried out in the presence of NTP . Fitting to a sum of single exponential and Gaussian functions is shown in blue . Right: experiment carried out in the absence of NTPs . Fitting to a single exponential function is shown in blue . ( E ) Dependence of the peak dwell time of RNAP-DNA interactions on the length of the transcribed DNA segment: schematic of experiment . DNA templates containing transcribed segments spanning from +1 to +295 ( red ) , +633 ( blue ) , or +910 ( black ) were separately immobilized , and interactions of labeled RNAP were recorded at 2 . 5 Hz . ( F ) Dwell time probability distributions of RNAP-DNA interactions for the three DNA templates shown in ( E ) . N = 749 for the +1…+295 template ( red ) , N = 716 for the +1 … +633 template ( blue ) , and N = 213 for the +1 … 910 DNA template ( black ) . The peak dwell times were calculated by fitting the distributions to a sum of single exponential and Gaussian functions . ( G ) Plot of the peak dwell time of RNAP-DNA interactions vs the length of the transcribed DNA segment . ( H ) Decay of intensity of RNAP fluorescence signal during productive RNAP-DNA interactions as an indicator of elongation by RNAP . All RNAP-DNA interactions having dwell times longer than 0 . 8 s ( experiments in F ) were post-synchronized by RNAP binding ( t = 0 , circles ) and by RNAP run-off ( squares ) , and weight-averaged plots of RNAP binding and run-off were plotted for DNA templates having transcribed segments of different lengths ( red − 295 bp; blue − 633 bp; black − 910 bp ) . Time offsets between RNAP binding and run-off were set at peak dwell lifetimes , T1 , for the respective DNA templates measured in ( F ) . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 00810 . 7554/eLife . 01775 . 009Figure 3—figure supplement 1 . Labeling and biochemical characterization of T7 RNAP activity . ( A ) Synthesis of Cy5-conjugated HaloTag Ligand ( S3 ) used to label RNAP from Cy5 acid S1 and HaloTag ligand-amine S2 . See ‘Materials and methods’ for details . ( B ) SDS-PAGE gel images of the unlabeled ( ‘RNAP’: no HaloTag; ‘Halo-RNAP’: with HaloTag ) and the Cy5-labeled Halo-RNAP ( ‘Cy5-Halo-RNAP’ ) T7 RNAP . All RNAPs have a 6 ( His ) tag at the N-terminus used for purification . Top: image stained with Coomassie Brilliant Blue . Bottom: the same gel scanned for Cy5 fluorescence ( prior to Coomassie staining ) . ( C ) In vitro transcription activity of RNAP . The concentrations of RNAP derivatives were as indicated . The DNA template ( a PCR fragment spanning from −75 to +295 of the concensus T7 RNAP promoter ) , was used at 10 nM . RNA products were labeled by incorporation of α32P-ATP , resolved on a denaturing polyacrylamide gel , and imaged by autoradiography . The major bands at ∼295 nt are the expected run-off products . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 00910 . 7554/eLife . 01775 . 010Figure 3—figure supplement 2 . Measurements of photobleaching times of fluorophores used in this study . Double-stranded , biotinylated , labeled DNA molecules were immobilized on a passivated glass surface , imaged with TIRF microscope in the presence of oxygen scavengers , and photobleaching time-traces of fluorophores were recorded at 2 . 5 Hz . The same laser intensities were used as in single-molecule transcription experiments ( 532 nm at 300 W cm−2 to excite Cy3 , and 640 nm at 100 W cm−2 to excite Cy5 and Atto633 ) . The times of photobleaching of individual molecules were binned , plotted as probability histograms ( red crosses at bin centers ) , and the histograms were fit to single exponential function ( black circles at bin centers ) to estimate mean photobleaching lifetimes ( T ) . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 010 We interpret the long-lived , bell-shaped population of events to be full , productive transcription cycles , because ( i ) the long-lived events were not observed in the absence of NTPs ( Figure 3D ) ; ( ii ) the peak dwell time of the long-lived events , T1 , increased nearly linearly with the length of the transcribed DNA segment ( T1 ∼1 . 7 s , ∼2 . 7 s , and ∼3 . 7 s for DNA segments with l = 295 bp , 633 bp , and 910 bp , respectively , Figure 3E–G ) ; and ( iii ) the RNAP fluorescence signal , on average , decayed towards the end of long-lived events ( Figure 3C , H ) , consistent with RNAP initiating transcription at the promoter located close to the surface ( 75 bp , or ∼25 nm ) , and then elongating towards the free , untethered DNA end , down the gradient of the TIRF evanescent field . We conclude that the dwell time distributions of RNAP-DNA interactions define productive transcription events which can be used as a reference to determine the efficiency of nascent RNA detection by fastFISH , and to dissect the full transcription cycle by RNAP . We note that the slope of the plot of long-lived RNAP dwell times vs DNA length , ( ∼3 . 2 ± 0 . 6 ) × 10−3 s nt−1 ( Figure 3G ) , gives an estimate of RNAP elongation rate of ∼300 nt s−1 . The intercept of the plot with the time axis ( l = 0 ) gives an estimate of the net time that RNAP spends on the DNA template without elongating , Tstationary = 0 . 7 ± 0 . 3 s , which includes the net duration of promoter opening and abortive cycling ( RPc , RPo and RPits ) , and , possibly , the time RNAP idles at the free DNA end before run-off . To determine the efficiency of nascent RNA detection by fastFISH , and to demonstrate the use of fastFISH in dissecting the kinetics of the full transcription cycle , we simultaneously monitored RNAP-DNA interactions and the production of transcripts in real-time , using Cy5-labeled RNAP together with the Cy3-labeled probe F1 ( Figure 4A ) . In this two-color experiment , we expected to observe the following sequence of events: ( i ) initial appearance of an RNAP spot at the DNA locus , corresponding to promoter binding ( RPc ) ; ( ii ) continued occupancy of the DNA by RNAP , corresponding to promoter opening ( RPo ) , abortive cycling ( RPitc ) , elongation to +60 ( RDe ) and the time required for probe hybridization; ( iii ) appearance of an F1 probe spot; ( iv ) co-occupancy of the DNA by RNAP and probe corresponding to elongation ( RDe ) ; and ( v ) simultaneous disappearance of the RNAP and probe spots corresponding to run-off at +295 . As shown in a representative video montage , precisely this sequence of events was observed ( Figure 4B , C ) . Typically , the probe arrived at the DNA within 1 s after arrival of RNAP . 10 . 7554/eLife . 01775 . 011Figure 4 . Single-molecule dissection of the T7 RNAP transcription cycle using fastFISH . ( A ) Schematic of experiment . ( B ) Merged video montages ( 5 × 5 pixel region of interest ) centered at a single , previously photobleached DNA molecule . Interactions of RNAP ( false colored in red ) and probe ( false colored in green ) with the DNA locus were imaged simultaneously at 2 . 5 Hz . Four representative transcriptional events are shown . ( C ) Fluorescence time traces corresponding to the montage shown in Panel B ( RNAP and probe are shown in red and green , respectively ) . The first transcriptional event is zoomed in and shown on top . ( D ) Calculation of the time delay of probe binding with respect to RNAP binding ( ΔTon ) from heat maps of all RNAP-DNA ( top ) and all probe-DNA binding events ( middle ) post-synchronized by RNAP binding ( Ton , NDNA = 112 , Nevents = 469 ) . Baseline of zero intensity indicates no RNAP/probe binding . Time point t = 0 corresponds to the frame immediately before RNAP binding ( red dashed line ) . On the bottom are the weight-averaged , normalized signal intensities of RNAP and probe binding calculated based on the heat-maps of all RNAP-DNA ( red ) and probe-DNA ( green ) binding events . ( E ) Calculation of the time delay of probe dissociation with respect to RNAP run-off ( ΔToff ) from heat maps of all RNAP-DNA and probe-DNA dissociation events post-synchronized by RNAP dissociation ( Toff ) . Time point t = 0 corresponds to the frame immediately before RNAP dissociation ( red dashed line ) . ( F ) Calculation of the efficiency of real-time RNA detection ( left ) , and of the fraction of events in which RNA was released from DNA upon RNAP run-off ( right ) . Productive RNAP-DNA interactions were post-synchronized by RNAP dissociation as shown in Panel E , and probability distribution of probe signal intensity was plotted for the time point immediately before RNAP run-off ( left , t = 0 , for the efficiency of RNA detection ) and the time point immediately after RNAP run-off ( right , t = 0 . 4 s , for the fraction of RNA released upon run-off ) . Fits of distributions to sums of two Gaussian functions are shown in blue ( R2 = 0 . 92 ) . The higher mean-value Gaussian ( peak 1 ) corresponds to the events with the probe signal present and the lower mean value ( peak 2 ) corresponds to the events without the probe signal present . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 01110 . 7554/eLife . 01775 . 012Figure 4—figure supplement 1 . Control single-molecule transcription experiments in the presence of an incomplete set of NTPs . Cy5-labeled RNAP and Cy3-labeled F1 probe were used in a reaction at the presence of a full set of NTPs ( ATP , GTP , UTP , and CTP , 0 . 5 mM each , left ) , or ATP and GTP only ( 1 mM each , right ) . Top row: heat map of all RNAP-DNA interactions post-synchronized by RNAP binding ( red dashed line ) . Bottom row: heat map of all F1 probe-DNA interactions post-synchronized by RNAP binding . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 01210 . 7554/eLife . 01775 . 013Figure 4—figure supplement 2 . Sequence-specificity control of real-time RNA detection by fastFISH . ( A ) Sequence-specificity of probe F1 . Top row: schematic of experiments with DNA templates containing the sequence of F1 target ( left ) and DNA templates lacking the sequence of F1 target ( right ) . Middle row: heat map of all RNAP-DNA interactions post-synchronized by RNAP binding ( red dashed line ) . Bottom row: heat map of all F1 probe-DNA interactions post-synchronized by RNAP binding . Left panels show the same dataset as shown in Figure 3 for side-by-side comparison . ( B ) Same as panel ( A ) , but for probe F2 ( the probe signal was weaker , because lower laser power was used in the experiment shown ) . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 01310 . 7554/eLife . 01775 . 014Figure 4—figure supplement 3 . Effect of the distance between the promoter and the probe target sequence on the time delay between probe and RNAP binding , ΔTon . ( A ) Schematic of the experiment . The F1 target sequence was inserted at two different positions with respect to the promoter: +28 ( top template ) and +181 ( bottom template ) . The numbers ‘+60’ and ‘+213’ indicate the expected positions in the respective templates which the RNAP active site needs to reach before the probe target sequence in the nascent RNA becomes available for hybridization . ( B ) Calculation of the time delay between probe and RNAP binding ( ΔTon ) from heat maps of all RNAP-DNA ( top ) and all probe-DNA binding events ( bottom ) post-synchronized by RNAP binding . Data for the ‘+60’ and ‘+213’ templates are shown on the left and right , respectively . ( C ) Calculation of the difference in the time delay of probe binding ( ΔΔTon ) from weight-averaged signal profiles of RNAP ( red ) and probe binding ( green ) . Profiles for the +60 template are shown as circles , and profiles the +213 template are shown as triangles . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 014 Three lines of evidence suggested that the temporal co-occurrence of the F1 probe and RNAP corresponded to specific capture of nascent RNA in RDe . First , no binding of F1 after RNAP binding was observed in the absence of NTPs ( data not shown ) , or in the presence of only ATP and GTP , which limited initial transcription to positions from +1 to +6 ( Figure 4—figure supplement 1 ) , indicating that the probe bound specifically to the nascent RNA , and not to RNAP or to the DNA template . Second , no F1 probe binding was observed in the absence of the target sequence in the transcribed segment of the template , indicating that hybridization was specific for the F1 target ( Figure 4—figure supplement 2 ) . Third , and most importantly , when we moved the F1 target sequence from position +28 to position +181 , we found that binding of the probe was delayed by an additional ∼0 . 5 s ( Figure 4—figure supplement 3 ) , consistent with the extra time RDe needs to transcribe the extra 153 bp DNA segment at 300 nt s−1 ( Figure 3G ) . To estimate the efficiency of nascent RNA detection by fastFISH , we post-synchronized ( Blanchard et al . , 2004 ) all RNAP-DNA and probe-DNA interactions by RNAP run-off at the end of productive transcription events ( defined as RNAP interactions that lasted ≥0 . 8 s ) , and super-imposed them to generate heat maps of all RNAP-DNA and probe-DNA interactions ( Figure 4E ) . We found that ∼81% of RDes contained an RNA probe immediately before run-off ( Figure 4F ) . The residual ∼19% of undetected RDes were mostly likely due to the presence of dark fluorophores in the chemically synthesized probes ( Revyakin et al . , 2012 ) , and the inherent stochasticity of probe hybridization . The heat map analysis of all RNAP-DNA and probe-DNA interactions also showed that , in the majority of cases ( ∼72% ) , the probe and RNAP dissociated from the DNA simultaneously upon run-off ( ΔToff ∼0 ) . In the remaining ∼28% of cases , the RNA probe persisted on the DNA for ≥0 . 4 s after RNAP run-off ( Figure 4F ) ; the nature of these events remains to be determined . To extract the kinetic information on early stages of transcription , we post-synchronized all RNAP-DNA and probe-DNA interactions by RNAP binding during productive transcription ( RNAP-DNA interactions that lasted ≥0 . 8 s ) ( Figure 4D ) . Analysis of the resulting heat-map of probe and RNAP binding gave the average time delay between the RNAP and probe arrival , ΔTon of 0 . 7 ± 0 . 2 s . We interpret ΔTon as the net duration of promoter opening ( Topen ) , abortive cycling ( Tabortive ) , elongation from position +13 to position +60 ( Telongation ) , and the time for probe hybridization ( Thybridization ) . Because promoter opening by RNAP is generally very fast ( ∼30 s−1 , Stano et al . , 2002 ) , Topen is negligible . Therefore:Tabortive=ΔTon− ( Telongation+Thybridization ) Based on our measurement of the RNAP peak elongation rate ( 300 ± 60 nt s−1 , Figure 3 ) , Telongation = ( 60–13 ) /300 = ∼0 . 16 s . Based on our measurement of the F1 probe hybridization rate ( 6 × 106 M−1s−1 , Figure 1C ) , Thybridization = ∼0 . 33 s ( at the 500 nM probe concentration used in the experiment ) . Thus , Tabortive = 0 . 7 − ( 0 . 16 + 0 . 33 ) = ∼0 . 2 s . This estimate of Tabortive is within the upper limit set by our measurement of Tstationary = 0 . 7 ± 0 . 3 s ( the net time RNAP spends on the DNA template without elongating , Figure 3G ) . The fact that Tstationary is larger than Tabortive , suggests that RNAP might dwell at the end of the DNA template for ∼0 . 5 s before run-off . Pausing/arresting at free DNA ends has been previously observed with multi-subunit bacterial and eukaryotic RNA polymerases in ensemble assays , and likely involved backtracking by these RNAPs ( lifetimes of >1 min , Arndt and Chamberlin , 1988; Izban et al . , 1995 ) . It remains to be tested whether T7 RNAP dwells at the end of the DNA via a similar mechanism , and whether the pause is part of a natural termination process .
Here we present a strategy to design fast probe-target hybridization pairs for quantitative single-molecule detection of nascent RNA transcripts at sub-second time resolution under physiological conditions ( fastFISH ) . The hybridization rates of fastFISH probes were near ∼107 M−1s−1 which exceeded annealing rates of probe-target sequences reported in literature by up to three orders of magnitude . We followed three simple rules in fastFISH probe-target design . First , the targets and the probes should be unstructured , which we achieved using sequences composed of only three bases—A , U , and C for RNA targets , and A , T , and G for DNA probes . We note that the three-base rule of fast hybridization also applies to DNA–DNA pairs ( data not shown ) . Second , a complexity filter should be applied to ensure specificity and 1-to-1 stoichiometry of hybridization . This is essential for single-molecule counting , and cannot be achieved by using repetitive sequences such as poly ( A/T ) . Third , fastFISH probes should be self-quenched . This reduces the fluorescence background from the free probe , and enables the use of near-micromolar probe concentrations for real-time single-molecule imaging . Self-quenching of fastFISH probes likely occurs through random polymer motion and/or contact quenching ( Johansson et al . , 2002; Marras et al . , 2002 ) , and does not rely on hairpin formation ( which is known to compromise hybridization rates [Tsourkas et al . , 2003] ) . The choice of probe length of ∼20 nucleotides was based on the end-to-end distance of a 20-mer nucleic acid duplex , expected to separate the fluorophore and the quencher beyond typical Forster distance ( 4∼6 nm ) upon hybridization . Shorter probes in combination with a short-range quencher may be used ( Zhu et al . , 2005 ) if the potential faster off-rate of the probe is not a concern . We note that probe hybridization rates could be further increased using peptide nucleic acid ( PNA ) probes , because the neutral charge of the PNA backbone is expected to reduce the electrostatic repulsion between the probe and the target ( Kuhn et al . , 2002 ) . To use fastFISH , the three-base target sequence must be inserted within the context of an existing four-base ( i . e . , ‘structured’ ) RNA sequence , which , in principle , might sequester the fastFISH target from hybridization . However , in our experience , the presence of adjacent four-base sequences usually does not interfere with co-transcriptional RNA detection , likely because four-letter sequences become kinetically trapped within their own secondary structures . Nevertheless , the use of a secondary structure prediction tool is recommended to ensure that flanking sequences do not interfere with the fastFISH target . As a proof of concept , we used fastFISH to dissect the full transcription cycle of the prototypical single-subunit T7 RNAP , and obtained kinetic estimates of promoter search ( upper limit of non-specific RNAP-DNA interactions: Tsearch ∼80 ms ) , promoter binding , promoter escape , elongation and termination by RNAP ( summarized in Figure 5 ) . We recorded several differences between our measurements and previous studies . First , the measured rate of stochastic RPc dissociation ( T0 ∼0 . 3 s , koff ∼3 s−1 ) was higher than what had been reported in previous ensemble and single-molecule studies ( koff from 0 . 4 s−1 to 1 s−1 [Tang and Patel , 2006; Tang et al . , 2009] ) . Second , the measured rate of promoter escape ( Tabortive ∼0 . 2 s , kescape ∼5 s−1 ) was higher than in previous ensemble and single-molecule studies ( kescape from 0 . 25 s−1 to 1 s−1 , [Skinner et al . , 2004; Tang et al . , 2009] ) . Third , the measured peak elongation rate ( 300 ± 60 nt s−1 ) was somewhat higher than in previous ensemble measurements ( ∼240 nt s−1 , Bonner et al . , 1994; Golomb and Chamberlin , 1974 ) , and significantly higher than in previous single-molecule measurements ( from 40 nt s−1 to 120 nt s−1 , Thomen et al . , 2008; Skinner et al . , 2004 ) . The overall faster rates measured in our study are likely due to the use of optimal physiological temperatures ( 37°C ) . Indeed , the catalytic rate of the T7 RNAP measured in steady-state conditions is known to increase up to 10-fold in the 20°C–37°C temperature range ( Maslak and Martin , 1993 ) . Another potential contributing factor to the faster observed rates could be that our method to dissect the RNAP transcription cycle does not require the use of force , or covalent modification of the DNA templates . 10 . 7554/eLife . 01775 . 015Figure 5 . Summary of RNAP transcriptional kinetics measured in this work . DOI: http://dx . doi . org/10 . 7554/eLife . 01775 . 015 We note that the dwell time distribution of productive RNAP-DNA interactions was skewed towards longer-lasting events , likely due to spontaneous RNAP pausing . Our observation of pausing might explain previously reported premature dissociation of colliding elongating RNAPs , observed at high RNAP:template ratios ( ‘bumping’ , Zhou and Martin , 2006 ) . FastFISH detection of nascent RNA , coupled to single-molecule detection of protein-DNA interactions will be particularly useful to study the dynamics of initiation , escape , elongation , and termination by multi-subunit RNAPs , and the coupling of the transcriptional steps to downstream RNA-processing events . The guidelines for designing fastFISH probe-target pairs can be used to efficiently detect endogenous RNAs in situ and in vivo , to silence gene expression , and to build novel nucleic acid nanostructures .
Random 19-mer DNA and RNA sequences were generated using a home-written Matlab routine . Briefly , built-in matlab routine randperm was used to pick a random set of k integers from a pool of n integers , where n = 319 ( for 3-base sequences ) or 419 ( for 4-base sequences ) , and k = 312 ( 531441 ) . A different seed for the Matlab random number generator was used in independent trials to ensure independent sampling . ( Sets of 3-base 19-mers were used , because a 19-mer is representative of commonly used hybridization probes , and analysis of k = 312 19-mer sequences could be performed on a modern portable computer . ) Built-in Matlab routine dec2base was then used to convert sets of k integers into strings of numeric characters of base 3 ( 0 , 1 , and 2—for 3-base sequences ) or base 4 ( 0 , 1 , 2 , and 3—for 4-base sequences ) . The numeric characters were then replaced with A , U , C , and G , and sequences having GC-content ≥0 . 4 and ≤0 . 6 were saved as ASCII files , to be processed with the secondary structure prediction tool Mfold . Calculation of free energies of self-folding for DNA and RNA sequences was performed on a personal computer ( routine hybrid-ss-min , release 3 . 8 , available at http://mfold . rna . albany . edu , Zuker , 2003 ) . For DNA , folding parameters −‘sodium = 0 . 15 −magnesium = 0 . 01’ were used to match the composition of hybridization buffer used in single-molecule experiments on probe on-rate measurements . For RNA , default folding parameters were used . The free energies of self-folding were extracted from Mfold output files using a home-written Matlab parsing routine , and plotted as normalized probability histograms with 1 kcal mol−1 binning . At least three independently randomized sets of 312 sequences were analyzed for each alphabet ( rAUC , rAUG , rCAG , rCUG , rAUGC , ATC , ATG , CAG , CTG , and ATGC ) and results from independent sets were consistent to within 0 . 5% . Sequence complexity was calculated using Matlab routine kolmogorov ( provided by Stephen Faul , Radisens Diagnostics , code available at the Mathworks website ) , modified to output the absolute number of Lempel–Ziv operations , not normalized for the sequence length ( Kaspar and Schuster , 1987 ) . Per the modified kolmogorov routine , the complexity measure of a sequence comprised of 19 unique symbols ( e . g . , ‘abcdefghijklmnopqrs’ ) is 19 , and the complexity measure of a sequence comprised of 19 identical symbols ( e . g . , A19 ) is 2 . To calculate the complexity of all tiling 19-mers of the human chromosome 22 , the genomic sequence ( length: 51 , 304 , 560 bp ) and the annotation file indicating the locations of exons of known genes were downloaded from the UCSC genome browser , the sequences of exons in the forward strand were assembled into one contiguous string , and the complexities were calculated using a 19-base sliding window . The sequences of the F1 probes were as follows ( synthesized by Integrated DNA technologies , IDT , Coralville , IA ) :F1: 5′-Cy3-GTT AAG ATA AGG GAT AGG G-3′ ( not self-quenched ) ;F1: 5′-Cy3-GTT AAG ATA AGG GAT AGG G-FQ-3′ ( self-quenched with Iowa Black FQ ) F1: 5′-Atto633-GTT AAG ATA AGG GAT AGG G-RQ-3′ ( self-quenched with Iowa Black RQ ) The sequences of self-quenched F2 probes and the F2+1C , F2+2C , F2+3C , and F2+4C variants ( these variants were selected as representative of their categories based on the free energies of self-folding ) were as follows ( synthesized by Fidelity Systems , Gaithersburg , MD ) :F2: 5′-BHQ-3-GGT GTA TGT AAT TGG AGT GGT T-C6-Atto633-3′;F2+1C: 5′-BHQ-3-GGT GTA TCT AAT TGG AGT GGT T-C6-Atto633-3′;F2+2C: 5′-BHQ-3-GGT GTA TGC AAT TGG ACT GGT T-C6-Atto633-3′;F2+3C: 5′-BHQ-3-GGT GTA TGT AAC CGG AGT GCT T-C6-Atto633-3′;F2+4C: 5′-BHQ-3-GCT GTA TGC AAT TGG AGC CGT T-C6-Atto633-3′ . In the above sequences , BHQ-3 is Black Hole 3 quencher , C6 is a six-carbon linker . The sequences of RNA targets used in single-molecule TIRF/CoSMoS measurements of probe hybridization rates were as follows:F1F2: 5′- CCC UAU CCC UUA UCU UAA CCA CUC CAA UUA CAU ACA CCC UUC AAA CUU CAA ACU UCA AAG CAC AAG UUU UAU CCG GCC UUU AUU CAC AUU-bio-3′F1F2+1G: 5′- CCC UAU CCC UUA UCU UAA CCA CUC CAA UUA GAU ACA CCC UUC AAA CUU CAA ACU UCA AAG CAC AAG UUU UAU CCG GCC UUU AUU CAC AUU-bio-3′F1F2+2G: 5′- CCC UAU CCC UUA UCU UAA CCA GUC CAA UUG CAU ACA CCC UUC AAA CUU CAA ACU UCA AAG CAC AAG UUU UAU CCG GCC UUU AUU CAC AUU-bio-3′F1F2+3G:5′- CCC UAU CCC UUA UCU UAA GCA CUC CGG UUA CAU ACA CCC UUC AAA CUU CAAACU UCA AAG CAC AAG UUU UAU CCG GCC UUU AUU CAC AUU-bio-3′F1F2+4G:5′- CCC UAU CCC UUA UCU UAA CGG CUC CAA UUG CAU ACA GCC UUC AAA CUU CAA ACU UCA AAG CAC AAG UUU UAU CCG GCC UUU AUU CAC AUU-bio-3′ In the above sequences , regions that correspond to the F1 and F2 targets are underlined and italicized , respectively , and the variations within the F2 target region to introduce 1-4 G residues are highlighted in bold . Note that the F1 and F2 targets overlap by three bases . The biotin residue on the 3′ end enabled immobilization of the RNA targets on surface for single-molecule imaging by TIRF/CoSMoS . To fluorescently label the RNA targets , a Cy3-labeled DNA oligonucleotide ( sequence: 5′-Cy3-AAT GTG AAT AAA GGC CGG ATA AAA CTT GTG C-3′ IDT ) was annealed to the 3′ of the RNA targets . Single-molecule measurements of probe-target hybridization rates and T7 RNAP transcription were performed using a home-built multi-color total-internal-reflection microscope as described ( Revyakin et al . , 2012 ) . In brief , fluorescence was excited and imaged through a 60 × 1 . 49 NA objective lens ( Olympus , Center Valley , PA ) . The objective lens and the sample holder were pre-heated to 37°C ( Bioptechs , Butler , PA ) . Fluorescence was excited with 532 nm ( Coherent Verdi G2 , intensity 100–300 W/cm2 , Coherent , Santa Clara , CA ) and 640 nm ( Coherent Cube 100 , intensity 100 W/cm2 ) lasers , split into two imaging channels ( band centered at 580 nm , width 60 nm; and band centered at 675 nm , width 45 nm ) , and imaged using two separate , synchronized EMCCD cameras ( 512 × 512 pixels , 1 pixel = 200 nm , conventional acquisition at 2 . 5 Hz or electron-multiplied acquisition at 12 . 5 Hz ) ( Andor , Belfast , United Kingdom ) . The position of the sample with respect to the objective lens was actively stabilized in ( x , y , z ) . To that end , 2 . 8 μm-diameter magnetic beads ( Life Technologies , Carlsbad , CA ) decorating the imaging surface were illuminated with an infrared ( IR ) light-emitting diode ( 851 nm , Roithner LaserTechnik , Vienna , Austria ) , tracked with an IR camera using real-time image-processing ( Gosse and Croquette , 2002; Revyakin et al . , 2012 ) at 30 Hz , and the position of the bead in the field of view was adjusted in real-time at 1–5 Hz using a 3-axes nanopositioning stage ( Physik Instrumente , Karlsruhe , Germany ) . The IR camera and framegrabber for bead tracking were from 1stVision ( Andover , MA ) . Unless otherwise noted , all chemicals were purchased from Sigma-Aldrich ( St . Louis , MO ) . Borosilicate coverslips were placed in ceramic racks ( Thomas Scientific , Swedesboro , NJ ) , cleaned with piranha solution ( a mixture of three parts concentrated H2SO4 and one part 30% H2O2 , which is extremely corrosive and explosive ) twice for 30 min , rinsed copiously with deionized water , and hydroxylated with 0 . 5 M KOH solution for 1 hr with sonication . The coverslips were then rinsed copiously with deionized water , rinsed twice by dipping in acetone ( Chromasolv-Plus ) for 10 s , and placed into a 3% solution of aminopropyltriethoxylane ( APTES , Thermo Fischer Scientific , Waltham , MA ) in acetone for 45 min , with gentle shaking . APTES-treated coverslips were then rinsed copiously with deionized water , and blow-dried with nitrogen . 50 μl drops of solution of 10% PEG-succinimidyl valerate ( PEG-SVA , Mw = 5 , 000 , Laysan ) and 0 . 05% biotin-PEG-SVA ( Mw = 5 , 000 , Laysan ) in 0 . 45M K2SO4 and 0 . 1M NaHCO3 ( pH 9 . 0 ) was squeezed between pairs of coverslips , and the coverslip pairs were incubated with PEG at 30°C for 30 min . PEG-treated coverslips were then rinsed copiously with deionized water , blow-dried with nitrogen , and the unreacted amine groups were end-capped by squeezing a 50 μl drop of solution of 2 mg sulfo-succinimidyl acetate ( Pierce ) in 0 . 1M NaHCO3 ( Pierce ) for 10 min . The PEG-treated and amine-capped coverslips were rinsed copiously with deionized water , blow-dried with nitrogen , and stored dry at −80°C . ( We found that end-capping of unreacted APTES amine groups was essential to eliminate non-specific interactions of fluorescently labeled probes with the glass surfaces at high probe concentrations . ) An imaging flow cell containing seven reaction channels ( volume of each channel: ∼25 μl ) and side injection ports was constructed using two PEG-treated coverslips and double-sided adhesive tape ( 3M VHB 4095 ) . The flow cell was mounted on the microscope , and the inner surface was decorated with the 2 . 8 μm magnetic beads for active stage stabilization ( ∼1–3 beads per 100 × 100 micron field of view ) and functionalized with streptavidin ( by incubating 5 μg/ml solution of streptavidin in phosphate-buffered saline for 30 s in a channel immediately before use ) . Biotinylated , fluorescently labeled synthetic RNA targets were captured in the flow cell at a density ∼1000–2000 molecules per field of view ( ∼100 × 100 μm ) by injecting 20 pM solution of RNA target in loading buffer ( phosphate-buffered saline containing 0 . 08% Tween-20 ) . The position of the microscope stage was then actively stabilized in ( x , y , z ) ( see above ) , and a ‘mapping’ video of diffraction-limited spots indicating the positions of RNA target molecules was acquired at 2 . 5 Hz until all RNA spots were photobleached . Single-molecule imaging here and below was conducted in the presence of 0 . 9 mM Trolox , 2 . 2 mM protocatechuic acid ( PCA ) , and 10 μg/ml protocatechuate dehydrogenase ( Toyobo ) , further purified to remove contaminating nuclease activity ( Jonas Korlach , Pacific Biosciences , personal communication ) . After mapping of the RNA targets , the loading buffer was replaced with hybridization buffer ( loading buffer plus 10 mM MgCl2 ) and a solution of fluorescently labeled , self-quenched probes in hybridization buffer at concentrations in the 2–500 nM range was injected into the flow cell at flow rate ∼50 μl s−1 . A real-time video of probe binding events ( observed as appearance of diffraction-limited fluorescent spots , Figure 1—figure supplement 2 ) was acquired at 2 . 5 Hz . For most accurate measurements of the hybridization rates , the concentrations of probes were adjusted empirically to achieve average probe arrival times of 10–100 s . Data analysis was essentially as described ( Revyakin et al . , 2012 ) . Briefly , single-molecule spots were identified in every frame of the target and probe videos using the software Insight ( Huang et al . , 2010 ) , and each spot was localized in ( x , y ) by fitting a 5 × 5 pixel spot intensity distribution to a 2D Gaussian . The ( x , y ) coordinates of all identified spots in all video frames were grouped into clusters ( ‘blobs’ ) using a 2D histogram ( 1 pixel binning ) , and the average ( x , y ) of every blob ( indicating the locations of target and probe molecules ) was calculated . Then , for every target blob , the closest probe blob was found , the deviations ΔxΔy were calculated for all such probe-target pairs , and plotted as a 2D histogram ( ‘the co-localization plot’ ) . RNA targets that were located within two standard deviations of the central peak at position ( 0 , 0 ) of the co-localization plot ( ∼40 nm ) were selected . Such ‘active’ RNA molecules typically comprised ∼30% of all RNA molecules . Time series of probe-target binding was generated for every active RNA ( using the mean fluorescence intensity from a 5 × 5 pixel region of interest ( ROI ) , with the mean intensity of the ROI perimeter pixels subtracted as background ) . Each time series was examined , and the video frame corresponding to the probe arrival at the target was identified ( Figure 1—figure supplement 2 ) . The dataset containing all probe arrival times ( Twait , usually 100–500 events ) was binned , with the center of the first bin corresponding to the minimal observed Twait , the center of the last bin corresponding to the maximal observed Twait , and the number of bins Nbins = ³√ ( 2Nevents ) ( Scott , 1992 ) . The first bin was discarded to account for the discontinuity , and for the lag time due to the buffer exchange during probe injection . The probability histogram of Twait ( Figure 1—figure supplement 2 ) was fit to a single exponential function using the Matlab built-in routine nlinfit , which gave an estimate of the characteristic hybridization time ( 95% confidence interval ) , and the goodness of fit ( typically , R2 > 0 . 98 ) . On-rates for probes F1 , F2 , F2+1C , F2+2C , F2+3C and F2+4C were calculated as kon = 1/ ( Twait × [probe] ) . Promoter DNA constructs were amplified by PCR . To attach and image the DNA constructs , the PCR primer complementary to the sequence upstream from the promoter was labeled with biotin and Cy3/Cy5/Atto633 at the 5′-end . In most experiments , the PCR-amplified DNA template spanned from −75 to +295 with respect to the transcription start site ( +1 ) . In the DNA template sequence shown below , the underlined sequences are , respectively: the upstream PCR primer ( 5′ base at −75 ) , the consensus T7 RNAP promoter , the F1 probe target , the F2 probe target , and the downstream PCR primer ( 5′ base of the complementary sequence at +295 ) . The +1 base is shown in bold . ( −75 ) TTATGTATCATACACATACGATTTAGGTGACACTATAGAACTCGAGCAGCTGGATCC TAATACGACTCACTATAGGGAGACCACAACGGTTTCCCTCTAGACCCTATCCCTTATCTTAACGAATTGTGAGCGCTCACAATTCAAACTTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTCAAACTTGAATTCTTTCAAAACACTCCAATTACATACACCTTTCAAAACCACCGTTGATATATCCCAATGGCTGCAGCTGGATATTACGGCCTTTTTAAAGACCGTAAAGAAAAATAAGCACAAGTTTTATCCGGC ( +295 ) For PCR-amplify DNA templates containing longer transcribed sequences ( ending at +633 and +910 ) , the same upstream primer , and primers with 5′ ends corresponding to +633 and +910 were used . The sequence for the +910 DNA template is shown below , with the regions corresponding to the +633 and +910 primers underlined , and the sequence upstream from +296 identical to the sequence of the −75…+295 template: ( +296 ) CTTTATTCACATTCTTGCCCGCCTGATGAATGCTCATCCGGAATTCCGTATGGCAA TGAAAGACGGTGAGCTGGTGATATGGGATAGTGTTCACCCTTGTTACACCGTTTTCCATGAGCAAACTGAAACGTTTTCATCGCTCTGGAGTGAATACCACGACGATTTCCGGCAGTTTCTACACATATATTCGCAAGATGTGGCGTGTTACGGTGAAAACCTGGCCTATTTCCCTAAAGGGTTTATTGAGAATATGTTTTTCGTCTCAGCCAATCCCTGGGTGAGTTTCACCAGTTTTGATTTAAACGTGGCCAATATGGACAACTTCTTCGCCCCCGTTTTCACCATGGGCAAATATTATACGCAAGGCGACAAGGTGCTGATGCCGCTGGCGATTCAGGTTCATCATGCCGTCTGTGATGGCTTCCATGTCGGCAGAATGCTTAATGAATTACAACAGTACTGCGATGAGTGGCAGGGCGGGGCGTAATTTTTTTAAGGCAGTTATTGGTGCCCTTAAACGCCTGGTGCTACGCCTGAATAAGTGATAATAAGCGGATGAATGGCAGAAATTCGCCGGATCTTTGTGAAGGAACCTTACTTCTGTGGTGTGACATA ( +910 ) In the DNA template containing the null T7 RNAP promoter mutation ( experiments in Figures 2 and 3 ) , the wild type promoter sequence was replaced with TAA TAA CC ACT CAC TAT AGG G ( the mutation is underlined ) . In the DNA template containing deleted F1 target ( experiment in Figure 4—figure supplement 2A ) , the sequence of the F1 target was replaced with CAA ACT TCA AAC TTC AAA C . In the DNA template containing deleted F2 probe target ( experiment in Figure 4—figure supplement 2B ) , the sequence of the F2 target was replaced with CAA ACT TCA AAC TTC AAA C . We note that , in the context of the full transcript , the 3-base unstructured RNA target sequences might be potentially trapped in secondary structures formed by 4-base sequences present in the same transcript . Therefore , we used Vienna RNA-folding software ( Gruber et al . , 2008 ) to calculate the secondary structure of the full transcripts to ensure that 4-base sequences do not hybridize to the 3-base targets , and , instead , tend to self-hybridize locally . Commercial reagents were obtained from reputable suppliers and used as received . All solvents were purchased in septum-sealed bottles stored under an inert atmosphere . Reactions were monitored by thin layer chromatography ( TLC ) on precoated TLC glass plates ( silica gel 60 F254 , 250 µm thickness ) or by LC/MS ( 4 . 6 mm × 150 mm 5 μm C18 column; 5 μl injection; 10–95% or 50–95% CH3CN/H2O , linear gradient , with constant 0 . 1% vol/vol TFA additive; 20 min run; 1 ml/min flow; ESI; positive ion mode; UV detection at 254 nm ) . High-resolution mass spectrometry was performed by the Mass Spectrometry Center in the Department of Medicinal Chemistry at the University of Washington . NMR spectra were recorded on a 400 MHz spectrometer . 1H and 13C chemical shifts ( δ ) were referenced to TMS or residual solvent peaks , and 19F chemical shifts ( δ ) were referenced to CFCl3 . Data for 1H NMR spectra are reported as follows: chemical shift ( δ ppm ) , multiplicity ( s = singlet , d = doublet , t = triplet , q = quartet , dd = doublet of doublets , m = multiplet ) , coupling constant ( Hz ) , integration . T7 RNAP was purified as recombinant , N-terminal 6xHis and 6xHis-Halo fusions from the E . coli strain BL21 ( DE3 ) using standard Ni-NTA chromatography per recommendations of the Ni-NTA resin manufacturer ( Qiagen , Hilden , Germany ) . Purified proteins were dialyzed against storage buffer ( contains 20 mM potassium phosphate pH 7 . 5 , 100 mM NaCl , 50% glycerol , 10 mM DTT , 0 . 1 mM EDTA and 0 . 2% sodium azide ) and stored at −20°C . To label Halo-RNAP , 20 μM of protein was mixed with 60 μM Cy5-PEG4-HaloLigand in reaction buffer ( contains 50 mM HEPES pH 7 . 5 , 150 mM NaCl , 0 . 5 mM EDTA , 1 mM DTT , and 0 . 005% NP40 ) , incubated at room temperature for 1 hr , and then at 4°C overnight . To remove unreacted HaloLigand , the reaction mixture was passed through a PD-10 column ( GE Healthcare , Waukesha , WI ) pre-equilibrated with the storage buffer . Protein labeling efficiencies were >90% based on UV-Vis absorption spectroscopy . Proteins were examined using SDS-polyacrylamide gel electrophoresis and analysis of Cy5 fluorescence with Typhoon Trio+ , ( GE Healthcare ) , followed by Coomassie Brilliant Blue staining . All transcription reaction mixture contained the following ingredients unless otherwise specified: 40 mM Tris–HCl pH 7 . 9 , 6 mM MgCl2 , 2 mM Spermidine , 0 . 5 mM each nucleotide triphosphate ( NTP ) , 4 ng/μl yeast tRNA ( Sigma , further purified with protease K treatment and phenol/chloroform extraction ) , 100 ng/μl bovine serum albumin ( New England Biolabs , Beverly , MA ) , 2 μM carrier DNA oligonucleotide ( sequence: 5′-GTA TTG AGT CTT CAT TCT GTA T-3′ , IDT ) , 0 . 08% Tween 20 ( EMD Millipore , Gibbstown , NJ ) , 0 . 9 mM Trolox , 2 . 2 mM PCA , and 0 . 3 U/μl RNasin ( Promega Madison , WI ) . In ensemble measurements , 10 nM DNA template ( same PCR fragment as used in single-molecule assays ) , 0 . 17 μCi/μl α-32P-ATP ( Perkin Elmer , Waltham , MA ) and different concentrations of RNAP were also included in the reaction . After incubation for 10 min at 37°C , 2 μl of the transcription reaction was loaded onto a 6% denaturing polyacrylamide gel . The gel was dried under vacuum at 80°C for 1 hr , exposed to a PhosphorImager screen and scanned ( Typhoon Trio+ , GE Healthcare ) . The protocol for preparation of passivized glass surfaces for single-molecule transcription measurements will be described in detail elsewhere . Briefly , borosilicate coverslips ( VWR ) were cleaned with piranha solution as described above , blow-dried with nitrogen , and spin-coated to create a 50-nm layer of polystyrene containing 1% azide-terminated polystyrene on the glass surface . An imaging flow cell was assembled as described above , and the imaging surface was functionalized with biotin-PEG-alkyne as described ( Presolski et al . , 2011 ) . The flow cell was then mounted on the microscope holder , and the objective lens and the flow cell were pre-heated to 37°C . The imaging surface was blocked by incubation with loading buffer ( phosphate-buffered saline containing 0 . 08% Tween-20 ) for 5 min , and functionalized by incubation with the loading buffer containing 5 μm/ml streptavidin for 30 s . Biotinylated , fluorescently labeled DNA templates were captured and ‘mapped’ in the field of view of the microscope as described for the probe-target hybridization experiments . The position of the microscope stage was actively stabilized in ( x , y , z ) , and 100 μl of transcription reaction mixture ( see above ) supplemented with 10 μg/μl protocatechuate dehydrogenase , 5 nM Cy5-Halo-labeled or ( His ) 6 tagged , unlabeled RNAP , and/or 500 nM of fastFISH probe was injected into the flow cell . Videos of real-time interactions of RNAP and/or probe with the mapped , photobleached DNA loci were recorded with synchronized EMCCD cameras at 2 . 5 Hz , unless otherwise specified . Single-molecule transcription reactions typically lasted for 15 min . Diffraction-limited RNAP spots were identified in every video frame , localized by 2D Gaussian fitting , and co-localized with the previously mapped DNA loci as described above for the probe-target hybridization experiments . Time series of RNAP and probe fluorescence intensities were generated for every ‘active’ DNA molecule using an ROI of 3 × 3 pixels , with 1-pixel perimeter background subtraction . A DNA locus was defined as ‘active’ if it co-localized with an RNAP spot in 5–9 cumulative frames ( user-defined parameter ) during the 15-min reaction . Videos frames in which RNAP bound to DNA ( Ton ) and dissociated from DNA ( Toff ) were identified in the time series manually , and the dwell times of RNAP-DNA interactions ( Toff −Ton ) were calculated . The probability distributions of RNAP dwell times were fit to a single exponential function , or to a sum of single exponential and Gaussian functions using Matlab routine nlinfit . To measure the average time delay between binding of RNAP and the probe during productive RNAP-DNA interactions ( ΔTon ) , RNAP-DNA interactions that had dwell times ≥0 . 8 s were selected , post-synchronized by their Ton , and a two-dimensional histogram of all RNAP binding events ( a heat map of signal intensity vs frame number [Figure 4 , and Figure 4—figure supplements 1–3] ) was generated ( routine histcn , Bruno Luong , Fogale Nanotech , code available on the Mathworks website ) . The same dataset of RNAP Ton was then used as a reference to calculate a heat map of all probe binding events in the respective synchronized probe videos . For every frame of the heat map , the centers of mass of RNAP and probe signal intensity distributions were calculated , and normalized by setting the maximum intensity to 1 , and weight-averaged profiles of all RNAP and probe binding events were generated . The rising edges of the averaged RNAP and probe profiles were found by fitting the maxima of the respective first derivatives to second-degree polynomial , and ΔTon was calculated by subtracting the edge for probe from the edge for RNAP . The same approach was used to calculate ΔToff ( Figure 4E ) , except that video frames in which RNAP dissociated from the DNA ( Toff ) were used as references to post-synchronize RNAP- and probe-DNA dissociation events to generate respective heat maps , and to calculate weight-averaged profiles of all RNAP and probe dissociation events . To calculate the efficiency of nascent RNA detection by the probe ( Figure 4F ) , the probe dissociation heat map was used to calculate the distribution of the probe signal intensity at the last frame before RNAP dissociation . The distribution was then fit to a sum of two Gaussians using the Matlab routine nlinfit , and the ratio of the areas under the two Gaussians was calculated to give the percentage of productive RNAP-DNA interactions that contained the probe before run-off ( i . e . , the efficiency of RNA detection ) . To calculate the fraction of RNAP run-off events in which the RNA remained at the DNA locus after RNAP dissociation , the probe dissociation heat map was used to calculate the distribution of the probe signal intensity in the frame immediately after RNAP dissociation ( +0 . 4 s ) . The distribution was then fit to a sum of two Gaussians , and the ratio of the areas under the two Gaussians was calculated . To assess the decay of RNAP fluorescence signal during elongation out of the TIRF evanescent field ( Figure 3H ) , the weight-averaged profiles of all RNAP binding and dissociation events ( obtained for templates having transcribed segments of different lengths—295 , 633 , and 910 bp ) were plotted , and the edges of the RNAP dissociation profiles were manually offset in time from the edges of the RNAP binding profiles by the nearest-integer number of frames corresponding to the peak dwell time for the respective templates ( Figure 3F ) .
Transcription is an inherently stochastic , noisy , and multi-step process , in which fluctuations at every step can cause variations in RNA synthesis , and affect physiology and differentiation decisions in otherwise identical cells . However , it has been an experimental challenge to directly link the stochastic events at the promoter to transcript production . Here we established a fast fluorescence in situ hybridization ( fastFISH ) method that takes advantage of intrinsically unstructured nucleic acid sequences to achieve exceptionally fast rates of specific hybridization ( ∼10e7 M−1s−1 ) , and allows deterministic detection of single nascent transcripts . Using a prototypical RNA polymerase , we demonstrated the use of fastFISH to measure the kinetic rates of promoter escape , elongation , and termination in one assay at the single-molecule level , at sub-second temporal resolution . The principles of fastFISH design can be used to study stochasticity in gene regulation , to select targets for gene silencing , and to design nucleic acid nanostructures .
The body produces proteins by transcribing DNA ( genes ) to make messenger RNA , which is then translated to make a protein . Transcription begins when an enzyme called RNA polymerase binds to the DNA and catalyzes the process by which genetic information from the double helix is copied to a complementary RNA transcript , which subsequently becomes the messenger RNA . Because a living cell usually contains only one or a few copies ( alleles ) of a given gene , molecular fluctuations play a crucial role in cellular transcription . Therefore , studying transcription kinetics at the level of single molecules may provide critical insights into how cells deal with—or even take advantage of—molecular fluctuations . A number of different single-molecule techniques can be used to follow transcription , but these techniques are often relatively slow compared to transcription in living cells , or they suffer from other problems such as only being able to study one step in the transcription process . Now , Zhang , Revyakin et al . have systematically devised a technique called ‘fastFISH’ that is fast enough to track the production of single RNA molecules directly and instantaneously . FastFISH builds on an existing technique called FISH—short for fluorescence in situ hybridization—in which fluorescent molecules are attached to single strands of DNA or RNA . These single strands pair with specific regions of complementary DNA or RNA molecules , and they can be visualized with a fluorescence microscope . However , conventional FISH is a ‘snap-shot’ technique that is not suitable for making real-time observations under physiological conditions . FastFISH relies on single strands of fluorescently labeled DNA and RNA that bind to complementary strands of DNA or RNA extremely quickly , even under physiological conditions , because they contain only three of the four ‘regular’ nucleotides that make up DNA or RNA . As a proof of principle , Zhang , Revyakin et al . used fastFISH to study the kinetics of transcription by the bacteriophage T7 RNA polymerase and were able to measure multiple stages of the transcription cycle in a single-molecule experimental setup . By allowing each stage of transcription to be tracked in real-time at the level of single-molecules , fastFISH will permit a more in-depth analysis of the factors that regulate how genes are expressed as proteins in our cells . Moreover , the ability to design single-strand probes that bind rapidly to DNA and RNA targets could have many additional applications , including new strategies for more efficient gene silencing .