Much is known about the neural circuits of conditioned fear and its relevance to understanding anxiety disorders, but less is known about other anxiety-related behaviors such as active avoidance. Using a tone-signaled, platform-mediated avoidance task, we observed that pharmacological inactivation of the prelimbic prefrontal cortex (PL) delayed avoidance. Surprisingly, optogenetic silencing of PL glutamatergic neurons did not delay avoidance. Consistent with this, inhibitory but not excitatory responses of rostral PL neurons were associated with avoidance training. To test the importance of these inhibitory responses, we optogenetically stimulated PL neurons to counteract the tone-elicited reduction in firing rate. Photoactivation of rostral  PL neurons at 4 Hz impaired avoidance. These findings suggest that inhibitory responses of rostral PL neurons signal the avoidability of a potential threat and underscore the importance of designing behavioral optogenetic studies based on neuronal firing responses. Core symptoms of post-traumatic stress disorder and other anxiety disorders include excessive fear and avoidance . The neuImportant questions remain, however, regarding the role of PL in avoidance. First, how do PL neurons signal avoidance? Fear conditioning mainly induces excitatory responses to conditioned tones in PL that correlate with freezing , but theWe addressed these questions by recording PL neurons during tone-signaled, platform-mediated avoidance. We then optogenetically silenced or activated PL neurons based on the observed firing patterns. We found that inhibitory (rather than excitatory) tone responses of rostral PL neurons were associated with avoidance. Opposing these inhibitory responses with photoactivation delayed or prevented active avoidance, suggesting that prefrontal inhibition signals the ‘avoidability’ of danger.We first replicated our prior findings that pharmacological inactivation of PL with the GABA-A agonist muscimol (MUS) impaired avoidance in this task , with tw(28) = −4.019, p<0.001, Bonferroni corrected). An analysis of avoidance across the tone in 3 s bins  = 4.076, p<0.001; post hoc, 0–15 s **p<0.01, 15–21 s *p<0.05), and 2/13 rats never avoided  = 2.460, p=0.020) but had no effect on suppression of bar pressing ((28) = 0.194, p=0.848). Inactivation of PL had no effect on locomotion, as indicated by distance traveled during a 5 min open field test  = 0.513, p=0.614, (18) = 0.933, p=0.363, Histological analysis showed that MUS was confined to PL in its mid rostral-caudal extent . Rats wi3 s bins  indicateBecause pharmacological inactivation of PL delayed avoidance, we reasoned that tone-induced activity in PL would be essential for avoidance early in the tone. To assess this, we used an optogenetic approach, expressing the microbial opsin archaerhodopsin (ArchT) in PL, which causes a hydrogen proton efflux to hyperpolarize neurons when exposed to 532 nm (green) light . We deli(30) = 0.792, p=0.435) or cPL ((14) = 0.471, p=0.646). Photosilencing also had no effect on the time course of avoidance in rPL  = 1.939, p=0.062) or cPL ((14) = 0.590, p=0.565). Suppression of bar pressing was also unaffected by photosilencing in either location ((30) = 0.415, p=0.681; (14) = 0.984, p=0.342). The lack of impairment of avoidance may suggest that we failed to sufficiently inhibit PL activity via ArchT photosilencing. However, photosilencing rPL neurons during early avoidance training (on day 2) significantly reduced tone-induced freezing (eYFP-control: 31% (n = 9) vs. eYFP-ArchT: 7% (n = 8), t(15) = 0.288, p=0.012, Next, we infused ArchT bilaterally into PL, distinguishing rostral PL  from caudal PL , raising the possibility that avoidance signaling may involve rPL inhibition rather than excitation.An assumption of our photosilencing approach was that increased activity in PL neurons is correlated with avoidance; however, this hypothesis had never been tested. We therefore performed extracellular single unit recordings in PL of well-trained rats during avoidance expression. Units were recorded from the full rostral-caudal extent of PL . We firsTo determine if these tone responses were correlated with avoidance rather than simply auditory processing, we compared PL responses in this group of rats with those of a naïve control group trained to press for food and presented with tones in the same chamber with the platform. Naïve rats were free to mount the platform and explore the chamber but were never shocked. In addition, to determine whether activity at tone onset might represent the conditioned aversiveness of the tone, we compared responses in avoidance rats with responses in rats subjected to auditory fear conditioning in the same chamber  that was significantly longer than the average pre-tone ISI . 133/205 neurons showed at least one ISI that satisfied this criterion. The latency of inhibition showed no correlation with the latency of platform entry , with none in cPL . Most inIf inhibition within rPL signals the avoidability of a tone-signaled shock, we reasoned that opposing this inhibition should remove this option and impair avoidance. To oppose inhibition, we used channelrhodopsin (ChR2) targeting CAMKIIα-positive neurons to activate rPL neurons throughout the tone at 4 Hz, to counter the tone-induced decrease from 6 to 2 Hz. To validate our method, we first measured extracellular unit activity in anesthetized rats from ChR2-expressing rPL neurons exposed to blue light 473 nm, . Figure (21) = −4.779, p<0.001, Bonferroni corrected; see (14) = 1.531, p=0.148) or its time course  = 18.642, p<0.001, interaction effect (Group x Time) F(9) = 1.156, p=0.326, post hoc, 3–30 s, all p’s < 0.01). Photoactivation delayed avoidance in 7/14 rats and blocked avoidance entirely in 7/14 rats ((21) = 1.121, p=0.275; suppression: t(21) = 1.343, p=0.194) or cPL ((14) = 0.0702, p=0.494; suppression: t(14) = 0.483, p=0.636). Photoactivation at 2 Hz had no effect on avoidance expression ((17) = 3.363, p=0.004). 4 Hz photoactivation of rPL had no effect on locomotion, as indicated by distance traveled in an open field  = 0.941, p=0.356, (24) = 4.82e-4, p=0.999, Examination of the time course of avoidance showed that photoactivation of rPL significantly reduced avoidance throughout the tone  and ventral striatum VS; , both neExcessive avoidance is clinically relevant for PTSD and other anxiety disorders. Rodent PL is considered to be homologous to the human dorsal anterior cingulate cortex dACC; . In humaA total of 155 adult male Sprague Dawley rats  aged 3–5 months and weighing 320–420 g were housed and handled as previously described . Rats weRats were anesthetized with isofluorane inhalant gas (5%) first in an induction chamber, then positioned in a stereotaxic frame . Isofluorane (2–3%) was delivered through a facemask for anesthesia maintenance. For pharmacological inactivations, rats were implanted with 26-gauge double guide cannulas  in the prelimbic prefrontal cortex . For optogenetic experiments, rats were bilaterally implanted with 22-gauge single guide cannulas  in the prelimbic prefrontal cortex . An injector extending 2 mm beyond the tip of each cannula was used to infuse 0.5 μl of virus at a rate of 0.05 μl/min. The injector was kept inside the cannula for an additional 10 min to reduce back-flow. The injector was then removed and an optical fiber  with 1 mm of projection beyond the tip of each cannula was inserted for PL illumination. The guide cannula and the optical fiber were cemented to the skull . For unit recording experiments, rats were implanted with a moveable array of 9 or 16 microwires  targeting regions of PL along the rostral-caudal axis. After surgery, triple antibiotic was applied topically around the surgery incision, and an analgesic  was injected subcutaneously. Rats were allowed a minimum of 7 days to recover from surgery prior to behavioral training.Rats were initially trained to press a bar to receive food pellets on a variable interval reinforcement schedule (VI-30) inside standard operant chambers  located in sound-attenuating cubicles . Bar-pressing was used to maintain a constant level of activity against which avoidance and freezing could reliably be measured. Rats were trained until they reached a criterion of ≥15 presses/min. Rats pressed for food throughout all phases of the experiment.For platform-mediated avoidance, rats were trained as previously described . BrieflyThe GABA-A agonist muscimol  was used to enhance GABA-A receptor activity, thereby inactivating target structures. Infusions were made 45 min before testing at a rate of 0.2 µl/min (0.11 nmol/ 0.2 µl/ per side), similar to our previous studies .12 particles/ml for channelrhodopsin (AAV5:CaMKIIα::hChR2(H134R)-eYFP) and archaerhodopsin (AAV5:CaMKIIα::eArchT3.0-eYFP) and 3 × 1012 particles/ml for control (AAV5:CaMKIIα::eYFP). Rats expressing eYFP in PL were used to control for any nonspecific effects of viral infection or laser heating. The CaMKIIα promoter was used to enable transgene expression favoring pyramidal neurons  were obtained from the University of North Carolina Vector Core . Viral titers were 4 × 10 neurons  in corti neurons . VirusesRats expressing channelrhodopsin (ChR2) in PL were illuminated using a blue diode-pump solid state laser , similar to our previous study . Rats exRats implanted with moveable electrode arrays targeting PL/Cg1 were either avoidance conditioned as previously described or exposed to the training environment  in the absence of the shock. Extracellular waveforms that exceeded a voltage threshold were digitized at 40 kHz and stored on a computer. Waveforms were then sorted offline using three-dimensional plots of principal component and voltage vectors  and clusters formed by individual neurons were tracked. Timestamps of neural spiking and flags for the occurrence of tones and shocks were imported to NeuroExplorer for analysis . Because we used a high impedance electrode in the current study (~750–1000 kOhm), we were unable to sample interneurons. Single units were recorded across the extent of Cg1, Cg2, and PL. We excluded any units in Cg2 based on histological verification. Portions of Cg1 dorsal to rPL were grouped together for analyses, and portions of Cg1 dorsal to cPL were grouped together for analyses, ensuring that the proportion of Cg1 units was similar across both PL regions. Data was recorded during the entire session except during the 2 s shock. After conditioning, rats were tested for avoidance expression.For avoidance assessment, rats received full conditioning sessions (with shocks) across days. Inclusion of the shock prevented extinction of avoidance. After each day, electrodes were lowered 150 µM to isolate new neurons for the following session the next day. To detect tone-elicited changes in PL activity, we assessed whether neurons changed their firing rate significantly during the first 500–1000 ms after tone onset across the first five trials. A Z-score for each 500 ms bin was calculated relative to 20 pre-tone bins of equal duration (10 s pretone). PL neurons were classified as showing excitatory tone responses if the initial bins exceeded 2.58 z’s . PL neurons were classified as showing inhibitory tone responses across time if any of the initial two tone bins exceeded −1.96 Z’s . A longer response latency for inhibition was chosen to take into account multi-synaptic pathways that are present in inhibitory circuits.To detect changes in PL activity during platform entry, we employed the same procedure used for assessing tone responses. We assessed whether neurons changed their firing rate significantly during the first 500–1000 ms after platform entry. A Z-score for each 500 ms bin was calculated relative to the same pretone baseline. Heat maps of single unit data were generated with Z-scores from baseline through the 28 s after tone onset or platform entry.To assess the relations between inhibition and avoidance on a trial-by-trial basis, we compared the latency of inhibition with the latency of platform entry. The latency of the inhibitory response to the tone was identified as the start of the first interspike interval (ISI) that was significantly longer than the average ISI in 30 s of pre-tone activity  recorded in all cells for each trial. We then computed the average latency of inhibition and platform entry for each cell recorded across all the trials in which successful avoidance was observed . Avoidance latency was also averaged on those trials for each cell.Rats expressing ArchT or ChR2 in PL were anesthetized with urethane  and mounted in a stereotaxic frame. An optrode consisting of an optical fiber surrounded by 8 or 16 single-unit recording wires  was inserted and aimed at PL . The optrode was ventrally advanced in steps of 0.03 mm. Single-units were monitored in real time . After isolating a single-unit, a 532 nm laser was activated for 10 s within a 20 s period, at least 10 times for ArchT-infected PL neurons. For ChR2-infected PL neurons, a 473 nm laser was activated for 30 s at a rate of 2 or 4 Hz (5 ms pulse width) within a 90 s period (60 s ITI), at least five times. Single-units were recorded and stored for spike sorting  and spike-train analysis . Excitatory and inhibitory responses were calculated by comparing the average firing rate of each neuron during the 10 s of laser OFF with the 10 s of laser ON for ArchT neurons and during 30 s laser OFF just prior to the 30 s of laser ON for ChR2 neurons .Locomotor activity in the open field arena (90 cm diameter) was automatically assessed (ANY-Maze) by comparing the total distance travelled between 30 s trials (laser off versus laser on), following a 3 min acclimation period for optogenetic experiments. The distance traveled was used to assess locomotion and time in center was used to assess anxiety. For pharmacological inactivation experiments, distance traveled and time in center was measured over a 5 min period following a 3 min acclimation period 45 min after MUS or SAL was infused prior to sacrificing animals.After behavioral experiments, rats were deeply anesthetized with sodium pentobarbital (450 mg/kg i.p.) and transcardially perfused with 0.9% saline followed by a 10% formalin solution. Brains were removed from the skull and stored in 30% sucrose for cryoprotection for at least 72 hr before sectioning and Nissl staining. Histology was analyzed for placement of cannulas, virus expression, and electrodes.Behavior was recorded with digital video cameras . Freezing and platform avoidance was quantified by observers blind to the experimental group. Freezing was defined as the absence of all movement except for respiration. Avoidance was defined as the rat having at least three paws on the platform. We calculated percent suppression of bar pressing for each tone as previously described :. The time spent avoiding during the tone (percent time on platform) was used as our avoidance measure. Avoidance and freezing to the tone was expressed as a percentage of the 30 s tone presentation. Our experimental groups typically consisted of approximately 15 animals. This is typical of other laboratories and results in sufficient statistical confidence. Moreover, it also agrees with the theoretical minimum sample size given by: In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, one of whom, Geoffrey Schoenbaum, is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Michael Frank as the Senior Editor. Michael McDannald has agreed to reveal his identity as one of the other reviewers.Thank you for submitting your article "Active avoidance requires inhibitory signaling in the rodent prelimbic prefrontal cortex" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:This study examines the role of the prelimibic cortex (PL) in active avoidance. The authors use fluorescent-tagged muscimol to extend a previous finding that PL inhibition delays already established active avoidance. To the author's surprise, optogenetic PL inhibition at the time of cue in this same task had no effect on avoidance – or even sped avoidance initiation when the rostral PL was photo-inhibited. Using single-unit recording they uncovered a novel, inhibitory signal in rostral PL neurons that only emerged during tone presentation in avoidance rats. Accounting for the magnitude of firing decrease observed by these neurons, the authors show that 4 Hz photo-stimulation via channelrhodopsin at only the time of the tone – cancelling out the observed inhibitory – delayed inhibitory avoidance. Collectively the results point to an unappreciated role of inhibition in PL in controlling the initiation of the decision to avoid. The topic is timely, the results are quite novel, and technically these experiments are excellent. Further, using neural activity to calibrate the optogenetic manipulation is smart and would be a good practice for the field. Overall, this is a very strong manuscript, mostly requiring just some clarifying analyses.Essential revisions:In our discussion, the reviewers identified three key areas that some additional information would be helpful. I have left the comments below intact, but these three revisions are the ones that are most important to us. The first is to provide additional detail on what behavior the rats do instead of avoiding when PL is manipulated. This is interesting in its own right and also will help to identify the role of PL – for example what happens might be different depending on whether PL is actually involved in triggering the decision versus evoking fear. All three reviewers agreed this was useful, though it is described by R1. In addition, we also thought additional detail on the single unit data would be helpful. R2 would like more information regarding the excitatory correlates and their relation or lack thereof to behavior, since they are presumably affected by the inhibitory tone. R3 is interested in developing stronger correlative relationships between firing activity and the actual decision. In part, the question here is whether there is any better metric than is provided and/or if not to discuss in more detail what is meant here, given that the actual decision to avoid is so hard to define experimentally – how can you say this is really what the neurons are doing?Reviewer #1:In this study, the authors examine the roles of rostral and caudal PL in active avoidance. Rats were trained to avoid a cue-signaled shock by interrupting their ongoing responding for food and stepping onto a platform. Prior work had shown that inactivating PL disrupted this behavior without affecting the cue-induced freezing. The current study replicated this effect with muscimol and then explored the neural correlates and effects of more temporally specific optogenetic manipulations. Contrary to expectations, they found that optogenetic inhibition of PL had minimal effects on expression of the active avoidance response. Subsequent recording work suggested that this was because the activity in rPL correlated with the response was inhibitory rather than excitatory. Based on this, the authors optogenetically activated PL during the cue, modestly to counteract the normal inhibition. Activation of rPL (but not cPL) impaired avoidance selectively and completely.This is a remarkable set of studies. The authors do an excellent job of exploring a puzzling initial result, showing as they note the importance of linking optogenetic manipulations to known firing patterns in areas of interest in relevant behaviors. A particular strength of the study is the match between the effect of the effective activation on unit activity and the size of the suppression, as well as the remarkable specificity of the findings to rostral but not caudal PL, which provides a very effective control for general effects. I was a bit confused as to what the precise role of the PL contribution was to avoidance and how this related to its role in fear/freezing, which led to the following suggestions.1) Probably the most important one is that I'd like to see the alternative behaviors plotted in detail similar to the one of interest – platform time. While I do not doubt the specificity of the role of rPL, it remains a question from the current data whether disrupting this function makes the rats no longer fearful or fearful but just incapable of organizing the escape response. There is an increase in freezing in one experiment but no effect I think in a later experiment…… but the freezing is very low. Does this mean that the rats continue to barpress for food? This question can be resolved simply by comparing the different behaviors across time – freezing, barpressing, platform. As they can be defined to be mutually exclusive, this more complete analysis may be quite interesting.2) A second related minor suggestion – which I understand may not be worth doing – is that it would be interesting to see what happens to the response if the rPL is activated later in the cue, when the rat is on the platform. That is, in the final experiment, the rPL was activated from the start of the cue, and the escape response was essentially put on hold until the stimulation was terminated. This suggests that the area is triggering the response to avoid. But does it have an ongoing role? This could be addressed by waiting until a platform response was executed and then activating the rPL – do the rats leave the platform? And what do they do – resume barpressing? Freeze?3) Lastly, I think the authors might provide a bit more overview as to how these results fit with the existing data regarding how PL is involved in simple fear conditioning. They seem to suggest that the entire network has been altered by the avoidance training. And yet there are still neurons that seem to signal the fear. How does the lack of effect here fit with effects in experiments lacking avoidance. Some integration with the simpler picture would be helpful.Reviewer #2:In this manuscript, Diehl and colleagues performed a set of experiments examining the role of the prelimibic cortex (PL) in active avoidance. The authors use fluorescent-tagged muscimol to extend a previous finding that PL inhibition delays already established active avoidance. To the author's surprise, optogenetic PL inhibition at the time of cue in this same task had no effect on avoidance – or even sped avoidance initiation when the rostral PL was photo-inhibited. Using single-unit recording they uncovered a novel, inhibitory signal in rostral PL neurons that only emerged during tone presentation in avoidance rats. Accounting for the magnitude of firing decrease observed by these neurons, the authors show that 4 Hz photo-stimulation via channelrhodopsin at only the time of the tone – cancelling out the observed inhibitory – delayed inhibitory avoidance. By contrast, 4 Hz stimulation outside of cue presentation and 2 Hz photo-stimulation during the same cue period had no effect on avoidance. Collectively, the results reveal a new role for the rostral PL in active avoidance that is underpinned by inhibition of firing by presumptive output neurons.The topic is timely, and avoidance is severely understudied compared to fear conditioning. This might be due to the notorious difficulty in establishing avoidance behavior in the lab. The procedure used here is very clever and looks to produce robust avoidance behavior. Technically these experiments are excellent. Further, using neural activity to calibrate the optogenetic manipulation is smart and would be a good practice for the field. Overall, this is a very strong manuscript. My primary concern is the single-unit recording results. Actually, I am not so much concerned as I am convinced that there is a lot more information in the firing than is presented. The manuscript would be greatly improved by digging into this a bit more. Specific comments are below.1) The authors convincingly show that the proportion of excitatory neurons recruited by tone onset does not differ between avoidance, naïve and fear groups. However, the authors do not directly compare neural activity over tone presentation between these three groups. This is a major oversight. In Figure 3D (bottom left) it is clear that while Avoidance and Naïve rats show similar proportions on at tone onset, neuron # falls off dramatically for Avoidance but not Naïve. It would be most informative to plot Z firing  for entirety of tone presentation for the excitatory neurons of the three groups . This is critical not only for understanding what these neurons are doing in the task, but for interpreting the optogenetic stimulation results. As the authors point out, the optogenetic manipulation affects both the excitatory and inhibitory populations. For this reason, it is essential to see the full 28-s excitatory response . ANOVA with factors of time and group would be capable of revealing differential firing (main effect of group or group x time interaction) or supporting the author's claim of no differential firing by revealing only a main effect of time.2) A recurring claim  is that initiation of avoidance is correlated with inhibitory tone responses of rostral PL neurons. This claim is based on of the observation that a significantly greater proportion of inhibitory neurons are observed in the Avoidance group, compared to Naïve and Fear. It is further shown that within this population, the majority of neurons show inhibition linked to cue onset (20/25) whereas a smaller population maintains inhibition for the cue duration (5/25). However, given the analyses performed, it would be more accurate to say that inhibitory tone responses are a correlate observed only in Avoidance rats. If the authors wish to claim that avoidance is correlated with activity, then they need to perform an analysis that directly addresses this. For example, showing that the magnitude of the firing decrease (or some other aspect of firing) predicts the latency of platform entry – percent time on platform – on a trial-by-trial basis. Finding a significant correlation would support the author's claim. However, failing to observe a significant correlation would provide more information about this signal. For that matter, failing to observe a correlation would not dampen my enthusiasm for this manuscript. Inhibitory PL neurons may signal that, within a given context, shock can be avoided. If this were the case, one would expect the population activity observed in Figure 4A, but would not necessarily expect PL activity to predict avoidance on a trial-by-trial basis.3) The analysis and visualization methods used to show that neural activity to the tone and platform entry were not optimal. The population data shown in Figure 3H are a good start, but this is only a small part of the story. For example, the authors do not show the corresponding population activity for the platform entry responsive neurons. Even further, it is clear from Figure 4H that there was variability in the platform response by tone neurons, indicating that some when responsive to platform entry. It could be that the magnitude of the tone response predicts the magnitude of the platform response, but that the tone response was higher across the board. The authors note that activity to platform entry could simply result from a continuing response to tone. A simple way to address this would be to compare differential tone firing (tone onset – baseline) against differential platform entry firing (platform entry onset vs last 10 s of tone). This would provide a more thorough description of the relationship between these two signals.Reviewer #3:eLife following relatively modest revisions and will make a valuable contribution to the literature.Diehl et al. is an interesting, well-designed, appropriately-controlled study that uses electrophysiology and optogenetics to provide compelling evidence for the importance of PL inhibitory activity during active avoidance. I think this manuscript will be appropriate for publication in 1) It is not clear that the authors addressed their primary question: Is PL activity correlated with the initial decision to avoid? They showed PL inhibitory activity is associated with tone onset, and disrupting this activity pattern impairs avoidance, but I think they can't yet make the jump to this inhibitory activity being correlated with the decision-making process. Further support for this claim could potentially be gained by further analysis- e.g. looking in individual animals at whether presence/frequency of inhibitory unit activity is correlated with latency/likelihood to avoid. Alternatively, the scope of the question to be addressed could be changed so it's more limited.2) Similarly, the authors state that inhibitory responses at tone onset correlated with avoidance initiation. However, this seems to be inferred via comparison with control groups instead of being temporally evident from their data- in fact, the data suggest the inhibitory responses are not correlated with avoidance initiation . Please clarify. On a related note, it is difficult to confidently assign the inhibitory responses to avoidance initiation, since it's not clear what that behavior would look like- the first movement to the platform? a mental decision with no observable behavioral correlate? cessation of lever pressing? are we looking at the correlate of one of these other behaviors, instead of avoidance initiation? This can potentially be addressed via examination of behavioral correlates of single unit activity at tone onset if they have the data, or by limiting the interpretation.3) Rats were included whose viral expression spread into Cg1, due to the rationale that Cg1 and PL perform similar functions. While this has been shown in fear conditioning , it has not been examined in active avoidance. More discussion of this is warranted, since many of the caudal PL recording placements in Figure 3A are in Cg1, not cPL.4) The authors optogenetically stimulate or inhibit PL neurons during the first of two extinction tones, but the rationale is not discussed. If Tone 2 is meant to serve as an unstimulated within-subject control, they should discuss potential confounding factors that could affect behavior during Tone 2 5) Rationale for stimulating at 4Hz instead of 6Hz isn't clear. Is there evidence to indicate optogenetic stimulation at a certain frequency has an additive effect on a cell's current frequency, rather than causing entrainment at the stimulation frequency?6) The authors should discuss differences between rPL and cPL further and provide a stronger rationale for analyzing them independently. Where does cPL project? What might explain why rPL, not cPL, is involved in active avoidance? Is there a different breakdown in rPL and cPL in their previous cFos studies?7) One of the major reasons for selecting the brief post-tone latency for analysis was to ensure PL neuron activity is limited to tone, and not subsequent behavior. However, this is not convincing, given there seems to be significant avoidance even at that point. Expanding the Figure 3C x-axis around the time of tone onset will help evaluate this issue. Essential revisions:In our discussion, the reviewers identified three key areas that some additional information would be helpful. I have left the comments below intact, but these three revisions are the ones that are most important to us. The first is to provide additional detail on what behavior the rats do instead of avoiding when PL is manipulated. This is interesting in its own right and also will help to identify the role of PL – for example what happens might be different depending on whether PL is actually involved in triggering the decision versus evoking fear. All three reviewers agreed this was useful, though it is described by R1. In addition, we also thought additional detail on the single unit data would be helpful. R2 would like more information regarding the excitatory correlates and their relation or lack thereof to behavior, since they are presumably affected by the inhibitory tone. R3 is interested in developing stronger correlative relationships between firing activity and the actual decision. In part, the question here is whether there is any better metric than is provided and/or if not to discuss in more detail what is meant here, given that the actual decision to avoid is so hard to define experimentally – how can you say this is really what the neurons are doing?Reviewer #1:[…] This is a remarkable set of studies. The authors do an excellent job of exploring a puzzling initial result, showing as they note the importance of linking optogenetic manipulations to known firing patterns in areas of interest in relevant behaviors. A particular strength of the study is the match between the effect of the effective activation on unit activity and the size of the suppression, as well as the remarkable specificity of the findings to rostral but not caudal PL, which provides a very effective control for general effects. I was a bit confused as to what the precise role of the PL contribution was to avoidance and how this related to its role in fear/freezing, which led to the following suggestions.1) Probably the most important one is that I'd like to see the alternative behaviors plotted in detail similar to the one of interest – platform time. While I do not doubt the specificity of the role of rPL, it remains a question from the current data whether disrupting this function makes the rats no longer fearful or fearful but just incapable of organizing the escape response. There is an increase in freezing in one experiment but no effect I think in a later experiment…… but the freezing is very low. Does this mean that the rats continue to barpress for food? This question can be resolved simply by comparing the different behaviors across time – freezing, barpressing, platform. As they can be defined to be mutually exclusive, this more complete analysis may be quite interesting.The reviewer logically asks, “what is the rat doing if it is not avoiding?” when rPL is manipulated. To address this, we further assessed freezing and suppression of bar pressing when PL was manipulated with MUS, ARCH, or ChR2. Neither freezing nor suppression were significantly reduced by any of the manipulations, indicating that the reduction in avoidance was not accompanied by a reduction in fear. We have added insets to all the behavioral figures  showing freezing and suppression of bar pressing. As we had originally reported, MUS in PL actually increased freezing during the tone . Analysis of 3-second bins revealed that this effect reached significance only at seconds 18-21 , making it unlikely that the reduction in avoidance early in the tone was due to increased freezing. A similar 3-second bin analysis of freezing for ARCH  or ChR2  is in 2) A second related minor suggestion – which I understand may not be worth doing – is that it would be interesting to see what happens to the response if the rPL is activated later in the cue, when the rat is on the platform. That is, in the final experiment, the rPL was activated from the start of the cue, and the escape response was essentially put on hold until the stimulation was terminated. This suggests that the area is triggering the response to avoid. But does it have an ongoing role? This could be addressed by waiting until a platform response was executed and then activating the rPL – do the rats leave the platform? And what do they do – resume barpressing? Freeze?This is an interesting question that would tell us if PL signaling is needed for the maintenance of avoidance behavior. Our single-unit data demonstrate that most of the inhibitory responses at platform entry terminated soon after entry , suggesting that sustained inhibition may not be necessary for maintaining avoidance.3) Lastly, I think the authors might provide a bit more overview as to how these results fit with the existing data regarding how PL is involved in simple fear conditioning. They seem to suggest that the entire network has been altered by the avoidance training. And yet there are still neurons that seem to signal the fear. How does the lack of effect here fit with effects in experiments lacking avoidance. Some integration with the simpler picture would be helpful.The reviewer wants to know how the current findings, that manipulations of PL have little effect on freezing, can be reconciled with previous studies of ours and others demonstrating PL’s critical role in expression of Pavlovian conditioned freezing. It is well-established that early in avoidance training, rats use Pavlovian conditioning to learn that the tone signals shock, and then switch to instrumental avoidance learning as training continues. We suggest, therefore, that PL was serving the well-established role of supporting freezing in the early stages of training. In fact, we observed that silencing rPL during the second day of avoidance conditioning significantly reduced freezing (see subsection “Photosilencing of PL glutamatergic neurons does not delay avoidance”). However, as rats learn the avoidance response, freezing decreases and is no longer susceptible to PL manipulations. We initially reported this in our 2014 MUS study  and observed it again here with MUS and ARCH inhibition of PL. Thus, the circuit for conditioned freezing changes dramatically with avoidance training. We now emphasize this in the Discussion section.Reviewer #2:[…] The topic is timely, and avoidance is severely understudied compared to fear conditioning. This might be due to the notorious difficulty in establishing avoidance behavior in the lab. The procedure used here is very clever and looks to produce robust avoidance behavior. Technically these experiments are excellent. Further, using neural activity to calibrate the optogenetic manipulation is smart and would be a good practice for the field. Overall, this is a very strong manuscript. My primary concern is the single-unit recording results. Actually, I am not so much concerned as I am convinced that there is a lot more information in the firing than is presented. The manuscript would be greatly improved by digging into this a bit more. Specific comments are below.1) The authors convincingly show that the proportion of excitatory neurons recruited by tone onset does not differ between avoidance, naïve and fear groups. However, the authors do not directly compare neural activity over tone presentation between these three groups. This is a major oversight. In Figure 3D (bottom left) it is clear that while Avoidance and Naïve rats show similar proportions on at tone onset, neuron # falls off dramatically for Avoidance but not Naïve. It would be most informative to plot Z firing  for entirety of tone presentation for the excitatory neurons of the three groups . This is critical not only for understanding what these neurons are doing in the task, but for interpreting the optogenetic stimulation results. As the authors point out, the optogenetic manipulation affects both the excitatory and inhibitory populations. For this reason, it is essential to see the full 28-s excitatory response . ANOVA with factors of time and group would be capable of revealing differential firing (main effect of group or group x time interaction) or supporting the author's claim of no differential firing by revealing only a main effect of time.=1.17, p=0.316), but a main effect of time (p<0.001), and an interaction of Group x Time =1.245, p=0.0443), which revealed that the fear conditioned group was significantly higher than the avoidance group at the first 500 ms time point  A recurring claim  is that initiation of avoidance is correlated with inhibitory tone responses of rostral PL neurons. This claim is based on of the observation that a significantly greater proportion of inhibitory neurons are observed in the Avoidance group, compared to Naïve and Fear. It is further shown that within this population, the majority of neurons show inhibition linked to cue onset (20/25) whereas a smaller population maintains inhibition for the cue duration (5/25). However, given the analyses performed, it would be more accurate to say that inhibitory tone responses are a correlate observed only in Avoidance rats. If the authors wish to claim that avoidance is correlated with activity, then they need to perform an analysis that directly addresses this. For example, showing that the magnitude of the firing decrease (or some other aspect of firing) predicts the latency of platform entry – percent time on platform – on a trial-by-trial basis. Finding a significant correlation would support the author's claim. However, failing to observe a significant correlation would provide more information about this signal. For that matter, failing to observe a correlation would not dampen my enthusiasm for this manuscript. Inhibitory PL neurons may signal that, within a given context, shock can be avoided. If this were the case, one would expect the population activity observed in Figure 4A, but would not necessarily expect PL activity to predict avoidance on a trial-by-trial basis.The reviewer raises the valid question of whether or not the inhibitory response correlates with avoidance behavior on a trial-by-trial basis. To address this, we performed a new analysis comparing the latency of inhibition with the latency of platform entry, on a trial-by-trial basis. For a given cell on a given trial, the latency of the inhibitory response to the tone was identified as the start of the first interspike interval (ISI) that was significantly longer than the average ISI in 30 seconds of pre-tone activity . 133/205 neurons showed at least one ISI that satisfied this criterion. For 133 neurons, the correlation between the latency of inhibition and latency of platform entry was only r=0.022 (not correlated). We then computed for each cell the average latency of inhibition and platform entry. For each cell, we averaged its inhibitory latency across all the trials in which successful avoidance was observed . We also averaged the avoidance latency on those trials. The correlation between these two averages across cells was r=0.078 . This result is plotted in new Figure 3—figure supplement 1E-F. Figure 3—figure supplement 1E shows that the inhibitory response of the majority of cells preceded platform entry (88/133 cells) but was not correlated with platform entry. The frequency distribution shown in Figure 3—figure supplement 1F confirm that most inhibition preceded platform entry. For trials in which the rat did not avoid , there was a similar latency of inhibition . Thus, these new analyses do not support our original hypothesis that PL inhibition initiates avoidance and is more consistent with the reviewer’s suggested hypothesis: that PL inhibitory responses signal that, within a given context, footshocks can be avoided . We thank the reviewer for suggesting this analysis and the alternative interpretation of our results. We have modified the text throughout.3) The analysis and visualization methods used to show that neural activity to the tone and platform entry were not optimal. The population data shown in Figure 3H are a good start, but this is only a small part of the story. For example, the authors do not show the corresponding population activity for the platform entry responsive neurons. Even further, it is clear from Figure 4H that there was variability in the platform response by tone neurons, indicating that some when responsive to platform entry. It could be that the magnitude of the tone response predicts the magnitude of the platform response, but that the tone response was higher across the board. The authors note that activity to platform entry could simply result from a continuing response to tone. A simple way to address this would be to compare differential tone firing (tone onset – baseline) against differential platform entry firing (platform entry onset vs last 10 s of tone). This would provide a more thorough description of the relationship between these two signals.To more clearly indicate whether neurons were responsive to tone onset, platform entry or both, we removed the original population graph in 3H, and now show a Venn diagram indicating the number of neurons that overlapped across response categories . Only a small proportion of excitatory cells were responsive to both tone onset and platform entry, suggesting that these were generated by separate groups of cells. However, the inhibitory responses show more overlap between tone onset and platform entry responses: out of 22 inhibitory tone responsive and 16 inhibitory entry responsive, 9 cells were responsive to both events. The suggestion by the reviewer of comparing platform entry responses to activity during the last 10 seconds of the tone may not reveal any differences because PL activity at the end of the tone may reflect other factors such as tone duration, anticipation of shock, anticipation of platform exit to resume food-seeking, and is therefore not a reliable baseline.Reviewer #3:Diehl et al. is an interesting, well-designed, appropriately-controlled study that uses electrophysiology and optogenetics to provide compelling evidence for the importance of PL inhibitory activity during active avoidance. I think this manuscript will be appropriate for publication in eLife following relatively modest revisions and will make a valuable contribution to the literature.1) It is not clear that the authors addressed their primary question: Is PL activity correlated with the initial decision to avoid? They showed PL inhibitory activity is associated with tone onset, and disrupting this activity pattern impairs avoidance, but I think they can't yet make the jump to this inhibitory activity being correlated with the decision-making process. Further support for this claim could potentially be gained by further analysis- e.g. looking in individual animals at whether presence/frequency of inhibitory unit activity is correlated with latency/likelihood to avoid. Alternatively, the scope of the question to be addressed could be changed so it's more limited.The reviewer raises the valid question of whether or not the inhibitory response correlates with avoidance behavior on a trial-by-trial basis. To address this, we performed a new analysis comparing the latency of inhibition with the latency of platform entry, on a trial-by-trial basis. For a given cell on a given trial, the latency of the inhibitory response to the tone was identified as the start of the first interspike interval (ISI) that was significantly longer than the average ISI in 30 seconds of pre-tone activity . 133/205 neurons showed at least one ISI that satisfied this criterion. For 133 neurons, the correlation between the latency of inhibition and latency of platform entry was only r=0.022 (not correlated). We then computed for each cell the average latency of inhibition and platform entry. For each cell, we averaged its inhibitory latency across all the trials in which successful avoidance was observed . We also averaged the avoidance latency on those trials. The correlation between these two averages across cells was r=0.078 . This result is plotted in new Figure 3—figure-supplement 1E-F. Figure 3—figure supplement 1E shows that the inhibitory response of the majority of cells preceded platform entry (88/133 cells) but was not correlated with platform entry. The frequency distribution shown in Figure 3—figure supplement 1F confirm that most inhibition preceded platform entry. For trials in which the rat did not avoid , there was a similar latency of inhibition .2) Similarly, the authors state that inhibitory responses at tone onset correlated with avoidance initiation. However, this seems to be inferred via comparison with control groups instead of being temporally evident from their data- in fact, the data suggest the inhibitory responses are not correlated with avoidance initiation . Please clarify. On a related note, it is difficult to confidently assign the inhibitory responses to avoidance initiation, since it's not clear what that behavior would look like- the first movement to the platform? a mental decision with no observable behavioral correlate? cessation of lever pressing? are we looking at the correlate of one of these other behaviors, instead of avoidance initiation? This can potentially be addressed via examination of behavioral correlates of single unit activity at tone onset if they have the data, or by limiting the interpretation.See response to your point #1 above. Figure 3G show responses at platform entry – the time at which the rat’s head entered the platform zone after the action to avoid had already commenced. We therefore searched for behavioral correlates that might precede platform entry, focusing on the first headturn after tone onset – which is the first movement the rat makes before proceeding to the platform. We compared the average inhibition latency with average the time of headturn for each cell showing inhibition, shown in Figure 3—figure supplement 1E-F. This analysis revealed similar results: 82/133 cells showed inhibition prior to headturn, but there was no correlation between inhibition latency and headturn latency (r=0.054).3) Rats were included whose viral expression spread into Cg1, due to the rationale that Cg1 and PL perform similar functions. While this has been shown in fear conditioning , it has not been examined in active avoidance. More discussion of this is warranted, since many of the caudal PL recording placements in Figure 3A are in Cg1, not cPL.The reviewer wants to know if Cg1 and PL have a similar function during avoidance, as our PL viral expression reaches into Cg1. Previous studies in rabbits have found that neuronal firing in both the anterior cingulate cortex and PL correlate with avoidance learning, in which rabbits must activate a running wheel to prevent a tone-signaled footshock . Regarding our single units, we re-assessed our histology and found that one of the cPL rats had all its units located in Cg1. Removing this rat reduced the number of Cg1 units in cPL, so that the percentage of Cg1 units is now more similar in rPL and cPL (~36%). We now state this in the Materials and methods section. With this rat removed, all cells showing inhibitory responses were located in rPL, with none in cPL .4) The authors optogenetically stimulate or inhibit PL neurons during the first of two extinction tones, but the rationale is not discussed. If Tone 2 is meant to serve as an unstimulated within-subject control, they should discuss potential confounding factors that could affect behavior during Tone 2 As the reviewer surmised, Tone 2 served as an unstimulated within-subject control. In terms of confounding factors, rebound excitation is unlikely as Tone 2 was presented 3 minutes after Tone 1. Short-term plasticity may have affected the behavioral response to Tone 2; however, in both ARCH and ChR2 experiments, the response to Tone 1 was statistically compared to the eYFP control group at Tone 1. Tone 2 is simply added to identify any persistent effects of the laser activation (none were observed). The rationale of Tone 2 is now discussed in the Materials and methods section.5) Rationale for stimulating at 4Hz instead of 6Hz isn't clear. Is there evidence to indicate optogenetic stimulation at a certain frequency has an additive effect on a cell's current frequency, rather than causing entrainment at the stimulation frequency?Yes, our intention was that naturally-occurring and optogenetically-induced spikes would sum, so that 4 Hz stimulation would cause a neuron normally firing at 2 Hz to fire at 6 Hz. However, as shown in Figure 4C, this was not the case. In anesthetized rats, cells firing at an average of 1.5 Hz baseline rate only increased to 3.3 Hz with 4 Hz optogenetic stimulation. This may be due to entrainment, as the reviewer suggests, or poor frequency following at the current levels we used. Prior studies have reported that entrainment tends to occur at low levels of ChR2 stimulation . It is therefore difficult to predict exactly how cortical neurons will respond to ChR2 stimulation. Suffice it to say that our 4Hz stimulation significantly increased the rate of the PL neurons expressing ChR2 (see figure 4C). We now discuss this in the Results section.6) The authors should discuss differences between rPL and cPL further and provide a stronger rationale for analyzing them independently. Where does cPL project? What might explain why rPL, not cPL, is involved in active avoidance? Is there a different breakdown in rPL and cPL in their previous cFos studies?Very few studies have examined anatomical  or functional  differences between rostral and caudal portions of PL. We investigated anatomical differences in projections of rPL and cPL within broader anatomical studies on prelimbic prefrontal cortex, which show that rPL projects less densely to ventral striatum compared to cPL . With respect to midbrain structures, rPL projects more densely to vlPAG whereas cPL projects more densely to dlPAG , which could be a factor in selecting freezing vs. flight. Although our previous Fos studies have not differentiated rPL from cPL, we are currently examining our cFos findings in light of the new differences we have observed in rPL and cPL.7) One of the major reasons for selecting the brief post-tone latency for analysis was to ensure PL neuron activity is limited to tone, and not subsequent behavior. However, this is not convincing, given there seems to be significant avoidance even at that point. Expanding the Figure 3C x-axis around the time of tone onset will help evaluate this issue.The reviewer is concerned that some of the tone onset responses may be due to avoidance behavior since some avoidance latencies were <1 second. However, in only 25/284 (9%) trials did avoidance occur prior to 1000ms. Below is an expanded view of the Figure 3C showing the times of platform entry (black dots,


Glycolysis provides precursors for the synthesis of macromolecules and may contribute to the ATP supply required for the constant and accelerated cellular duplication in cancer cells. In consequence, inhibition of glycolysis has been reiteratively considered as an anti-cancer therapeutic option. In previous studies, kinetic modeling of glycolysis in cancer cells allowed the identification of the main steps that control the glycolytic flux: glucose transporter, hexokinase (HK), hexose phosphate isomerase (HPI), and glycogen degradation in human cervix HeLa cancer cells and rat AS-30D ascites hepatocarcinoma. It was also previously experimentally determined that simultaneous inhibition of the non-controlling enzymes lactate dehydrogenase (LDH), pyruvate kinase (PYK), and enolase (ENO) brings about significant decrease in the glycolytic flux of cancer cells and accumulation of intermediate metabolites, mainly fructose-1,6-bisphosphate , and dihydroxyacetone phosphate (DHAP), which are inhibitors of HK and HPI, respectively. Here it was found by kinetic modeling that inhibition of cancer glycolysis can be attained by blocking downstream non flux-controlling steps as long as Fru1,6BP and DHAP, regulatory metabolites of flux-controlling enzymes, are accumulated. Furthermore, experimental results and further modeling showed that oxamate and iodoacetate inhibitions of PYK, ENO, and glyceraldehyde3-phosphate dehydrogenase (GAPDH), but not of LDH and phosphoglycerate kinase, induced accumulation of Fru1,6BP and DHAP in AS-30D hepatoma cells. Indeed, PYK, ENO, and GAPDH exerted the highest control on the Fru1,6BP and DHAP concentrations. The high levels of these metabolites inhibited HK and HPI and led to glycolytic flux inhibition, ATP diminution, and accumulation of toxic methylglyoxal. Hence, the anticancer effects of downstream glycolytic inhibitors are very likely mediated by this mechanism. In parallel, it was also found that uncompetitive inhibition of the flux-controlling steps is a more potent mechanism than competitive and mixed-type inhibition to efficiently perturb cancer glycolysis. In recent years it has been extensively documented that oxidative phosphorylation (OxPhos) is predominant for supplying ATP in cancer cells under aerobic conditions , pyruvate kinase (PYK), and lactate dehydrogenase (LDH) have been also proposed as suitable targets for inhibition of cancer glycolysis  and fructose-1,6-bisphosphate  and the pentose phosphate pathway metabolites erythrose-4-phosphate (Ery4P) and 6-phosphogluconate (6PG) can modulate the activities of the controlling enzymes HK and HPI through competitive and mixed-type inhibitions. Furthermore, some metabolites that at low, physiological concentrations are innocuous, at high concentrations may become inhibitors of the controlling steps HK  and HPI , inducing significant inhibition of the glycolytic flux in cancer cells  on controlling enzymes impact the pathway systemic properties (fluxes and metabolite concentrations) were also carried out using the kinetic glycolysis models.Such a goal was pursued and resolved in the present paper by using our published AS-30D and HeLa cells glycolysis kinetic models  inhibition of GAPDH with iodoacetate, or PYK/ENO with oxamate but not LDH, PGK, or PGAM, induces Fru1,6BP and DHAP accumulation and methylglyoxal production, leading to significant suppression of glycolysis; and (ii) uncompetitive inhibition of the most controlling pathway steps is the most direct and potent mechanism to efficiently perturb cancer glycolysis.+, NADP+, and oxamate were from Sigma Chemical .HK, Glc6PDH, HPI, aldolase, α-glycerophosphate dehydrogenase, triosephosphate isomerase (TPI), LDH, and Fru6P were purchased from Roche . Glucose, iodoacetate, methylglyoxal, NADH, NAD8 cells/mL. After 5–6 days, the intraperitoneal cavity liquid was extracted and tumor cells were isolated by centrifugation as previously described  were incubated in saline Krebs-Ringer medium supplied with oxamate (10 or 20 mM) or iodoacetate (2 or 4 mM) for 60 min under orbital shaking at 150 rpm and 37°C; under such conditions cell viability was always higher than 90%. Thereafter, a cell sample was withdrawn (time 0) and 5 mM glucose was added; after further 10 min of incubation another cell sample (time 10) was withdrawn. The cell samples were immediately mixed with ice-cold perchloric acid , vortexed and centrifuged at 1800 × g for 1 min at 4°C. The supernatants were neutralized with 3 M KOH/0.1 M Tris, further incubated in ice for at least 30 min and then centrifuged. The supernatants were stored at −72°C until use for determination of Glc6P, Fru6P, Fru1,6BP, G3P, DHAP, ATP, ADP, and L-lactate contents as described by Bergmeyer . The rat2 (40 ml/min) mix was used as carrier gas. The cell sample (15 mg/ml) was withdrawn after time 10 and centrifuged at 1800 × g for 2 min. 0.5 mL of the supernatant was removed and the cell pellet was resuspended in the remaining supernatant. The suspension was sonicated with a Branson sonicator three times for 15 s at 60% of maximal output with 1 min rest, in an ice bath. The sonicate was centrifuged at 20 800 × g for 5 min. The supernantant was filtered and 1–2 μl were injected in the gas chromatograph. The limit of detection of methylglyoxal was lower than 0.3 nmoles. The concentration in the stock solution of methlyglyoxal was enzymatically calibrated by using human ALDH2 and saturating NAD+.Methylglyoxal was determined by gas chromatography in a Shimadzu GC2010 apparatus  equipped with a capillary column HP-PLOT/U of 30 m length, 0.32 mm I.D. and 10 μm film , and flame ionization detector. A methylglyoxal standard curve was carried out in the range of 0.3–30 nmoles, and the time of retention was 4.7 min. The equipment conditions were FID temperature 200°C, column temperature 180°C, oven temperature 180°C, and linear velocity 26.4 cm/s. He (10 ml/min) and H+-based medium at pH 7.0 and 37°C; Marín-Hernández et al., The previous kinetic models of glycolysis built for HeLa and AS-30D cells ] as it was previously determined , representing the co-existence of two isoforms  used for the present updated AS-30D model was a random Bi-Bi system Segel,  with mixA = [Glcin], B = [ATP], P = [Glc6P] and Q = [ADP]. Ka, Kb, Kp, and Kq are the Km values for the corresponding substrates and products. α1 and α2 values are the factors by which Ka (Kmglc) changes when B (ATP) and I  are bound to the enzyme, respectively. Ki is the inhibition constant for Fru1,6BP .where In the HeLa model, the HK rate equation (Equation 4) was a double random-bisubstrate Michaelis-Menten to also represent the coexistence of two enzyme isoforms as previously reported  with (a) competitive  with competitive inhibition by four modulators: Ery4P, 6PG, Fru1,6BP and DHAP as experimentally determined  in all kinetic models was the concerted transition model of Monod, Wyman and Changeux for exclusive ligand binding  together with mixed-type activation and simple Michaelis–Menten terms for ATP and reverse reaction  to that defined in the reaction specification window. If the order of substrates and products in the reaction does not match with that stated in the rate equation, then the computer program mix-up the identity of the ligands in the ordinary differential equations. Therefore, to correct for this type of errors both the syntax reaction and the rate equation have to be displayed in the same order of substrates and products; then one should be aware that the reaction syntax does not necessarily reflect the order of binding in the enzyme, which defines the type of reaction mechanism.Reaction: ATP + Fru6P = ADP + Fru1,6BPThe ALDO rate equation was the reversible Uni-Bi random Michaelis-Menten equation (Equation 8) in all kinetic models as was reported in previous kinetic models  with mixed type inhibition by Fru1,6BP as it was previously determined .α value is the factor by which In the HeLa model, the TPI rate equation (Equation 10) was a mono-substrate simple reversible Michaelis-Menten equation as it was previously determined  with mixed type inhibition by Fru1,6BP as previously determined . Ki is the inhibition constant for Fru1,6BP . α value is the factor by which Kb (KmG3P) changes when Fru1,6BP is bound to the enzyme.where In the HeLa model, the GAPDH rate equation (Equation 12) was a simplified ordered Ter-Bi Michaelis-Menten equation as was previously determined and used in previous models :S] and [P] are the respective concentrations of substrates and products and their respective Km values (Ks and Kp) which were experimentally determined in previous works  in all models was defined as simple random-bisubstrate Michaelis-Menten that represents the kinetics of the prevalent PYK isoform in cancer cells with no cooperativity or allosteric modulation by typical metabolites, as experimentally determined for AS-30D cells  for PGK and LDH were defined by random Bi-Bi reversible Michaelis-Menten for non-interacting substrates (α and β = 1) according to the reported literature  for the monocarboxylate transporter (MCT) activity was incorporated . The models were optimized using the ArgusLab 4.0.1  available at: http://www.arguslab.com and Maestro, version 9.1  softwares. For docking analysis, the ligands from the above protein crystal structures were removed using the software UCSF Chimera package 1.6 .Crystal structures of human HK type I, TPI and GAPDH, and mouse HPI, were obtained from the protein data bank . The three dimensional models of the ligands used in the study were obtained from different crystal structures found in the protein data bank or downloaded from PubChem  of the activity to decrease the pathway flux to the levels reached by inhibiting a flux-controlling step. However, there are experimental evidences indicating that oxamate and iodoacetate, presumed specific inhibitors of LDH and GAPDH, i.e., two non-controlling glycolytic enzymes, do affect the glycolytic flux of cancer, and non-cancer cells  with respect to the models previously published  and not flux-controlling (TPI and GADPH) enzymes, several simulations were made with the AS-30D model Figure . When ind Figure .2 and glucose culture conditions.Furthermore, the Fru1,6BP and DHAP levels indeed increased in cells treated with oxamate  of HPI inhibitors was modeled. A decrease of 90% in the Ki value  increased the HPI flux-control coefficient to a value of 0.27  to keep unaltered the HPI flux-control coefficient, pathway flux and Glc6P concentration  was envisioned three decades ago  and catalytic efficiency (Vmax/Km). It is recall that the Vmax value is directly linked to the content of active enzyme  and hence to transcriptional/translational regulation and protein degradation. The design of new inhibitors should consider the uncompetitive and mixed-type inhibition mechanisms to generate potent drugs against cancer glycolysis.These Ki values (in mM) were 0.076 (Ery4P), 0.45 (6PG), 2.2 , and 11.6 (DHAP) which indicated that Ery4P and 6PG bind more tightly to the enzyme active site compared with the other two metabolites. These results correlated with previous data indicating that the most potent HPI inhibitors are Ery4P (Ki = 0.8–2.5 μM) and 6PG . However, enzyme structures are flexible and upon substrate or modifier binding, the active sites have in general conformational changes that in most cases favor tighter ligand coupling. However, despite these limitations, the docking data analysis predicted the order of binding efficiency and potency of the HPI inhibitors. Also, docking analysis showed that Fru1,6BP can bind to the active sites of HK, TPI, and GAPDH  might have similar effects on non-cancer cells, both inhibitors are well-tolerated in animals and human non-cancer cell lines, suggesting that normal cells are less sensitive to glycolysis inhibition, likely due to a lower dependence on glycolysis for their proliferation with respect to tumor cells. In addition, glycolysis inhibition of tumor associated fibroblasts (reverse Warburg effect) may be also beneficial to deter tumor growth  than with a competitive one  was the lowest (Bakker et al., Uncompetitive and mixed-type inhibitions modify the Kinetic modeling studies have shown that only the simultaneous inhibition of several flux-controlling steps will have significant impact on glycolytic flux and ATP concentration in cancer cells. This can be accomplished by direct inhibition using, preferentially, uncompetitive specific drugs or indirectly through the accumulation of regulatory metabolites of the flux-controlling steps by inhibiting enzymes that exert low flux-control.in vitro and in silico experiments and docking analysis, AM-H, SR-E, RM-S, and ES planned experiments, analyzed data, contributed reagents, and wrote the paper.AM-H, IDM-M, and JSR-Z performed the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Antibody-drug conjugates (ADCs) have become a promising class of antitumor agents with four conjugates being approved by regulatory agencies for treating cancer patients. To improve the conventional conjugations that are currently applied to generate these heterogeneous products, various site-specific approaches have been developed. These methods couple cytotoxins or chemotherapeutic drugs to specifically defined sites in antibody molecules including cysteine, glutamine, unnatural amino acids, short peptide tags, and glycans. The ADCs produced showed high homogeneity, increased therapeutic index, and strong antitumor activities in vitro and in vivo. Moreover, there are recent trends in using these next generation technologies beyond the cytotoxin-conjugated ADC. These site-specific conjugations have been applied for the generation of many different immunoconjugates including bispecific Fab or small molecule–antibody conjugates, immunosuppressive antibodies, and antibody–antibiotic conjugates. Thus, it is likely that additional technologies and related site-specific conjugates will emerge in the near future, with various chemicals or small molecular weight proteins in addition to cytotoxin for better treatment of many challenging diseases. Therapeutic antibodies have become a major class of biologics in treating many challenging diseases, including cancer. Due to the fact that they have high specificity and affinity, the monoclonal antibodies have less off-target side-effects as compared to small molecular weight compounds. Currently, many monoclonal antibodies are under accelerated clinical developments . It was As one of the targeted therapies or the “magic bullet” proposed by Paul Ehrlich more than a century ago , the conThus, this unique format would allow the use of certain chemotherapeutic drugs which are too potent or toxic to be applied systemically. Since these cytotoxins need to be delivered into the tumor cells targeting intracellular microtubules or DNA, the chemotherapeutic drugs carrying antibodies should be efficiently internalized into lysosome once binding to the antigen on the tumor surface . Within All these ADCs were prepared using conventional conjugation methods that couple antibodies through either surface-exposed lysines (~70 to 90) or cysteines from interchain disulfides (8 in IgG1) after partial reduction. These lysine and cysteine methods generate heterogeneous products with varied numbers of drugs coupled across several possible sites although the average drug-to-antibody ratio (DAR) appears around 4 to 6, creating significant challenges for process consistency and product characterization ,24,25. IIn contrast to the conventional conjugations to the lysines or cysteines, which are abundant in an antibody, the site-specific conjugations couple the antibodies with cytotoxins through the unique and defined sites based on antibody engineering. There are four major categories of methods based on the conjugation sites in the antibody molecules, including specific amino acids, unnatural amino acids, short peptide tags, or glycans .Several native or engineered amino acids, including cysteines and glutamines, are selected as the sites for conjugation.The unpaired cysteine-mediated conjugation was the first described site-specific ADC as THIOMAB or TDC . A cysteMoreover, cysteine insertion was also described in antibody before and after selected sites in either IgG HC or LC, including LC-V205, HC-A114, and HC-S239 . There wIn addition to conjugation through unpaired cysteine, thiol bridge methods were developed to conjugate a bifunctional drug-linker to both cysteines from each of interchain disulfide, instead of only one cysteine in the conventional cysteine conjugation, after partial reduction and re-oxidation ,32. ThusThe site-specific conjugation through glutamine was also reported ,34. InstThe site-specific conjugation through unpaired cysteine is relatively simple and scalable. The drug coupling was done without the need of special reagents. The method has been applied to prepare multiple site-specific ADCs for preclinical or clinical developments. As described above, the ADCs prepared through site-specific cysteines showed two-fold stronger in vivo antitumor activities and were better tolerated than the conventional conjugates. However, the stability of conjugate generated through unpaired cysteine varied dependent on where the cysteine was introduced in an antibody molecule . It appeMethanococcus jannaschii was expressed in the cells to site-specifically incorporate p-acetylphenylalanine (pAcF) in response to an amber nonsense codon engineered in the antibodies. The keto group of pAcF was then selectively coupled to a drug-linker with aminooxy functionality. The pAcF-containing anti-HER2 was produced from Chinese hamster ovary (CHO) cells co-expressing antibody with an amber codon at heavy chain (HC-A121) and an orthogonal amber suppressor tRNA/aaRS pair. The pAcF residue was coupled with a non-cleavable auristatin linker, which is a potent tubulin inhibitor, through oxime chemistry with DAR at ~2. The anti-HER2 ADC showed strong in vitro and in vivo antitumor activities. The method was further optimized, and a stable CHO cell line was generated to express orthogonal amber suppressor tRNA/aaRS pair ..60].Methanococcus jannaschii was co-expressed to site-specifically incorporate pAcF at defined sites in each of two Fab fragments in response to an amber nonsense codon. The unnatural amino acids was incorporated into LC-S202 of Fab fragment of anti-HER2 and subsequently conjugated with PEG linker containing azide, while pAcF was incorporated in HC-K138 of Fab fragment of anti-CD3 before conjugated with PEG linker containing BCN. Both Fab fragments were subsequently coupled using copper-free click chemistry. In an in vitro cytotoxicity assay, the bispecific antibody Fab conjugate efficiently recruited T cells from human peripheral blood mononuclear cells (PBMCs) to kill the target tumor cells at picomolar concentration. Moreover, the same site-specific antibody conjugation approach was applied to prepare bispecific antibody Fab conjugates against both CD3 and C-type lectin-like molecule-1 (CLL1) as well as both CD3 and CD33 [The antibody fragments have been coupled using site-specific method as bispecific antibody Fab conjugates. In a study, bispecific antibody Fab conjugate was generated using genetically encoded unnatural amino acids with orthogonal chemical reactivity as described above for cytotoxin containing ADC . A tRNA/and CD33 . CLL1 anand CD33 . As descBesides the bispecific antibody Fab conjugation, chemically programmed bispecific antibody conjugation is another strategy for site-specifically preparing a bispecific antibody. Kim et al. reported the generation of a bispecific small molecule-antibody conjugate for targeting prostate cancer . They inStaphylococcus aureus that can establish infection even in the presence of antibiotics vancomycin. They prepared an AAC in which an anti-S. aureus antibody was conjugated to a highly efficacious antibiotics rifalogue that is activated only after being released in lysosome. A cysteine residue was engineered at the V205 position of ant-bacteria antibody light chain and the thiol containing antibody was conjugated to MC-vc-PAB-rifalogue. The AAC is superior to vancomycin for the treatment of bacteremia in vivo.Lehar et al. reported generation of novel antibody-antibiotic conjugate (AAC) using THIOMAB approach . They foA site-specific antibody-polymer conjugation (APC) approach was also reported . An unna50 at nM range, but had no significant effect in hepatocytes, indicating that payload delivery was CD11a-mediated. This approach represents a fundamentally different strategy that uses tissue targeting to overcome the limitations of LXR agonists for potential use in treating atherosclerosis.The site-specific antibody conjugation has been applied for preparing immunoconjugates against other diseases such as autoimmune disease and atherosclerosis. A highly potent phosphodiesterase 4 (PDE4) inhibitor, GSK256066, was site-specifically coupled to a human anti-CD11a through unnatural amino acid, pAcF, introduced at HC-A122 with DAR at ~2 . PDE4 isAs next generation technologies, the site-specific antibody conjugations are likely to be applied to different therapeutic areas for preparing homogeneous immunoconjugates. The combination of therapeutic antibodies with wide varieties of small molecular weight proteins or drugs would potentially expand the current treatment options for many challenging diseases. Although it is unknown which methods are better than others, each category of these methods may have their unique advantages related to the in vivo and in vitro properties of the conjugates.Site-specific antibody drug conjugation technologies have been developed by coupling the cytotoxin to engineered specific amino acids, unnatural amino acids, short peptide tags, and N297 glycans. As next generation methods, these approaches generated homogeneous ADCs with a high therapeutic index as compared to the conventional conjugations. Some of the site-specific ADCs even showed better antitumor efficacy in vivo than the ADCs prepared using conventional methods. Moreover, there are trends in applying these site-specific antibody conjugations to other therapeutic areas or diagnosis. All those studies have provided promising results that suggest the usefulness of these next generation methods in the coupling of small proteins, small molecular weight compounds, DNAs, and RNAs. It is not surprising that these new technologies will lead to important therapeutic platforms for many unmet medical needs.


Prior to local translation, mRNA that is to be translated is packed into ribonucleoprotein particles (RNPs) where RNA binding proteins ensure mRNA silencing and provide a link to molecular motors. ZBP1 is a component of RNP transport particles and is known for its role in the local translation of β-actin mRNA. Its binding to mRNA is regulated by tyrosine 396 phosphorylation, and this particular modification was shown to be vital for axonal growth and dendritic branching. Recently, additional phosphorylation of ZBP1 at serine 181 (Ser181) was described in non-neuronal cells. In the present study, we found that ZBP1 is also phosphorylated at Ser181 in neurons in a mammalian/mechanistic target of rapamycin complex 2-, Src kinase-, and mRNA binding-dependent manner. Furthermore, Ser181 ZBP1 phosphorylation was essential for the proper dendritic branching of hippocampal neurons that were cultured  Local translation requires the transportation of translationally dormant mRNA to the destination point, often over relatively long distances, where mRNA becomes derepressed and translationally competent. mRNAs that are to be locally synthesized contain tagging sequences that are recognized and bound by protein complexes that provide both translational silencing and attachment to molecular motors . These so-called ribonucleoprotein particles (RNPs) can be transported along microtubules and microfilaments, or they may stall at destination points while awaiting a signal to release bound mRNA for translation4. In neurons, changes in RNP dynamics and the translational unsilencing of mRNA can occur very rapidly, often in response to extracellular stimuli  and are controlled by the phosphorylation of RNP proteins7.Local protein synthesis is a phenomenon of regulated translation that occurs in subdomains of a cell, often distant from the major sites of protein production . It provides a means of local and transient cell polarization and enables fast responses to local stimuli. Neurons have been the most intensely studied because of their importance for local protein synthesis. In these cells, local protein synthesis regulates axonal growth cone navigation, dendritic arbor and spine formation, and synaptic plasticity12. The ability of ZBP1 to silence β-actin mRNA is dynamically regulated by phosphorylation. In response to trophic factors, ZBP1 is phosphorylated at tyrosine 396 (Tyr396) by Src and releases β-actin mRNA for translation13. In fact, proper axonal growth cone navigation and dendritic branching both require the ability of ZBP1 to be phosphorylated at Tyr3969. Recently, additional phosphorylation sites of ZBP1 and its orthologs were described. For example, in non-neuronal cells, serine 181 (Ser181) of IMP1 is cotranslationally phosphorylated by mammalian/mechanistic target of rapamycin complex 2 (mTORC2) and protected by RNA binding. In mouse embryonic fibroblasts and RD rhabdomyosarcoma cells, Ser181 ZBP1 phosphorylation is needed for proper splicing and the cap-independent translation of insulin growth factor 2 (IGF2) mRNA. However, to date, the presence of Ser181 ZBP1 phosphorylation and its regulation in neurons and significance for neuronal development have not been tested.Zipcode binding protein 1  is an mRNA binding protein that is found in RNPs. ZBP1 was described as β-actin mRNA-binding protein, which ensures its proper cellular distribution and translational silencing. In neurons, the local synthesis of β-actin, controlled by ZBP1 and its orthologs , contributes to axonal growth cone navigation, proper dendritic arborization, and dendritic spine formationS181A) provided evidence that Ser181 ZBP1 phosphorylation was critical for the proper dendritic branching of hippocampal neurons that were cultured in vitro. Finally, we found that Ser181 phosphorylation is needed for proper ZBP1 mobility and dendritic distribution. Taken together these findings uncover the role of Ser181 phosphorylation in ZBP1 trafficking and dendritic development.The present study showed that ZBP1 is stably phosphorylated at Ser181 in neurons. This phosphorylation was mTORC2- and mRNA binding-dependent. Moreover, we found less ZBP1 with phosphorylated Ser181 in cells with increased Src activity. Furthermore, rescue experiments with ZBP1 short-hairpin RNA (shRNA) and a ZBP1 mutant that mimicked non-phosphorylated ZBP1 -tagged wildtype rat ZBP1 (~96 kDa) but not ZBP1 with Ser181 mutated to alanine (S181A) that was overexpressed in Neuro2a cells  wildtype mice  or pSuper that encoded previously validated shRNA against Raptor or Rictor  electroporated neurons indeed revealed a decrease in P-ZBP1(S181)/ZBP1 ratio in cells with Rictor knockdown compared with Raptor knockdown and control cells  was poorly phosphorylated at Ser181 when it was overexpressed in Neuro2a cells compared with wildtype ZBP1 , should less efficiently release bound mRNA and be more phosphorylated at Ser181. Indeed, as opposed to ZBP1GXXG, ZBP1Y396F was slightly, although significantly, more phosphorylated at Ser181 compared with wildtype protein when it was overexpressed in Neuro2a cells  and a plasmid that encoded an RNA interference-resistant wildtype, S181A or S181E EGFP-ZBP1 mRNA . As an additional control, we used cells that were transfected with pSuper-ZBP1sh and EGFP. After 3 days, the total number of dendritic tips (TNDT) was analyzed. As previously reported, an shRNA against ZBP1 resulted in a significant decrease in the TNDT, and co-transfection of EGFP-ZBP1* fully rescued this defect , confirming that ZBP1S181A was more equally distributed and not enriched at dendritic branch points.In our previous work, we found that ZBP1 is differentially distributed in dendrites of neurons that are actively growing their dendritic arbors compared with mature dendrites. This suggested that proper dendritogenesis requires accurate ZBP1 distribution, namely the concentration of ZBP1 at dendrite branching points, which may correspond to hot spot of local synthesis of β-actin and other proteins needed for dendritic growth and branching. Accordingly, we tested whether Ser181 ZBP1 phosphorylation contributes to the spatial dendritic distribution of this protein. For more accurate quantitative analysis, we designed plasmids that simultaneously expressed EGFP-ZBP1 (or S181A and S181E mutants) and fluorescent protein - tdTomato  or oscillatory (<2.5 µm). The total number of movements per neuron was normalized per 10 µm of the dendrite and then to the mean number of anterograde movements in the wildtype variant in each experiment, respectively, to account for the variability of transfection. As shown in Fig. S181A granules exhibited significantly more directed movements in the anterograde direction compared with the wildtype variant. At the same time, the velocity of retrograde directed movements was significantly elevated. In the case of the oscillatory movements, ZBP1S181A granules were more motile in both directions, anterograde and retrograde. Consistent with this observation, we found more molecular motor KIF5A-GFP precipitated with ZBP1S181A than with wildtype ZBP1 when both proteins were overexpressed in Neuro2a cells , Ser181 phosphorylation is protected by mRNA binding. Although not directly, our data support the existence of such a mechanism also in neurons. For example, we showed that ZBP1GXXG, which cannot bind mRNA, is poorly phosphorylated at S181. We also found that the overexpression of active Src decreased Ser181 ZBP1 phosphorylation. Tyr396 ZBP1 phosphorylation by Src results in the release of ZBP1-bound mRNA, and our data are consistent with the model that was proposed by Dai et al.14. Src-driven ZBP1 phosphorylation is locally and dynamically regulated in neurons by extracellular stimuli that control neuronal development 6. Thus, the present findings suggest that phosphorylation at Ser181 may undergo local dynamic regulation during different steps of neuronal development . However, as discussed below, our study does not address directly physiological consequences of such local and dynamic dephosphorylation of ZBP1.The first important finding of the present study was that in neurons, similar to non-neuronal cells, ZBP1 is phosphorylated at Ser181 in an mTORC2-dependent manner. Under basal conditions, this phosphorylation was stable. In fact, in neurons, the stability of Ser181 phosphorylation appears to be greater than in RD rhabdomyosarcoma cellsS181E did not present different abilities to rescue the effects of endogenous ZBP1 knockdown. This observation is consistent with the hypothesis that the majority of cellular ZBP1 is phosphorylated at Ser18114. However, it raises a legitimate question, namely the way in which insufficient Ser181 ZBP1 phosphorylation disturbs dendritogenesis. Our previous study suggested that ZBP1 contributes to dendritic growth to ensure the accuracy of local β-actin translation9. While our results from Neuro2a cells confirm that the S181A mutant binds less β-actin mRNA, this difference did not show complete loss of function. Additionally, our preliminary results did not reveal differences in β-actin mRNA colocalization with wildtype ZBP1 and its Ser181 mutant that were overexpressed in hippocampal neurons . Thus, one possibility is that in neurons that lack Ser181-phosphorylated ZBP1, only the IRES-driven translation of a subset of proteins that are needed for dendritogenesis is decreased. The regulation of IGF2 translation in neurons and the impact of IGF2 on dendritic arborization remain unknown. Several mRNAs that are transported and locally translated in dendrites can utilize IRES-dependent translation20. Among these are tropomyosin receptor kinase B (TrkB), fragile X mental retardation protein (FMRP1), microtubule associate protein 2 (MAP2), and Ca2+/calmodulin-dependent protein kinase II (CamKIIα), which are known regulators of dendritic arborization21. However, whether their IRES-dependent translation contributes to this process and can be controlled by ZBP1 remain unknown. Finally, we previously found that during intensive dendritogenesis, unlike in more mature neurons, ZBP1 is not equally distributed and is concentrated at dendritic branching points9, suggesting a functional link between this specific distribution pattern and dendritic growth. In the present study, ZBP1S181A failed to concentrate at dendritic branching points and was more evenly distributed along dendrites, thus resembling the distribution of ZBP1 in neurons that passed the dendritogenesis stage. We hypothesize that Ser181 phosphorylation ensures the accurate spatial distribution of ZBP1 that is needed for efficient dendritic growth and branching. Ser181 phosphorylation may promote enrichment of ZBP1 at dendritic branch points and augment the locally translated pool of β-actin mRNA. Previous work has shown that axonal synthesis of β-actin supports axon branching of sensory neurons in vitro and in vivo22. It has also been demonstrated that axonal branch points are hotspots of local protein synthesis, and they are enriched in ZBP1 and stalled mitochondria, the latter one being critical for local protein synthesis23. Curiously, in addition to ZBP1, dendritic branch points are also enriched in mitochondria24 as well as translational machinery25, suggesting some parallels between dendrite and axon branch points. Therefore, while the role of potential protein synthesis in dendritic branch points remains unclear and ZBP1 S181 phosphorylation in axonal branching has not been investigated, the results of our study suggest a potential mechanisms and provide motivation for future work on shared mechanisms between the dendrite and axon.Another important finding in the present study was that Ser181 ZBP1 phosphorylation is required for proper dendritic arborization. In contrast, Ser181 dephosphorylation does not appear to be as critical for this process, since ZBP1WT and ZBP1S181A moved more than its wildtype counterpart. The greatest difference was observed in the number of movements, whereas the average velocity of the movements of the non-phosphorylated mutant was significantly greater but not as striking. This essentially means that ZBP1S181A-containing granules do not stop as often, suggesting that the increase in motility in the S181A variant was attributable to a disturbance in the mechanism that is responsible for granule docking 28 and/or interactions with other scaffolds 28, leading to lower capability of ZBP1 to enter stationary state at the correct destination. Regardless of the exact molecular mechanism enforcing more uniform ZBP1S181A distribution in dendrites, loss of proper ZBP1 localization likely impairs the discrete pattern of local protein synthesis, required for proper dendritogenesis.How does Ser181 phosphorylation regulate proper dendritic ZBP1 distribution? In this work, we found that ZBP1The present work focused on the role of ZBP1 S181 phosphorylation by examining the consequences of its absence. Our results indicate that phosphorylation of ZBP1 at S181 is needed for its full capacity to bind β-actin mRNA and accurate mobility of ZBP1-containing granules 5, pcDNA-SrcKD(Y416F)5, pEGFPC2-BIO32, HA-BirA32, and tdTomato33. pEGFP-ZBP1-P2A-tdTomato was constructed based on pEGFP-ZBP1, in which the GFP stop codon was exchanged with sequences that encoded the P2A signal followed by tdTomato. The change of ZBP1 (or ZBP1*1) Ser181 to alanine (A) or glutamic acid (E) was performed using the Quick Change Site Mutagenesis System . To change Ser181 to A, the following primers were used: 5′-CCCAGGCAGGGGGCACCGGTAGCAG-3′ (forward) and 5′-CTGCTACCGGTGCCCCCTGCCTGGG-3′ (reverse). The following primers were used for S181E substitution: 5′-CCCAGGCAGGGGGAACCGGTAGCAG-3′ (forward) and 5′-CTGCTACCGGTTCCCCCTGCCTGGG-3′ (reverse). Substitution of Y396 to F was performed as described previously9. Bio-Thrombin-HA plasmid was generated by changing the GFP coding sequence of pEGFPC2-BIO to a sequence that encoded the thrombin recognition site followed by an HA tag and was a kind gift from Dr. Swiech. Next, Bio-Thrombin-HA-ZBP1 and its mutated derivatives were constructed by the polymerase chain reaction (PCR) subcloning of the ZBP1 (or its mutants) coding sequence to EcoRI/SalI sites of Bio-Thrombin-HA. pGW1-SrcWT-HA, pGW1-SrcCA-HA, and pGW1-SrcKD-HA were obtained by subcloning cDNA-encoding Src and its mutants that were obtained by PCR (5′-GCAGATCTATGGGGAGCAGCAAGAGCAAGC-3′ and 5′-GGGAATTCCTATAGGTTCTCTCCAGGCTGG-3′) in BglII/EcoRI sites of the GW1-HA plasmid. β-actin-KIF5A-GFP plasmid was a kind gift from Drs. Lipka and Hoogenraad.The following plasmids were described previously: pGW1-HA6. Cross-affinity purified rabbit polyclonal anti-ZBP1(S181) was produced by Eurogentec  against PRQGS*PVAAGA peptide. Both were used at a 1:100 dilution for Western blot. Horseradish peroxidase-conjugated secondary antibodies and IRDye® 680RD anti-mouse and IRDye® 800CW were obtained from Jackson ImmunoResearch  and LI-COR Biosciences , respectively. INK128 was purchased from Selleckchem . Cycloheximide and alkaline phosphatase (FastAP), were obtained from Sigma-Aldrich  and Thermo Scientific , respectively.The commercially available primary antibodies that were used in the present study are listed in Table 9 in accordance with the institutional guidelines of the First Local Ethics Committee in Warsaw , which are in compliance with the European Community Council Directive (86/609/EEC). Cells were transfected on the indicated DIV using Lipofectamine2000 or nucleofected on DIV0 as described previously9. Primary cultures of hippocampal neurons of IMP1−/− mice were prepared from E17 embryos obtained by crossing IMP1+/− mice as described34 and in accordance with the institutional guidelines of Emory University (protocol approved by Emory University IACUC committee [GJB]). DIV7 cells were transfected using Lipofectamine2000.Primary cultures of rat hippocampal and cortical neurons were prepared as described previously2 atmosphere. The cells were transfected using JetPEI  at a 3:1 PEI:DNA ratio according to the manufacturer’s instructions. Eighteen hours after transfection, the cells were treated with cycloheximide (10 μg/ml) for 0.5, 1, 3, 6 or 24 hours. The control cells were treated with vehicle (98% ethanol).Neuro2a cells  were grown in Dulbecco’s Modified Eagle Medium that contained 10% fetal bovine serum and 1% penicillin-streptomycin  at 37 °C in a 5% COIn vitro phosphatase assay is described in Supplementary Materials and Methods.32. Eighteen hours after transfection, the cells were placed in ice-cold PBS, centrifuged at 8,000 × g for 3 min, and lysed for 10 min in lysis buffer  supplemented with protease and phosphatase inhibitors. The cell lysate was clarified by centrifugation at 18,000 × g at 4 °C for 20 min and incubated for 1.5 h at 4 °C with streptavidin-coated magnetic beads . After incubation, the beads were washed five times with lysis buffer, and bound proteins were recovered by boiling the samples with 1× Laemmli buffer.Biotinylated forms of proteins were produced in the Neuro2a cell line. These cells were transfected with a plasmid that encoded ZBP1 or its mutants with an avi-tag and BirA plasmid that encoded the biotin ligaseS181-Bio-HA. Forty-eight hours after transfection, the cells were collected in ice-cold TBS-K , centrifuged at 4,000 × g for 10 min, and lysed for 20 min in lysis buffer  supplemented with 2 mM ATP. The cell lysate was cleared by centrifugation at 13,000 × g at 4 °C for 20 min and incubated overnight with magnetic beads covered with anti-HA antibody . After incubation, the beads were washed four times with lysis buffer without ATP, and boiled in 1 × Laemmli buffer.For immunprecipitation Neuro2a cells were transfected with plasmids encoding Kif5a-GFP and Bio-HA (negative control), ZBP1-Bio-HA, or ZBP1et al., 2013)35. Briefly, Neuro2A cells were transfected with EGFP-ZBP1 or EGFP-ZBP1S181A plasmid. Next day, cells were collected, washed with PBS and suspended in 1 ml of a buffer containing 140 mM KCl, 1.5 mM MgCl2, 20 mM Tris-HCl (pH 7.4), 0.5% Nonidet P-40, 0.5 mM dithiothreitol, 100 U/ml RiboLock (Thermo Scientific) and protease inhibitors. Extracts  were precleared with 60 µl of Dynabeads Protein G (Invitrogen) for 2.5 h. Afterward, 1/10 of each supernatant was saved as input fraction for WB and RNA isolation. Protein-RNA complexes were precipitated overnight in 4 °C with 60 µl of Dynabeads Protein G, conjugated with either mouse anti-GFP antibody (Sigma-Aldrich) or normal mouse IgG (Sigma-Aldrich). Next, 1/6 of the beads was collected and boiled with 1× Laemmli buffer for WB. The remaining beads were suspended in 500 µl TRIzol (Thermo Scientific) for 5 min. Then, TRIzol was collected and RNA was isolated. For the quantitative real-time (qRT)-PCR, RNA was suspended in 11 µl of H2O, then its concentration was determined with NanoDrop (Thermo Scientific). Reverse-transcription was performed with High Capacity cDNA Reverse Transcription Kit , according to manufacturer’s instruction.Immunoprecipitation was performed as before, with modifications . Fold enrichment in the IP fraction was calculated for both mRNAs according to the standard curve method, using Input ZBP1 WT cDNA as a standard. Results were corrected for the non-specific background in the IgG fraction and ratios of β-actin and USP16 mRNA were calculated. To account for the difference in the transfection levels ratios were normalized to the ZBP1 WT IP fraction.36.Qualitative and quantitative Western blot analyses were performed as described previously9. Dendritic distribution of overexpressed EGFP-ZBP1 and its mutants was analyzed as previously9 with additional normalization step. Briefly, images of cells were obtained using a Zeiss LSM710 NLO laser confocal microscope with a 100 × 1.3 objective. Images were acquired in z-series (0.5 µm steps), with identical acquisition settings for all neurons. For analysis, z-series were rendered using maximum intensity projections, exported into TIFF format, and analyzed using MetaMorph software. Profiles of EGFP-ZBP1 and TdTomato fluorescence along the dendrites were made using the Linescan function, with the scan width set to 6 pixels. For each pixel EGFP fluorescence was standardized to fluorescence of TdTomato. Next, branching sites were indicated manually, based on the TdTomato imaging of dendrites and the mean standardized intensities of EGFP fluorescence at (R segments) and between (D segments) the branching sites were calculated using OpenOffice Calc software. D and R segments were not of the same length or area.The acquisition of confocal images of fixed neurons and morphometric analysis were performed as described previously9. Neurons were transfected on DIV7-8 with pEGFP-ZBP1 or pEGFP-ZBP1S181A. Time-lapse images  of neurons that expressed EGFP-ZBP1 or EGFP-ZBP1S181A were collected 10-14 h after transfection. Image analysis was performed using ImageJ software. All stack images were first corrected for X-Y drift. Afterward, to remove immobile background foci, the averaged image was subtracted from the image stack. The region of interest (ROI) for all dendrites in focus that were longer than 15 µm were converted to kymographs . All single movements were counted and divided into anterograde or retrograde based on their x-y slope, then classified as either directed (>2.5 µm) or oscillatory (<2.5 µm).For live imaging, rat primary hippocampal neurons were cultured on glass-bottom multi-well plate dishes , pre-cleaned with 1 M HCl according to the manufacturer’s specifications, and then coated with laminin and poly-L-lysinen) and culture batches (N) that were examined and the statistical tests that were used for the respective experiments are indicated in the figure legends. The statistical analyses were performed using Prism software .The exact numbers of cells (Supplementary InformationSupplementary Table S1