In pain management as well as other clinical applications of neuromodulation, it is important to consider the timing parameters influencing activity-dependent plasticity, including pulsed versus sustained currents, as well as the spatial action of electrical currents as they polarize the complex convolutions of the cortical mantle. These factors are of course related; studying temporal factors is not possible when the spatial resolution of current delivery to the cortex is so uncertain to make it unclear whether excitability is increased or decreased with anodal vs. cathodal current flow. In the present study we attempted to improve the targeting of specific cortical locations by applying current through flexible source-sink configurations of 256 electrodes in a geodesic array. We constructed a precision electric head model for 12 healthy individuals. Extraction of the individual’s cortical surface allowed computation of the component of the induced current that is normal to the target cortical surface. In an effort to replicate the long-term depression (LTD) induced with pulsed protocols in invasive animal research and transcranial magnetic stimulation studies, we applied 100 ms pulses at 1.9 s intervals either in cortical-surface-anodal or cortical-surface-cathodal directions, with a placebo (sham) control. The results showed significant LTD of the motor evoked potential as a result of the cortical-surface-cathodal pulses in contrast to the placebo control, with a smaller but similar LTD effect for anodal pulses. The cathodal LTD after-effect was sustained over 90 min following current injection. These results support the feasibility of pulsed protocols with low total charge in non-invasive neuromodulation when the precision of targeting is improved with a dense electrode array and accurate head modeling. Over the last two decades there has been a resurgence of interest in non-invasive transcranial electrical stimulation (TES) for the modulation of neural function in humans . In addiThe current for TES can be direct current (DC or polarizing) or alternating (AC). Direct current can be applied in intervals as an “oscillatory” or variable manner, with similar effects as transcranial direct current stimulation (tDCS) in some studies , and driExogenous current sources appear to affect neuronal excitability  in the same way as endogenous electrical fields generated by populations of active neurons , with boDespite these advances, TES as a technology can still be regarded as being in its early stages, with many issues to still be resolved . BecauseThe goal of the present research was to evaluate the feasibility of more effective neuromodulation through improving targeting precision with a number of technical advances and use of a slow-frequency pulsed-stimulation protocol. We employ the standard protocol for assessing the effects of tDCS by targeting the hand area of the primary motor cortex and use of transcranial magnetic stimulation (TMS) as the cortical excitability probe. To minimize after-effect variability that may be attributable to previous technological and methodological limitations, in the present study for each participant we (1) identify the TMS motor hotspot through use of a neuronavigation system, (2) construct a high-resolution electric head model to determine direction of current distribution at the cortical surface, (3) select the optimal scalp electrode montage for current injection based on the reciprocity theorem, and (4) use dense-sensor arrays and multiple current sources to optimize current flow to the targeted cortical region. These technological and methodological procedures enable us to account for variations in individual anatomy and ensure that the target region always has the intended radial current direction.in vivo animal work indicating that supra-threshold, low-frequency (0.5–3.0 Hz) stimulation induces LTD  pulses will produce consistent inhibitory responses, regardless of the direction of current. Moreover, based on the first hypothesis, we also examine a second hypothesis: total charge required to affect cortical excitability will be minimal, compared to levels required in previous tDCS (including pulse and oscillatory) studies.ependent , like suSD = 10) and all were right handed. No participants were excluded from the study for any reason, including non-canonical after-effect responses.Twelve participants took part in the study and completed all five sessions. Participants were recruited from Electrical Geodesics Inc. (EGI) and the University of Oregon. All participants were screened for MRI and TMS contraindications prior to acceptance into the study. Ten participants were male and the average age was 37 (SD = 11).Institutional Review Boards (IRB) at EGI and the University of Oregon approved the human subject use protocol for the present study. Prior to each session, participants provided informed consent. The study required five sessions (1 day per session) to complete. The first involved MRI acquisition and took approximately 20 min per participant. The second session involved TMS mapping to determine the location in primary motor cortex that elicited the strongest  index finger EMG response. The second session also involved application of the HydroCel GSN (HC GSN) and Geodesic Photogrammetry to determine the 3-dimensional position of each sensor (see below). After the second session, the electric head model and stimulation plan were constructed. The three remaining sessions involved either a placebo (sham), anodal, or cathodal protocol; the order was counter-balanced across participants using a 3 × 3 latin square design. Participants were informed that one of three stimulation sessions would be a placebo. Both participants and TMS operator were blind to the electrical stimulation condition for any given session. A minimum of 48 h separated the three electrical stimulation sessions  = 2.5 s; echo time (TE) = 3.4 ms; flip angle (FA) = 8°] with a 1 mm × 1 mm × 1 mm resolution covering 256 voxels in each spatial direction. Data were acquired in Siemen’s 3T Skyra  scanner using a 20-channel, head-neck coil. Sequence time was approximately 10 min. Foam padding was used to minimize head movements, and all participants were highly cooperative.Transcranial magnetic stimulation was accomplished with the Brainsight neuronavigation system  and the STM9000 TMS system . Each participant’s T1 MRI data was used in the Brainsight system to reconstruct the scalp surface. The scalp surface was registered with the participant’s head for each TMS session. A figure-of-eight coil  was used and all stimulation employed a monophasic pulse. Motor evoked potentials (MEP) were recorded from the right first dorsal interosseous (FDI) muscle with Ag-Ag Cl electrodes arranged in the belly tendon montage and connected to Brainsight’s integrated EMG module. The MEP signal was bandpass filtered between 16 and 470 Hz, amplified by 4444, and digitized with a 12 bit ADC at a 3 kHZ sampling rate.Figure 1A.To identify the location that elicited the strongest index finger response, the cortical surface was characterized with Brainsight’s curvilinear reconstruction method, and the hand region was identified using anatomical landmarks . Once thSD = 0.35).Resting motor threshold (rMT) was defined as a percentage of TMS power output required to elicit MEP amplitudes of 50 μV in 5 out of 10 stimulation pulses, and this was determined with the hand and fingers in the relaxed state. Baseline MEP was specified as the TMS power output of 130% of rMT and the MEP amplitude (peak-to-peak) was specified as the average MEP amplitude of 10 stimulation pulses (each separated by at least 6 s). On average, this translated to 75% of maximum machine output. In certain participants, 130% of rMT still produced MEPs that were below 1 mV. In order to allow MEP decrement due to TES , in these participants TMS power was increased to achieve an MEP average of 1 mV over 10 stimulation pulses. In some participants, 1 mV MEP could not be obtained even as we increased the power output up to 87%, and we accepted the MEP amplitude at 87% (arbitrarily set limit) as the baseline. On average, this was equal to 122% of rMT in these participants. Across the 12 participants, the average baseline MEP amplitude across all three sessions (see Procedure) was 0.97 mV : eyeball, flesh, skull, cerebral-spinal fluid (CSF), gray matter (GM), white matter (WM), and air. Because the skull is the most electrically resistive tissue, it is important to model, and yet bone can not be accurately obtained from MRI data. To estimate the skull, an atlas skull model derived from CT (1 mm × 1 mm × 1 mm) was non-linearly warped to the participant’s MRI tissues (using the other tissues as a guide). Detailed information about tissue segmentation and CT warping procedures is described in 2 in size. For each patch, perpendicular directions of vertices within the patch were averaged to derive the average, perpendicular orientation for that cortical patch. This average, perpendicular orientation is used to describe the direction of current flow. Electrode sensor positions of the 256-channel HC GSN 100  were digitized using the Geodesic Photogrammetry System .To describe current flow from the cortex to the scalp, the cortical surface was first characterized through the use of triangular meshes, which were then parceled into patches of approximately equal size. All models used in the present study contained 1200 dipole patches per hemisphere, with each patch ∼1 cmFrom the complete head model, a lead-field matrix (LFM), which describes the propagation of current from each cortical patch to each sensor position, was computed using the finite difference method FDM, . The folPresent approaches to targeting the primary motor cortex with TES employ the standard M1-contralateral supraorbital placement with two large electrode patches. This standard placement is a limitation because current paths and cortical distribution are estimated based on scalp placement, but the spatial relation between electrode on the scalp and underlying cortex does not accurately characterize current flow through the head. Therefore, this approach can not ensure that current will be optimally delivered to the intended target. Accurate head models are required for selection of optimal current injection electrodes for each individual . In the In order to select the optimal current injection electrode montage and determine the appropriate amount of current to deliver through each of the active electrodes for a given target, we rely on the Lorentz reciprocity relating current densities at differing points and their electromagnetic fields in a complex resistive volume in the Rayleigh-Carson formulation, which assumes that all current sources have compact support (for detailed information see 2) was limited to 200 μA. Given the weighting scheme described, this resulted in variable total current for each participant  given the set number (eight) of electrodes. The average current density across all electrodes and participants is 0.15 mA/cm2 (SD = 0.02). Two examples from this procedure are illustrated in Figure 2.In the present feasibility study, we used a 16 channel prototype of the GTEN 100 system, such that the total number of electrodes used for each participant was eight anodes and eight cathodes. Maximum current at any given electrode  with the 256-channel HC GSN 100, which is an evenly spaced network of Ag-Ag Cl electrodes. The GTEN 100 has a double-fault Sentinel Circuit®, capable of maintaining the designed balanced source-sink configurations over time.With targeting formulated mathematically through use of the reciprocity principle (as described above), the targeting is achieved in GTEN 100 via hardware that drives multiple constant current circuits to be balanced in the presence of multiple electrode impedances that are changing in time . GTEN uses a proprietary balancing circuit, the AccuCharge CircuitElefix conductive paste  was mixed with over-the-counter lidocaine cream (5%) and used as the conductive material between the electrode and scalp. All electrode starting impedance were below 100 KΩ. Due to the iontophoretic mechanisms , lidocaiCathodal and anodal stimulation used the same electrode montage for each participant with current direction reversed. In addition to cathodal and anodal stimulation, a placebo condition was also employed in the present research. To minimize current flow to the targeted region while still maintaining potential for sensory perception associated with current flow in the placebo condition, stimulation used the same anodal-cathodal electrode clusters employed in the non-placebo conditions with the following modification. First, within each anodal and cathodal cluster, the electrode with the lowest current level used in the actual stimulation conditions were selected and the closest electrode neighbor was used to pass current. Therefore, in each cluster there was one pair (one anode and one cathode), and current  passed through these pairs are prevented from penetrating deeply to affect the targeted region. Second, current was only delivered for five pulses (over 10 s) to further reduce the likelihood of any charge accumulation in the targeted brain region.In sessions 2–5, participants were seated comfortably in a TMS chair . Across sessions 2–5, participants were always scheduled for the study at the same time of day. Sessions 3–5  started with the determination of MEP baseline followed by application of the Sensor Net and electrode-scalp impedance verification of the 100 KΩ threshold . Application of the Sensor Net in sessions 3–5 was guided by sensor positions in the 11 GPS images acquired in the second session (hotspot mapping). The GPS images provide 11 different views of the Sensor Net on the participant’s head. Following this procedure ensures that the sensors for a given session maintains the original sensor positions used to create the head model and stimulation plan.Each electrical stimulation session (including placebo) started with a 30-s direct current conditioning period in one direction followed by another 30 s period in the opposite direction to facilitate the uptake of lidocaine through iontophoresis. The current level for each electrode was 50 μA . This brief duration of stimulation (with 1 mA) has been shown not to significantly affect neuronal excitability . Next, cParticipants were asked if they felt sensations  during the direct current conditioning period, and during the pulse stimulation, participants were also asked if they felt any sensation at the following intervals: at start of stimulation and 4, 9, 13, and 17 min after start of the pulse stimulation. Upon cessation of stimulation, the HC GSN 100 was quickly removed (about 15–30 s) and TMS MEPs were immediately sampled followed by measurements at 5-min intervals for 30 min and at 60 and 90 min. Between the immediate to 30 post-stimulation measurement interval, participants remained seated in the TMS chair. After 30 min, participants were allowed to leave the room and return for the two remaining intervals. At each measurement interval, 12 stimulation pulses (separated by at least 6 s) were applied and the smallest and largest MEP amplitudes were excluded prior to averaging the remaining 10 MEPs.None of the participants reported adverse effects from participation in the study. Across the 72 (12 participants × 3 sessions × 2 polarities), 30-s current condition blocks , participants reported sensations in 67 conditioning blocks. During pulse stimulation, participants reported feeling sensations in 21 blocks at the start of stimulation, 12 blocks after 4 min of stimulation, eight blocks after 9 min of stimulation, eight blocks after 13 min of stimulation, and three blocks after 17 min of stimulation. These data show that the conditioning period used for lidocaine delivery was effective in reducing sensations produced by the current by approximately 33%, and after 4 min of pulse stimulation, sensation was eliminated in approximately 66% of the sessions. By the end of the study, only one participant continued to report any sensation; this participant continued to experience slight sensations in all three sessions (including placebo). However, in the placebo session, pulses were only delivered for the first 10 s. No other participant reported sensations in the placebo session beyond the 1st minute after stimulation.Figure 2), suggesting that they experienced retinal phosphenes. All of these three participants also correctly identified the placebo condition. An additional five participants were also able to identify the placebo condition; only four participants were not able to identify it.Only three participants reported experiencing phosphenes during pulse stimulation, and then only during anodal and cathodal sessions (and not for placebo). In these participants, the current injection electrode configuration included more frontal electrodes  but rather by the direction of current at the cortical surface of the target region as determined by each participant’s head model. Therefore, there is no ambiguity concerning cortical current direction, as would be the case without a model and the ability to optimize the stimulating electrode configuration.Figure 3 shows the average MEP (as a percentage of the baseline MEP) for each condition. Consistent with our hypothe sis, over the post-stimulation course MEP amplitude for both cathodal and anodal stimulation protocols were reduced compared to placebo, with cathodal stimulation producing a larger reduction. Based on our hypothesis, we performed two one-tailed, paired t-test comparisons across the entire post-stimulation period: Anodal vs. Placebo and Cathodal vs. Placebo. The results showed that the difference between anodal stimulation and placebo was not significant, although the mean MEP amplitude after anodal stimulation also decreased  relative to placebo . In contrast, cathodal stimulation produce a significant reduction  compared to placebo, t(11) = -2.41, p < 0.02. To explore the time course of the cathodal stimulation effect, we compared the post-stimulation MEP amplitude against MEP placebo amplitude for 0–30 and 60–90 min intervals. Paired t-test revealed that the difference was significant for the 0–30 min interval, t(11) = -2.26, p < 0.03, and 60–90 min interval, t(11) = -2.43, p < 0.02. As can be seen in Figure 3, the placebo condition showed a large increase at 60 and 90 min. Examination of the data showed that this increase was mainly due to one participant . Therefore, we performed an analysis of the 60–90 min interval with this participant excluded to confirm the result. The paired t-test result showed that with this participant excluded, the effect is still significant, t(10) = -2.17, p < 0.03.Figure 4 shows the average MEP  change relative to baseline for each participant. Of the 12 participants, eight demonstrated MEP amplitude decreases after cathodal stimulation in comparison to the placebo condition. The MEP response to anodal stimulation is more variable, with only five participants showing an amplitude reduction relative to placebo.Figure 4, relative to the baseline, in our sample there are a total of 10 participants who have inhibitory responses. Given the sample size, we computed an exact goodness-of-fit test. The test revealed that the observed distribution  is indeed significantly different, p < 0.01 (one tailed).To test whether the cathodal stimulation produced more consistent inhibitory responses than conventional low spatial resolution methods, we compare our results to those reported by p < 0.004 (one tailed).We also performed an exact goodness-of-fit test to determine whether the number of participants showing an inhibitory response to anodal stimulation differed from the 26% reported by Table 1). A previous study by A second hypothesis was that total charge is not the critical factor for determining the effect of TES. Given the present study’s stimulation protocol, the total stimulation time (100 ms at 0.5 Hz over 17 min) is 51 s and the total charge is 59.16 milli-coulombs  is greater than those used in previous studies, it is important that participants did not report uncomfortable sensations during the conditioning period (before lidocaine became effective at reducing sensations). The time-course of reported sensations showed that lidocaine became increasingly effective at reducing reports of sensations. It is expected that with constant current (rather than tPCS), the time course would be accelerated because of a more sustained iontophoretic application of the lidocaine.Participants in the present feasibility study did not report any adverse side effect from the tPCS protocol using the dense-array electrode configuration. Given that the current density for the electrode with the maximum current  after lidocaine application would minimize sensation. In the present experiment, 8 out of 12 participants correctly guessed the placebo condition, but this was due in part to the greater experience of phosphenes during tPCS compared to the placebo condition.2+ flux, which is controlled via voltage gated channels, into the postsynaptic cell  of the cortex is relevant for the induction of LTD by slow pulses. In this regard, the anodal and cathodal pulses were not equivalent, suggesting polarization with respect to the cortex is important. The observation of relatively weak anodal after-effects has been reported previously in several studies with tDCS. In a study by Transcranial current delivery produces diffuse current flow and thus affects synapses and cells distributed across all cortical layers  and over2+ influx, it is important to consider a regulatory mechanism [Ca2+-activated small conductance (SK) channels] at the dendritic spine that prevents over activation produced by Ca2+ influx. 2+ flux in dendritic compartments and the interaction with Ca2+ levels in the soma must be considered for a complete picture of how long term plasticity is induced. Although this interaction is not fully understood at present, it may be that the more powerful effect of cortical-surface-cathodal current on the dendritic region may explain why this direction of polarization is more effective in producing both tDCS and tPCS after-effects.Recognizing that LTD and LTP effects are mediated by Ca2+ flux) in the apical compartments. The summed effect reflects plasticity changes centered on the somatic compartment . For surface-cathodal current, changes occur primarily in the apical compartment, and the soma’s integration of activity is affected by the polarized state induced by a cathodal electric field. Because the effects are primarily in the apical dendritic compartment, surface-cathodal current may be more effective due to the dense distribution of plasticity inducing mechanisms (such as mGluR1 and SK channels) in this compartment. Consistent with this reasoning is the observation that only cathodal tDCS significantly modulates TMS input-output curves  is not of the desired polarity. Additionally, given the demonstration of non-linear effects of total charge on after-effects direction , the ina2+ influx, which in turn affects the cascade of neurophysiological events that induce LTD. In the present feasibility study, we did not manipulate these factors separately, so we cannot determine the extent to which these three variables contributed to the reduced variability.In the present study, we observed greater consistency of LTD across participants. By employing the reciprocity principle between EEG and TES with high resolution subject-specific head models, the optimal stimulating electrode montage was always individually adjusted such that current delivered to the motor cortex hotspot was maximized radially. Because of the very nature of the low-frequency pulsed protocol, total charge is relatively low. Moreover, low-frequency stimulation is a well-established protocol for inducing LTD because it directly affects the rate of CaTables 1 and 2, results from prior tDCS and so-tDCS studies suggest that total charge is important to the after-effects. In tDCS, low total charge produces little to no significant after-effects. In the so-tDCS study, We also predicted that total charge is not the critical factor in determination of the effectiveness of tPCS, and that brief pulses would be adequate. As shown in The explanation proposed by In the present research, we demonstrated feasibility of a pulsed protocol with low current when high resolution modeling of cortical targeting is employed, yet we did not include experimental manipulation of each of the potentially contributing factors. Future studies will be required to clarify the contribution of each variable. Although we showed that very low total charge can still induce significant after-effects, it is still possible that there exists a relation between total charge and magnitude as well as duration of after-effects using a tPCS protocol. Future studies should address this possibility. We, as well as By considering the greater concentration of plasticity mechanisms at dendritic spines rather than at soma levels, we have suggested a model to understand the effects of the direction of polarization on cortical excitability that generates testable predictions. For example, one prediction is that faster frequency stimulation, known to induce LTP, will also show greater facilitation for cathodal stimulation pulses.In this feasibility study, we were able to implement a number of improvements in the spatial targeting of cortical-surface-normal electrical current to the specific finger motor area of each participant, and to observe that the slow pulse electrical stimulation was effective for the induction of LTD. As hypothesized, LTD was achieved with much lower total charge levels than are required for tDCS protocols. Although not significantly different from placebo in this sample of 12 participants, 0.5 Hz anodal tPCS also reduced cortical excitability. The consistency of reduced cortical excitability was greater across participants than has been reported in previous research. Finally, we proposed a model for how to understand the apparent asymmetry of anodal and cathodal stimulation effects of tDCS and tPCS. For non-invasive TES to contribute maximally to clinical applications particularly, it is clearly important to understand how to achieve reliable induction of cortical plasticity in each person.PL, EMEA, and DT contributed to the design of the study. DT, EA, and ST contributed to the design of the Reciprocity algorithm. DR designed of hardware system for current injection. EMEA, AG, and PL were responsible for data acquisition and analysis. All authors contributed to the interpretation of the results and preparation of the manuscript. All authors acknowledge that they are accountable for all aspects of the work.Authors of this paper are employees of a commercial EEG company, Electrical Geodesics, Inc., and EGI holds several patents for technologies used in the present research including: US Pat. No. 7,840,250, No. 6,594,521, No. 7,190,826, and 8,478,011.


HMS2, encoding a growth-regulated transcription factor, switches between sense- or antisense-dominant states that also coordinate up- and down-regulation of transcription at neighbouring genes. Engineering HMS2 reveals alternative mono-, di- or tri-cistronic and antisense transcription units (TUs), using different promoter and terminator combinations, that underlie state-switching. Promoters or terminators are excluded from functional TUs by read-through transcriptional interference, while antisense TUs insulate downstream genes from interference. We propose that the balance of transcriptional insulation and interference at gene clusters facilitates gene expression switches during intracellular and extracellular environmental change.In yeast, many tandemly arranged genes show peak expression in different phases of the metabolic cycle (YMC) or in different carbon sources, indicative of regulation by a bi-modal switch, but it is not clear how these switches are controlled. Using native elongating transcript analysis (NET-seq), we show that transcription itself is a component of bi-modal switches, facilitating reciprocal expression in gene clusters. DOI:http://dx.doi.org/10.7554/eLife.03635.001 A DNA double helix is made up of two DNA strands, which in turn are made of molecules that are each known by a single letter—A, T, C, or G. The sequence of these ‘letters’ in each DNA strand contains biological information.Genes are sections of DNA that can be ‘expressed’ to produce proteins and RNA molecules. To express a gene, the DNA strands in the double helix must first be partially separated so that one of them can be used as a template to build an RNA molecule in a process called transcription. Either of the DNA strands in a helix can be used as an RNA template, but contain different genes and are read in opposite directions. One of the two strands is called the ‘sense’ strand, the other the ‘antisense’ strand.The RNA molecule does not transcribe a whole DNA strand; instead, it transcribes a section of DNA, known as a transcription unit, which contains at least one gene. The end of a transcription unit is marked by certain signals that stop transcription. However, some transcription units in a DNA strand overlap, so there must be some way that the transcription machinery can sometimes ignore these stop signals.The activity of some genes is linked to the activity of their immediate neighbours. Furthermore, some genes are expressed in different amounts in response to changes in environmental conditions. Researchers have previously suggested that there must be some form of switch that controls when these genes are expressed.HMS2 and BAT2, in yeast. When one gene is switched on, the other is switched off and which gene is active depends on the diet of the yeast cells.Nguyen et al. now engineer start and stop signals at a neighbouring pair of genes, called HMS2 is another gene, SUT650. Nguyen et al. show that when this gene is transcribed, the transcription of HMS2 on the other DNA strand is blocked. This has the knock-on effect of turning on BAT2. Conversely, transcribing HMS2 switches off SUT650 and BAT2 because the end of HMS2 overlaps with the beginning of both SUT650 and BAT2. Switching between different genes relies on loops that physically link the start and stop signals of the gene to be transcribed while ignoring the start and stop signals for neighbouring genes.On the antisense DNA strand opposite to HMS2 gene helps to control which DNA strand is transcribed. When transcription factors do not bind to the start of HMS2, antisense transcription—and the expression of SUT650—occurs instead.Proteins called transcription factors can bind to DNA and affect whether a gene is transcribed. Nguyen et al. found that a transcription factor that binds near the start of the Overall, Nguyen et al. show that the transcription process itself makes up part of a switch that can control the expression of several genes on both the sense and antisense strands of a DNA double helix. This may also explain how many other, more complex, gene networks are activated in response to changes in the environment.DOI:http://dx.doi.org/10.7554/eLife.03635.002 Saccharomyces cerevisiae has revealed an extensive array of coding and non-coding transcripts, giving rise to a genome that is heavily interleaved. Individual genes can possess multiple, overlapping transcripts, in the sense and the antisense orientations with respect to the pre-mRNA, as well as poly-cistronic transcripts, which span neighbouring genes , co-expression of clustered genes in S. cerevisiae is largely independent of similarly controlled transcription, gene orientation, and/or shared regulatory sequences. However, members of adjacent gene pairs or clusters are more likely to belong to the same functional pathway than expected by chance - to galactose (GAL)-containing media and show a remarkable enrichment for genes whose transcripts cycle during the YMC. The majority of these genes have no functional associations with transcription factors that might mediate repression or induction in GLU or GAL, but are organised in clusters and subject to overlapping sense and antisense transcription. We exemplify this mode of gene regulation, state-switching by transcriptional interference and insulation, at the + RNA, we show that for the majority (≈88%) of genes, the change in transcript levels on the GLU to GAL shift reflects altered transcription rather than altered transcript stability (−5) for OX phase genes that are mainly involved in ribosome biosynthesis and growth (−5) for genes whose expression peaks in the reductive charging phase (RC) of the YMC  to galactose-containing media (GAL) for 3 h and analysed the native transcripts associated with elongating RNA polymerase II (NET-seq)  to identtability . Gene ontability . The gend growth . By cont the YMC . These g the YMC . In addi the YMC  and 25.7 the YMC .10.7554/We used a computer simulation to obtain the expected number of occurrences of genome-wide features, by randomly shuffling genes, their orientation, YMC status, and expression levels . BAT2 transcripts peak in the RC phase of the YMC and in GAL, reciprocal to HMS2 sense transcripts, which peak in the OX phase of the YMC and in GLU (HMS2 and its antisense SUT650 (transcripts A and B respectively). Dual-labelled RNA FISH revealed a degree of temporal separation in the production of the HMS2 and SUT650 transcripts. In multiple analyses, no examples of FISH signals for both HMS2 and SUT650 at the site of transcription in the nucleus are observed in either GLU or GAL. Cells with nascent transcripts  on the HMS2 sense strand extending through the coding region of BAT2 and beyond, consistent with low-level read-through transcripts initiating at the HMS2 promoter (rrp6Δ) (HMS2 is at the head of a contiguous gene cluster including the downstream genes BAT2 and YJR149W (HMS2 transcript is of variable length. Polyadenylation (pA) occurs either 85 nt  or 426 nt  downstream from the HMS2 stop codon. The distal pA site is 45 nt upstream of the BAT2 initiation codon, such that this longer transcription event is likely to interfere with initiation of BAT2 transcription. Additional transcriptional interference might be mediated through the production of the longer HMS2-BAT2 di-cistronic RNA species.A number of different methods revealed heterogeneity at both the 5′ and 3′ ends of the promoter . These r (rrp6Δ) . Thus HM YJR149W . The 3′ HMS2 and BAT2 supports (i) an overlapping, reciprocally related and temporally segregated, sense–antisense pair (SAP) at HMS2, (ii) reciprocally expressed sense transcripts at HMS2 and BAT2, and (iii) low-level read-through di-cistronic transcripts (HMS2:BAT2 and SUT650:RPS4A). We ask if overlapping transcription in the sense and antisense orientations at HMS2 contributes to the reciprocal regulation of HMS2 and BAT2, by dissociating one transcription unit from the other.In summary, analysis of transcripts around ADH1 transcription terminator (ADH1t) into the middle to HMS2, to separate HMS2 transcription from BAT2, allows us to test directly whether the HMS2 sense transcription over the HMS2:BAT2 intergenic region represses BAT2 transcription (ADH1t efficiently terminates the HMS2 transcript (HMS2 3′ region (ADH1t inserted showed a ≈twofold increase in BAT2 transcript levels compared to WT in both GLU and GAL (HMS2 sense transcription in repressing the BAT2 promoter. We conclude that HMS2 sense transcription interferes with BAT2 transcription.Insertion of the cription . We confanscript  and that′ region . The str and GAL  supportiADH1t into the HMS2 coding region resulted in a ≈fourfold increase in levels of a truncated HMS2 sense transcript (AA)    and blocipt (BA) . We confA)  for SUT650 located between +953 and +1038 relative to the HMS2 ATG, near the end of the HMS2 coding region. We chose to do this by substituting the complete coding region of HMS2 with that of URA3, to ensure a natural ORF between the HMS2 promoter and terminator, rather than mutating the regions containing multiple TSSs for SUT650 within the ORF  relative to the HMS2:URA3 sense transcript (AU) (HMS2:URA3 hybrid gene (UT) (HMS2 promoter remain sensitive to a change in carbon source in the absence of antisense transcription (HMS2:ADH1t (see 1U) relative to the HMS2:URA3 sense transcript (AU) in the absence of antisense transcription suggests a role for antisense transcription in attenuating sense transcription and preventing interference at the BAT2 promoter. Consistent with this, a twofold decrease in BAT2 sense transcript is observed in the antisense-less HMS2:URA3 strain relative to WT in GLU, concomitant with a threefold increase in AU and C1U  analysis at the HMS2:BAT2 intergenic region reveals reduced initiation-related modifications (H3K4me3 and H3K56ac) and increased elongation-related modifications (H3K79me3 and H3K36me3) in the HMS2:URA3 hybrid gene, consistent with transcriptional interference leading to repression of BAT2 transcription initiation (SUT650 antisense transcription (i) changes the proportion of cells expressing HMS2 and (ii) controls the amount of overlapping and read-through transcription from HMS2 and thus levels of BAT2 transcript. We envisage that at any one time in a single cell, formation of the HMS2 and SUT650 transcription units (TUs) is mutually exclusive, but the formation of the SUT650 TU and the BAT2 TU is not. Thus formation of the SUT650 transcription unit insulates BAT2 from interference by HMS2 transcription, as the HMS2 TU cannot form when SUT650 is expressed.Next, we asked whether transcription of  the ORF . We notetability , so we fr SUT650 . Second,ipt (AU) . We confrid gene  and obseene (UT) . We notecription , as we oDH1t see  and cons and C1U . Taken t and C1U  or incre and C1U  HMS2 traitiation . We concHMS2 transcription influences SUT650 antisense transcription, we replaced the HMS2 promoter with the inducible GAL1 promoter (pGAL1)  is evident in GLU and remains until the sense transcript is induced by GAL  and leads to restoration of the antisense transcript (BG) , a region transcribed in both constructs. No changes in induction rate were apparent, with the sense transcript only detectable after 2 h in both strains, signifying that antisense transcription does not impair sense activation kinetics  . When cualactose . SUT650 hift see . Howeverd by GAL . This suechnique  to depleipt (BG) . This copromoter . The senkinetics . Rather,kinetics . Activat of BAT2 , consisttose see . We concGAL1:HMS2; a long species (BG1), dominant until 30 min after the shift to GAL, and a shorter species (BG2), also detectable after 30 min of growth in GAL and which becomes the dominant antisense transcript form after 1 h  in the cbf1Δ and fkh1Δ strains   in a gln3Δ strain in minimal medium (HMS2 promoter (Input) to mediate state-changing (antisense-dominant to sense-dominant) in response to environmental conditions  at promoters of RC and OX genes, using a large data set of 202 factors   and durifactors) . We ablas)  (HMS2 (A), BAT2 (D), and SUT650 (B) transcripts, as expected upon depletion of an essential transcription factor. To explore this further, we used a well-characterised allele of SUA7 (sua7-1) (E62K) (HMS2 transcript (A) and sense read-through transcripts (C), coupled with a decrease in the SUT650 antisense transcript (B)  . However) (E62K) , associa) (E62K) . Remarkaript (B) . Thus, Tript (B) . For insHMS2 locus was engineered by insertion of the pTEF.KanMX.TEFt expression cassette (HMS2:TEF:Kan), there are two promoters in tandem (HMS2 and TEF) and two terminators in tandem (TEF and HMS2). This is sufficient to disrupt the HMS2 and SUT650 transcription units. The SUT650 antisense promoter is functional and produces a truncated antisense transcript (BK) that ends in the vicinity of TEFt , the sense transcript from pTEF, expressing the kanamycin resistance (KanMX) transcript (K), and the sense transcript (AK) initiated at the HMS2 promoter and terminating at TEFt  and considerably reduced levels of antisense transcript (E) (The cassette  at positcassette . In this of TEFt . Thus TE at TEFt . pTEF iscterised  strong b of pTEF . This reript (E) .10.7554/TEF promoter, we would be able to ask how disabling pTEF affects the HMS2 and SUT650 transcription units. Using the HMS2:TEF:Kan construct as a starting point, mutations were introduced into the TEF promoter, including deletions of putative transcription factor binding sites (HMS2.TEFdel1:Kan), removing all the TEF promoter sequences upstream of the TATA box, results in a significant reduction in expression of the KanMX cassette itself (transcript K) and in levels of the antisense transcript (E) (HMS2 that reads through TEFt (BpTEFdel)  the remarkable plasticity of interleaved transcription units. We suggest that the pTEF.KanMX.TEFt expression cassette is strongly expressed  . RemarkapTEFdel) . We confAS probe . Thus, tpromoter . This ext genome .HMS2 and BAT2 that combines the effects of temporal separation, overlapping interfering transcription able to bypass typical termination and promoter signals, and insulation from interference by the formation of an antisense transcription unit . Moreover, antisense transcription arising from divergent promoters may have to bypass the terminator of the upstream gene. This work indicates the capacity of a terminator to function is conditional on the strength of the proximal promoter. We suggest that this reflects the role for promoters in defining the beginnings and ends of TUs ; strongesua7-1 allele. A simple scenario in which 3′end TFIIB directs transcription by promoting both antisense transcription and physically terminating sense transcription is compatible with the interference/insulation model proposed here. It is also plausible that alternative higher order structures linking the sense or antisense promoters to one of a possible number of terminators could also explain dynamic state-switching between sense and antisense or multi-cistronic transcripts  and FKBP12 Rapamycin binding (FRB) domain of human mTOR protein in order to deplete target proteins from the nucleus in a time-dependent manner . Native elongating transcript sequencing, (NET-seq) was done and analysed as described in In Situ hybridization (FISH) protocol was adapted from hms2Δ cells to determine threshold signal for expression. Images displayed as 2D compressions of z-stacks 12–22 (11 stacks), which included most of the nucleus and cytoplasm. Error bars represent standard error of the mean. Chromatin immunoprecipitation (ChIP) was performed as described by All experiments were performed at least in duplicate to ensure that the trends observed were reproducible. Briefly, unless otherwise stated, cells were grown to exponential phase in rich medium (YP) supplemented with 2% glucose (YPD) or 2% galactose . The strains of t manner . Control review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent , a Reviewing editor, and 3 reviewers.Thank you for sending your work entitled “Transcription mediated insulation and interference direct gene cluster expression switches during biological rhythms” for consideration at eLife after addressing the concerns listed below.After a thorough discussion, the consensus among the reviewers and the editors was that this is an excellent paper reporting some remarkable findings, which would be worthy of publication in The metabolic cycle has emerged as a fundamental biological phenomenon that is critical for proper cell function. It has been appreciated that oxidative conditions are in conflict with reducing reactions, and vice versa. Consequently, cells have evolved mechanisms to temporarily separate these conflicting conditions, by oscillating both the oxygen consumption as well as the expression of ∼3000 genes. The remarkable precision of the synchrony in maintaining oscillating levels of mRNAs must involve intracellular events and communication, the basis of which remains obscure. This paper provides some solutions to this enigma by demonstrating how transcription of tandemly arrayed genes can regulate a bi-modal switch so that activation of one gene would repress the other and vice versa. This paper will serve the scientific community in various aspects. First, it will drive the attention of the readers to the complexity of the YMC, an issue that is still underrepresented in the literature. Second, it illustrates the critical roles played by transcription terminators in both terminating transcription and initiating transcription in the anti-sense direction. Third, transcription of anti-sense (AS) as a key modulator of gene expression, in general, and its involvement in the bi-modal switch, in particular. Fourth, and most importantly, the paper demonstrates, in many ways, the intricate relationship between transcription of sense, anti-sense and neighbouring genes in a manner that supports the bimodal switch.The major concerns raised by the reviewers are:1) Generality of findings. The impact of this work would certainly be higher upon defining the prevalence of the key regulatory mechanisms described. The paper focuses on two tandemly arrayed genes (HMS2/BAT2) whose expression switches during the YMC. They provide a detailed mechanism of the switching whereby transcription read-through into the downstream promoter downregulates transcription of the downstream gene and how AS transcription is involved. Their conclusion that the sense and AS transcription are in conflict, and that cells tend to separate the “sense state” from the “AS state” temporarily is by itself remarkable. However, how general is this mechanism? What fraction of YMC-regulated genes is adjacent or anti-sense? More than expected by chance? And then what fraction of adjacent or anti-sense transcripts is co-regulated in the YMC? Moreover, if the mechanism is more prevalent than just HMS2/BAT2, do the anti-sense transcripts always fall into opposite YMC categories, i.e., oxidative vs reductive? Is this locus even representative of other glu-gal clusters? If 10 loci are chosen at random , do the neighbouring genes show potent regulation like the one well-explored region? Reviewers agreed that a more global assessment of the prevalence of the mechanism described would raise the impact significantly. However, it was noted that the bioinformatics involved for a global analysis would not be trivial. Thus, reviewers request that the authors manually mine the NET-seq data regarding transcript isoforms (like the data shown in 2) Weak links to YMC and circadian rhythms. Although the reviewers appreciated the novelty and elegance of the molecular mechanisms discovered, there was agreement that in its current form the manuscript does not make a convincing argument about general relevance to YMC or circadian rhythms and it was agreed that the writing, including the title, should be tempered to focus more on the mechanistic aspects and less on the YMC and circadian biology. It is proposed that the title be changed to “Transcription mediated insulation and interference direct gene cluster expression switches”.3) The choice of sua7-1 is not well communicated. The reader of the “Results” section is puzzled why TFIIB was chosen to begin, and why this specific allele was used, in particular. Only in the Discussion the reader learns that sua7-1 is defective in loop formation.4) 5) The replacement of HMS2 ORF with URA3 requires some clarifications. Why didn't the authors simply remove the region around the TSS, leaving all other sequences unchanged? Why did they prefer to introduce the entire URA3? There are two issues that need to be addressed. (1) The possibility that URA3 sequences, in both orientations, introduce stability biases onto the RNAs. (2) The possibility that the URA3 sequence contains a terminator in the AS direction, explaining why the AS RNA was not detected by H1 probe, located downstream of this hypothetical terminator. These issues can be discussed or addressed experimentally.6) In  1) Generality of findings. The impact of this work would certainly be higher upon defining the prevalence of the key regulatory mechanisms described.We agree with the reviewers about this point and had, in fact, already embarked on a computational genome-wide analysis. Part of this very large dataset has been analysed for this work and is presented in the revised version of the paper.The paper focuses on two tandemly arrayed genes (HMS2/BAT2) whose expression switches during the YMC. They provide a detailed mechanism of the switching whereby transcription read-through into the downstream promoter downregulates transcription of the downstream gene and how AS transcription is involved. Their conclusion that the sense and AS transcription are in conflict, and that cells tend to separate the “sense state” from the "AS state" temporarily is by itself remarkable. However, how general is this mechanism?PHO84 . We also have as yet unpublished evidence that at GAL10, the sense and antisense transcripts are present in different cells during early induction. Given the FISH evidence for YMC regulated genes from the Singer and Botstein labs, we think that switching is likely to be common.From the point of switching sense and antisense states there is now one experiment in a recent paper from the Zenklusen lab supporting the idea of separation of the sense and antisense states in individual cells, in this case at What fraction of YMC-regulated genes is adjacent or anti-sense? More than expected by chance? And then what fraction of adjacent or anti-sense transcripts is co-regulated in the YMC?We have data in the revised manuscript addressing these issues (Tables S5 to S9). The antisense question is hard to address adequately due to the relatively poor annotation of the antisense transcriptome – being limited to CUTs and SUTs. There are 1772 annotated CUTs and SUTs but much more transcription antisense to genes is evident from the NET-seq analysis. A separate analysis suggests that 75% of all yeast genes are subject to some antisense transcription in the vicinity of the sense promoter that influences the chromatin organization around that promoter. Nevertheless, our analysis for this work suggests that YMC genes are much more likely to have antisense transcription, although the number of genes is relatively small because of the high thresholds (>3-fold change in GLU/GAL both the YMC gene and the SUT or CUT). 71 of the 206 genes (34.4%) with regulated sense and antisense have SUTs/CUTs whose transcription also changes 3-fold in the GLU/GAL shift. 26% of all SUTs and CUTs show a >3-fold change on the GLU/GAL shift. Thus regulated SUTs and CUTs are enriched opposite to ORFs that also show a > 3-fold shift.Moreover, if the mechanism is more prevalent than just HMS2/BAT2, do the anti-sense transcripts always fall into opposite YMC categories, i.e., oxidative vs reductive?HMS2.BAT2), 9 (90%) of the OX genes have an antisense (annotated or not) that shows reciprocal transcription to the OX gene.Our selected gene study shows that for the 10 OX.RC tandem genes , do the neighbouring genes show potent regulation like the one well-explored region?Yes, see Table S9 and Reviewers agreed that a more global assessment of the prevalence of the mechanism described would raise the impact significantly.I hope that we have persuaded the reviewers that this is likely to be a more general phenomenon.However, it was noted that the bioinformatics involved for a global analysis would not be trivial. Thus, reviewers request that the authors manually mine the NET-seq data regarding transcript isoforms (like the data shown in) and examine whether transcription of one gene invades the promoter of its neighbouring gene, and whether the AS transcription is anti-correlated. The control should be the same number of tandemly positioned gene pairs that are chosen at random. If the authors have the bioinformatic means to take a whole genome view, all the better.We have used both approaches to provide the data in order to conclude this is a wider phenomenon.2) Weak links to YMC and circadian rhythms. Although the reviewers appreciated the novelty and elegance of the molecular mechanisms discovered, there was agreement that in its current form the manuscript does not make a convincing argument about general relevance to YMC or circadian rhythms and it was agreed that the writing, including the title, should be tempered to focus more on the mechanistic aspects and less on the YMC and circadian biology. It is proposed that the title be changed to “Transcription mediated insulation and interference direct gene cluster expression switches”.We are happy to do this and have removed this from the title and tempered our references to these mechanisms in the text.3) The choice of sua7-1 is not well communicated. The reader of the “Results”" section is puzzled why TFIIB was chosen to begin, and why this specific allele was used, in particular. Only in the Discussion the reader learns that sua7-1 is defective in loop formation.We agree with this point and have included more details in the Results section.4)shows that the insertion of ADH1t abolished the signal detected by probe H2.This is correct for the H2AS probe.From the point of view of the AS transcription, this probe is located downstream of ADH1t.This is correct.The authors concluded that ADH1t blocks SUT650 AS transcription. However, it is possible that ADHt acts in both orientation and simply terminated transcription and therefore H2 could not detect any transcript.This is correct.If the authors know that ADH1t does not act as terminator in the reverse orientation, they should indicate it.GAL10 (see We do know that the ADH1t acts as a terminator in both directions. It does so in its native context (terminating the YOL086AW TU) and when used out of context in AL10 see  NAR.Moreover, even if the ADH1t is not acting as terminator of the AS, it can introduce a destabilization element that leads to its rapid degradation. In order to support this important conclusion, the authors could use a decay mutant strain  and probe the membrane to detect the region between the ADHt and SUT650 promoter.rrp6) using probe H2AS. There are no unstable transcripts detectable in the rrp6 strain.We have included two additional pieces of data in HMS2 sense transcription and SUT650 antisense transcription are prematurely terminated in this strain.Second we use probe H3AS to show that SUT650 is prematurely terminated. Thus both 5) The replacement of HMS2 ORF with URA3 requires some clarifications. Why didn't the authors simply remove the region around the TSS, leaving all other sequences unchanged? Why did they prefer to introduce the entire URA3?HMS2 ORF with the URA3 ORF so as to avoid problems with changing codons, deleting bases, or altering transcript stability while leaving the HMS2 flanking sequences unaltered.We chose to completely replace the There are two issues that need to be addressed. (1) The possibility that URA3 sequences, in both orientations, introduce stability biases onto the RNAs. (2) The possibility that the URA3 sequence contains a terminator in the AS direction, explaining why the AS RNA was not detected by H1 probe, located downstream of this hypothetical terminator. These issues can be discussed or addressed experimentally.ura3Δ and thus the URA3 gene is not in our datasets to test for the presence of an early terminator. Given that the promoter of a gene is reported to determine sense RNA stability , we felt the URA3 ORF replacement was an appropriate strategy. We have discussed these potential problems in the text and how we have interpreted our data given these provisos.We cannot address this using experimental data as BY4741 is 6) In, the authors used TFs with putative binding sites at intergenic region between HMS2 and BAT2 (no references were included). The membranes were probed only with the H1 probe. This case might be an opportunity to examine if any of these factors play a role in the transcription of BAT2, by probing the membrane with an appropriate probe. URA3 ORF can be replaced back to HMS2 ORF by homologous recombination and selection on 5-FOA, thus resulting in a precise deletion of just the region around the TSS. Maybe one of these TFs is required for BAT2 transcriptional repression by C1 transcription .HMS2 sense and SUT650 antisense suggest that ablation of some factors coupled to mild nutrient limitation leads to cells where transcription in the HMS2:SUT650 region is predominantly in sense or antisense orientations. This provides evidence for reciprocal switching between HMS2 sense and SUT650 antisense and suggests a signalling input regulates this only at the HMS2 promoter. We have a number of experiments in the paper to support this, particularly those in SUT650 and BAT2) is constitutive in the absence of sense transcription, regardless of growth conditions (GLU or GAL). Normally SUT650 transcription increases on the GLU to GAL shift but this reflects the reduction in HMS2 sense transcription in GAL. Without sense, SUT650 levels remain high in GLU. Similar arguments apply to BAT2. Elimination of sense transcript in the pGAL1:HMS2 anchor away experiment in BAT2 transcript levels. Thus the primary BAT2 regulation is transcriptional interference by the sense transcription in GAL (in this experiment only as the inserted GAL1 promoter is GAL-regulated).We apologise for not including references to the putative TF binding sites – this is now done. Putative factor binding sites, and even ChIP data with tagged factors, does not provide evidence that a particular factor is functional at a particular site, for a variety of reasons . Indeed, many of the experiments linking transcription factors to changes in particular transcriptional responses at genes are likely to be artefacts resulting simply from altered growth rate as a result of the genetic intervention , (and the different times spent in the OX and RC phases of the YMC). We think this criticism applies to all the experiments we have done with TF KO strains in HMS2 switches on and interferes with the transcription of SUT650 and BAT2 as long as the growth signal remains. If there is no growth signal, transcription of BAT2 and SUT650 is constitutive, as if cells are in the quiescent state that occurs naturally when nutrients are limited. In fact all the changes that occur when yeast naturally enter stationary phase due to nutrient depletion also occur in RC cells . This does not rule out TFs in the regulation of RC genes, but it does suggest they are not condition-specific. This is supported by our two new genome-wide analyses now included in the manuscript (Table S10). We have examined the nature of the transcription factors’ association with the promoters of RC or OX genes (in GLU) from the Venters and Pugh work (2011) (now included in reference list). They looked at the association of 202 factors at yeast promoters. We used their dataset to ask whether OX and RC genes are enriched for particular factors, as both will be expressed in GLU-grown cells. We show significantly different (p<0.01) ChIP-Chip binding patterns for factors at the two groups of genes. The RC genes are enriched for cohesion, the CCR4/NOT complex, elongator, chromatin and chromatin remodelling factors and four TFs, . By contrast, OX genes are associated with GTFs, TEFs, TFIID, and the TFs Ifh1 and Rap1. Although “stress” related transcription factors may play a role at the RC genes, these data suggest chromatin-mediated regulation as a central feature for RC genes. Our data support TI-mediated chromatin changes at the BAT2 promoter.Our view is that the (semi-) quiescent RC phase in the YMC is likely to be the default and RC genes would be expressed unless a specific growth signal is received. HMS2 and BAT2 regulate BAT2 expression or more simply, contribute to limiting HMS2 read-through  but do see a role for Gln3  in preventing transcript C (HMS2:BAT2 read through) and a reduction in SUT650 levels (supporting increased TI at the HMS2:BAT2 intergenic region). Given the literature supports a role for TFs and promoters in determining transcript stability, another explanation for the effect of loss of Gln3 is that transcript C is stabilised, but there is no change in transcription per se and thus no change in the transcript ratios. How RC genes are regulated is clearly complicated and beyond the scope of what we can do for a 2 month revision. We think the suggestion of the referee is excellent but have a number of reservations about this type of approach, especially as some of the putative TF binding sites are within the HMS2 ORF (similar arguments to the URA3 question above). Instead we have provided an Anchor-Away experiment to deplete nuclear Gln3 in Galactose (conditions expected to increase BAT2 and SUT650 expression). In the same experiment nuclear depletion of Sua7 results in loss of both BAT2 and SUT650 transcripts. We find no evidence that Gln3 is required for BAT2 or SUT650 expression in these conditions and the Sua7 control suggests this is not simple a result of the BAT2 transcript being particularly stable in GAL. These data are now included in So to the question of whether the putative TF binding sites between -through . As it s


Honey bees are important model systems for the investigation of learning and memory and for a better understanding of the neuronal basics of brain function. Honey bees also possess a rich repertoire of tones and sounds, from queen piping and quacking to worker hissing and buzzing. In this study, we tested whether the worker bees’ sounds can be used as a measure of learning. We therefore conditioned honey bees aversively to odours in a walking arena and recorded both their sound production and their movement. Bees were presented with two odours, one of which was paired with an electric shock. Initially, the bees did not produce any sound upon odour presentation, but responded to the electric shock with a strong hissing response. After learning, many bees hissed at the presentation of the learned odour, while fewer bees hissed upon presentation of another odour. We also found that hissing and movement away from the conditioned odour are independent behaviours that can co-occur but do not necessarily do so. Our data suggest that hissing can be used as a readout for learning after olfactory conditioning, but that there are large individual differences between bees concerning their hissing reaction. The basis for this variability and the possible ecological relevance of the bees’ hissing remain to be investigated. Birds do it, bees do it, only educated fleas (presumably) don’t do it—they produce tones and sounds. These sounds are often used for intra- and interspecific communication, but besides that, animal sound production has also been used by researchers for the investigation of learning and memory in both animals and humans. Many different animals have been successfully conditioned to vocalise upon presentation of a stimulus: dogs learned to bark ,2, rats Apis mellifera to ask whether they can be conditioned to produce sounds upon presentation of an odour by classical conditioning with a mild electric shock as unconditioned stimulus. Honey bees are good model organisms for this question because they produce several sounds, such as buzzing, hissing and piping [Insects are missing in this list, and we chose the honey bee d piping –15 and td piping  for an oHoney bee learning and memory has been studied mostly in the laboratory using appetitive conditioning with the proboscis extension response (PER) paradigm ,18 and aOur results demonstrate that hissing can be used as a conditioned response (CR) in honey bee conditioning, with approximately 40% of the bees showing this behaviour to the conditioned odour alone during a recall test five minutes later. We also find that hissing as CR and the bees’ being repelled by the odour as CR are independent behaviours: bees display either one, or both, upon smelling a conditioned odour. Our results offer new insights into honey bee behaviour and provide a new tool to investigate honey bee learning and memory.Apis mellifera forager bees, which were caught at feeders placed nearby the hives on the roof of the University of Konstanz. A total of 104 bees were used in these studies.All experiments were conducted on APIS has been described in detail elsewhere . In brieBees were differentially conditioned to two odours in a classical conditioning paradigm.-3 in mineral oil, all chemicals were obtained from Sigma Aldrich, Taufkirchen, Germany, >98% purity) were applied to absorbent cellulose rectangles  placed at the distal end of 2 ml plastic syringes . Odours were delivered to the chamber from either side using computer-controlled valves. Continuous air suction at the centre and the ends of the conditioning chamber removed the odours from APIS.150 μl of diluted odour (1-hexanol and 1-decanol diluted 10Odour stimulus duration was 6 seconds. For the conditioned stimulus (CS+), a mild electric shock  was administered 2 s after odour onset for a total duration of 4 s. The US consisted of five 200 ms shocks (10 V) given every 950 ms . A non-pAll odours were delivered at the side where the bee was located. The US was delivered on both sides of the chamber.The inter-trial interval (ITI) was 36 s. Bees were exposed to 8 training trials  in pseudorandomised order (ABBABAAB or BAABABBA). After conditioning, the lights in the chamber were shut off, but the bee remained in the chamber. After five minutes the lights were switched on again, and after additional 30 s bees were tested for their short-term memory in a 4-trial test, in which both odours were presented with an ITI of 36 s without shocks in a pseudorandomised order (ABBA or BAAB). The bee’s position was continuously sampled by IR sensors and written to a log-file.After the experiment, the bee was removed from the chamber, chilled in a freezer and sacrificed in 70% ethanol. The interior of the chamber was cleaned with ethanol to remove possible contaminations. The chamber was rinsed with hot water and detergent every day.Honey bee hissing was recorded using a Sennheiser ME 64 microphone  attached to a computer sound card. All recordings were made as uncompressed 16-bit PCM audio at a sampling rate of 44.1 kHz using the software Audacity , and stoWe used a customised script written in R  to extraSound data was read into R using the package “seewave”  and the Hissing was determined by creating a spectrogram  and evaluating the summed intensities (in dB) at different frequency ranges  were considered as actual hissing see ..before); the two seconds following the odour onset  in case of the CS+); and two seconds following the ISI-phase of the odour stimulation .Occurrence of hissing was quantified as a binary value. If a bee did not hiss at all during one such span, it received a 0, if it did hiss, it received a 1. We calculated learning curves as the fraction of hissing bees. From the responses to the CS+ and the CS-, a learning index (LI) was calculated for each bee and each test trial by subtracting the bee’s response to the CS- from the response to the CS+. The mean of the 104 bees’ individual LIs was calculated to obtain a LI for each section  and appropriate post-hoc comparisons on the data. It is permissible to use ANOVA on dichotomous data when there are at least 40 degrees of freedom ,28. ThesBees underwent an 8-trial differential conditioning paradigm consisting of four reinforced trials  and four non-reinforced trials . The three bees that never responded during conditioning also did not respond during testing.before), the two seconds during ISI where only the odour was present (during) and the first two seconds after the ISI, when shocks were administered in case of the CS+ , whereas bees started hissing at shock onset , or generalised from the CS+ to the CS- by responding to the presentation of the new odour with hissing (during). Generalisation was symmetric for odour: 9 of these 18 animals had hexanol as CS+, 9 decanol.Learning acquisition of hissing was evaluated using three temporal sections: the two seconds before odour onset .There was no difference between CS+ and CS- in the during response for the last conditioning trial was 42.3% to the CS+ and 27.8% to the CS- , indicating that bees hissed more to the CS+ than to the CS-;. In the after section of the last conditioning trial, 84.6% of the bees hissed during the CS+ while being shocked, while only 28.8% of the bees hissed during the same section of the CS- .The  the CS- . This diduring and after section combined since no shocks were given in the after section).5 minutes after the end of conditioning bees were tested two times for each odour without reinforcement. 53.8% (56 out of 104 bees) responded to at least one CS+ with a hiss , indicating that the bees clearly had learned the two odours, and that this was displayed in their hissing response. The response to the odours was similar for the during and the after section  responded to both stimuli (consistent learners), 48 bees did not respond (consistent non-learners), 14 bees hissed only for the first CS+ and not to the second (memory extinction), and 5 bees responded only to the second CS+ ("inconsistent" bees).To assess the consistency of the bees behaviour, we analysed the individual bees’ responses to the first and second CS+ for the during sections of all CS+ , whereas only 2 bees (1.9%) responded to all CS- . Interestingly, the bees that hissed for all CS- were not the same bees that hissed for all CS+. 24 bees (23.1%) hissed to at least 4 of the 5 CS+—when taking into consideration only the 52 bees that responded during the during section of at least one of the CS+ test trials, almost half of these bees (46.1%) were consistent with respect to their hissing behaviour.Eight bees (7.7%) investigated hissed in the before section, -0.02). In the period after odour onset, more bees hissed to the CS+ compared to the CS-, resulting in LIs of 0.27 (during) and 0.28 , but there was no statistically significant difference between the two latter sections concerning the LIs .A higher learning index LI corresponds to a stronger hissing towards the CS+ compared to the CS-, thus higher discrimination ability of the honey bees. The LI averaged across the two test trials  varied b8 after, . The LI during section or in the after section .Both odours were balanced as CS+, and there was no significant difference between the two odours with respect to hissing during the test phase in the We defined the “Escape” response as moving away from the odour within the first two seconds after odour onset, crossing the midline and not returning to the side the odour was injected on. We excluded five bees from the analysis of their locomotion behaviour because they stopped moving, suggesting that they were exhausted. Thus, 99 bees were analysed.1, 97 = 0.25, P = 0.618), but already at the second conditioning trial, more bees escaped from the CS+ compared to the CS- . The effect waned in the third conditioning trial, but the last conditioning trial was again statistically significant  and from the CS- : while 45.5% and 51.5% of the bees escaped from the CS+ , only 22.2% and 24.2% of the bees escaped from the CS- .Also during the recall test five minutes after the end of conditioning significantly more bees escaped from the CS+ than from the CS-. This difference was similar for both recall test trials .As with hissing, we could not find any significant difference between the two odours with respect to escape probability , which is slightly lower than the escape rate with 48.4%. Compared to other paradigms, the learning rate is relatively low: appetitive PER-conditioning results in learning rates of 80% or higher  might be more comparable to the acquisition of flower handling skills in generalist pollinators as shown in bumble bees . While tWhen combining the two readouts “hissing” and “escape”, one quarter of bees responded upon presentation of the CS+ (24.2%). This very low learning rate is compensated by the low level of generalisation : only 2.0% of the bees responded in that way, even though 23.2% of bees responded with an escape, and 12.9% with hissing. This indicates that bees which hiss and escape upon presentation of an odour can distinguish the odours precisely and are not likely to generalise.Our results show that not every bee that hisses also escapes, and vice versa. For example, a significant number of bees hissed but did not escape —it remaiHissing has been shown to act as a warning cue aimed at an attacker , and it We were able to show that hissing can be used as readout for learning in honey bees, adding an insect to the list of animals which can be conditioned to produce sound. So far, we only analysed the bees’ responses in a binary manner (hissing/no hissing). Future experiments need to look into temporal differences between the hissing , our results suggest that hissing is behaviourally similar to reflex-like behaviours such as the extension of the bees’ proboscis or it’s sting. We propose that honey bee hissing might serve as an intraspecific signal to warn conspecifics.S1 FigThis figure shows the movement trace within APIS of three example bees during conditioning (upper part) and test (lower part). Times of odour delivery (on the side the respective bee was located on) and electric shock (given on both sides of the chamber) are indicated, grey bars indicate hissing (see legend). a) The bee shown in this example hissed very scarcely during conditioning and generalised during the test towards the first CS-. We observed very little generalisation in our data, so hissing seems to be a very robust readout Click here for additional data file.S2 FigThis example spectrogram belongs to the bee shown in (PDF)Click here for additional data file.S3 Figa) Histogram of the durations of all sounds recorded and initially classified as hissing before removing hisses shorter than ca. 0.09 s, which were regarded as valve clicking sounds and other events not related to bees’ hissing. b) Histogram of hissing lengths. Bin size for both plots 0.05 s. n = 104 bees.(PDF)Click here for additional data file.S4 FigGrey double lines indicate odour presentations. In the upper part are all bees that underwent an ABBA conditioning paradigm (CS+ first), in the lower part all bees that underwent a BAAB conditioning paradigm (CS- first). Before the first CS+, few bees hiss, whereas after conditioning (300 to 600 ms), the bees’ general tendency to hiss is increased. Very few bees hissed constantly, and very few bees never hissed during the experiment . n = 104 bees.(PDF)Click here for additional data file.S5 FigLearning studies often use ANOVA to analyse the data, however, modelling binary behavioural data is a more appropriate approach. Hissing and escape response served as binary response variables, while trial, conditioned stimulus (CS+ or CS-) and odour (hexanol or decanol) with interactions were included as fixed effects. Bee identity served as random effect to account for the repeated measurements. The credible interval for the first data point  in a) and c) spans from 0 to 1 because no observations could be made for this event. The model cannot estimate data and interval without any incident to start the estimation from. Asterisks denote statistical difference (p<0.001).(PDF)Click here for additional data file.S6 FigTo compare the observed means  and the modelled values (“fit”), both were plotted in one figure, showing that the model generally underestimates the bees’ hissing response (see difference in a), whereas it matches the escape response (see b). Combining the two variables leads to a slight underestimation of the model compared to the observed data (c).(PDF)Click here for additional data file.S7 FigObserved vs. fitted values (open circles) are plotted with class-wise means and 95% confidence interval for the observations (orange dots and bars). The dotted line indicates perfect coincidence between the observed data and the model prediction. The confidence intervals of the class-wise means mostly span the diagonal line, which indicates that the logistic regression model predicts the data tolerably well.(PDF)Click here for additional data file.S8 Figa-c) Decanol was used as CS+ and hexanol as CS-. d-f) Hexanol was used as CS+ and decanol as CS-. There was no statistically significant difference between the two odour configurations detectable.(PDF)Click here for additional data file.S9 FigNo statistically significant differences could be found when analysing the bees’ escape behaviour with respect to the odour configuration. Bees which were conditioned to decanol as CS+ (a) as well as bees that were conditioned to hexanol as CS+ (b) distinguished between CS+ and CS- after conditioning to the same extent.(PDF)Click here for additional data file.S10 FigDuring the test, responses to the CS+ are higher as compared to the CS-. Error bars denote 95% confidence interval.(PDF)Click here for additional data file.S11 FigError bars denote 95% confidence interval.(PDF)Click here for additional data file.S12 FigMost hisses are less than 1 s long, only very few hisses are longer than 10 seconds. Duration increases (not very surprisingly) with shock onset. n = 104 bees.(PDF)Click here for additional data file.


The National Institutes of Health (NIH) Health Care Systems Research Collaboratory (NIH Collaboratory) seeks to produce generalizable knowledge about the conduct of pragmatic research in health systems. This analysis applied the PRECIS-2 pragmatic trial criteria to five NIH Collaboratory pragmatic trials to better understand 1) the pragmatic aspects of the design and implementation of treatments delivered in real world settings and 2) the usability of the PRECIS-2 criteria for assessing pragmatic features across studies and across time.Using the PRECIS-2 criteria, five pragmatic trials were each rated by eight raters. For each trial, we reviewed the original grant application and a required progress report written at the end of a 1-year planning period that included changes to the protocol or implementation approach. We calculated median scores and interrater reliability for each PRECIS domain and for the overall trial at both time points, as well as the differences in scores between the two time points. We also reviewed the rater comments associated with the scores.All five trials were rated to be more pragmatic than explanatory, with comments indicating that raters generally perceived them to closely mirror routine clinical care across multiple domains. The PRECIS-2 domains for which the trials were, on average, rated as most pragmatic on the 1 to 5 scale at the conclusion of the planning period included primary analysis (mean = 4.7 (range = 4.5 to 4.9)), recruitment (4.3 (3.6 to 4.8)), eligibility (4.1 (3.4 to 4.8)), setting (4.1 (4.0 to 4.4)), follow-up (4.1 (3.4 to 4.9)), and primary outcome (4.1 (3.5 to 4.9)). On average, the less pragmatic domains were organization (3.3 (2.6 to 4.4)), flexibility of intervention delivery (3.5 (2.1-4.5)), and flexibility of intervention adherence (3.8 (2.8-4.5)). Interrater agreement was modest but statistically significant for four trials (Gwet’s AC1 statistic range 0.23 to 0.40) and the intraclass correlation coefficient ranged from 0.05 to 0.31. Rating challenges included assigning a single score for domains that may relate to both patients and care settings  and determining to what extent aspects of complex research interventions differ from usual care.These five trials in diverse healthcare settings were rated as highly pragmatic using the PRECIS-2 criteria. Applying the tool generated insightful discussion about real-world design decisions but also highlighted challenges using the tool. PRECIS-2 raters would benefit from additional guidance about how to rate the interwoven patient and practice-level considerations that arise in pragmatic trials.NCT02019225, NCT01742065, NCT02015455, NCT02113592, NCT02063867.Clinicaltrials.gov trial registrations:  Pragmatic clinical trials are “primarily designed to determine the effects of an intervention under the usual conditions in which it will be applied”; they contrast with explanatory trials which “are primarily designed to determine the effects of an intervention under ideal circumstances” . The UniThe purpose of this analysis was to measure the degree to which the NIH Collaboratory trials are pragmatic at both the design and implementation phases using a version of the Pragmatic Explanatory Continuum Indicator Summary framework (PRECIS-2) . In addiThe individual NIH Collaboratory Trials were approved by the relevant research ethics boards. This analysis did not require informed consent from raters nor ethical approval because the data sources were limited to the study protocols, not information about human subjects. In addition, all raters were co-authors of the paper rather than subjects of the research.The U.S. NIH is the largest medical research agency in the world. Through funding from the NIH, the NIH Collaboratory seeks “to strengthen the national capacity to implement cost-effective large-scale research studies that engage health care delivery organizations as research partners. The aim of the program is to provide a framework of implementation methods and best practices that will enable the participation of many health care systems in clinical research” . The NIHn = 4), Coordinating Center staff (1), or NIH staff (6). Six of the raters had familiarity with all five trials either because they had participated in funding decisions or regular cross-project meetings. Two raters (both NIH staff) had limited knowledge of any of the projects prior to participating in the PRECIS 2 exercise. Raters were recruited based on their interest and availability. The six NIH staff rated all five trials. The PIs or other investigators, as well as the Coordinating Center staff, each rated only two trials, one of which was his/her own.Raters were trial principal investigators (PIs) or other investigators from their team (https://crs.dundee.ac.uk/precis). The CONSORT workgroup on Pragmatic Trials created the PRECIS criteria to help trialists design trials that are pragmatic across multiple domains [To measure the pragmatic nature of the NIH Collaboratory trials, we used the PRECIS-2 toolkit  eligibility - who is selected to participate in the trial; (2) recruitment - how participants are recruited into the trial; (3) setting - where the trial is being done; (4) organization - what expertise and resources are needed to deliver the intervention; (5) delivery flexibility - how the intervention is delivered; (6) adherence flexibility - what measures are in place to make sure participants adhere to the intervention; (7) follow-up - how closely participants are followed-up; (8) primary outcome - how relevant is it to participants; and (9) primary analysis - to what extent all data all included. Each domain is scored on a five-point Likert scale from very explanatory (1) to very pragmatic (5), with a score of 3 indicating that a trial is equally pragmatic and explanatory. In addition, an overall composite score is reported for a given trial to characterize the overall pragmatic nature of the trial. We also calculated an overall mean score for each domain across trials, to illustrate for which domains the trials, in general, were more or less pragmatic.All raters received training in applying PRECIS-2. The training consisted of an orientation webinar by one author (RG) based on the PRECIS-2 toolkit, practice with a published protocol, and a second web conference to calibrate ratings by discussing ratings that differed among the individuals participating in the training. Following the training, each of the five demonstration projects was rated by eight raters and evaluated at two time points, using the initial grant application and a required progress report written at the end of a 1-year planning period that included changes to the protocol or implementation approach. Four trials included a rating by a trial team member. Each rater entered their two sets of ratings on a form, which included space for comments.We produced one PRECIS wheel for each time point (pilot/planning phase and implementation phase) for each of the five trials using the PRECIS-2 Toolkit, which calculates the median scores for ratings for a given trial. The data were analyzed using STATA 12.0  and SAS 9.3. We calculated the mean and median scores and the range of scores for each domain, trial, and time point. We also calculated the differences in scores between the two time points for each of the PRECIS-2 domains for each trial. To evaluate change over time, we examined the spread in these differences and determined the level of statistical significance  using the sign test in Stata 12.0, a Wilcoxon nonparametric test of equality of matched pairs. Interrater agreement or reliability was calculated for each trial using Gwet’s AC1 statistic , a more To inform our secondary goal of assessing PRECIS-2 usability, we reviewed the comments provided by the raters for each trial. Two authors (KJ and GN) organized the comments by domain and indicated study design aspects that raters considered in their scoring that were not specified in the PRECIS-2 toolkit, as well as rating challenges. All raters reviewed these results.All five demonstration projects were rated to be more pragmatic than explanatory. The overall composite scores, calculated on the basis of the average score of the means and medians across the domains, are all greater than 3 on a scale where 3 signifies equally pragmatic/explanatory. Mean and median scores for each trial at the implementation phase for each domain are presented in Table p values ≤ 0.001; Table p values were ≤ 0.001 (data not shown). We examined outliers to see if differences existed among raters who were and were not previously familiar with the studies or for raters who were rating their own project. We did not observe any notable patterns. However, the principal investigators’ on-the-ground experience did not always match the rater-assessed examples of change, as discussed further below.At the implementation phase, we found modest but statistically significant interrater agreement for four of the five trials . Furthermore, institutions where these trials were occurring all had the resources and infrastructure to support a systems-change intervention, making it possible that these institutions had relatively high organizational resources to support complex quality improvement. Even if this infrastructure was not research-specific, this potential difference from usual care led to more explanatory ratings of the setting and organization domains.The flexibility of delivery domain, the determination of whether an intervention was relatively more restrictive than a strict quality control protocol in usual care was challenging. Similarly, it was challenging to rate the flexibility of adherence for an intervention relative to usual care because, if the intervention was successful, the adherence procedures could become usual care. Second, few studies documented extensively efforts undertaken to maintain “adherence” at the organizational level. For example, when leadership changes occur, the need arises for substantial discussion and planning to continually “engage” the stakeholders/leadership in the health system. Most of these activities are not planned but are undertaken ad hoc when health systems lose their leadership. To what extent these efforts to re-engage leadership in the conduct of the trial represented less pragmatic adherence is unclear.For the Primary outcome is rated according to the extent to which it is relevant to participants, but raters struggled with how to rate outcomes that might be more important to health systems than to patients, for example, process efficiency. Raters also had to determine how to factor in criteria that pertained to multiple domains, and whether they should “be counted” more than once. For example, consent by patients or organizational willingness to participate pertained to multiple domains: eligibility, recruitment, setting. Thus, some raters attempted to provide an average score across unrelated subdomains; other raters may have only considered a single subdomain.The objective of this study was to analyze five pragmatic trials in order to characterize pragmatic versus explanatory design by PRECIS-2 domains and how design details changed over the course of a yearlong study-planning period. In five trials designed as pragmatic trials in diverse U.S. healthcare settings, we observed that trials were designed as more pragmatic than explanatory as measured by all PRECIS-2 domains.r = 0.88. The large difference in interrater reliability is surprising given that we used a similar training approach and had access to detailed study information.Raters struggled to use the PRECIS system for this analysis, as illustrated by the comments in Table Whereas the rating challenges limit our ability to draw conclusions about specific studies, some general observations emerge. Across studies and time points, the domains rated as most pragmatic were analysis and recruitment, whereas those that were closer to explanatory (average range 3 to 4) were organization, delivery, and adherence. This could reflect, in part, that it may be easier to be pragmatic for some domains than for others. For example, it is relatively easy to be pragmatic for patient eligibility by taking all comers; but it is often difficult to be pragmatic when trying to deliver an intervention.It is important to note that explanatory elements of pragmatic design do not necessarily relate to study quality. Some trial aspects may need to be designed in a more explanatory manner in order to answer the study question. PRECIS-2 ratings provide guidance to researchers on the appropriate corresponding study procedures. For example, the more explanatory rating of the organization domain  indicates that the study involves extra resources such as training. By noting this during the design phase, study teams can make sure they communicate with involved health systems about time and resource requirements. However, it is important to note that requiring additional training does not necessarily make the organizational domain more explanatory: the same approaches to training personnel to roll out a trial intervention could be the same as those approaches used by the organization to roll out a clinical or quality improvement intervention.It is difficult to compare our overall findings to other reports that rated studies using PRECIS domains because they utilized an earlier version of the tool and had different study questions. However, one other study has used PRECIS criteria to examine change over time. Elder and Munk  used a mThis study generated insights that may be useful for future use or refinement of the PRECIS-2 tool. As per Table In addition, it would be helpful to have guidance about the amount of study information that teams need in order to best use the PRECIS-2 tool. If we had this guidance, the benefit would be that all trials could more easily capture information. In turn, this would enable better comparisons across trials and allow for analysis of a broader trial portfolio. Additionally, looking across trials and across time points would be useful, but we were limited by what information we had. Therefore, providing guidance on what information is needed to best apply this tool would better enable its utility.The materials that we used to rate the study were the grant application and progress report, which contained many details that pertained to the PRECIS-2 domains but were not organized according to PRECIS-2 domains. The information in these documents may have contributed to low interrater reliability; however, they contained a substantial amount of implementation-oriented information. It is possible that ratings would have been even more difficult using the details typically available in a protocol or manuscript of study findings. It also is possible that the limited number of raters for each study could have contributed to the low interrater reliability. However, in both the Loudon et al. paper  and our The raters participating in the process found it an informative way to learn about pragmatic design in general as well as about specific studies. This study demonstrates that PRECIS-2 can be used to rate protocols, as well as for study planning, and helps address the need for systematic approaches to reporting pragmatic studies . However