In this study, we present a computer model of starve fed single screw extrusion of wood plastic composites (WPC). Experimental studies have been performed on the extrusion of the polypropylene (PP) based composites with various wood fiber contents (WF). The melting mechanisms of the composites in the extruder have been observed, and melting models have been proposed for partially and fully filled sections of the screw. It was observed that in the partially filled section the material is melted by conduction, as in the case of extrusion of neat polymers. On the other hand, in the fully filled section, the Tadmor melting mechanism appears, which is different compared to the melting mechanism of neat polymers at starve fed extrusion, where dispersed melting is observed. Using the melting models, the global computer model of the process has been developed which makes it possible to predict the process flow, i.e., the polymer melt temperature and pressure, the polymer melting rate, and the degree of screw filling. To build the model, the specific forward/backward procedure was developed, which consists in determining “forward” the melting profile, and “backward” the pressure and screw filling profile. The temperature profile in the melting section is computed “forward”, while “backward” in the metering section. This procedure makes it possible to solve the crucial problem of modeling of the starve fed extrusion process, which is to find the location of the point where the screw is fully filled, and the pressure is developed. The model has been tested by pressure measurements in the extruder. Extrusion can be performed using two ways of feeding. The conventional feeding by gravity, often called as flood feeding, is mostly applied in single screw extruders. The non-conventional, metered feeding, also known as starve feeding, is primarily applied in twin screw extruders. Extrusion with metered feeding ensures faster melting and better mixing of the material, and therefore, this may be also applied in single screw extruders.In the case of feeding by gravity, the screw takes as much polymer as it can, and the screw is completely filled with it. In the case of metered feeding, the polymer is delivered to the extruder by a dosing device, and the beginning section of the screw is only partially filled with the polymer. This is shown in The starve fed extrusion has several advantages over the flood fed extrusion, as discussed in the literature, e.g., ,4,5,6,7,The conventional single screw extrusion is relatively well understood, and well described in the literature. Tadmor et al. were the first who proposed the mathematical model of melting (fusion) of polymers in the single screw extruder, and later the global (composite) model of the process, which was composed of the models of solid conveying, fusion of the polymer, and melt conveying ,10,11. LThe state-of-the-art of modeling the extrusion process was discussed in the fundamental monographs, e.g., of Rauwendaal , White aAlthough the conventional extrusion was widely studied and described in the literature, little information was delivered on the extrusion with metered feeding. Wilczyński et al. ,27 perfoWood plastic composites (WPC) are composed of the thermoplastic matrix and the wood filler, that is, the wood flour or fiber. These materials have high durability, high stiffness/strength and low price compared to other competing materials. In addition, they are water and weather resistant and can be used for a variety of outdoor applications.The wood plastic composites (WPC) market has grown substantially in the last years, which primarily results from increasing the building industry and the automotive industry. The most used wood plastics composites are polypropylene (PP) composites, high density polyethylene (HDPE) composites, and polyvinyl chloride (PVC) composites ,33,34,35The fundamental technology for processing wood plastic composites (WPC) is extrusion due to an extensive use of these as profiles. Extrusion of wood plastic composites differs substantially from extrusion of thermoplastics, which results from different thermo-rheological characteristics of these filled materials, various structure, etc.Limited studies were performed on rheology of wood plastic composites (WPC), as well as on extrusion of these. Basic research was carried out by Xiao and Tzoganakis ,37,38,39Currently, it is generally known that wood plastic composites (WPC) are pseudoplastics and viscoelastics. Their viscosity lowers when the shear rate and temperature rise and rises when the filler content rises.Wood plastic composites (WPC) exhibit slipping and yield stress, which was presented and discussed by Xiao and Tzoganakis , Li and Designing an extrusion process of wood plastic composites (WPC) requires a deep knowledge on the flow mechanism of these in the extruder. Only a few fusion studies were carried out, e.g., by Xiao and Tzoganakis ,37,39 foWilczyński et al.  performe➢Based on these investigations, the first global (composite) computer model of single screw extrusion of wood plastic composites (WPC) has been developed for extrusion with flood feeding. The model predicts the extrusion throughput, the polymer melting temperature and pressure, the melting (fusion) rate, and the power consumption. The model has been successfully tested by experiment .➢Up to now, there is not any model of starve fed single screw extrusion of wood plastic composites (WPC). The only preliminary simulation studies were performed for this process using the classical computer model of starve fed extrusion developed for thermoplastics .In the research presented here, experimental studies have been performed on the extrusion of polypropylene (PP) composites with various wood fiber contents (WF), and a novel global computer model of single screw extrusion of wood plastic composites (WPC) with metered feeding has been developed.F = 10.78, the section of compression (L/D)C = 7.11, and the section of metering (L/D)M = 9.11. The channel depth (HF) in the feeding section was equal to HF = 8 mm, and the channel depth (HM) in the metering section was equal to HM = 3 mm.In the study, a single screw extruder was used with a screw/barrel system of a diameter D = 45 mm and a length/diameter ratio (L/D) = 27. The conventional screw was applied with the section of feeding (L/D)n = 30 rpm, n = 70 rpm, and the barrel/die temperatures were equal to TI = 150 °C, TII = 175 °C, TIII = 180 °C, TIV = 180 °C, and TDIE = 180 °C. The extrusion process was performed at the flood feeding, and at the starve feeding with the flow rates equal to GSF 1 = 0.9 GFF, and GSF 2 = 0.8 GFF, where GFF is the flow rate at the flood feeding, which each time is dependent on the process and material conditions.A flat die for tapes of width W = 20 mm and thickness H = 2 mm was applied. A “screw pulling-out technique” was used to analyze the material transport and fusion mechanism. This well-known technique is described elsewhere . The preThe polypropylene (PP) based composites were used in the study. These were (WPC) of compositions (WF/PP) equal to 20/80 and 40/80, i.e., (i) WPC 20/80 ForMi GP20 and (ii) WPC 40/60 ForMi EXP40 .In is worth noting here that in terms of product segmentation, the (WPC) market is categorized into polyethylene, polypropylene, and polyvinylchloride . The polThe composites used in the study are cellulose fiber reinforced plastic composites with high renewable material content. Principal ingredients are specially selected cellulose fibers and virgin polypropylene. Cellulose fibers significantly increase the stiffness and strength of polypropylene. These environmentally sound composites are optimized for use in extrusion, and injection molding applications instead of polypropylene, filled polypropylene, or several other plastics. These are fully recyclable or can be burned for energy. All cellulose fibers are from sustainably managed forests.A small amount of the composite (4%) has been colored with 2% of Ramafin Orange CEK071 dye-stuff to distinguish between the solid and melt. The material was dried at 80 °C for 4–6 h.s = 0.99 g/cm3 and ρs = 1.08 g/cm3, the melt density equal to ρm = 0.85 g/cm3 and ρm = 0.98 g/cm3 at the temperature 190 °C, and the bulk density equal to ρbulk = 0.4–0.6 g/cm3. The melting point is about Tm = 160 °C.The (WPC) composites (20/80 and 40/60) have, respectively, the solid density equal to ρ−1. The viscosity curves are presented in Viscosity curves were determined for both composites. The tests were performed with the use of capillary rheometer RG-25 . The four capillaries of diameter D = 1 mm, D = 2 mm, and the length/diameter ratios L/D = 0/1, 0/2, 10/1 and 20/2 were used, and the Rabinowitsch and Bagley corrections were applied in rheological computations. The measurements were performed in the temperature ranges of 180 °C, 190 °C, and 200 °C and in the shear rate range of 1–2000 sLL = 17 g/10 min., MFRHL = 580 g/10 min. for WPC 20/80, and MFRLL = 3 g/10 min., MFRHL = 92 g/10 min. for WPC 40/60.A mass flow rate (MFR) index was determined for both composites with the use of Melt Indexer MI-2 . The tests were made at the temperature 190 °C, and two loads were applied, the Low Load (LL = 5.0 kg) and the High Load (HL = 21.6 kg), and the (MFR) indexes were equal to MFRThe goal of experimentation was to learn the flow mechanism of composites in the extruder, as well as the fusion mechanism. These were the starting points for extrusion modeling, as well as for the validation of the model developed.SF 1 > GSF 2). The length of the fully filled section of the screw is also higher when the flow rate is higher (GSF 1 > GSF 2).The screws, which were pulled out of the extruder, and the results of pressure measurements are presented in Examples of the material samples removed from the screw are depicted in FF), the classical 2D fusion is seen, while when metered feeding (GSF), the fusion by conduction is seen in the partially filled section of the screw, and the classical fusion is observed in the fully filled section which is different compared to the fusion mechanism of neat polymers at the starve fed extrusion, where dispersed fusion is observed [Examples of the cross-sections of the material samples removed from the screw are depicted in observed .Based on the experimental observations, melting (fusion) mechanisms for starve fed extrusion of wood plastic composites (WPC) have been proposed, which are depicted in It was seen that at the beginning of the screw, the material thickens gradually, starting from the active flight of the screw. It is here melted in the whole mass mainly by conduction, as in the case of extrusion of neat polymers, e.g., low density polyethylene (LDPE), polypropylene (PP), and polystyrene (PS), as reported in . On the Modeling of the extrusion process must include both the flow in the screw and the flow in the die, and must take into consideration the interaction between these, describing the flow phenomena in the screw/die system.The flow of polymers through extrusion dies is rather well understood and mathematically modeled for viscous flows. However, this is not for viscoelastic flows, as well as for materials such as wood plastic composites (WPC), for the reason of possible slipping at the wall and yield stress. The flow of polymers in extruders (screws) is much more complex, as it involves the solids conveying, the polymer fusion, and the melt conveying. This is difficult to model even in the case of neat polymers for viscous flows, and extremely difficult and still poorly understood in the case of complex materials such as wood plastic composites (WPC).In the classical extrusion , the mass/volume flow rate of the polymer is not a known a-priori since it is not set by the process operator, but it is due to the co-operation of the screw/die system. Process conditions of this co-operation are defined by the extruder operating point, which determines the extruder throughput (the polymer flow rate), and the extruder die pressure. In this case, the fundamental for the computation procedure is solving the problem of simultaneously computing the flow rate and the pressure in the screw/die system. This can be obtained by iterative computations in which the pressure increase in the screw is compared with the pressure drop in the die, and the convergence of these computations is sought This classical modeling approach was presented, e.g., in .In the extrusion process with metered feeding, the flow rate of the polymer is known as it is set by the process operator. When process modeling, there is no need to search for the extruder operating point. However, it is not known here where the screw is completely filled with the material. This can be computed and defined by iterative computations in which the computed polymer melt temperature is compared with the polymer fusion temperature at the point where the fusion finishes. This modeling approach was presented, e.g., in .The composite extrusion model may be represented as a series of connections of the elementary models that describe the solid conveying, the polymer fusion, and the melt conveying, as well as the flow in the die.i_out (z) is the process parameter  is the process parameter at the beginning of (i + 1)–increment, z is the location of the increment, and Δz is the length of the screw channel.For engineering computation purposes, the lumped parameter approach is sufficient to apply . AccordiThe global (composite) extrusion model, which is discussed here, contains certain elements of our previous models , and int(1)the partially filled region: fusion by conduction.(2)the fully filled region: fusion according to the classical 2D model instead of the dispersed fusion model, which is valid for neat polymers.(3)the polymer melt conveying in the screw: modeling with the use of 3D FEM based screw pumping characteristics.(4)the polymer melt flow in the die: modeling with the use of 1D approach.Summarizing the model consists of the following elementary models:The scheme of computations has been depicted in In the initial part of the screw, in the partially filled screw section, the polymer fusion is modeled using the conductive model. In the fully filled screw section, the 2D model is used. These computations are performed in the forward direction. When fusion is completed, the computations are transferred towards the die. Starting with the initially assumed melt temperature, the pressure drop in the die is computed in the forward direction. From the principle, it is equal to the pressure increase in the screw. Then, the screw pumping characteristics is used, and the pressure gradient over the screw channel in the backward direction is computed. When pressure diminishes to zero, starving develops, and filling of the screw is computed. The process parameters are computed in the backward direction until the fusion is completed. At this point, the polymer melt temperature is compared with polymer fusion temperature. The computations are repeated by iterations of the modified die melt temperature, and the convergence of these computations is sought. At each iteration, the fusion computations are performed, and the fusion end as well as the melting profile are changed.s is the polymer solid specific heat, T is the polymer mean temperature; Tb and Ts are the temperatures of the barrel and the screw, respectively, hb and hs are the heat transfer coefficients at the barrel and screw surfaces, respectively, Xb and Xs are the widths of the polymer solid at the barrel and screw surfaces, respectively.In the partially filled section, an energy balance is performed on the elementary material volume . The prefusion is the energy rate, which is necessary for polymer fusion, Tm is the polymer fusion temperature, T0 is the starting temperature, and λ is the fusion heat.The polymer gets hot according to this equation, and the polymer temperature rises. When the polymer fusion temperature is reached, the fusion starts. The energy rate that is necessary to melt the polymer is expressed asIn the fully filled screw section, the classical 2D model is applied. The velocity and temperature distributions in the melt film and temperature distribution in the solid bed are determined first, and then an energy balance at the melt/solid interface and the mass balance in the melt film and the solid is made, which allows to predict the fusion rate, e.g., . FollowiThe composite modeling of the extrusion process requires iterative, multiple calculations (hundreds of iterations), and for that reason, the time-consuming finite element method (FEM) is not applied here. However, the pumping flow characteristics based on the (FEM) computations may be developed, and implemented in the form of regression models into the composite model. In this way, a good accuracy of calculations may be achieved within a reasonable time.x is the flow rate (dimensionless), and Δpx is the pressure gradient (dimensionless).The screw pumping characteristics are the dimensionless functions of the flow rate and the pressure gradientThis modeling approach has been recently used by the authors for modeling the single screw extrusion with conventional screws  and withbz = π Db N cos φ is the z-component of the peripheral velocity of the barrel, Db is the diameter of the barrel, n is the rotational speed of the screw, φ is the helix angle of the screw, Δp_ch is the pressure change, Lp_ch is the screw length of the pressure change, m is the coefficient of consistency, and n is the power-law exponent.In the study presented here, the single screw extrusion with the use of conventional screws is modeled. Thus, the screw pumping characteristics may be presented as (5)Qx= 2−1, T is the temperature, °C, and A0, A1, A11, A12, A2, A22 are the Klein model parameters: for WPC of WF/PP = 20/80 , and for WPC of WF/PP = 40/60 .Simulations were made in the range of experiment data. The material data were taken from the literature . The visThe results of the simulation are presented in At the beginning of the screw, the material gets hot until the polymer fusion temperature is reached, and the solid fraction (SF) is equal to unity, SF = 1 (blue line). When the polymer fusion temperature is reached (green line), the fusion starts, and the solid faction (SF) reduces, SF < 1. When the screw channel gets fully filled (red line), the fill factor (FF) is equal to unity, FF = 1, and the second mechanism of fusion occurs. Finally, when the polymer is completely fused, the solid fraction (SF) falls to zero, SF = 0. There is no pressure development in the partially filled region (navy line) where the fill factor (FF) is lower than the unity, FF < 1. However, when the screw channel gets fully filled where the fill factor (FF) is equal to unity, FF = 1, the pressure is developed (navy line). The pressure rises in the screw and drops in the die. From the principle, the pressure increase in the screw is equal to the pressure decrease in the die.n = 30 rpm and n = 70 rpm, and at the flood/starve fed conditions, each time at two levels of starving (GSF 1 > G SF 2). The pressure computations were validated by experimental data.In the study, the extrusion process was simulated for both composites (WF/PP = 20/80 and WF/PP = 40/60), at two screw speeds The results of validation are presented in Wood plastic composites (WPC) are wall-slipping materials that exhibit yield stress, and these properties were not considered in this study. Thus, this might be the possible cause of discrepancies between simulations and experimentations. Another possible reason might be the effect of the elongational viscosity  which may occur at the low shear/elongation rates, and which was also not included into the model. These were recently discussed in the literature .An impact of these properties on the process flow, i.e., wall-slipping and yield stress, which are not included into the model, increases with an increase in the content of wood filler (WF) content. Moreover, for higher (WF) content, the fusion mechanism may be closer to the one-dimensional model which is observed for the composites of more than 50% (WF) content .Experimental research has shown that the flow and fusion of the polypropylene (PP) based wood composites (WPC) in the starve fed extrusion are considerably different from those of the neat polypropylene (PP).It was seen that in the initial part of the screw, the polymer thickens gradually, and it is generally fused in the whole mass, by conduction primarily as in the case of the extrusion of neat polymers. On the other hand, in the area of the fully filled screw, the classical Tadmor fusion mechanism appears with a melt pool at the active flight of the screw, which is different compared to the fusion mechanism of neat polymers at starve fed extrusion, where dispersed fusion is observed.Based on the experimentation, the fusion mechanisms for starve fed extrusion of wood plastic composites (WPC) have been proposed. In the partially filled section, fusion by conduction is postulated, while in the fully filled section, the classical Tadmor mechanism is proposed.Using these fusion models, the composite computer model of the starve fed single screw extrusion of wood plastic composites (WPC) has been built, which predicts the pressure and temperature distributions, the fusion rate, and the degree of screw filling. To build the model, the specific forward/backward computation procedure has been developed, which consists in computing “forward” the fusion profile, and ”backward” the pressure and screw filling profiles. The temperature profile in the fusion section is computed “forward”, while it is computed “backward” in the metering section. This procedure makes it possible to solve the crucial problem of modeling the starve fed extrusion process, which is to find the location of the point where the screw is fully filled. From this point, the pressure is developed and the fusion mechanism changes. The location of this point varies at each iteration of computation and it is found by searching the convergence of the computed polymer melt temperature and the polymer fusion temperature at the point where the fusion finishes.The model has been successfully validated experimentally by pressure measurements. However, for the higher (40%) content of wood fiber (WF) some discrepancies were observed between the simulation and experiment.The possible causes of these discrepancies might be the specific properties of wood plastic composites (WPC), such as wall-slipping and yield stress, which were not included into the model. Thus, including these into the model could be suggested, as well as further experimentation.It can be concluded that starve fed extrusion, which was discussed first in the eighties and then was the subject of very little research, was finally successfully modeled in recent years, and is worthy of intensive experimental and modeling research, especially with regard to the demanding processing tasks related to the processing of advanced materials, such as filled polymers, polymer blends, or polymer composites.


Angiogenesis inhibition has become a mainstay of oncology despite having fallen short of its early promise. As originally envisioned, angiogenesis inhibition would cut off the blood supply, deprive tumor cells of key nutrients, leading to their death. In practice, while there is evidence that tumors under angiogenesis treatment do in fact exhibit some degree of metabolic stress, this is stress is not sufficient to induce significant cancer cell death. We posit that the full potential of angiogenesis inhibition can be realized by the combination of angiogenesis inhibition with emerging tumor metabolism targeting therapies. Because tumors under angiogenesis inhibition are already in a state of nutrient stress, the effects of metabolically targeted therapies such as amino acid depletion , inhibitors of stress adaption (AMPK and GCN2 inhibitors) or energy metabolism  stand to dramatically increase in potency whilst remaining selective for (angiogenic) tumor versus (non-angiogenic) normal tissue. Here, we provide proof-of-principal for this thesis. First, we performed metabolomic profiling of angiogenesis-inhibited tumors, which corroborates a state of nutrient stress in angiogenesis-inhibited tumors. Second, we demonstrate dramatic anti-neoplastic synergy , without enhanced adverse toxicities, between the OxPhos inhibitor IACS-010759 and the angiogenesis tyrosine kinase inhibitor, Tivozanib. The same results were recapitulated with the anti-VEGFA antibody, Avastin, and the OxPhos inhibitor could be substituted with the Enolase inhibitor HEX, with similar effects. The synergy was observed in a broad range of tumor types, even those without clear genetic susceptibilities. Together, these results suggest that angiogenesis inhibitors synergize broadly with cancer therapies targeting metabolism, allowing the realization of the full potential of these previously disappointing drugs. Our results warrant systematic combination clinical trials between angiogenesis inhibitors and established, as well as emerging anti-metabolic cancer therapies.


LDHA is a promising target for cancer therapy, whereas LDHB is necessary for basal autophagy and cancer cell proliferation in oxidative and glycolytic cancer cells. To the best of our knowledge, selective inhibitors for LDHB have not yet been reported. Here, we developed a high-throughput mass spectrometry screening system using an LDHB enzyme assay by detecting NADH and NAD+. As a result, we identified a small-molecule LDHB selective inhibitor AXKO-0046, an indole derivative. This compound exhibited uncompetitive LDHB inhibition (EC50 = 42 nM). X-ray crystallography revealed that AXKO-0046 bound to the potential allosteric site away from the LDHB catalytic active site, suggesting that targeting the tetramerisation interface of the two dimers is critical for the enzymatic activity. AXKO-0046 and its derivatives can be used to validate LDHB-associated pathways in cancer metabolism.Lactate dehydrogenase (LDH) catalyses the conversion of pyruvate to lactate and NADH to NAD Unlike most normal cells, cancer cells can adapt to various microenvironments, such as hypoxia, glucose and other nutrient deficiencies, and acidosis1. Moreover, in tumours and other proliferating or developing cells, a metabolic switch from normal oxidative phosphorylation to aerobic glycolysis is common1. This adaptation, known as the Warburg effect, allows cancer cells to produce ATP from glucose by promoting glycolysis to produce lactate from the mitochondrial pyruvate pool, even in the presence of oxygen2. Increased aerobic glycolysis provides cancer cells with a growth advantage, despite its energetic inefficiency compared with oxidative phosphorylation3.Cancer cells can reprogram various genes to promote their rapid proliferation and metastatic potential+). The LDH enzymes are tetrameric enzymes comprising two separate subunits, M and H, and can form five isozymes, namely, the LDH1 (4H), LDH2 , LDH3 , LDH4 , and LDH5 (4M) subunits. LDH1 and LDH5 are transcribed from the LDHB and LDHA genes, respectively4.During aerobic glycolysis, the conversion of pyruvate to lactate is mediated by cytosolic lactate dehydrogenase (LDH) enzymes with nicotinamide adenine dinucleotide (NADH) as a cofactor, which is converted to nicotinamide adenine dinucleotide 9.Previous studies have reported that LDHA (LDH5) plays a critical role in cancer. For example, in patients with gastric cancer or non-small-cell lung cancer, high LDHA levels are correlated with tumour size and poor prognosis11. One study used clinical samples derived from patients with colorectal cancer and found that MYC expression is highly correlated with the expression of various metabolic genes. In that study, 231 unique metabolic genes were identified, and the LDHB levels were upregulated, whereas the LDHA levels remained unchanged in colorectal cancer12. Furthermore, LDHB is a key contributor to lysosomal activity and autophagy in cancer13. Because various cancer cells upregulate autophagy, which is required to support metabolism, tumourigenesis, and resistance to therapy14, inhibition of LDHB could be an excellent target for the prevention and treatment of several cancers. Moreover, LDHB is differentially expressed in triple-negative breast cancers, defined by the absence of detectable estrogen receptor and progesterone receptor expression and the lack of human epidermal growth factor 2 gene amplification11. LDHB knockdown selectively reduces the proliferation of breast cancer cells, both in vitro and in vivo11. Triple-negative breast cancer cells exhibit enhanced glycolysis and utilise pyruvate or lactate as an energy source11. Therefore, we hypothesised that the inhibition of LDHB may be a promising therapeutic approach for targeting cancer metabolism.LDHB (LDH1) is associated with aggressive cancer phenotypes+ by LDHB using the RapidFire-Mass (RF-MS) system. This assay system was robust and avoided false-positive results. We then identified that AXKO-0046, an indole derivative, selectively inhibited LDHB activity in an uncompetitive manner with respect to NADH and pyruvate. Moreover, structural analysis showed that AXKO-0046 did not bind in the catalytic site of the enzyme but significantly bound to LDHB in the novel allosteric site of the tetramer. The allosteric site was unique to LDHB based on sequence alignment, resulting in LDHB-selective inhibition. Overall, our findings suggest that AXKO-0046 may be a promising chemical probe to elucidate the role of LDHB-associated pathways in cancer metabolism.Despite the suggested association between LDHB and cancer metabolism, LDHB-selective inhibitors remain unexplored. In this study, to identify selective LDHB inhibitors, we developed a screening system to monitor the conversion of NADH to NAD+ by RF-MS . The extracted ion chromatogram of NADH also showed a NAD+ fragment originating from the in-source decay (ISD) of NADH during ionisation. Because the ISD of NAD+ observed with NADH was less than 10% of the peak area of NADH, there was no contribution to the detection of LDHB activity.To identify small-molecule LDHB inhibitors, we developed an assay system in a 384-well format to measure LDHB activity through NADH and NAD-MS Fig. a. The inm values of NADH and pyruvate were 64 and 116 μM, respectively, in the presence of 500 μM pyruvate and increasing concentrations of NADH or 500 µM NADH and increasing concentrations of pyruvate . The Km values obtained from the two assays were consistent with the reported values for LDHB16. Based on the Km of each substrate and the robustness of the assay signal, NADH and pyruvate concentrations were both set at 75 μM for screening.Next, we optimised the assay conditions of RF-MS. Titration of human LDHB was examined at concentrations ranging from 0.0625 to 1 nM. Supplementary Fig. 2 shows a linear relationship between the velocity and enzyme concentration (0.0625–0.5 nM). We used 0.25 nM LDHB throughout assay development and screening to ensure enzyme activation. Next, the concentrations of NADH and pyruvate were optimised. The KThe screening campaign was performed on an in-house pooled diverse library of more than 345,000 compounds at a concentration of 10 μM, as shown in the workflow , corresponding to a hit rate of 0.006%. Subsequent dose–response experiments determined the EC50 values for all identified hit compounds.To identify the hit compounds in pooled samples, deconvolution assays were conducted at a compound concentration of 30 μM. Compounds containing oxalate salt, which had inhibitory activities toward LDH, were excluded as undesirable inhibitors because oxalate and its derivatives show only moderate potency and selectivity50 values, the substrate concentration was fixed to each Km determined using our assay conditions for each substrate pair. For LDHA, time-dependent accumulation of NADH was confirmed in a protein concentration-dependent manner . The Km value was also determined for the LDHA reaction. All EC50 values are listed in Supplementary Table 1.To compare the selectivity potency of the 22 selected compounds, we evaluated the compounds against human LDHB and LDHA by RF-MS. To obtain comparable EC50) between LDHB and LDHA. Although AXKO-010 was a partial inhibitor at the highest compound concentration, this was not due to compound concentration effects, such as aggregation, instability, and assay interference. Moreover, this compound exhibited LDHB inhibitory activity, with an EC50 of less than or equal to 3 μM, but no inhibitory activity against LDHA at 300 μM, thus showing greater than 100-fold selectivity over LDHA (Supplementary Table 1).Four compounds  exhibited significant differences in potency (EC50 = 42 nM) with selectivity over LDHA  ethyl]-1H-indol-2-yl} methyl) cycloheptanamine and achieved highly potent LDHB inhibitory activity .19. The structure and inhibitory activity of each compound are listed in Fig. To assess the structure–activity relationships (SARs) of AXKO-0046, its derivatives were synthesised, and their inhibitory activities were evaluated. Methyl scanning is a well-known systematic approach to determine interaction sites between small molecules and macromolecular targets, thus providing opportunities for structural modifications to improve potency50 = 0.25 µM), whereas the addition of the methyl group at the cycloheptylamino group (AXKO-0077) resulted in a considerable loss of activity (EC50 = 7.4 µM). The incorporation of two methyl groups into both amino groups (AXKO-0058) simultaneously reduced activity (EC50 = 8.3 µM). Finally, methylation at the 1-position of indole (AXKO-0067) led to a significant loss of potency (EC50 > 100 µM).AXKO-0046 contains three hydrogen bond donors, that is, the NH group of indole, benzylamine, and cycloheptylamine, which can interact with the counter amino acid residues of LDHB. The introduction of a methyl group to the benzylamino group (AXKO-0060) resulted in a moderate loss of inhibitory activity (EC20. There were two tetramers for the binary complex and one tetramer for the quaternary complex in the asymmetric unit. The average root-mean-square deviation (RMSD) values between the monomers in the asymmetric unit were 0.5 and 0.3 Å for two tetramers of the binary complex and one tetramer of the quaternary complex, respectively. Electron density was visible for NADH and oxamate at the cofactor- and substrate-binding sites, respectively, whereas relatively weak but distinct electron density was visible for AXKO-0046 at the interface between the two monomers . These results indicated that the compound had alternative conformations on the two-fold axis of the tetramer with relatively low occupancies.To investigate the binding site, we solved the two crystal structures of LDHB, that is, the binary complex with the cofactor NADH and the quaternary complex with NADH using the substrate analogue oxamate and the inhibitor AXKO-0046 at 1.80 and 1.55 Å resolution, respectively , which was in a closed conformation. In contrast, in the binary complex, the active-site loops were partially disordered with an open conformation for the two tetramers in the asymmetric units, except for two of eight monomers in which the loop was well ordered owing to crystal packing . The superimposition of our two structures clearly indicated structural changes corresponding to AXKO-0046 inhibition. Significant structural differences were observed around the active-site loop, with a maximum RMSD of approximately 7 Å for the main-chain atoms. Other marked structural deviations, except for the active site, were observed in the two helices near the active site (residues Trp228–Lys246 and residues Asp311–Asp330), with a maximum RMSD of approximately 2 Å for backbone atoms . These structural variations are further described in the Discussion to elucidate the inhibitory mechanism of AXKO-0046.The binding conformation of NADH with the enzyme was essentially identical between the binary complex and the quaternary complex, and their binding interactions were consistent with those of published structuresAXKO-0046 was located in an interfacial allosteric site between two monomers, approximately more than 20 Å away from the active site Fig. b. Althou23. Furthermore, high-throughput screening for the identification of LDHB-specific inhibitors has not yet been reported.Several metabolic enzymes play major roles in cancer survival; however, they are not extensively exploited as drug targets. Therefore, in this study, we utilised LDHB as a drug target and developed an assay for high-throughput compound screening to identify LDHB inhibitors. To the best of our knowledge, LDHB-specific inhibitors have not been reported owing to the high structural homology between LDHB and LDHA and the high structural homology of their catalytic sites 25, where LDHB is a key molecule of the oxidative pathway of lactate that controls metabolic symbiosis between glycolytic and oxidative cancer cells27. In oxidative cancer cells, lactate is imported by MCT1, located in the cell plasma membrane, and LDHB oxidizes lactate to pyruvate to produce energy. Comparatively, glycolytic cancer cells generate lactate from pyruvate via the LDHA reaction. LDHB is needed to sustain glycolytic cancer cell survival. In other words, targeting lactate in oxidative cancer cells could offer a unique opportunity to induce necrosis of distant glycolytic cancer cells known to be resistant to conventional antitumor treatments26. Therapeutic strategies to induce necrosis in glycolytic cancer via the inhibition of lactate transport are currently being applied in early clinical trials for cancer treatments using the MCT-1-selective inhibitor AZD396528. AZD3965 is in the early phase clinical trials  with phase I expansion cohort enrichment for Burkitt lymphoma and diffuse large B cell lymphoma cases. Moreover, studies have indicated that complete hereditary deficiency of LDHB has no symptomatic consequences in humans30. On the contrary, patients with hereditary LDHA deficiency have been reported to present with exertional myopathy, erythematosquamous skin lesions, and uterine stiffness during pregnancy32. Therefore, these results indicate the possibility of the future clinical development of pharmacological inhibitors of LDHB with high efficacy and safety.The metabolic model of lactate shuttling in the tumour microenvironment is known as metabolic symbiosis in tumours33. However, this procedure can give rise to false positives and negatives because of fluorescence interference at the excitation and emission wavelengths of NADH. Although other methods, such as measuring NADH through the conversion of resazurin to resorufin by diaphorase using enzyme-coupled detection methods9, have also been suggested, inhibition of the coupling enzymes by test compounds may affect the assay and lead to false positives in HTS campaigns.To date, in vitro LDH assays have been used to measure the fluorescence of NADH, with a characteristic excitation maximum at 340 nm and an emission maximum at 480 nm34. However, this approach was only used for secondary assays to confirm the selected compounds from initial screening employing fluorescence assay. In this study, instead of measuring the conversion of pyruvate to lactate, we established a robust RF-MS assay system to monitor that from NADH to NAD+ using LDH activities. This method may be useful not only for LDH but also for other dehydrogenases utilizing NADH or NAD+. Additionally, this approach allowed us to conduct HTS campaign using a large compound library. The assay showed excellent performance, with an average Z’ factor greater than or equal to 0.65 when more than 345,000 compounds were screened.Therefore, the Genentech group developed a label-free assay to monitor the conversion of pyruvate to lactate by LDHA using RF-MS34. LDHA is considered a highly intractable target against small molecules18. However, we found 22 substantially potent LDHB inhibitors, of which only four compounds  showed high selectivity for LDHB after retesting at five concentrations. Among these hit compounds, AXKO-0010, which contained a central indole scaffold, showed excellent potency and selectivity as a LDHB inhibitor. However, this compound did not completely inhibit enzyme activity, even after an increase in the concentration. Therefore, we next assessed the inhibitory effects of a subfamily of structurally related compounds to AXKO-0010. We found that 63 of 75 related compounds showed highly potent LDHB inhibitory activities while maintaining selectivity. Of these, AXKO-0046 showed the greatest potency for LDHB inhibition (EC50 = 42 nM).The hit rate in the screening campaign was very low (0.006% with 30% inhibition threshold). This low hit rate corresponded to the data when screened against LDHA using a small compound library37.Next, the mechanism of LDHB inhibition of AXKO-0046 was evaluated using substrate-competition assays. AXKO-0046 was tested at five different NADH and pyruvate concentrations. Unexpectedly, increasing the concentration of pyruvate and NADH correlated with increased AXKO-0046 inhibitory activity, suggesting an uncompetitive inhibitory mechanism with respect to both NADH and pyruvate. These findings indicated that this compound likely bound to the enzyme–substrate complex. Several other selective LDHA inhibitors, such as galloflavin, oxamate, diacid-malonate scaffolds, and quinoline 3-sulphonamides, have been described; however, these compounds are substrate-competitive inhibitors owing to the interaction with the catalytic site38. LDHA likely binds to NADH in cells. Thus, a competitive inhibitor of NADH may yield poor cellular activity37. Because AXKO-0046 is uncompetitive with respect to both NADH and pyruvate, we hypothesise that increased intracellular NADH and pyruvate concentrations may increase enzyme inhibition, unlike competitive behaviour. Structural studies provide further insights into the binding site of AXKO-0046 and the interaction residues of the LDHB protein for compound design to inhibit LDHB activity.Notably, the NADH concentration in cancer cells is generally elevated and has been reported to range from 168 to 870 μMThe crystal structure of the quaternary complex of LDHB with NADH, oxamate, and AXKO-0046 revealed that AXKO-0046 was an allosteric inhibitor distant from the catalytic site. The binding mode of AXKO-0046 spatially correlated with SAR studies to rationalise critical functional groups. The indole ring occupied a shallow pocket between the dimer interface, and its NH group formed a hydrogen bond with the main chain oxygen of Ser203. The reduced LDHB inhibitory activity of the N-Me derivative (AXKO-0067) was attributed to the disappearance of the interaction. In addition, two amino groups of AXKO-0046 could form hydrogen bonds with Glu214 at the symmetry-related location of the tetramer. The methylated derivatives of AXKO-0046  also showed reduced LDHB inhibitory activity, which may be related to the attenuation of the interactions. The glutamic acid of LDHB (Glu214) was replaced by threonine in LDHA . Near the AXKO-0046 binding site, two lysine residues of LDHB (Lys308 and Lys310) were also substituted by threonine in LDHA. Thus, the selectivity of AXKO-0046 may be attributed to these amino acid differences.39. The FBP-binding site is also located at the dimer interface but is structurally distinct from the binding site of AXKO-0046. Moreover, the regulatory mechanism of bacterial LDHs is not applicable to the inhibitory mechanism of AXKO-0046 against LDHA and LDHB. Based on the crystal structures, the allosteric transition by the activator within two subunits is not required for the LDHB activity. Machilin A (MA) has been reported to bind to LDHA in an interfacial allosteric site close to the FBP binding site40. However, its binding conformation of MA remains controversial because steric clashes of the protein–ligand interactions have been observed. Recently, selective allosteric inhibitors of the human LDHA isoenzyme with submicromolar activity in vitro41. Two compounds with selectivity against LDHA are bound to a novel binding site adjacent to the active site. Overall, we concluded that the binding site of AXKO-0046 was a unique allosteric binding site of a selective LDHB inhibitor.There are two binding sites in the tetramer that are located at the interface of two dimers. In bacterial LDH enzymes, the allosteric site of the activator, fructose 1,6-bisphosphate (FBP), is involved in the regulation of enzymatic activityA structural comparison between our quaternary and binary complexes revealed that the active-site loop, referred to as the substrate-specificity loop, exhibited closed and open conformations during the binding and release of substrates, respectively . The active-site loop of the closed conformation interacted with the C-terminal helix through hydrophobic interactions among Leu108, Thr323, Leu324, and Ile327. The substantial conformational changes in the active-site loop, accompanied by the conformational shift in the C-terminal helix, were associated with the binding site of AXKO-0046 . DTT, NaCl, and Triton X-100 were obtained from Sigma-Aldrich . Dihexylammonium acetate (DHAA) was obtained from Tokyo Kasei Kogyo . NADH, pyruvate, bovine serum albumin (BSA), and other reagents were purchased from Fujifilm Wako .Recombinant human LDHA and LDHB were purchased from R&D Systems . NADAXKO-0046 was synthesised by Takeda Pharmaceutical Co., Ltd. ; AXKO-0058, AXKO-0060, AXKO-0067, and AXKO-0077 were synthesised by Axcelead Drug Discovery Partners, Inc. .g for 1 min) and incubated at room temperature for 30 min, and 5 μL of NADH and pyruvate were added to the assay buffer . After incubation for 30 min at room temperature, acetonitrile (10 μL) and water (50 μL) were added to quench the reaction. All additions were performed using a Multidrop Combi . Assay plates were sealed and centrifuged (2700× g for 10 min) before storage at − 20 °C.We screened for compounds  within pooled libraries consisting of more than 345,000 compounds. Each compound in DMSO (1 mM) was dispensed into 384-well V base plates (100 nL/well) using an Echo 555 acoustic dispenser . LDHB (5 μL) was diluted in assay buffer  and dispensed into assay plates . The plates were centrifuged .The conditions for LDHA assays were as described above, except for substrate concentrations, that is, 400 µM pyruvate and 100 µM NADH. These concentrations were chosen based on fitting to the Michaelis–Menten model with the K+ were detected by multiple reaction monitoring with QI/Q3 transitions at m/z 664.2 to 397.0 and m/z 662.1 to 540.1, respectively, on a Sciex API4000 triple quadrupole mass spectrometer  in the negative electrospray ionization mode. The extracted ion chromatograms for each transition were integrated and processed using RapidFire Integrator (Agilent). The data for each well were normalised using the monitoring product conversion with the ratio of AUCproduct / (AUCproduct + AUCsubstrate).For RF-MS , the enzyme reaction solution (5 μL) was aspirated directly from the quenched assay plates and loaded onto a C8 solid-phase extraction cartridge (Agilent) with a mobile phase of water containing DHAA (5 mM) for 2500 ms at a flow rate of 1.25 mL/min. The analytes were then co-eluted into the mass spectrometer using water:acetonitrile:acetone (2:1:1) containing ammonium acetate (5 mM) for 5000 ms at a flow rate of 1.0 ml/min. NADH and NADTo determine the compound activities, percent inhibition data normalised to 0% (DMSO only) and 100% inhibition (no-enzyme control) wells were calculated. Data analysis was performed using the Tibco Spotfire  packages.m and Vmax values using GraphPad Prism. Lineweaver–Burk plots were generated by superimposing the data of 1/[velocity] and 1/[substrate] and the line corresponding to the Michaelis–Menten nonlinear fit.To evaluate the mechanism of inhibition of the selected compounds, their initial reaction velocities were measured using five concentrations of NADH or pyruvate  incubated with 100 μM pyruvate for NADH titration or 100 μM NADH for pyruvate titration. A solution of AXKO-0046  with 0.25 nM LDHB was then added. The enzymatic reactions were performed at room temperature for 15 min in triplicate. At each inhibitor concentration, the dependence of the initial reaction velocity on the substrate concentration was fitted to a nonlinear Michaelis–Menten model to obtain the KLDHB  DNA was synthesised and ligated into a pET21a vector  with an N-terminal His-Avi tag followed by a TEV protease cleavage site using VectorBuilder . The expression plasmid was transfected into Escherichia coli BL21 (DE3) , and the cells were grown in lysogeny broth medium containing ampicillin (100 mg/mL). Protein expression was induced with isopropyl β-d-1-thiogalactopyranoside (0.2 mM) following culture for 16 h at 16 °C. The harvested cells were lysed by sonication in lysis buffer  containing NaCl (150 mM) nuclease (5 U/mL) and centrifuged at 15,000× g for 10 min at 4 °C. The clarified supernatant was loaded onto an Ni–NTA cartridge , and the eluted fraction was purified on a HiLoad 26/60 Superdex 200 pg column . The His-Avi tag was digested using TEV protease (Sigma-Aldrich), and the digested solution was subsequently passed through an Ni–NTA column to remove TEV protease and the uncleaved protein.Human The protein was further purified by anion-exchange chromatography  with a linear gradient of NaCl. The products of all purification steps were assessed by sodium dodecyl sulfate polyacrylamide gel electrophoresis and Coomassie Blue staining (Sigma-Aldrich). The final yield of protein was 46 mg for every 1 L of culture. For crystallisation, the purified protein was buffer-exchanged to the final buffer (50 mM Tris [pH 7.6] with 150 mM NaCl), concentrated (20 mg/mL) by ultrafiltration , and stored at − 80 °C.42.The complexes of LDHB with NADH or NADH, oxamate, and AXKO-0046 were generated by incubating threefold molar excesses of ligands on ice for 2–3 h before crystallisation experiments. Both complexes were crystallised from a reservoir solution containing HEPES (0.1 M [pH 7.5]), potassium formate or ammonium acetate (0.2 M), and PEG 3350 (20% v/v) at 20 °C via the sitting-drop vapour diffusion method. Prior to data collection, crystals were immersed in the reservoir solution containing ethylene glycol (30%) as a cryoprotectant and flash-frozen in liquid nitrogen. Diffraction data were collected from a single crystal using a DECTRIS Pilatus3-S6M PAD detector  with a BL45XU beamline  under a 100-K nitrogen cryostream. The diffraction data were reduced and scaled using HKL200043 in the CCP4 software suite44 and the LDHB structure (PDB code 1I0Z18) as a search model. Refinement was performed using REFMAC545 with individual isotropic restrained B factors. Some data (5%) were set aside for crossvalidation before refinement, and progress was monitored using Rfree. For TLS refinement, the tetramer of the protein and ligands was set as a single rigid body46. Interactive model building was performed using COOT47. The final models were validated using Molprobity48. All graphical figures were generated using PyMOL . Crystallographic processing and refinement statistics are summarised in Supplementary Table The structure was solved following the molecular replacement method using Phaserm and Vmax values, the initial rates were fit to the Michaelis–Menten equation. EC50 and Hill slope calculation and curve fitting using four-parameter fits were performed using GraphPad Prism v6.07  or XLfit  with nonlinear regression analysis, wherein the EC50 value equaled the concentration at which the inflection point of the fitted model was reached. The quality and robustness of the screening campaign process were determined by analysing the Z’ factor.For the kinetic parameters, the initial rates of LDH activity were determined by incubating LDHA or LDHB with various concentrations of NADH and pyruvate in the assay buffer at room temperature. The reaction product was measured by RF-MS. To estimate the KSupplementary Information.


Intracortical microelectrodes are neuroprosthetic devices used in brain-machine interfaces to both record and stimulate neural activity in the brain. These technologies have been improved by advances in microfabrication, which have led to the creation of subcellular and high-density microelectrodes. The greater number of independent stimulation channels in these devices allows for improved neuromodulation selectivity, compared to single-site microelectrodes. Elements of electrode design such as electrode-site placement can influence the long-term performance of neuroprostheses. Previous studies have shown that electrode-sites placed on the edge of a planar microelectrode have greater chronic recording functionality than sites placed in the center. However, the effect of electrode-site placement on long-term intracortical microstimulation (ICMS) is still unknown. Here, we show that, in rats chronically implanted with custom-made planar silicon microelectrodes, electrode-sites on the tip of the device outperformed those on both the edge and center in terms of the effect per charge delivered, though there is still a slight advantage to using edge sites over center sites for ICMS. Longitudinal analysis of ICMS detection thresholds over a 16-week period revealed that while all sites followed a similar trend over time, the tip and edge sites consistently elicited the behavioral response with less charge compared to center sites. Furthermore, we quantified channel activity over time and found that edge sites remained more active than center sites over time, though the rate of decay of active sites for center and edge sites was comparable. Our results demonstrate that electrode-site placement plays an important role in the long-term stability of intracortical microstimulation and could be a potential factor to consider in the design of future intracortical electrodes. Bidirectional brain-machine interfaces (BMIs) have the potential to restore function in patients with neurological disabilities by recording and stimulating selected neurons . While rMuch work has been done to investigate methods to mitigate the FBR to improve performance by changing the device shape and size , site geHere, we investigated the role of electrode-site placement by implanting a single-shank silicon microelectrode array with sites on the edge, center, and tip. ICMS detection thresholds and voltage transients were measured for 16 weeks post implantation (WPI). This data was used to determine chronic microstimulation performance and number of active sites for edge, center, and tip sites over time. We found that edge sites generally performed more efficiently than corresponding center sites at the same depth, eliciting the desired response with less charge especially in the long term. Furthermore, we observed an upward trend in performance with increasing cortical depth. These results suggest that electrode-site placement is a factor of electrode design that can be targeted to improve longitudinal microstimulation performance.Custom-made planar silicon microelectrode arrays were chronically implanted in the primary somatosensory cortex of six adult Sprague-Dawley rats . The micF = 3.19, p = 0.0416, ANCOVA]. While the tip site consistently had the lowest thresholds of the three groups, edge site thresholds seemed to remain the most stable throughout the entire period. The difference in thresholds between the three groups at 14 and 16 weeks post-implantation was statistically significant  = 17.0, p = 1.32 × 10–5, one-way ANOVA; week 16: F = 3.76, p = 0.0361, one-way ANOVA), with center channels requiring more charge to elicit the behavioral response than both edge and tip channels.The primary objective of this study was to determine what, if any, effect electrode-site placement has on ICMS performance. We first analyzed how electrode-site placement affects long-term ICMS stability. It is important to note, however, that cortical depth plays a role in ICMS performance, as shown in previous studies . TherefoTo further evaluate how electrode-site placement affects microstimulation performance, we assessed the number of active channels, defined as the site’s ability to elicit a response with charge below 30 nC/Phase during an experimental session . p = 0.043, unpaired t-test with Dunn-Bonferroni correction; month 4; center vs. tip: p = 0.019, edge vs. tip: p = 0.021, unpaired t-test with Dunn-Bonferroni correction). Additionally, the number of active channels for all sites decreased gradually after the second month, which further demonstrates the decline in performance seen in , we compared the slopes from the point of max channel activity (week 6) until the end of the study. This analysis showed that center sites decreased at a rate of −0.318 active channels/week while edge sites decreased at −0.296 active channels/week (linear regression slope from week 6 to week 16). The difference between the slopes for the active sites over time for center and edge was not statistically significant . These analyses suggest that unlike detection thresholds . resholds , the ratp > 0.05, one-way ANOVA).To investigate how electrode-site placement affects long-term electrode stability for ICMS, voltage transients were measured to determine the maximum polarization at the electrode-electrolyte interface. Voltage transients were measured from each electrode in response to a symmetric biphasic pulse in awake rats prior to stimulation sessions. While microstimulation has the potential to treat many neurological disorders, a major limitation of this technology is the poor chronic performance of intracortical microelectrodes . In thisConsistent with previous work investigating the role of electrode-site placement on recordings, we found that in most cases edge sites perform with greater efficacy than center sites for microstimulation, especially for long-term use. For instance, using the same microelectrode design, The decrease in performance over time could be a result of the FBR, known to cause the formation of a glial encapsulation of the device, leading to a decay in recording capabilities . Though Despite differences in microstimulation capabilities observed between center and edge channels, electrochemical characterizations of the sites revealed nearly identical peak voltages from measurements of voltage transients over time. Similarly, Interestingly, we also observed that deeper channels had lower detection thresholds than superficial channels, which is consistent with previous findings stating that deeper cortical layers are more sensitive to microstimulation . We obseAlthough determining the effects of electrode-site placement on intracortical microstimulation is an important step in designing more effective neuroprostheses, more work must be done to address the limitations of the present study. Using a single electrode design across all animals, we found that edge sites carry a slight advantage over center sites in terms of long-term performance, so future studies could investigate how shanks of different widths affect center and edge site longitudinal microstimulation abilities. Decreasing the width of the shank would effectively move center sites closer to the edge, potentially reducing the differences we observed between the two. The results presented here will lead to the design of intracortical microelectrodes that are more viable for chronic use, with implications for bidirectional brain-machine interfaces that are able to both record and stimulate critical neuron populations. Our results show that placing electrode-sites on the edge of microelectrode arrays could potentially prolong the active lifespan of these devices and provides further support that the shape and architecture of a device affects the foreign body response, which has been observed in several instances . Further2 and the tip site had an area of 946 μm2. Each 16-channel device was approximately 2.2 mm long and 15 μm thick with a width of 249 μm. The electrodes had an insulation material of silicon dioxide. A flexible polyimide cable was used to connect the shank to a ZIF connector.Six custom-made planar silicon microelectrode arrays  with seven iridium oxide electrode-sites in the center, eight on the edge, and one on the tip of the device were used in this study and previously by 2 cranial window over the primary somatosensory cortex  following a midline skin incision and periosteum removal. Four titanium bone screws  used for electrical grounding and headcap anchoring were placed by drilling burr holes. Following a durotomy, the microelectrode device was inserted 1600 μm at 100 mm/s using an automated micro-insertion system . Using a surgical microscope, the implantation depth was verified by confirming complete insertion of the most superficial electrode. Silicon elastomer  was inserted into the craniotomy site, and headstage connectors were secured with layers of UV cured dental composite .All surgeries and experiments were performed in accordance with the University of Florida’s Institutional Animal Care and Use Committee (IACUC). Surgeries were performed using aseptic techniques, and devices were sterilized with ethylene oxide and rinsed with sterile saline prior to implantation. Six adult male Sprague-Dawley rats  were anesthetized with 5% isoflurane  in oxygen at 1.5–2 L/min. Meloxicam  was administered subcutaneously and then the isoflurane was reduced to 1.5–3% for the duration of the procedure. A microdrill was used to prepare a 1 mmIntracortical microstimulation detection was evaluated using a conditioned avoidance behavioral paradigm . The aniExperimental sessions began 5 days after surgery to allow for sufficient recovery and data was collected 5 times per week for 16 weeks post-implantation (WPI). During each session, ICMS detection thresholds were obtained from randomly selected channels until the animal was satiated. Microstimulation was administered using an IZ-32 stimulator with an LZ48-200 battery  to a single electrode-site on the device, with stimulus upper and lower bounds set manually. Cathode-leading charge-balanced symmetric waveforms with a phase duration of 0.2 ms, phase delay of 0.04 ms, and frequency of 320 Hz were used for all microstimulation experiments. The stimulus amplitude (μA) of detection thresholds were multiplied by the phase duration (ms) to report values in charge per phase (nC). The total charge delivered was limited to a maximum of 30 nC/phase (150 μA) for all experiments.Voltage transients were measured from each electrode-site prior to microstimulation at least once per week for 16 WPI. Symmetric biphasic pulses at 50 Hz with a 50 μs phase duration and amplitude of 5 μA were applied. Current-controlled stimulation was delivered using an IZ-32 stimulator with an LZ48-200 battery  to each electrode-site on the device. Data was acquired using the RZ5D Bioamp processor .∗p ≤ 0.05, ∗∗p ≤ 0.01, ∗∗∗p ≤ 0.001, ****p ≤ 0.0001. After verification of normality and homogeneity of variances, parametric tests were performed. In particular, analysis of variance in threshold charge between site placement groups was assessed using a one-way ANOVA. With time as a covariate, differences in threshold charge across the site placement groups were also analyzed with an ANCOVA. Pairwise comparisons for electrode-site activity were performed using a t-test with Bonferroni-Dunn correction. A linear regression was used to determine the slopes for the change in number of active sites over time for center and edge sites, and they were compared using a t-test. Statistical analyses were executed in R Statistical Software Version 4.0.1 .For statistical reporting, the following significance levels were used: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by University of Florida Institutional Animal Care and Use Committee (IACUC).KO sourced the funding. RS, MU, and KO conceived and designed the study and reviewed and edited the manuscript. MU performed the surgical implantations. RS and MU collected and analyzed the microstimulation data. RS wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Repeating earthquakes are a global phenomenon of tectonic faults. Multiple ruptures on the same fault asperities lead to nearly identical waveforms characteristic for these seismic events. We identify their microseismic counterparts beneath an Alpine glacier, where basal sliding accounts for a significant amount of ice flow. In contrast to tectonic faults, Alpine glacier beds are subject to large variations in sliding velocity and effective normal stresses. This leads to inter- and sub-seasonal variations in released seismic moment from stick–slip asperities, which we explain with the rate-and-state friction formalism. During summer, numerically modelled effective normal stresses at asperities are three times higher than in winter, which increases the local shear resistance by the same factor. Stronger summer asperities therefore tend to form in bed regions well connected to the efficient subglacial drainage system. Moreover, asperities organise themselves into a state of subcriticality, transferring stresses between each other. We argue that this seismic stick–slip behavior has potentially far-reaching consequences for glacier sliding and in particular for catastrophic failure of unstable ice masses. These basal processes regulate stagnation or acceleration of polar ice streams3, are responsible for seasonal speed up of tidewater outlet glaciers4, initialize local instabilities and enable their propagation as surges along the entire glacier bed5. This may cause catastrophic failure of basal resistance resulting in break-off events6 or runaway surges during which entire glacier tongues detach from their beds7.Processes controlling glacier and ice stream dynamics occur at or close to the ice-bed interface8. On soft beds, till deformation and true basal sliding of the ice over the till surface takes place10. Though initially ignored in sliding investigations, dynamically changing friction at the bed may also play a critical role in basal sliding: Sudden sliding events of Antarctic ice streams suggest a frictional resistance, which evolves over sub hourly time scales11. Laboratory experiments confirm that under certain conditions, rate-weakening friction at the ice stream bed can explain sliding instabilities and thus the episodic ice stream acceleration13. Moreover, sliding episodes seem to be the sum of countless microseismic stick–slip events, which themselves are a manifestation of rate-weakening friction14.In conventional glacier sliding theories, normal traction at perfectly lubricated bed obstacles controls basal sliding by enhanced viscous creep and melt-refreeze cycles17 as well as slowly moving parts of the Greenland ice sheet and Alpine glaciers20. Microseismic stick–slip events tend to cluster at distinct bed locations producing nearly identical seismic waveforms and repeated ruptures may coalesce into sustained tremor-like signals21. The clustering behavior can be explained with rate-weakening friction asperities embedded within an otherwise smoothly sliding, rate-strengthening ice-bed interface, a concept, which has been extensively studied in the context of tectonic faults22.In recent years, microseismic stick–slip events have been observed at fast ice streams24. In this regard, the configuration of the subglacial drainage system is of primary importance, as it can consist of efficient channels operating under low pressures or of networks of smaller, inefficient and pressurized drainage pathways25. Depending on water availability, subglacial pressures and drainage channels evolve over seasonal or sub seasonal time scales: water-filled cavities, which are part of the inefficient drainage system, open during periods of high subglacial water pressure and stay open throughout the melt season reducing the contact forces between ice and bed thus enhancing sliding26. In contrast, efficient drainage channels characteristic for the melt season are more dynamic and react to diurnal variations in meltwater supply from the surface27. The spatially and temporarily varying hydraulic regimes have to be accounted for in realistic theories of basal sliding. Although microseismic stick–slip events seem to react to meltwater input20, a systematic analysis of stick–slip activity is still needed to clarify if dynamic friction satisfies the hydraulic constraints on basal sliding.The underlying theoretical principles are still debated but have to include a dependence on subglacial water pressures supported by decades of observationsIn this study, we investigate the interplay between frictional glacier sliding and varying sub-glacial conditions beneath an Alpine glacier. Stick–slip asperities react to seasonal changes in glacial melt water supply and organize themselves into a sub-critical state in which they react to each other’s activity over hundreds of meters. Elucidating how stresses and sliding velocity at the glacier bed change on inter- and sub-seasonal time scales, we show that rate-and-state friction developed for tectonic earthquake cycles is a viable theoretical framework to describe basal sliding.28. As shown below, seasonal and diurnal variations in surface velocity indicate a significant contribution of basal sliding to ice flow. During a winter measurement period  and a summer period , we deployed seismometer arrays consisting of seven and nine seismometers, respectively, forming 300–500 m large apertures  at an elevation of ~ 2500 m above sea level, where the glacier is ~ 200 m thick and at the pressure melting point  with shear faulting source mechanisms indicated by mixed P-wave polarities throughout the arrays. We detect the stick–slip signals with a spectral discriminator, apply hierarchical clustering to identify events with identical waveforms and perform a template match search on the continuous data . In contrast, rate-strengthening friction tends to stabilize sliding via increased frictional drag and therefore arrests transient increases in sliding velocity.On frictional faults, sliding and cycles of quiescence and seismic activity are described by rate-and-state laws relating the coefficient of friction a, b are material parameters of the interface and rate-weakening holds when L is often interpreted as a memory distance over which the population of small-scale contacts between the two fault sides changes39. 37:Rate-and-state friction is commonly described by the logarithmic lawWe use  in combi26. The parameters L, a, b are difficult to constrain, but laboratory measurements have established conditions resulting in rate-weakening beds for ice at the pressure melting point and specific interface conditions40.Sliding velocities vary in response to these pressure variationsL, a and b are found in characteristic material behavior. For ice-bed contacts, healing may be related to pressure-enhanced melting at contacts between ice and small-scale bed bumps41. Regelation and viscous ice flow near the ice-bed interface are candidates for rate-strengthening mechanisms8, whereas sediment entrainment at the ice sole can lead to rate-weakening42.The rate-and-state formalism describes friction as velocity dependent and allows interface strengthening  between events. This means that simple failure thresholds for sliding velocity or shear stress do not exist, but that stick–slip initiation depends nonlinearly on various parameters, including the time elapsed since the previous event. Rate-and-state friction is a semi-empirical formulation, which holds for different materials in laboratory and natural faults. Physical interpretation for rate-strengthening and weakening parametrized by L, a, and b constant within these pairs  between pairs of summer and winter simulations while keeping 44 with data variance given by our spread in moment and recurrence time measurements and priors listed in the Supplementary Table We apply Bayes’ theorementclass1pt{minimaentclass1pt{minima27 and nearby asperities which highlights the hydraulic control on frictional resistance to ice flow.An increase in basal loading velocity for the summer season agrees with surface velocity measurements Fig. b. No sim45. Measured surface velocity variations result from sliding variations and mirror released seismic moment rate: Within one or two days, moment rate maxima and minima respectively coincide with minima and maxima in surface velocity  postholes in the ablation zone of Rhonegletscher (station RA51-53 of network 4D). The postholes had to be re-drilled several times during the deployment due to a surface melt of more than 10 m. We deployed these seismometers together with Nanometrics Taurus and Centaur digitizers sampling sensor output voltage at 500 Hz.3 digitizers sampling at 400 Hz. During the summer measurement period , we extended the existing three-seismometer array with six additional Lennartz 3D/BHs sensors, each connected to a Nanometrics Centaur digitizer sampling at 500 Hz. Locations and specifications of all passive seismic stations are in the Supplementary Table During the winter measurement period analyzed here , we extended the triangular array with four HL-6B 3-D geophones. We record their measurements with DIGOS DATA-CUBECo-located with the three multiannual Lennartz 3D/BHs stations, we operated three PPM 2022-S13 GNSS sensors sampled at 15 s. Additionally, we installed a reference station on the orographic right moraine of the glacier for differential positioning in the data post-processing.Signal discrimination between basal icequakes (stick–slip and tensile faulting) and surface icequakes mainly caused by crevassing, is based on high frequency content and short duration of the former. Elevated melt-induced seismic background noise in the ablation zone of alpine glaciers limits detectability of relatively weak stick–slip signals. In continuous spectrograms we automatically detect basal icequakes by searching for events with high (> 10 Hz) and broad frequency content. We verify these detections by the existence of distinct P- and S-wave arrivals and assess their frequency content and the relative power within both phases  in the displacement seismogram to determine seismic moments of stick–slip eventsFSH is the radiation pattern of a double couple source for a given focal mechanism59. The factor 2 accounts for the free surface amplification. The distance between hypocenter and recording seismic station is denoted by R. The integral over the ground displacement caused by the SH-wave uSH is taken over the full SH-wave cycle from time t1 to t2. The ground displacement is obtained by integrating the recorded ground velocity seismogram and correcting for the instrument response.Since some of our seismometers were installed in shallow boreholes, in a prior step the horizontal sensor orientation must be determined. This was done by horizontally rotating the seismogram of strong events from each asperity such that the P-wave amplitude is maximized on one horizontal component of the seismogram. From the known location of each station and each stick–slip cluster epicenter, the sensor orientation could be determined by calculating the mean rotation angle of all station-cluster pairs.t1 to t2) for the SH-wave of each cluster and use the alignment of the events in the stack to integrate for each event separately. For each event and station, we determine the seismic moment using Eq.  measurements on the glacier surface sampled at 15 s, velocities were calculated by using a static post processing method resulting in one velocity value per two hours. Outliers are removed by dropping data points of vertical velocity with a standard deviation larger than 3 m/d that result from adjustments of the antenna, and replacing them with linearly interpolated values. We also resample the data to the same resolution as the seismic moment rate and apply a Butterworth bandpass filter with corner frequencies of 3 days and 20 days.During the winter seismometer deployment, GNSS stations were buried by more than two meters of snow and therefore were not operational. This is why we cannot compare the winter stick–slip activity with ice flow velocity. However, winter GPS velocity measurements from November 2018 exist. Since already in November winter conditions are present at the measurement site, we assume that on monthly averages, these velocities are equal to the velocities that were present during the winter seismometer deployment. The distribution of measured velocities in Fig. Supplementary Information.


WDR5 nucleates the assembly of histone-modifying complexes and acts outside this context in a range of chromatin-centric processes. WDR5 is also a prominent target for pharmacological inhibition in cancer. Small-molecule degraders of WDR5 have been described, but most drug discovery efforts center on blocking the WIN site of WDR5, an arginine binding cavity that engages MLL/SET enzymes that deposit histone H3 lysine 4 methylation (H3K4me). Therapeutic application of WIN site inhibitors is complicated by the disparate functions of WDR5, but is generally guided by two assumptions—that WIN site inhibitors disable all functions of WDR5, and that changes in H3K4me drive the transcriptional response of cancer cells to WIN site blockade. Here, we test these assumptions by comparing the impact of WIN site inhibition versus WDR5 degradation on H3K4me and transcriptional processes. We show that WIN site inhibition disables only a specific subset of WDR5 activity, and that H3K4me changes induced by WDR5 depletion do not explain accompanying transcriptional responses. These data recast WIN site inhibitors as selective loss-of-function agents, contradict H3K4me as a relevant mechanism of action for WDR5 inhibitors, and indicate distinct clinical applications of WIN site inhibitors and WDR5 degraders. Its best-known role is scaffolding the MLL/SET complexes that catalyze histone H3 lysine 4 di- and tri-methylation (H3K4Me2/Me3), but WDR5 acts outside this setting to promote ribosomal protein gene transcription2, recruit MYC to chromatin4, and bookmark genes for reactivation after mitosis5. WDR5 is also overexpressed in cancer, and is an auspicious target for pharmacological inhibition in malignancy1. Most drug discovery efforts focus on blocking the “WIN site” of WDR512, an arginine-binding cavity that tethers WDR5 to chromatin and recognizes an arginine-containing “WIN motif” in partner proteins such as the MLL/SET family of histone methyltransferases13, KIF2A14, the kinase PDPK115, and others1. Although in vivo studies are limited by the poor drug-like characteristics of extant WIN site inhibitors, in vitro profiling demonstrates that small molecule WIN site blockers can inhibit cancer cells carrying oncogenic mutations in MLL1, C/EBPα, p53, and MYC12, forecasting that WIN site inhibitors could have widespread utility as anti-cancer agents.WDR5 is a highly-conserved protein that performs a variety of functions in the nucleus16. And WDR5 is no exception. RNAi-mediated knockdown is often used to predict whether WIN site inhibitors will have activity in specific contexts, and changes in H3K4 methylation almost always assumed to drive the molecular mechanism of response22. But knockdown studies conflate blocking the WIN site of WDR5 with loss of the entire protein, and because WDR5 is pan-essential23 cannot explain how WIN site inhibitors show cancer cell-selective inhibition in vitro17. Moreover, linking WIN site inhibition to changes in H3K4me fails to discriminate between H3K4me as a mark of active chromatin versus a mark that promotes transcription24, does not recognize that the WIN site is only required for the catalytic activity of one of five MLL/SET enzymes25, and cannot explain how WIN site inhibitors induce transcriptional changes without altering H3K4me11.Successful application of WIN site inhibitors will require understanding the role of the WIN site in tumor cell processes and knowing precisely how WIN site blockade leads to a cancer cell response. This information is essential to apply WIN site inhibitors as a targeted therapy, to define patient selection criteria, and to predict therapeutic windows and on-target toxicities. In modern drug discovery, this understanding often comes from probing the impact of long-term loss or depletion of the target protein on the cancer cell milieu and from correlative studies that tie phenotypic responses to a canonical molecular function of that target27. We also reasoned that monitoring the impact of WDR5 loss on H3K4me3 and transcriptional patterns would allow us to test the idea that WDR5 regulates transcription via modulation of H3K4 methylation. Here, we report that WIN site inhibitor impacts only a subset of transcriptional events controlled by WDR5, and show that the influence of WDR5 on transcription is not explained via its role in H3K4 methylation. These findings reveal that WDR5 loss cannot be used to model the effects of WIN site inhibitors on cancer cells, show how an essential protein can be partially inhibited to induce a pro-therapeutic response, and support distinct applications of WIN site inhibitors and WDR5 degraders in the clinic.We reasoned that comparison of the impact of WDR5 loss versus WIN site inhibition could resolve whether WIN site inhibitors block some or all of the function of WDR5, and would be timely given that the arsenal of WDR5 inhibitors has recently moved beyond those targeting the WIN site to those that trigger WDR5 degradationc-MYC translocation and expressing mutant p5328. Because both WDR5 loss29 and WIN site inhibition11 elicit a cellular response via induction of p53, we reasoned that the mutant TP53 status of Ramos cells would allow us to monitor transcriptional changes independent of complications from p53 activation. We engineered Ramos cells so that WDR5 could be degraded via an auxin-inducible degron (AID)30 , tagged WDR5 is rapidly depleted from AIDW cells, but not wild-type (WT) Ramos cells —and to attempt to understand the extensive transcriptomic impact of WDR5 depletion—we next asked whether mRNA changes caused by loss of WDR5 correlate with changes in H3K4me3 status.The role of H3K4me3 as activating epigenetic mark is controversial40, peaking immediately downstream of the TSS , different pools of modified histones, or other method-specific considerations. Reductions in H3K4me3 occur throughout the transcription unit  to localize H3K4me3 on chromatin in AIDW cells, before and after WDR5 depletion. In unperturbed cells, we tracked ~ 12,500 sites of H3K4me3 . pUC57, containing a U6 promoter, scaffold, and terminator was synthesized by Genscript and gRNAs for WDR5 (CTTCAGTGTTCGGGGTCGGA and TTATTTACTGACCGCATATC) individually inserted by whole plasmid PCR. The AID-WDR5 targeting vector was made by assembly of six fragments into pBluescript II SK+: (i) [WDR5 Promoter region  as KpnI/XhoI]; (ii) [AID Tag : Ex2-Int2 : loxP: Int2-Ex3  was synthesized by Genscript and inserted as XhoI/HindIII]; (iii) [Puromycin resistance (from pcDNA3.1-Puro) as HindIII/XmaI]; (iv) P2A (synthesized by Genscript) as XmaI/EcoRI]; (v) [Ex2-Int2 : loxP as EcoRI/BamHI]; and (vi) [Int2-Ex3-Int3  as BamHI/XbaI]. pLL4-osTIR1 was made by PCR-amplification of osTIR1-9xMyc from pBabe-osTIR1-9Myc  and used to replace GFP in pLentiLox (gift from Al Reynolds).l-glutamine, 10% FBS, 100 IU/ml Penicillin, and 100 μg/ml streptomycin. Ramos cells expressing CRE–ERT2 were described previously4 and used to construct the AIDW line. AIDW cells were created in a four step process. First, the AID tag was integrated into the endogenous WDR5 gene via CRISPR-mediated homologous recombination by electroporation with 10 μg targeting vector, 15 μg of gRNA vector, and 15 μg of pX330-U6-Chimeric_BB-CBh-hSpCas9. Second, after a 2-day recovery, stable cells were selected with 200 ng/ml puromycin, expanded, treated with 4-OHT to excise the puromycin cassette, and clones obtained by limited dilution. These clones were then expanded and screened by Western blotting to identify clones in which the apparent molecular weight of WDR5 was shifted by the expected amount for the AID tag. At this stage, positive clones we recovered expressed both AID-tagged and untagged WDR5 species. Third, to target the remaining WDR5 allele, steps one and two were repeated with a second unique gRNA. Finally, a clone expressing only AID-tagged WDR5 was transduced to express the OsTIR1 ubiquitin ligase carrying a c-Myc epitope tag. Lentiviral infections of the selected Ramos cell clone with pLL4-osTIR1 were performed as described3; OsTIR1 expression was confirmed by Western blotting with antibodies against the Myc epitope.Ramos cells were obtained from the ATCC (CRL-1596) and cultured in RPMI media supplemented with 12 or 0.1% DMSO (control). To compare the effects of WDR5 degradation with WIN site inhibition on AIDW cell proliferation, AIDW cells were seeded in 96-well plates and treated for up to four days with either 0.1% DMSO, 100 uM IAA, or 500 nM C16. At each timepoint, viable cells were quantified using Promega CellTiter-Glo Reagent. For cell cycle analysis, 106 AIDW cells were collected after no treatment, or treatment with 0.1% DMSO, IAA, or C16, fixed in ice-cold 70% ethanol, and stored at − 20 °C for at least 4 h. Fixed cells were washed with 1× phosphate buffered saline (PBS), resuspended in propidium iodide (PI) staining buffer (1× PBS + 10 μg/ml PI + 100 μg/ml RNAse A + 2 mM MgCl2) and stained overnight at 4 °C. Cell cycle distribution was quantified using a Becton Dickinson LSRFortessa instrument and BD FACSDiva software. At least 10,000 cells were counted using forward and side scatter pulse geometry gating to select single cells for each sample. IC50 determination for C16 in AIDW cells was performed as described11.For WDR5 degradation, cells were treated with 100 μM IAA (Sigma-Aldrich). For WIN site inhibition, cells were treated with 500 nM C1644. Antibodies used were: α-WDR5 #13105, α-H3K4me3 #9751, α-GAPDH–HRP #8884 and #5174, α-p53 #32532, α-Myc #2278 ; α-p53 (Santa Cruz sc-126); α-rabbit Fc Secondary 31463 (ThermoFisher); α-mouse Fc Secondary Antibody and α-rabbit IgG–HRP, Light Chain Specific 211-032-171 (Jackson ImmunoResearch).Whole cell lysates were prepared, separated by SDS-PAGE, and probed by Western blotting as described4 using antibodies against WDR5 (#13105) or a rabbit IgG control . ChIP-qPCR primers used were:SNHG15: (CGCCACTGAACCCAATCC and TCTAGTCATCCACCGCCATC),RPL35: (CTTGTGCAGCAATGGTGAGA and GCCTAGGTGGCAGATAGAATC),RPL5: (CCTGCAGGTCTCTGTCGAG and GGCATACGGGCAAGAAAAG),RPS24: (TTGGCTGTCTGAAGATAGATCG and CGCGTGCCTATAGCTCAAGT),RPTOR: (CCCTTGAGCAGATGAATACT and GACAATTTGCAGGACAGAG),RPL14: (GTCTCCTTTGGACCTCATGC and ATGGCCTGTCTCCTCACTTG).ChIP was performed as described4. Libraries were sequenced on an Illumina NovaSeq 6000 instrument by the VANTAGE Core at Vanderbilt University.ChIP signals were expressed as percent input. For ChIP-Seq, ChIP was performed with an anti-H3K4me3 antibody . ChIP DNA was purified and libraries prepared as described45, and submitted to the VANTAGE Core who performed ribosomal RNA depletion, library preparation, and sequencing on an Illumina NovaSeq 6000. For PRO-Seq, 3 × 107 cells were either untreated or treated with IAA 100 μM IAA for 2 or 4 hours, at which point cells were harvested and PRO-Seq reactions performed as described47. PRO-Seq libraries were submitted for sequencing on an Illumina NovaSeq 6000 with 150 paired-end reads by the VANTAGE Core.For RNA-Seq, cells were either not treated, or treated for 18 h with 0.1% DMSO, 100 μM IAA, or 500 nM C16, for 18 h. They were then collected in Trizol (Invitrogen), RNA purifiedChIP-Seq ChIP-Seq reads were aligned to the human genome hg19 using Bowtie248. Peaks in each sample were called using MACS2 with q-value of 1e−549. Peaks were annotated using Homer (http://homer.ucsd.edu/homer/) to assign target genes. Consensus peaks in each condition were identified using DiffBind50. Differential analyses were performed by DESeq251. False Discovery Rate (FDR) < 0.05 was used to identify significantly changed peaks. (2) RNA-Seq After trimming by Cutadapt52, RNA-Seq reads were aligned to hg19 using STAR53 and quantified by featureCounts54. Differential analysis was performed by DESeq251. FDR < 0.05 was used to identify significantly changed genes. (3) PRO-Seq After adapter trimming and low quality sequence removal by Cutadapt52, PRO-seq reads longer than 15 bp were reversed complemented using FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit). Reverse-complemented reads were aligned to hg19 using Bowtie2m48. Reads mapping to rRNA loci and reads with mapping quality < 10 were removed. Reads were normalized by the RLE implemented in DESeq248. Alignment files were used as inputs to NRSA (http://bioinfo.vanderbilt.edu/NRSA/) for estimating alterations of RNA polymerase abundance in proximal-promoter and gene body regions55. The promoter-proximal region was defined by examining each 50 bp window with a 5 bp sliding step along the coding strand spanning ± 500 bp from known TSSs; the 50 bp region with the largest number of reads was considered as the promoter-proximal region and its read density was calculated56. Gene body was defined as the region from + 1 kb downstream of a transcription start site (TSS) to its transcription termination site. DESeq251 was implemented to detect significant transcriptional changes for promoter-proximal and gene body regions accounting for the batch effect. Transcriptional changes with an FDR < 0.05 were considered significant.(1) Supplementary Figures.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.