Myocardial infarction (MI) is caused by the occlusion of a coronary artery due to underlying atherosclerosis complicated by localized thrombosis. The blockage of blood flow leads to cardiomyocyte (CM) death in the infarcted area. Adult mammalian cardiomyocytes have little capacity to proliferate in response to injury; however, some pathways active during embryogenesis and silent during adult life are recruited in response to tissue injury. One such example is hedgehog (Hh) signaling. Hh is involved in the embryonic development of the heart and coronary vascular system. Pathological conditions including ischemia activate Hh signaling in adult tissues. This review highlights the involvement of Hh signaling in ischemic tissue regeneration with a particular emphasis on heart regeneration and discusses its potential role as a therapeutic agent. Myocardial infarction (MI) is caused by the occlusion of a coronary artery due to atherothrombosis. Blood flow to the heart muscle is blocked resulting in cardiomyocyte (CM) death in the infarcted area. As a consequence, progressive and negative left ventricular remodeling (LV) and scar tissue formation take place . After MIt has become evident that some pathways active during embryogenesis and silent during adult life are recruited in response to tissue injury and regeneration. Among them is hedgehog (Hh) signaling. The process of regeneration includes such events as cellular proliferation, differentiation and dedifferentiation. Hh signaling controls both cell proliferation and differentiation and it is involved in cell cycle regulation. Hh is implicated in the regulation of embryonic heart and coronary vascular system development –7. Hh siSonic hedgehog (Shh), Indian hedgehog (Ihh), and Desert hedgehog (Dhh) are secreted signaling proteins, which act as morphogens during embryonic development. The Hh signaling pathway is initiated by the binding of Hh proteins to Patched1 (Ptc1) or Patched2 (Ptc2) receptors. In the absence of Hh proteins, the 12-transmembrane receptor Ptc1 inhibits activity of smoothened (Smo), a 7-transmembrane protein that regulates activation of the Glioma-associated oncogene homologue (Gli) family of transcription factors; Gli1, Gli2, and Gli3 . In the FUCCI technology demonstrated the role of Hh signaling also in cardiac proliferation. The treatment of embryos with either Hh signaling Smoothened agonist (SAG) or antagonist cyclopamine (CyA) increased or reduced the number of proliferating cardiomyocyte, respectively [As indicated above, the signaling pathways that regulate cardiac development are often reactivated during heart repair in response to injury. Several studies on zebrafish embryos implicated Hh signaling in cardiac development. Genetic or pharmacological inhibition or activation of Hh signaling in zebrafish embryos revealed that Hh signaling is involved in cardiomyocyte formation via specification of myocardial progenitors during gastrulation and early somitogenesis stages . Furtherectively . These rptch2 in cardiomyocytes in the area of regeneration was a marker of Hh signaling activation. In addition, similar to the zebrafish embryo, treatment of animals with CyA for 6 days after ventricle resection or diffuse genetic ablation of cardiomyocytes displayed a decrease of cardiomyocyte proliferation.Zebrafish models have also been used to study the cardiac recovery in response to injury due to the ability to effectively regenerate their heart. To check whether heart injury activated Hh signaling during regeneration, Choi et al.  generateA recent study on genetic depletion of the epicardium in adult zebrafish identified Hh signaling as a mediator of epicardial regeneration . The epiLikewise, adult newts have the ability to regenerate heart  as well Taken together, upregulation of Hh signaling as a response to heart injury is common for zebrafish and newt. It seems likely that Shh activated in epicardium is responsible for increased proliferation of cardiomyocytes via Ptc receptors.Similar to zebrafish and amphibians, fetal and neonatal mice show a robust capacity for cardiac regeneration after injury , 22. HowGli1 and Ptc1 genes and treatment with CyA abolished this response suggesting that these cells are Hh responsive [2O2 treated control group. Together, these results indicate Hh signaling is functional in neonatal murine cardiomyocytes and might participate in cardiac regeneration in response to heart injury.Nothing is known about the involvement of Hh signaling in regeneration of fetal or neonatal rodent hearts. However, intact Hh signaling has been demonstrated in neonatal ventricular myocytes isolated from 1 to 3 days rat pups (NRVM). Incubation of NRVMs with recombinant Shh resulted in upregulation of sponsive . Responssponsive , 25. PreHh signaling has also been implicated in adult heart homeostasis and in response to heart injury. In rodent adult heart expression of Hh signaling components, especially Ptc1, was detected in several resident cell populations: perivascular interstitial fibroblasts , myocardmer) or in cardiomyocytes and vascular smooth muscle cells  in mouse heart caused cardiomegaly, ventricular dilation, impaired systolic function and fibrotic replacement of myocardial tissue. Acute inhibition of myocardial Hh signaling led to heart failure and subsequent lethality due to coronary vascular disruption and tissue hypoxia suggesting that Hh signaling is critical for adult heart maintenance [The direct role of Hh signaling in homeostasis of adult heart is rather controversial. Inactivation of Hh signaling via Smo deletion in cardiomyocytes . Myocardial ischemia reactivated Hh signaling as Shh and Ptc1 expressions were upregulated in the adult mouse heart , 27, 30.+ cells are hematopoietic cells that have been previously used for stem cell therapy to preserve the functions of ischemic myocardium or to treat refractory angina [+ cells, genetically modified to express Shh (CD34Shh), were injected into the border zone of mice with acute MI, they induced a robust increase in border zone capillary density accompanied by reduced infarct size in comparison with unmodified CD34+ cells or cells transfected with the empty vector [Shh cells, injection of MSCs engineered to overexpress Shh (MSCShh) in infarcted rat hearts resulted in increased capillary development and density within the infarct border zone, accompanied by reduced infarct sizes. Thus, Shh improved functional preservation of cardiac tissue compared with control cells [+ cells) were observed in mice treated with MSCShh. Furthermore, genetic modification of MSCs with Shh improved their survival and angiogenic potential in the ischemic heart via upregulation of VEGF, Ang-1, iNOS, netrin-1, hepatocyte growth factor (HGF), stromal cell-derived factor 1a (SDF-1a) and insulin-like growth factor-1 (IGF-1).The results described above demonstrate that Hh signaling has a potential to preserve cardiac function and to influence cardiac recovery in the context of myocardial ischemia. To activate Hh pathway in ischemic heart, several cell-based therapeutic strategies have been applied. CD34y angina . When CDy vector . Mesenchy vector . SimilarRecent studies on rodent models of acute and chronic MI reported that the effectiveness of pro-angiogenic gene therapy could be improved by its combination with progenitor cell mobilization. Indeed, Roncalli et al.  demonstrReprogramming of somatic cells into cardiomyocytes is another strategy for regeneration of injured heart. Previous studies identified adult cardiac fibroblasts as the most abundant cell population in the heart and as a promising cell source for reprogramming. However, recently Pinto et al.  demonstr2SO), P19 cells aggregate and spontaneously differentiate into beating cardiomyocytes [2SO and led to upregulation of expression of Ptc1, Gli1, Gli2 and cardiac muscle transcription factors such as GATA binding protein 4 (Gata4), myocyte-specific enhancer factor C2 (MEF2C), and Nkx2.5 [The P19 cells, a pluripotent mouse embryonal carcinoma stem cell line, can differentiate in vitro into multiple cell types including cardiomyocytes. In the presence of dimethyl sulfoxide , and medulloblastoma. Increased expression of Hh signaling components is usually observed in tumors. Many small molecules with antagonistic effects on various components of Hh signaling have been identified. Currently, around 90 studies have been either initiated, running or completed with several compounds, which inhibit either Smo or Gli proteins. The use of Hh inhibitors as monotherapy in the clinical setting has been effective for BCC and medulloblastoma. The results of these trials indicate that Hh signaling is an attractive and promising candidate for anticancer therapy.In case of the ischemic heart, the activation of Hh signaling protects against ischemic injuries. Several therapeutic Hh agonists for ischemia treatment including SAG were also proposed. SAG is a derivative of chlorobenzo thiophene that binds to and activated Smo. It has been shown that up-regulation of the Hh pathway by SAG was efficacious. However, whether SAG can be a proper candidate has to be determined, since it crosses the gut, the placenta and the blood barrier –49 and cMany other questions still have to be answered before Hh based therapy can be applied clinically. What is the molecular mechanism by which exogenous Hh affect in ischemia-induced tissue injury? What component of Hh signaling will be most useful as a target in a clinical setting? Hh proteins are morphogens which have effect on many cell types and cell responses are dependent on the dose of Hh proteins and time of exposure. Can Hh activation increase the potential risk for cancer induction? It is important to determine such factors as right cell type, a right dose, and duration of treatment.Comparison of the Hh function in regeneration of ischemic heart in lower vertebrates and mammals reveals both similarities and differences. In general, Hh signaling reactivation is a common response to heart ischemia. However, in lower vertebrates, heart ischemia reactivates Hh signaling in epicardial cells and this activation seems essential for cardiomyocyte proliferation, while observations so far in mammals suggest that Hh signaling is crucial for neovascularization.Hh signaling has a rather complex effect on the ischemic heart. Its activation in vivo triggers responses in all cardiac cell populations including cardiomyoblasts, endothelial cells, smooth muscle cells and epicardial cells. During injury Hh signaling triggers expression of pro-angiogenic factors such as members of VEGF family , Ang-1, Ang-2, and SDF-1 in cardiac fibroblast. It also participates in repair by promoting cell survival, proliferation and differentiation. Thus, the alteration of Hh signaling activity in one cell population leads to changes in other cells. We, therefore, suggest the following model for Hh-based cardiac cell–cell interaction (Fig.


Pulmonary artery hypertension (PAH) is a rare lung disorder in which the arteries that carry blood from the heart to the lungs progressively narrow down, making it difficult for blood to flow through the vessels. In many cases, PAH leads to right ventricular failure. The recent estimate of 1-, 3-, and 5-year survival rates from the time of diagnosis were estimated to be 87.7%, 72.1% , and 60.3%, which are substantially lower than breast cancer or colon cancers [Arguably the most critical signaling pathway for the onset and progression of PAH is the Bone Morphogenetic Protein (BMP) signaling . MutatioCirculation, Hwangbo and colleagues reported that VEGFR3, a tyrosine-protein kinase that acts as a receptor for VEGF-C and VEGF-D, may function as a potential modifier for BMP signaling in PAH setting by modulating the endocytosis of BMPR2 [floxed/ floxed; Cadherin5-CreERT2) in mice led to exacerbated pulmonary hypertension after exposure to chronic hypoxia and impaired BMP signaling responses compared to their phenotypic wild-type littermates, further corroborating the critical role of VEGFR3 in BMP signaling. Consistent with these data, they found pulmonary arterial endothelial cells (PAECs) isolated from PAH patients were insensitive to BMP stimulation also displayed significantly decreased level of VEGFR3 expression. Interestingly, these cells became responsive to BMP stimulation upon forced expression of VEGFR3, raising the possibility that manipulation of VEGFR3 in PAECs may be used to restore BMP responsiveness in PAECs in PAH setting. Further investigation on the molecular basis of BMPR2-VEGFR3 interaction may shed light on intricate interplay among diverse signaling nodes during the pathogenesis of PAH.Similar to other signaling pathways mediated by surface receptors, the amplitude and duration of BMP signaling is regulated by the endocytosis . Therefoof BMPR2 . VEGFR3


Animals that visit multiple foraging sites face a problem, analogous to the Travelling Salesman Problem, of finding an efficient route. We explored bumblebees’ route development on an array of five artificial flowers in which minimising travel distances between individual feeders conflicted with minimising overall distance. No previous study of bee spatial navigation has been able to follow animals’ movement during learning; we tracked bumblebee foragers continuously, using harmonic radar, and examined the process of route formation in detail for a small number of selected individuals. On our array, bees did not settle on visit sequences that gave the shortest overall path, but prioritised movements to nearby feeders. Nonetheless, flight distance and duration reduced with experience. This increased efficiency was attributable mainly to experienced bees reducing exploration beyond the feeder array and flights becoming straighter with experience, rather than improvements in the sequence of feeder visits. Flight paths of all legs of a flight stabilised at similar rates, whereas the first few feeder visits became fixed early while bees continued to experiment with the order of later visits. Stabilising early sections of a route and prioritising travel between nearby destinations may reduce the search space, allowing rapid adoption of efficient routes. Traplining ensures animals do not need to search afresh on each trip10 and reduces the variance in the frequency of returns to each patch12. Traplines might also be advantageous by increasing the probability of finding resources like slowly accumulating nectar before competitors, preventing build-ups of resources that might attract more competitors; and ensuring optimal rates of visitation to each patch14.Central place foragers, like bees, that visit multiple feeding destinations on a single foraging trip, often show evidence of ‘trapline’ routes, returning to the same locations in a repeatable order, like hunters checking a series of traps19. Examining route formation at the level of visit sequences means prior studies have been unable to examine in detail the flight paths by which animals move around the feeder array. Lihoreau et al.20 recorded the flight paths of experienced bees but could not study how bees first found the feeders, how or whether they explored in search of alternative food sources, how their movements changed as they refined their visit sequence or whether movements between flowers improved and stabilised in similar ways to the sequence of visits to the flowers themselves. In this study, we used harmonic radar to record the flight of bumblebee workers continuously, for up to two days, as they foraged on an artificial feeder array. We were thus able to examine in detail their movements between feeders in parallel with analysis of the visit sequences, throughout the entire period of route learning. We developed new methods to compare flight paths, by estimating the probability that the bee passed over the same parts of the landscape in different flights, using methods derived from Brownian Bridge Movement Models21, allowing us to use this unprecedentedly detailed spatial data to understand how bees’ movements develop and stabilise with experience.The development of trapline routes in bees has been examined by recording the sequence of visits to flowers to infer the rules underlying route formationCurrent technology only allows us to track one individual at a time and technical challenges mean that continuous tracking is more difficult than tracking individuals for a single flight each, necessitating a trade-off between the number of individuals tracked and the number of flights recorded from each. We have chosen to record the full histories of 6 bees rather than fragments of behaviour from a larger number of individuals. Although unconventional, this technique gives unprecedented insight into the route formation process for these bees, although caution must be exercised in extrapolating from these bees to the larger population.22, for which there is no solution short of testing every possible route. Bees seldom develop completely stereotyped routes, but show significantly non-random patterns of visitation and often follow preferred sequences of feeder visits23. In developing efficient routes, bees might minimise either the distance travelled between pairs of locations12 or total distance travelled on each journey20; these are often correlated, and can be difficult to disentangle. Additionally, there is evidence for a trade-off between finding the shortest route and prioritising visits to more rewarding food sources15, and between accuracy of route following and travel speed19. Ohashi et al.12 found bees preferred to minimise feeder-to-feeder distances over forming a straight path in an indoor array with feeders spaced ~1 m apart, preventing them from taking the optimal path which would minimise the overall travel distance. It has been suggested that bees may be more motivated to optimise routes at large spatial scales20. Lihoreau et al. developed a traplining heuristic model using a process of iterative improvement based on the overall length of each route tried24, which reproduced a number of results seen in the behaviour of real bees24, but predicted there are certain spatial configurations for which bees cannot form stable traplines that minimise travel distance, including the conflicting array used by Ohashi et al.12.The problem faced by traplining bees is analogous to the Travelling Salesman Problem (TSP), an extensively studied mathematical problemet al.20 found that bees developed a repeatable trapline on a pentagonal feeder array, following the route which required the shortest possible flight path; however this was also the route that would result from use of a nearest-neighbour heuristic, where an agent always travels to the closest as-yet-unvisited location . We attempted to deduce whether bees landed on the feeders during these visits or merely overflew them, by looking for occasions when the bee moved less than 2.5 m between consecutive radar datapoints. The mean proportion of first visits to a full feeder within each bout in which the bee met this criterion of stillness was 0.92 ± 0.17. That of revisits was only 0.58 ± 0.35, but this is likely to be an underestimate since this method only detects stops longer than 4.5 s on average (due to the rotation of the radar) and we have previously observed bees landing, sampling an empty feeder and taking to the air again in only 1–2 s.legs, sections of flight between one feeder (or nest) and another. We characterised any leg in which the bees flew mores than 50 m from all previously discovered feeders as exploration legs. These were observed to originate at all locations but most commonly started from the nest  stayed largely constant . Reduction in time spent on exploration legs explains around half the observed reduction in total flight duration (0.53 ± 0.22).20) after 17–34 bouts  identical consecutive bouts. This means that the true routes taken by the bees never became fully stereotyped.All except bees 4 and 6 met the established definition of route stabilisation , and increased significantly with time and experience Table , althougGiven that improvement in visitation sequence was not an important contributor to increasing route efficiency, what rules were involved in determining sequence choice? One easily computed rule is the nearest-neighbour heuristic in which a bee should always travel to the nearest unvisited feeder Fig. . Two beeA similarity score which compared each bout’s visitation sequence to that of the previous bout showed no significant change over day 1 Table . We alsoAn increase in similarity across an entire bout could reflect either an increasing tendency to fly between locations along a similar path or an increasing number of transitions between the same start and end points, meaning that the bee would be more likely to be in the same general areas of the landscape. To control for this we calculated the similarity of each individual leg within a bout to the most recent occasion on which that bee had flown from the same start point to the same end point. The mean self-similarity of all the legs in each bout also increased with experience Table , demonst24 suggested that foraging routes do not change or improve all at once, but as a consequence of altering the probabilities of individual feeder-to-feeder transitions (legs). Figure The traplining heuristic model25 and suggests that these parts of a visitation sequence were generated in a purely stochastic way. However, the most commonly occurring segments, toward the left of each plot, deviate greatly from an exponential distribution. This indicates that approximately the 20 most common sections of flight were not randomly chosen and presumably resulted from the bees’ memory and decision making, while a random element in the choice of rarer segments allowed them to experiment with new sequences.To examine the plasticity of segments of foraging routes, we broke down each bout into segments of two, three or four consecutive feeder visits. Supplementary Fig. Figure Three bees were recorded foraging over two full days. Bees 2 and 3 were confined to the nest overnight between days. Bee 1 was confined to the nest for four days and five nights between the first and second day of tracking (bee 2 was tracked during the intervening period). To investigate whether this break between bouts affected foraging routes we tested for a difference between the final five bouts of the first day and the initial five bouts of the second day’s foraging in all variables that had showed a significant effect of experience over the first day, plus the distance flown during exploration legs Table , mean st20. We used harmonic radar to track the flight paths of bees continuously for the entire duration of testing and examined the development of flights, as well as visit sequences, for the first time. We tested whether bumblebee foragers were able to find the shortest route on a large-scale feeder array, designed so that consistently minimising the travel distance between individual pairs of feeders would lead to suboptimal overall route lengths12. None of our bees regularly managed to choose a route that minimised overall travel distance, instead showing behaviour consistent with a preference for shorter inter-feeder travel distances. Analysis of the actual flight paths taken by our subject bees suggested that the flight paths between feeders became both straighter and more repeatable with experience and that this process was independent of changes to the feeder visit sequence. Travel distance and duration reduced with experience and these efficiency gains had two main causes: a reduction in the distance and time spent flying outside the area of the feeder array, and an increasing tendency to take straighter routes between feeders. Changes in visit sequence did not lead to a significant reduction in travel distance, although it is likely that in other spatial arrangements of feeders, similar sequence refinement would reduce distances.Previous studies into multi-destination route formation have focussed on sequences of feeder visits but researchers have not been able to track the ontogeny of actual flight paths (routes taken between feeding stations) of their subjects26 we tracked free-foraging bumblebees throughout their lives and identified a class of long, circuitous exploration flights which largely occurred during the first few flights ever made by bumblebee workers. The exploration legs we identified in this study bear some resemblance to those of new foragers, being long, highly circuitous and apparently using the nest as a central point from which to explore. It is not clear what caused bees to make exploration legs in this study. The subject bees had previous experience of the field site, accrued during the training stage of the experiment, so exploration legs were unlikely to serve a similar purpose to orientation flights. They typically occurred after bees had visited several feeders but were less common after all five rewards had been consumed, so it is possible that bees were triggered to search for other food sources if they had visited all the feeders whose location they remembered, but were left unsated. Under this hypothesis, decreasing distance and duration of exploration legs would reflect increasing certainty about the position of all five feeders. Alternatively, Woodgate et al.26 suggest that bees may simply explore the landscape during the early stages of their foraging career, subsequently switching to efficient exploitation of the best foraging sources discovered. Thus, changes in exploration in this experiment might reflect a typical switch from exploration to exploitation behaviour. Finally, bees may explore in search of reserve food sources in case of changing resource distributions27. Foraging bumblebees switch flexibly between flower species29, so may explore for other flowers even when trained to a single feeder. We conducted the experiment in the autumn to limit the availability of natural flowers so reduced exploration might reflect the bees’ increasing certainty that there were no alternative food sources to be discovered.Inexperienced bees made frequent looping flights beyond the feeder array, but reduced the incidence of these exploration flights as they gained experience, reducing the distance and duration of foraging bouts . In a previous study26, so there may not be any time for further stabilisation to occur under natural conditions.We developed new techniques to compare flights in terms of their use of space and showed that flight paths became more similar to one another as bees gained experience. Much of this increasing similarity can be attributed to the pattern of increasing flight straightness over the same timescale but there is also evidence of repeatable, idiosyncratic flight paths  but without further experimentation it is not possible to be certain at what distance they can detect them. It is possible that stochasticity in when a bee catches sight of familiar but hard-to-see targets like our feeders, and consequent variation between visually-guided and memory-driven processes of navigation, may explain some of the variation we observed in route structure.24 - that routes develop by holding some feeder-to-feeder transitions constant while others continue to be swapped around - as demonstrated graphically in the supplementary videos (S1–S3) where certain segments of path were continually reinforced while other segments of the route gradually fade, since they were not repeated in subsequent bouts. Interestingly, the repeatable and rarer path segments were not distributed evenly throughout the visit sequence: destinations of the earliest legs in each bout became highly repeatable, while later parts of the visitation sequence continue to change. Potentially, memorising the beginning of a route while continuing to experiment with later visits might allow a bee to search for more efficient routes while exploiting the increased speed possible on familiar routes.The majority of sub-sequences of feeder visits closely fitted an exponential distribution . Our array had an identical number of feeders, total path length of the minimal-distance route and the same minimal-distance solution (travel around the outside of the array), to that used by20. While our relatively small sample size makes it impossible to conclude with certainty that bees can never choose the minimal distance solution on our array, it seems clear that such a solution is found more rarely than on the array used by Lihoreau et al.20. We suggest that the observed differences in route structure and repeatability are attributable to the different spatial relationships between feeders, specifically the fact that in our array the minimal distance sequence required bees to ignore the short nearest-neighbour transitions that were possible between feeders #1 and #5, and between #2 and #4.None of our bees continued to visit feeders in the order that they were discovered, supporting previous observationset al.20 was identical to the minimal overall distance route, so the two strategies could not be distinguished. In our study most bees did not use full nearest-neighbour routes, but it is possible to prioritise low travel distances without the entire feeder visit sequence being determined solely by nearest-neighbour transitions. Over half of all legs on our array were nearest-neighbour movements and the mean distance rank was 1.45, suggesting that our bees prioritised low between-feeder distances. This preference for closer feeders was remarkably consistent across all bees and mirrors the results of a similarly structured array on a smaller spatial scale12. The traplining heuristic model24 proposed that bees may use an iterative improvement process of route development whereby the probability of flying between any pair of locations is enhanced or decreased as a function of the length of past routes using the same transitions. If probabilities were also influenced by the length of individual legs (with a higher weighting given to short travel distances) this would lead to routes in which low between-feeder travel distances were prioritised but which were flexible enough to also include non-nearest-neighbour transitions. This hypothesis is consistent with the observation that the bees in Lihoreau et al.20 did not exclusively make nearest neighbour transitions, the fact bees were less likely to hit on the minimal-distance sequence in our array than20, and the fact that our bees’ routes were less stable than theirs .The nearest-neighbour route between feeders in the array used by Lihoreau et al.26).One striking pattern in the flights of those bees we tracked over two days was an increase in the distance flown during exploration flights and a corresponding drop in flight path straightness and repeatability, between days of tracking. This reflects an increase in exploration behaviour on the morning of the second day and, intriguingly, the changes were more noticeable in the flights of bee 1, which had a four-day gap between the first and second days of tracking. It is unclear whether this resurgence of exploration was caused by degradation in memory, preventing bees from resuming the previous day’s route or whether bumblebees have a general tendency to explore at the beginning of each day. Such a strategy might allow them to respond effectively to changes in the distribution of floral resources over the course of their foraging career . Radar tracking individual bees over multiple consecutive flights presents a significantly greater challenge than tracking individuals for one flight each so there was an unavoidable trade-off between the depth of data we could acquire on the development of individual bees’ routes and the total number of individuals we were able to track. We believe that the insights our data provide into the development of the individual bees we tracked justify that trade-off and could not have been obtained any other way.Care must be taken in extrapolating our results to the population as a whole since the tracks are derived from only 6 bees. Understanding how the habitual routes of central place foragers develop with experience requires long-term tracking of individuals throughout the entire duration of the experiment, which no previous study of spatial orientation and learning has accomplished. The complete dataset is among the largest harmonic radar datasets ever recorded . Attempts to train bees to visit our feeders in July and August 2014, April 2015, and May and June 2017 were unsuccessful as the bees showed a strong preference for natural forage sources. Consequently, data collection could only take place late in the season when there were few naturally occurring sources of food in the area. Bees were tracked in two locations: In location 1, the nest was situated at the East margin of a recently harvested wheat field (approx. 250 × 175 m), with the feeder array extending West into the field and the radar at the North-western corner, approximately 220 m from the nest. In location 2, the nest was placed at the edge of a field of mown grass (approx. 700 × 300 m), with the feeders extending roughly North-west into the field and the radar at the Northern edge of the field, approximately 300 m from the nest. In both cases there were linear landscape features such as paths, field edges and hedgerows, but the feeder arrays were placed in locally homogenous areas.Bombus terrestris audax from commercially sourced colonies . Colonies were kept in wooden nest boxes (30 × 21 × 16 cm high), which were kept in a wooden shed to provide shelter and further insulation. A Perspex tunnel (26 × 4 × 4 cm high) allowed access to the outside world through a hole in the shed wall (Ø = 50 mm). The colony was fed with pollen directly in the nestbox every day and with 40% sucrose solution (w/w) in a gravity feeder every few days to ensure that the colony never ran out of food in the honey pots.Our study subjects were During the experiment, focal bees fed from artificial feeders consisting of a blue painted wooden platform (20 × 20 cm) mounted on top of a 92 cm white plastic pole . After three days, the colony was transferred to the field and two feeders set up directly outside the nest entrance. These feeders were gradually moved away from the nest over the course of a day until they were 50 m from the colony entrance. The bee that visited the feeders most regularly was chosen as our focal bee. We used tunnel gates to confine all other bees to the nest and only allowed the focal bee to forage. We had no information on the ages of our focal bees. No bees had any flight experience prior to training and all experienced similar amounts of training but, since the experiment involved free-flying bees in an outdoor field site, we were unable to control for any differences in how they explored the landscape during training.To train bees at these artificial feeders, the colony was placed inside a flight room (390 × 285 × 230 cm high), with three feeders which were kept constantly topped up to allow We measured the functional crop volume of each focal bee by allowing it to forage at a row of five feeders placed next to each other, 50 m from the nest. In 2014 we attached transponders to the focal bees before measuring the crop volume; in 2015 and 2017 we measured the crop volume first and only attached transponders to bees whose crops had been measured successfully. We adjusted the volume of sucrose between visits by the bee until we found the maximum volume at which the bee would consume all five reward droplets before returning to the nest. During the experiment all feeders contained this volume of sugar solution (1/5 of the crop capacity per feeder) to ensure that the bee was motivated to visit all five feeders but would then be sufficiently full to return to the nest without foraging further. A further adjustment of the reward volume was necessary for one bee, which showed a tendency to continue to explore the field after consuming the contents of all feeders (see supplementary Table There was a high rate of attrition at every step of training. We estimate that no more than 5–10% of bees that fed at our feeders in the flight room continued to do so in the field during September and October (and considerably fewer earlier in the summer). Approximately 50 (±20%) of bees that foraged on the feeders immediately in front of the shed were still regular visitors once the feeders had been moved to 50 m. No more than 4–6 regular foragers were ever available at 50 m. Non-focal bees were confined to the nest during the time we measured the crop capacity of the focal bee. If the focal bee could not be tracked, it was rare for any previously regular foragers to still be motivated to visit the feeders so training typically had to begin again. Over the course of the study we attempted to measure crop volumes for 24 focal bees. Crop measurement could not be completed for 9 bees as they stopped foraging and remained in the nest; after crop measurement, but before they could be tracked on the experimental array, five more bees appeared to lose motivation and stopped foraging, while two died. We attempted to track the remaining 8 bees but two stopped visiting the feeder at the training point, presumably visiting wild flowers instead, so could not be tracked on the array and were abandoned after 4 and 7 unsuccessful flights, respectively. Six focal bees were successfully tracked as they foraged on the experimental array.We continuously monitored these bees and tracked every foraging bout they made. Bees 1 and 2 were tracked at location 1 over two full days of foraging . If true, no feeder should be visible from any other although it is likely that both feeders 1 and 5 would be visible to a bee that returned to the position the feeders had been in during training. The bees were confined to the nest for approximately 4–5 minutes between bouts while an experimenter refilled the feeders.Once the focal bee had completed at least five foraging bouts visiting the feeders in their start position, we moved the feeders into the experimental positions. The experimental array comprised five feeders and the nest, forming a hexagon in which the distances between feeders forming the edges of the hexagon were 50 m, but the distance across the body of the hexagon was only 25 m Fig. . The sho34. The radar returned distance and direction coordinates of the bees’ position every 3 s while the bees remained in line-of-sight within a radius of about 800 m (accuracy ≈ ± 2 m). Radar transponders weigh around 15 mg, consist of a 16 mm vertical dipole and were attached to the numbered tag on the thorax of the focal bees using superglue . Bumblebees can carry nectar loads of up to 90% of their body mass28, and the transponder represents only 8–10% of a typical worker’s mass of 175–200 mg.All movements of the focal bees outside the nest were tracked using 32 mm harmonic radarlocations. Bees were considered to have visited a location if they were detected within a 5 m radius. We also tried to deduce from the flight paths whether the bees had landed by identifying pairs of consecutive radar signals that were within 2.5 m of each other. The proportion of visits in which the bee was still for at least 2 consecutive rotations of the radar was 0.88 ± 0.16. Each path was broken down into a number of legs, each of which was defined as the segment of a track beginning when the bee left the vicinity of any location and ending when it next approached any location. Legs in which the bee remained within 50 m of at least one location were categorised as within-array and those in which it travelled more than 50 m from every location that that bee had previously discovered (i.e. it was further from any known location than the locations are from one another) were categorised as exploration.A number of variables were derived from the radar track data. The five feeders and the nest will be referred to as Path length was the cumulative length of a straight-line path between every positional fix over the entire foraging bout and could be further broken down into distance travelled on within-array or exploration legs. Straight-line path length was calculated as the straight-line distance joining all the feeders visited in each bout in the order they were visited; this is the shortest distance a bee could travel while maintaining the observed visit sequence. Bout duration was the total time elapsed between the bee’s departure from the nest and its return. The straightness of each leg of a track was defined as the distance component of the vector sum of the straight lines connecting every pair of positional fixes within that leg and can range from 0 (datapoints form a circle) to 1 (the path forms a straight line). The straightness of an entire bout was the mean of the straightness score for all legs; a score of 1 would indicate that the route was composed of perfect straight lines between locations, although there may be changes of direction from one leg to the next.21 to estimate the probability of the bees’ location between radar positional fixes. The landscape was broken down into 5 × 5 m pixels and the time interval between each pair of consecutive datapoints into 50 timeslices of equal duration. The probability density function of the bee being at location x, y at time t is given byThe radar data tells us the bees’ position every 3 s on average but not where they were between radar fixes. We used a method derived from Brownian bridge movement modelsT represents the time elapsed between two consecutive radar fixes while xn, yn and xn+1, yn+1 represent the coordinates of the two fixes (i.e. the bee’s position at t = 0 and t = T). Flight speed s was estimated for each bout from the radar data: datapoints that were less than 5 m apart were assumed to result from the bee being stationary rather than in flight and were excluded, then the total distance covered by the remaining datapoints was divided by the total duration. This procedure results in an estimate of the likelihood of the bee having passed through each pixel in the time between the two radar fixes, for which we know its position with certainty. The probability maps thus generated for each timeslice can be summed across all timeslices in a bout  to calculate the probability that the bee passed through any given pixel at any point during the foraging bout  that was repeated on at least three consecutive bouts. If more than one such sequence occurred, the trapline was the most commonly occurring sequence. We investigated whether visitation sequences have a tendency to stabilise with experience using a similarity index (SI), as described by Saleh and Chittka10, which quantifies the similarity between pairs of visitation sequences. SI scores range from 0 for completely different sequences to 1 for identical sequences. The sequence self-similarity score was the SI generated by comparing the full sequence for each bout (including revisits to empty feeders) with the previous bout, and the optimality score was calculated by comparing each bout sequence to the ‘optimal’ sequence, defined as the order of visits that allows a bee to visit all five feeders with the shortest possible total travel distance ). Bees 4 and 6 were excluded because they did not perform enough bouts to gauge their improvement with experience. Dependent variables were path length, straight-line path length, straight-line/observed path length, bout duration, optimality score, straightness, sequence self-similarity score, flight self-similarity score and the mean leg similarity score. Experience level  was the predictor and bee ID was included as a random factor. To investigate whether an overnight break affected behaviour, another set of ANOVAs were used to compare the performance of bees 1–3 over the last five bouts flown on the first day with the first five bouts flown on the second day of tracking. Dependent variables were the total length of exploration legs in each bout and all variables that showed a significant effect of experience over the first day . All tests were two-tailed and significance was determined at α = 0.05.To test whether the bees routes changed with experience, we tested for a difference in route characteristics between the first and last five bouts flown by bees 1–3 and 5 over the first day of tracking, using a series of ANOVAs (using the All harmonic radar tracks of bee flights recorded in this study are available in graphical form as Supplementary Figs Supplementary materialSupplementary video S1Supplementary video S2Supplementary video S3Supplementary video S4Supplementary video S5Supplementary video S6Supplementary Dataset 1


Xenopus laevis eggs and cultured human cells and show that variation is typically much lower, in the range of 5–15%, compatible with accurate single‐cell transmission. Focusing on bimodal ERK signaling, we show that variation and covariation in MEK and ERK expression improves controllability of the percentage of activated cells, demonstrating how variation and covariation in expression enables population‐level control of binary cell‐fate decisions. Together, our study argues for a control principle whereby low expression variation enables accurate control of analog single‐cell signaling, while increased variation, covariation, and numbers of pathway components are required to widen the stimulus range over which external inputs regulate binary cell activation to enable precise control of the fraction of activated cells in a population.Due to noise in the synthesis and degradation of proteins, the concentrations of individual vertebrate signaling proteins were estimated to vary with a coefficient of variation (CV) of approximately 25% between cells. Such high variation is beneficial for population‐level regulation of cell functions but abolishes accurate single‐cell signal transmission. Here, we measure cell‐to‐cell variability of relative protein abundance using quantitative proteomics of individual  To determine how accurately a multi‐step signaling pathway can transmit a relative input stimulus (R) to an analog output (A*), we modeled the signaling pathway shown in Fig One way to overcome this dramatic loss in signaling accuracy due to expression variation of pathway components is to increase the input stimulus. We reasoned that we could use a fold‐increase parameter to quantify the loss in signal accuracy. We thus defined a fold‐Input Detection Limit (fIDL) as the minimal fold‐stimulus needed to generate signaling responses that can, in 95% of cases, be distinguished from cell responses in unstimulated cells see . As showet al, We also wanted to determine whether the expression of vertebrate proteins may covary since covariance has been shown to exist in a yeast regulatory pathway , a low‐noise quantitative mass spectrometry method  that measures how well the population‐level output can be controlled by the input. The fitted Hill coefficients for systems with different amounts of protein expression variation are shown in the bar plot in Fig et al, et al, et al, et al, Since the MEK/ERK signaling pathway often controls binary single‐cell decisions such as whether cells divide or differentiate . We use fold‐Input Detection Limits (fIDLs), as defined in Fig We used our experimentally measured low CV values for relative protein abundances, together with our finding that covariation can further improve the controllability of binary signaling outputs, to explore the respective ranges of variation and covariation where single‐cell and population‐level signaling can be effectively controlled. As depicted in Fig As shown in Fig et al, et al, et al, et al, et al, As shown in Fig et al, Our modeling and experimental data in Figs Variation in mRNA and protein expression between individual cells is believed to be a main limitation for cells to accurately transduce receptor inputs to control analog functional outputs. In particular, studies in model organisms and cultured mammalian cells suggest that the main sources of noise are likely the small number of mRNA molecules, which is common for signaling proteins, and the frequently observed bursting behavior in gene expression which can further increase the variation in the number of mRNA molecules present in a cell at a given time. Together with the observed variation in the expression of fluorescently conjugated signaling proteins and the observed variation in antibody staining of signaling proteins, it has often been assumed that the CV of signaling proteins between cells in the same population must be quite high, with numbers of about 25% CV being frequently used.Xenopus eggs and a subset of proteins also in mammalian cells. Specifically, we measured variation by normalizing the expression of individual proteins by the total protein mass. Using this strategy, we found CV values for proteins between individual Xenopus eggs of 5–10% and between human cells in the 10–15% range, much lower than expected. We used in both cases total protein mass of a cell for normalization since cell volume is believed to scale closely with cell protein mass. Variation of the concentration is in most cases an optimal measure of variation, as the relevant parameter for the activity of a signaling protein is its cytosolic concentration, or the abundance of a particular signaling protein in a cell divided by the volume of the cell. The low CV values of 5–15% that we measured would make it possible for sensory, hormonal, or other analog signal transduction systems to accurately transduce information about the amplitude of an input to gradually control the output, as we demonstrated using a minimal model of a typical signaling pathway with five steps. As shown in Fig Our study investigated signaling protein variation by measuring variation of a small set of signaling proteins in A main interest of our study was to better understand the competing requirements of analog signaling systems, that need to accurately control a gradual output response of a single cell, from binary signaling systems that need to control the percentage of cells in a population that trigger a particular cell‐fate transition. In the analog single‐cell case, low noise is optimal, while in the latter binary population‐level case, high noise is optimal. In the binary case, the critical role of increased variation in the expression of signaling proteins is to broaden the response behavior in a population of cells so that the fraction of cells that trigger a cell‐fate switch can be controlled over a broader range of input signals. If there is no noise, all cells would trigger the cell‐fate change at precisely the same amplitude of an input stimulus. Given that input signals can also be noisy, one can argue that optimal binary systems should be able to control whether 10 or 50% of cells in a population are activated over a range of input stimuli of about 5, which would allow for approximately linear control of the fraction of activated cells by changes in the amplitude of typical receptor inputs. Our model calculations showed that such a system requires much higher variation in the expression of signaling proteins in the 40% range compared to the low variation required for optimal signaling for analog systems.Xenopus eggs and human cells, and we observed a significant covariation between MEK and ERK expression in both systems. Model calculations of the ERK pathway, together with measurements of ERK activity and ERK and MEK expression levels, showed that the increased variation due to covariation increases the range over which input EGF signals can control binary ERK activity output. Of note, the contribution from a single pair of covarying signaling proteins is relatively small, and strong effects resulting from covariation require multiple signaling proteins covarying with each other. Future studies with high quality antibodies for multiple pathway components will be needed to more generally test this covariation hypothesis in different signaling systems.These competing needs for high versus low variation for different types of signaling raised the question whether cells use alternative mechanisms to increase overall signaling noise in a system in order to still allow cells to keep the variation of individual signaling proteins relatively low if these same components are also needed in other situations for binary signaling. We show that having high numbers of signaling components involved in a binary decision is a powerful strategy to generate more noise as more components make a cumulative noise contribution that increases noise. We further showed in model calculations that covariation between signaling proteins in the same pathway reduces analog signal transmission accuracy but also found that covariation can both increase the overall noise/variation of the functional output. These considerations led us to measure protein covariation in Another goal of our study was to develop a general formalism to better understand how variation and covariation of signaling protein expression and also the number of pathway can be modulated to optimize different types of signal transmission in cells. These factors impede the accuracy of single cell signal transmission while improving the controllability of the population‐level regulation of binary cell activation. Our analysis in Fig In conclusion, our study employed sensitive single‐cell mass spectrometry and single‐cell immunofluorescence analysis to reveal a low variation in relative protein abundances with CV values in the 5–15% range, suggesting that expression variation is not prohibitively high for analog signal transmission in single cells as was often assumed in previous studies. However, such low levels of variation make it difficult for signaling pathways to control population‐level binary signaling outputs over broad ranges of input stimuli. We show that covariance of signaling components and increased numbers of pathway components can be effective mechanisms to increase overall signaling output noise and thereby allow for optimal control of binary cell‐fate switches at the population level even if the variation of individual signaling components is low.Xenopus egg extracts were prepared based on modifications of a previous protocol  buffer . To remove the jelly coat from the eggs, they were placed in a solution of 2% cysteine in 1× MMR buffer for 4 min and gently agitated, after which they were washed four times with 1× MMR buffer. To activate the cell cycle, eggs were placed in a solution of 0.5 μg/ml of calcium ionophore A23187 (Sigma) and 1× MMR buffer for 3 min, after which they were washed four times with 1× MMR buffer. Single eggs were collected at their respective timepoints and placed into 600 μl tubes and snap frozen in liquid nitrogen before being stored at −80°C.g in a right angle centrifuge (Beckman Microfuge E) at 4°C for 5 min. The lipid layer was removed by using a razor blade to cut the tube off just beneath it, and the cytoplasmic fraction was pipetted into a 1.5‐ml protein LoBind tube (Fisher Scientific #13‐698‐794), being careful to leave the yolk behind. To precipitate the proteins from the cytoplasmic fraction, 1 ml of ice cold acetone was added to each sample and placed at −20°C overnight.Single eggs were lysed mechanically by pipetting the egg in 100 μl of lysis buffer . The lysate was then placed in a 400 μl natural polyethylene microcentrifuge tube (E&K Scientific #485050) and spun at 15,000 g for 20 min at 4°C. Acetone was decanted, and the protein pellets were resolubilized in 25 μl of 8 M urea. To fully solubilize the protein pellet, the samples were placed in a shaker for 1 h at room temperature. The samples were then diluted to 2 M urea with 50 mM ammonium bicarbonate to a 100 μl volume, after which protein concentration was measured in duplicate with a BCA assay by taking two 10 μl aliquots of each sample. The proteins in the remaining 80 μl of sample volume were reduced with 10 mM TCEP and incubated for 30 min at 37°C, then alkylated with 15 mM iodoacetamide and incubated in the dark at room temperature. Next, the samples were diluted to 1 M urea with 50 mM ammonium bicarbonate, and heavy peptides (JPT SpikeTides) were added based on BCA assay results. Trypsin (Promega #V5113) was then added at a ratio of 10 ng trypsin per 1ug protein (no < 500 ng was added to a sample). The trypsin digestion was carried out at 37°C for 12–16 h.To collect precipitated proteins, the samples were centrifuged at 18,000 To stop the trypsin, formic acid (Fisher #A117‐50) was added at a ratio of 3 μl per 100 μl of sample to bring the pH down to < 3. Peptides were cleaned up using an Oasis HLB uElution plate (Waters), equilibrated, and washed with 0.04% trifluoroacetic acid in water, and eluted in 80% acetonitrile with 0.2% formic acid. All solutions used are HPLC grade. Samples were then lyophilized. To remove any variance produced by phosphorylated peptides, the samples were phosphatase‐treated. Peptides were resolubilized in 50 μl of 1× NEBuffer 3 (no BSA), and calf intestinal alkaline phosphatase (NEB #M0290S) was added at a ratio 0.25 units per μg of peptide and incubated for 1 h at 37°C. The peptides were cleaned up again according to steps described above. Peptides were resolubilized in 2% acetonitrile and 0.1% formic acid before SRM analysis.et al, et al, As detailed in previous publications  were cultured in a growth media consisting of DMEM/F12 (Invitrogen) supplemented with 5% horse serum, 20 ng/ml EGF, 10 μg/ml insulin, 0.5 ng/ml hydrocortisone, 100 ng/ml cholera toxin, 50 U/ml penicillin, and 50 μg/ml streptomycin. HeLa cells were cultured in DMEM (Invitrogen) plus 10% fetal bovine serum (FBS) and penicillin–streptomycin–glutamine (PSG).et al, pPBbsr2‐EKAR‐EV‐NLS was described previously . Cells were then washed three times in PBS before they were permeabilized by adding 0.2% triton X‐100 for 20 min at 4°C before being washed again with PBS. To remove cell size effects, cells were then stained with Alexa 647 NHS Ester as a marker of total protein mass and surrogate for cell volume/thickness following protocols described in , built around a Nikon Ti‐E stand, equipped with Nikon 20×/0.75 N.A. objective, an epifluorescence light source (Xcite Exacte), and an sCMOS cameras (Hammamatsu Flash 4), enclosed by an environmental chamber (Haison), and controlled by SlideBook software (3i). Five non‐overlapping images were taken per well.For both fixed and live‐cell imaging, cells were plated in 96‐well, optically clear, polystyrene plates (Costar #3904). Approximately 10,000 HeLa cells or 5,000 MCF10A cells were plated per well. For MCF10A cells, the wells were first coated with collagen  by placing 50 μl of collagen dissolved at a ratio of 1:100 in PBS in each well, incubating for 2–3 h at room temperature, and then rinsing three times with PBS. MCF10A cells were then plated into the wells in MCF10A growth media. For assays to determine EGF responses, the media were aspirated from the cells 24 h after plating and replaced with serum starvation media for 60 h . For imaging, the cells were placed into an extracellular buffer consisting of 5 mM KCl, 125 mM NaCl, 20 mM Hepes, 1.5 mM MgClhttp://github.com/brookstaylorjr/MACKtrack, and described in , the two immunofluorescence, and the protein mass fluorescence channels. Signal intensities were corrected for non‐uniformity but were still restricted to a central R = 350 pixel region of 2 × 2 binned images  of the image to minimize potential spatial non‐uniformities in illumination and light collection toward the corners. The Hoechst stain was used to establish a nuclear mask and to select cells in the 2N G0/G1 state based on the integrated DNA stain. The Hoechst intensity levels used to define cells in the 2N state were selected by inspection of the Hoechst histograms. The live‐cell FRET measurements of nuclear ERK activity were performed on a Nikon Ti2 controlled by 3i software . The mean nuclear intensities of the FRET and CFP channels were ratioed for each cell to obtain the normalized FRET value at each timepoint. At the end of the timecourses, the cells were fixed and stained with either an ERK or MEK antibody, as well an Alexa 647 NHS Ester as an estimate of cell volume. To obtain ERK and MEK concentrations for each cell, the mean total cell intensities of the ERK and MEK antibodies were ratioed over the mean total cell intensity of the Alexa 647 NHS Ester. The final ERK and MEK concentrations for each cell were then matched to the corresponding FRET timecourse for that particular cell.t = 15.The goal of these figure panels is to illustrate how different amounts of noise (cell‐to‐cell variation) would affect the output of a multi‐step linear signaling system. We used MATLAB simulations to apply expression variation in the concentrations of pathway components in a five‐step linear signaling pathway with a single input and output, representing a typical vertebrate signaling pathway. The model is not saturated and uses a single fold‐input R to increase pathway activation linearly above the basal activity level. The last regulated signaling step y5 is shown as the analog output A*. We simulated protein expression variation of each of the 10 signaling pathway components using lognormal Monte Carlo noise simulations (each of the 10 system parameters was multiplied by randomly variable factors centered on 1). We followed the system over time using the ODE45 function until it reached equilibrium at Linear model: y1.R is the Receptor Input into the cell that activates y5∗ and denotes the final output signal . Each signaling step acts linearly on the next intermediate step.A* corresponds to y* states are generated from a relatively larger constant pool of precursor cells. In other words, yi, as well as A, denotes a pool of inactive precursors that is not significantly diminished during signal transmission  and is set equal to 1.The model is not saturated. For each step, we assume that the active To introduce uncorrelated lognormal noise into the system: i = 1–10, randn is a lognormally distributed random number and CV is the percent noise in the system, typically from 5 to 25%. We are introducing noise into the system as lognormal since we are assuming that the noise sources are multiplicative not additive in the system  which is a reasonable assumption in biology.For x| << 1, ex ≈ 1 + x, which keeps the CV of the real distribution approximately the same as the CV of the lognormal distribution.For |The ten lognormal stochastic values of a factorial parameter e(1‐10) are calculated for each of typically 5,000 runs to generate the plots, e(i:10)=, Var) in MATLAB. Var is the percent variation parameter that changes in different panels in the plots. Calculating a coefficient of variation (CV) of the resulting random parameter distribution returns the value Var.This figure illustrates how the fold‐Input Detection Limit (fIDL) is calculated for a particular noise level (CV) and Receptor Input. We assume there are N independent pathway components which increases the overall noise in the output by noise propagation to: The calculation of fIDL was done analytically using the inverse normal distribution function in MATLAB to determine the fraction of cells in a population that are in the desired tail region of the output probability distribution. The resulting value is half of the required signal output amplitude since both the unstimulated and stimulated distributions are symmetrical when they are plotted as a log scaled distribution. The factor 2 in the equation reflects that basal and stimulated output distributions are assumed to have the same noise  between signaling components in the pathway. In Fig The model is the same as shown in Fig y5∗ exceeds a threshold level of 10, and cells do not trigger the switch when the final output remains below this threshold level. The threshold of 10 was chosen arbitrarily . We used increasing fold‐stimuli strength R and analyzed in the simulations the increasing fraction of cells that triggers the switch. Figure The goal of these figures is to show how variation and covariation of proteins in a pathway contribute to the control of binary, population‐based signaling responses. We simulated binary pathways in Fig Similar to the calculation of a fIDL in Fig  et al, The goal of this figure is to show how covariation of MEK/ERK abundance improves the sharpness of the binary population‐level outcome. For numerical simulations, we used the ODE model of the ERK signaling network from (Sturm The goal of this figure is to illustrate the conflicting effects that expression variation, covariation, and number of pathway components have on controlling analog single‐cell and binary population‐level signaling responses. The equations for fIDL and aHC were presented earlier (Equations Figure https://github.com/Teruellab/Kovary_MSB_2018.Data and MATLAB analysis scripts used in this paper are available at KMK, MLZ, BT, and MNT conceived experiments. KMK and BT performed experiments. KMK, BT, and MNT carried out model simulations. KMK, MLZ, BT, and MNT analyzed data. KMK and MNT wrote the paper with input from all authors.The authors declare that they have no conflict of interest.Expanded View Figures PDFClick here for additional data file.Table EV1Click here for additional data file.Table EV2Click here for additional data file.Table EV3Click here for additional data file.Table EV4Click here for additional data file.Review Process FileClick here for additional data file.


Despite huge advances in the fight against HIV concerning diagnosis, clinical efficacy of antiretroviral treatments (ART), patient survival and quality of life, there is still no cure. Recent developments in HIV cure research have opened the way for clinical trials which could lead to a temporary or definitive end to ART. However, ethical questions exist about related trial-participation risks. The main goal of the ANRS-APSEC survey was, using Q-methodology, to investigate the viewpoints of people living with HIV (PLWH) and HIV healthcare providers (HHP) regarding motivations for and barriers to participation in HIV Cure-related clinical trials (HCRCT).Thirty-three statements were defined encompassing seven dimensions: treatment and follow-up; risks; benefits; patient-physician relationship; beliefs and attitudes; information; target population. Forty-one PLWH and 41 HHP from five French HIV services were asked to rank-order the statements.Five main viewpoints were elicited from “the most motivated” to “the most reluctant” vis-à-vis HCRCT participation. All placed importance on the wish to participate in HIV research. This result is in line with the HIV-specific culture of joint mobilization. For some viewpoints, the motivation to participate in/propose HCRCT was primarily conditioned by side-effects and/or by constraints, which overall were more accepted by PLWH than HHP. Some viewpoints placed particular importance on HCRCT recruitment strategies. Finally, some expressed a high acceptance of risks and constraints but emphasized the need for information.HIV cure research clinical trials (HCRCT) constitute a risky yet unavoidable step towards the goal of finding a cure. To improve future HCRCT and informed consent designs, based on PLWH and HHP preferences and expectations, we need greater knowledge about how these populations perceive the risks and the benefits of HCRCT. Our results confirmed the importance of careful, studied HCRCT design, management and communication, to ensure PLWH and HHP acceptability and convergence of their expectations. Since the advent of HIV and the first AZT treatment , huge adRecent developments in HIV-cure research have opened the way for HIV Cure-related clinical trials (HCRCT) which could lead to a temporary or definitive end to ART –15. The The multi-centre ANRS-APSEC project  formed part of the IAS “Towards an HIV cure” initiative which promotes multidisciplinary research for a safe, affordable and scalable cure ,26. The Q-methodology combines qualitative and quantitative approaches –33 and hviewpoints were obtained by a factor analysis performed on the Q-sorts: each factor represents a viewpoint shared by a group of respondents who rank-order a set of statements in a similar fashion. If different individuals have different viewpoints on the topic, their Q-sorts will not correlate. If significant clusters of correlation exist, they can be factorized, and individuals are assigned to a particular factor .The second characteristic of these two viewpoints was the rejection of constraints on participating patients that would bring about a modification of the patients’ way of life  and the most-motivated [PLWH/HHP-VP2] viewpoints).In addition to altruism, the main motivation for participating/proposing HCRCT is the possibility of avoiding the long-term consequences of ART (for the most-motivated (PLWH-VP2) and reticent (PLWH-VP4) PLWH viewpoints, as well as for the moderately-motivated HHP viewpoint (HHP-VP1). As regards the patient-physician relationship, our results highlighted that physicians involved in HCRCT would need to provide regular feedback on the trial’s results as it progressed. This was particularly the case for the most-motivated HHP (HHP-VP2) and reticent PLWH viewpoints. Some viewpoints highlighted that similar feedback by participating patients was also expected, but to a lesser extent. This was especially true of the most-motivated HHP viewpoint. Clear information about HCRCT treatments was an essential prerequisite for nearly all viewpoints. This result has key implications both for the information to provide to patients in informed consent and for the management of the support during future trials, in particular regarding communication.Another lever is the patient-physician relationship, with a consensus among PLWH and HHP that the patient’s HIV-physician needed to believe in HCRCT for patients and HHP to participate. Moreover, trial supervision by the HIV-physician was a motivation for participation for the reticent viewpoint placed more importance on an unchanged way of life, and no loss of autonomy. Therefore, innovative treatment modalities and follow-up were considered barriers because of the resulting loss of autonomy. In contrast, regular and closely monitored follow-up during the ART free-phase was of great importance to the most-motivated and the conditional-participation PLWH viewpoints. This tension between the unavoidable medical consultations for the viral load tests during the period without ART treatment and the burden of participation in such trials have to be carefully managed by HHP.With respect to burden and support during the trial, the most-motivated viewpoints. The possibility that vital organs might be affected by the innovative treatment, represented the second main barrier, for the PLWH conditional-participation [PLWH-VP1] and the moderately-motivated viewpoints. Globally, side-effects were only fully accepted by the most-motivated viewpoints, and conditionally by PLWH-VP1.Moreover, as has already been underlined in the literature [Attitudes towards side-effects, and their impact on QoL, is a split line in the decision to participate/propose HCRCT. Any irreversibility of side-effects was a barrier to participation except for the terature , viewpoiconditional participation and the most-motivated PLWH viewpoints saw any participant selection based on criteria perceived as non-clinical, to be a barrier to equal access to care for all. This point mirrors [Finally, differences in opinion were highlighted between viewpoints regarding the possibility that participation in HCRCT would be specific to target populations. The  mirrors , that th mirrors . On the PLWH reticent-viewpoint) and improving access to better medication for a higher number of PLWH (HHP benefit-centred viewpoint), rather than developing cure trials. This result reflects that by Chu et al. [With regard to the access to care, some viewpoints expressed a preference for developing prevention  constitute a risky yet unavoidable step towards the goal of finding a cure . To ensuOur results showed that scientific altruism and providing clear information on treatments and the associated side-effects are dimensions which have a strong impact in the decision-making process on whether to participate in or to propose HCRCT. Furthermore, we found that it is fundamental that the current HIV physician believe in HCRCT and participate in them. On the contrary, disparities were found between viewpoints regarding the accepted level of side-effects and the burden associated with HCRT participation on daily life, questioning the best strategy to adopt: whether to design HCRCT according to the expectations of the highest number of PLWH and HHP or to design them according to the most motivated PLWH and HHP.S1 Fig(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


LQB 123 presented a trypanocidal effect against bloodstream trypomastigotes (IC50 = 259.4 ± 6.1 μM) and intracellular amastigotes infecting peritoneal macrophages (IC50 = 188.2 ± 47.5 μM), with no harmful effects upon the mammalian cells , resulting in a high selectivity index (CC50/IC50 > 20). Additionally, metacyclic trypomastigotes submitted to LQB 123 presented an IC50 of about 191.8 ± 10.5 μM and epimastigotes forms incubated with different concentrations of LQB 123 presented an inhibition of parasite growth with an IC50 of 255.1 ± 3.6 μM. Finally, we investigated the mutagenic potential of the nitrone by the Salmonella/microsome assay and observed no induction of mutagenicity even in concentrations as high as 33000 μM. Taken together, these results present a nonmutagenic compound, with trypanocidal activity against all relevant forms of T. cruzi, offering new insights into CD treatment suggesting additional in vivo tests. The therapeutic options for Chagas disease are limited and its treatment presents a number of drawbacks including toxicity, drug resistance, and insufficient effectiveness against the chronic stage of the disease. Therefore, new therapeutical options are mandatory. In the present work, we evaluated the effect of a phenyl- T. cruzi is an obligate intracellular parasite with a complex life cycle that alternates between vertebrate host and invertebrate haematophagous triatomine insect and involves proliferative  and nonproliferative  stages pyrene, at 396 μM for TA102 and 2-aminoanthracene (2-AA), at 517 μM for TA97, TA98, TA100, and TA1535. All chemicals were from Sigma Co.Stationary growth cultures of histidine auxotrophicand Ames . DMSO wap < 0.05.Statistical analysis was conducted with GraphPad Prism 5 software . Data were analyzed by one-way ANOVA, and differences between groups were assessed with Tukey's posttest. The level of significance was set at μM. For bloodstream trypomastigotes IC50/24 h it was 259.4 ± 6.1 μM and for metacyclic trypomastigotes the IC50/24 h was 191.8 ± 10.5 μM. The mammalian proliferative form of T. cruzi was more susceptible to LQB 123, with IC50/48 h values of 188.2 ± 47.5 μM : TcI–VI [The treatment with LQB-123 was effective against epimastigotes, bloodstream, and metacyclic trypomastigotes with IC50 in the range of 75–1200  47.5 μM . It is i T. cruzi, the intracellular amastigotes. After 48 h, the compound decreased the number of infected cells in IC50 by 78.3%, the amastigotes inside each cell by 73.50%, and 50% of the infectivity index of amastigotes (188.2 μM) compared to DMSO control  was higher than 4000 μM (data not shown). Interestingly, comparing the CC50 with the IC50/48 h, the nitrone exhibited higher Selective Index values comparing to metacyclic trypomastigotes (>21) or bloodstream trypomastigotes (>16), the relevant clinical forms of T. cruzi , corresponding to 127 times the IC50 for bloodstream trypomastigotes, led to a significant decrease in the survival of TA100 and TA1535 strains. However, these toxic effects were not observed in the presence of exogenous metabolization (except TA100 strains in the highest concentration) indicating that S9 mix can have a detoxifying effect on the compounds responsible for bacterial growth inhibition.The incubation with LQB 123 in the absence or in the presence of exogenous metabolization showed no mutagenic activity over the sensitive strains (mutagenic index ≤ 2). Also, a major reduction of the induced revertants was obtained for TA97, TA98, and strains even in the absence of metabolic activation . MoreoveAfter 107 years of its discovery, the chemotherapy of this disease is still controversial and unsatisfactory, provided that the only two available drugs are toxic, possibly carcinogenic, besides presenting low effectiveness against the chronic phase of the disease .Despite that, efforts have been made in order to improve CD treatment using the available drug, benznidazole; however, so far, benznidazole did not result in a statistically significant improvement in cardiac clinical outcomes . The fac T. cruzi. However, these effects were not able to decrease the inflammatory infiltrate, or the parasite persistency.Wen et al.  demonstr T. cruzi. It is also possible to highlight the trypanocidal action against infective forms, metacyclic trypomastigotes, and bloodstream, with IC50/24 h 191.8 μM and 259.4 μM, respectively, and a higher susceptibility over the mammalian stage proliferative form (IC50/48 h 188.2 μM)  in patients with ischemic stroke, even when concentrations higher than 260 μM of the compound were administrated intravenously [LQB 123 compound showed effectiveness against all biologic forms of88.2 μM) . We also88.2 μM) . AlthougμM of the nitrone, a concentration 21 times higher than the necessary to abolish the intracellular amastigote infection. Also, the LQB 123 compound presented greater selective action for the parasite highly infective trypomastigote forms with selectivity index higher than 16 for bloodstream trypomastigotes and higher than 21 for metacyclic trypomastigotes  and in the absence of exogenous metabolization, strongly indicating that S9 mix probably has a detoxifying effect of the nitrone structure, responsible for the inhibition of bacterial growth (Following the method recommended by the Organization for Economic Cooperation and Development (OECD) TG471 , we applobtained , 29. LBQl growth .50 calculated for bloodstream trypomastigotes). This concentration when applied to LQB 123 presents no mutagenic effect.Another possible chemotherapy applicability of LQB 123 is further enhanced because the benznidazole mutagenic activity was tested by Ames assay . The maxThus, it is plausible to suggest that the LQB 123 molecule retained some of the chemical properties of PBN, such as the low toxicity and a prominent trypanocidal effect in vitro. It is important to point out that the the beneficial effect of PBN in vivo against CD was a consequence of its free radical scavenging properties; however, recent reports have shown that the antileukemic properties of the PBN derivate, the O-geranylated nitrone (LQB-278), were not free radical related but a consequence of cell cycle regulation by the inhibition of p21 expression . TherefoFinally, it is important to establish that a desired compound should have trypanocidal activity without inducing toxic effects to cells at concentrations that can be achieved in vitro. The relative effectiveness of an investigational product in inhibiting parasite survival compared to inducing cell death and the therapeutic or selectivity index has to be considered. Thus, the selection of new trypanocidal compounds should take into account a high selectivity index giving maximum trypanocidal activity with minimal cell toxicity.Also, the new therapies to be established should include new pediatric formulations of the available drug, benznidazole, and new benznidazole treatment regimens (including combination therapies), as well as a new therapeutic vaccine linked to benznidazole chemotherapy . T. cruzi. Furthermore, the low toxicity of LQB 123 against the vertebrate cells, proven in this work, is a very important result that justifies future animal experimentation, as well as the testing of new PBN analogues.Taken together, these results broaden new perspectives for the Chagas disease treatment once LQB 123, a novel nitrone derivate, significantly decreased mammalian cells infections by


Aberrant activation of Hedgehog (HH)/GLI signaling is causally involved in numerous human malignancies, including basal cell carcinoma (BCC) and medulloblastoma. HH pathway antagonists targeting smoothened (SMO), an essential effector of canonical HH/GLI signaling, show significant clinical success in BCC patients and have recently been approved for the treatment of advanced and metastatic BCC. However, rapid and frequent development of drug resistance to SMO inhibitors (SMOi) together with severe side effects caused by prolonged SMOi treatment call for alternative treatment strategies targeting HH/GLI signaling downstream of SMO. In this study, we report that 4SC‐202, a novel clinically validated inhibitor of class I histone deacetylases (HDACs), efficiently blocks HH/GLI signaling. Notably, 4SC‐202 treatment abrogates GLI activation and HH target gene expression in both SMOi‐sensitive and ‐resistant cells. Mechanistically, we propose that the inhibition of HDACs 1/2/3 is crucial for targeting oncogenic HH/GLI signaling, and that class I HDAC inhibitors either in combination with SMOi or as second‐line therapy may improve the treatment options for HH‐associated malignancies with SMOi resistance. What's new?Inhibition of signaling by Hedgehog polypeptide and the effector protein GLI is an effective therapeutic strategy for basal cell carcinoma and medulloblastoma. The frequent development of resistance to Hedgehog pathway inhibitors (HPI), however, calls for the identification of alternative drugs. This study identifies the class I histone deacetylase inhibitor 4SC‐202 as a novel Hedgehog/GLI antagonist. A clinically suitable small molecule, 4SC‐202, showed inhibitory efficacy, blocking GLI activation and Hedgehog target gene expression, even in cells with acquired HPI resistance. The findings suggest that 4SC‐202 could be effective against Hedgehog‐driven cancers that are refractory to standard targeted therapy. Hedgehog (HH)/GLI signaling plays a pivotal role in many human malignancies. Notably, targeted pathway inhibition has shown clinical success particularly in HH‐driven basal cell carcinoma (BCC) and medulloblastoma.Active GLI proteins drive tumor formation and promote cancer progression by inducing proliferation, survival, self‐renewal and metastasis.Targeting epigenetic regulators such as histone deacetylases (HDACs) has proven a successful therapeutic option in several malignancies. Intriguingly, HDACs have been shown to modulate the activity of HH/GLI signaling with evidence for both a positive and repressive impact, demanding selective inhibition of HDACs, which enhance oncogenic HH/GLI signaling.in vivo, thereby identifying 4SC‐202 as a promising epigenetic drug for the treatment of HH‐driven cancers.In this study, we show that the clinically suitable class I HDAC inhibitor (HDACi) 4SC‐202 efficiently abrogates HH/GLI signaling in a human model of oncogenic HH/GLI signaling. Importantly, 4SC‐202 inhibited HH/GLI signaling in both, SMOi‐sensitive and SMOi‐resistant settings and interfered with the growth of HH/GLI‐dependent BCC cells For an extended version of Materials and Methods, see Supporting Information.NIH/3T3 Gli reporter cells (AMS Biotechnology) were used to monitor Hh pathway activity in response to chemical treatments and cell viability was assayed in parallel.To study human HH/GLI signaling, we applied Daoy medulloblastoma cells (ATCC HTB‐186) responsive to chemical and genetic pathway activation. The following chemicals were used: Smoothened agonist SAG (Axxora), vismodegib and entinostat (LC Laboratories), OG‐L002, SAHA/vorinostat and 4SC‐202 (4SC AG). Cell proliferation and viability were determined by Alamar Blue assays .In vivo experiments were done in NSG mice. Following randomization of mice with palpable tumors, mice were treated with 4SC‐202  or solvent. Tumor volume was measured every 2–3 days using a caliper.Total RNA was isolated using TRI reagent (Sigma‐Aldrich) according to manufacturer's protocol followed by LiCl precipitation. qPCR was done on a Rotor‐Gene Q (Qiagen) using GoTaq 2× qPCR Mastermix (Promega). qPCR primers are listed in Supporting Information, Table 1.For protein detection by Western blot analysis, the following primary antibodies were applied: anti‐GLI1 (V812), anti‐Beta Actin (D6A8), anti‐HDAC1 (D5C6U), anti‐HDAC2 (D6S5P), anti‐HDAC3 (7G6C5), anti‐p44/42 MAPK (Erk1/2), anti‐PCNA (D3H8P), anti‐Cyclin D1 (92G2), anti‐β‐Tubulin  and anti‐SUFU . ChIP assays were conducted using the SimpleChIP Kit  with cross‐linked chromatin immunoprecipitated overnight with either anti‐H3K27ac antibody (D5E4) or anti‐MYC‐tag antibody (9B11) or mouse IgG isotype control . Immunohistochemistry was done on FFPE tissue of three different skin specimens with diagnosis of BCC. Sections were stained using the following primary antibodies: anti‐HDAC1 , anti‐HDAC2  and anti‐HDAC3 , 1:100).SUFU knockdown was done by lentiviral shRNA transduction as described in Ref. clinicaltrials.gov trial no. NCT01344707 and J Clin Oncol 32:5 sec, 2014 ). To analyze whether 4SC‐202 affects HH/GLI signaling, we first treated Sonic Hh stimulated murine Hh/Gli luciferase reporter cells with 4SC‐202 and found that 4SC‐202 strongly repressed Gli activity with an IC50 of ∼50 nM . To address the relevance of this finding to physiological HH/GLI signaling in a human context, we used HH responsive human medulloblastoma cells  as a human model of canonical HH/GLI signaling in cancer cells.b and c) and activation of HH signaling by Smoothened agonist SAG induces HH target genes (e.g. GLI1 and HHIP) at the mRNA and protein level.d) and HHIP  expression with an IC50 of ∼240 nM and ∼140 nM, respectively, without affecting primary cilia formation, an essential process for the coordination of HH/GLI signal activation .f and g). RNAi‐mediated inhibition of individual class I HDACs in Daoy cells suggests a dominant role for HDAC3, though the repressive effect on HH target gene activation was less pronounced when compared to 4SC‐202 treatment, most likely due to functional redundancy of class I HDACs . Furthermore, and in line with the proliferative role of HH/GLI in medulloblastoma, 4SC‐202 treatment also reduced the growth of SAG‐stimulated Daoy cells .4SC‐202 is a novel small‐molecule inhibitor selectively targeting class I HDACs 1/2/3 and the lysine‐specific demethylase LSD1.a), which has been shown to play key roles in many malignancies. To investigate whether 4SC‐202 represses HH/GLI by inhibiting LSD1, we first tested the potent LSD1 inhibitor OG‐L002b, OG‐L002 only moderately repressed SAG‐induced HH signaling to 75% of controls as monitored by GLI1 mRNA expression analysis. Furthermore, siRNA‐mediated knockdown of LSD1  did not reduce GLI1 mRNA levels in response to SAG stimulation . Thus, we conclude that the repressive effect of 4SC‐202 on HH/GLI signaling does not involve inhibition of LSD1. To further support the requirement of class I HDACs in HH/GLI signaling, we treated SAG‐stimulated Daoy cells with the selective HDAC1/2/3 inhibitor entinostat.d and e). By contrast, treatment with the FDA‐approved pan‐HDAC inhibitor SAHA (vorinostat) was unable to efficiently abrogate HH/GLI signaling , which may be a consequence of targeting HDAC6, whose inhibition has been shown to promote ciliogenesis and HH signaling.4SC‐202 displays a unique inhibitor profile blocking not only the class I HDACs HDAC1/2/3, but also the lysine‐specific demethylase LSD1 . Notably and in contrast to vismodegib, 4SC‐202 treatment reduced the expression of GLI1 and HHIP also in SMOi‐resistant Daoy cells at IC50 concentrations similar to those determined in the SMO‐dependent wild‐type Daoy model . We confirmed these observations also at the protein level by showing that 4SC‐202, but not vismodegib, was able to reduce GLI1 protein expression in SUFU‐deficient Daoy cells . Consistently, 4SC‐202 also repressed the growth of both SMOi sensitive (wild‐type) and SMOi‐resistant (shSUFU) Daoy cells in a concentration‐dependent manner .HH/GLI pathway inhibitors targeting SMO (SMOi) have been approved for the treatment of advanced and metastatic BCC.g), despite enhancing transcriptional activation marks  . These data corroborate the findings by Canettieri et al. (2010)Acetylation of GLI1 has been suggested to decrease its DNA binding capacity.a and 6b).To analyze a possible effect of 4SC‐202 treatment on GLI processing, we used Ptch1 deficient Med1 cells derived from a genetic mouse model of medulloblastoma. Notably, treatment of Med1 cells with 4SC‐202 not only reduced Gli1 expression, but also reduced the ratio of Gli3 full‐length activator (Gli3A) to Gli3 repressor (Gli3R), suggesting that acetylation may also contribute to efficient GLI repressor formation in addition to its effect on DNA binding of GLI transcription factors  mice ptch1/p53 double‐deficient murine BCC cells expressing readily detectable levels of Hdac1/2/3 in a Hh/Gli independent manner as assessed by vismodegib treatment . When tumors reached an average volume of 400 mm3, we randomized the mice into two groups. The verum group received 80 mg/kg/day of 4SC‐202 in 2% methocel solution, the control group was treated with solvent only. Notably, treatment of BCC bearing mice with 4SC‐202 significantly decelerated in vivo tumor growth , and markedly repressed the expression of the proliferation marker PCNA, which was paralleled by a moderate reduction of the Hh/Gli target gene and cell cycle regulator Cyclin d1 (Ccnd1)i). To support a direct effect of 4SC‐202 on the growth of murine BCC cells, we treated ptch1/p53‐deficient cells also in vitro and found reduced cellular proliferation in response to 4SC‐202 as well as entinostat .Having shown a pronounced inhibitory effect of 4SC‐202 on HH/GLI signaling and proliferation downstream of SMO, we next investigated whether 4SC‐202 treatment can repress the Together with high level expression of HDAC1 and HDAC2 in human BCC samples , our findings therefore warrant further studies of 4SC‐202 and other class I HDACi as combination or second‐line drugs to tackle the problem of frequent SMOi‐resistance development observed in HH‐driven cancers such as BCC.a priori insensitivity to SMO antagonists limit the therapeutic efficacy of SMO targeting.SMOi provide clear clinical benefit to BCC patients, though rapid development of SMOi resistance and a priori SMOi resistance. Inhibition of GLI transcription factors is also an attractive strategy as GLI transcription factors frequently integrate with other oncogenic signaling cascades, thereby contributing to cancer progression and malignant traits of cancer and cancer stem cells.In this study, we identify the potent and clinically suitable class I HDACi, 4SC‐202, as novel inhibitor of HH/GLI signaling in human cancer cells. Importantly, 4SC‐202 but not the FDA‐approved inhibitor vismodegib, efficiently abrogated HH/GLI signaling in SUFU‐depleted human medulloblastoma cells resistant to SMOi‐therapy. The SMO‐independent mode of action of 4SC‐202 may lead to benefits for patients, who do not qualify for therapy with SMOi either due to acquired or et al., who showed that acetylation of GLI proteins negatively regulates their DNA‐binding capacity.Mechanistically, our results are in agreement with a previous study by Canettieri et al. demonstrated a positive feedforward loop involving upregulation of HDAC1 expression in response to HH/GLI,et al. describe a positive role of HDAC6 in the regulation of the mammalian HH pathway.Previous studies have also identified interactions between different HDACs and HH/GLI signaling, though with partially different results. Canettieri Intriguingly, analysis of the genetic landscape of SHH subgroup medulloblastoma identified frequent somatic alterations in genes encoding histone acetyl transferases.The clinical relevance of our findings is further underlined by a recent phase I clinical trial with 4SC‐202, where 18 out of 24 patients with advanced hematologic malignancies went into follow up treatment, one patient showed complete response and remained on study medication for >28 months, while another patient had a partial response over a period of 8 months ). Although it is unclear whether the promising clinical response to 4SC‐202 treatment was due to inhibition of GLI activity, the results of the present study warrant further clinical evaluation of 4SC‐202 as a treatment for GLI‐dependent cancers including BCC, medulloblastoma and possibly other malignancies with high medical need.WG, EP, DPE, CS, ST, PDB, DN, SC, GC and HK performed experiments. WG, RB, HK, DV, GC and FA designed experiments and analyzed data. WG and FA wrote the article. All authors critically reviewed the article before submission.Supporting InformationClick here for additional data file.