Antarctic sea-ice is exposed to a wide range of environmental conditions during its annual existence; however, there is very little information describing the change in sea-ice-associated microbial communities (SIMCOs) during the changing seasons. It is well known that during the solar seasons, SIMCOs play an important role in the polar carbon-cycle, by increasing the total photosynthetic primary production of the South Ocean and participating in the remineralization of phosphates and nitrogen. What remains poorly understood is the dynamic of SIMCO populations and their ecological contribution to carbon and nutrient cycling throughout the entire annual life of Antarctic sea-ice, especially in winter. Sea ice at this time of the year is an extreme environment, characterized by complete darkness (which stops photosynthesis), extremely low temperatures in its upper horizons (down to −45 °C) and high salinity (up to 150–250 psu) in its brine inclusions, where SIMCOs thrive. Without a permanent station, wintering expeditions in Antarctica are technically difficult; therefore, in this study, the process of autumn freezing was modelled under laboratory conditions, and the resulting ‘young ice’ was further incubated in cold and darkness for one month. The ice formation experiment was primarily designed to reproduce two critical conditions: (i) total darkness, causing the photosynthesis to cease, and (ii) the presence of a large amount of algae-derived organic matter. As expected, in the absence of photosynthesis, the activity of aerobic heterotrophs quickly created micro-oxic conditions, which caused the emergence of new players, namely facultative anaerobic and anaerobic microorganisms. Following this finding, we can state that Antarctic pack-ice and its surrounding ambient (under-ice seawater and platelet ice) are likely to be very dynamic and can quickly respond to environmental changes caused by the seasonal fluctuations. Given the size of Antarctic pack-ice, even in complete darkness and cessation of photosynthesis, its ecosystem appears to remain active, continuing to participate in global carbon-and-sulfur cycling under harsh conditions. The sace area  and presace area . Thus, tAntarctic sea-ice is a very biologically active and productive habitat ,10. It iSIMCOs largely consist of a mixed population of autotrophic algae and heterotrophic prokaryotes, whose biomass production (BP) is based on sunlight and the assimilation of dissolved organic carbon (DOC), respectively. Although some studies have shown significant variations in BP values under conditions of high primary production, the bacterial carbon turnover typically increases during the sunlight season . SIMCOs Gammaproteobacteria  and Alphaproteobacteria , and the phylum Bacteroidota [Thaumarchaeota and the ubiquitous α-proteobacterial clade SAR11, were abundantly recovered in young sea ice samples, while they found to rarely be present in mature sea ice. These data suggest that seasonal change contributes greatly to shaping the sea-ice-associated microbial community via taxon-specific selection during ice formation in autumn, followed by taxon-specific mortality in the ice during the dark winter months.A comprehensive assessment of microbial diversity and community composition inhabiting Antarctic sea-ice was conducted through cultivation and cultivation-independent molecular techniques , a deep metabarcoding approach was applied to study SIMCOs thriving in the coastal annual pack ice of Terra Nova Bay . In particular, two pack-ice horizons were examined together with the ice–water interface, consisting of platelet interstitial and under-ice seawater samples. An additional study was performed to investigate the bacterial succession in Antarctic sea-ice as it formed, and to evaluate the effect of the algae-derived DOM content in the parent ice–water interface matrices on the developing sea-ice bacterial communities. Special emphasis was paid to determining whether or not the young SIMCOs, formed during freezing, reflected under-ice seawater or annual pack-ice communities. Given that anaerobic bacterial communities, including potential sulphate-reducing and sulfur-oxidizing bacteria, were recently tracked in Antarctic winter pack ice , osmolytMario Zucchelli Station (MZS). Using specially made sterile stainless-steel tubing and containers, brine was collected from the sibling cores by drilling incomplete holes and collecting the internal brine in a short time, similar to the process described elsewhere [top) and the lower horizon . After processing, the twin ice-cores were positioned horizontally on a wooden holder so that brine samples could be taken by gravity percolation in less than one hour. After this, approximately 1000 mL  of the brine was collected from each location of both ice cores. Using a conventional thermometer and refractometer Master-S28 OK , the brine temperature and salinity of both cores were measured directly at the sampling site. In addition, almost 2000 mL of platelet ice interstitial water (PLI) and 10,000 mL of under-ice seawater (UISW) were collected from the formed holes into two separate sterile plastic containers. All samples were immediately transported to MZS and processed within 6 h after sampling. Because both the temperature and salinity values were identical, brine samples collected from the same ice core horizons were pooled and filtered through 0.22 µm Sterivex filters  using a peristaltic pumping system. The filters were then stored in lysis buffer  at −20 °C. Before proceeding with the DNA extraction, performed in Italy, the Sterivex filters were first thawed on ice, then 400 μL of TE buffer (pH 8.0), containing lysozyme (5 mg mL−1) and proteinase K , was added inside the cartridges; they were shaken for 5 s and incubated for 10 min at room temperature. A total of 1600 μL of QRL1 lysis buffer (containing β-mercaptoethanol) was added inside the Sterivex cartridges and extraction was performed using a Qiagen RNA/DNA Mini Kit , according to the manufacturer’s instructions. The DNA samples were further concentrated using a microconcentrator . The quantity, integrity and purity of DNA was checked and evaluated using both agarose gel electrophoresis, and a NanoDrop® ND-1000 Spectrophotometer .During the XXXI Italian Expedition to Antarctica (November 2015), we investigated the distribution and taxonomic composition of sea-ice-associated microbial communities residing the brine inclusions in the annual sea pack-ice. For these purposes, two cores  were pulled out close to each other from the coastal annual pack ice of Terra Nova Bay , one nautical mile from the Italian base lsewhere . Two depIn order to simulate the winter freezing process, which leads to the fast formation of young pack ice, 1500 mL of platelet-ice interstitial water and 9000 mL of under-ice seawater were transferred in a sterile transparent Plexiglas cylinder  and incubated for one week at −10 °C in the dark. After the formation of ‘simulated fast ice’ (SFI), the cylinder was transferred into a 2000 L aquarium and kept floating for one moth at a constant temperature of −2 °C in the dark. Using the holes previously made in the Plexiglas cylinder with intervals of 15 cm and plugged with rubber stoppers, the SFI was checked weekly for oxygen and salt concentration. After one month of incubation, the bottom-most part of the formed SFI was cut, with an ethanol-wiped handsaw, into six pieces , crushed and melted at 2 °C in the dark for 12 h; after this, the rest of the ice was removed . The melLibraries of the V3–V4 hypervariable regions of 16 S rRNA were prepared by single PCR using double-indexed fusion primers with heterogeneity spacers, described by Fadrosh et al. (2014) . Part ofhttps://github.com/jstjohn/SeqPrep, accessed on 25 July 2017) with default parameters. The resulting read files were synchronized with index read files and demultiplexed.Libraries were sequenced with MiSeq™ Personal Sequencing System  using paired-end 300-bp reads. Demultiplexing was performed using a publicly available pipeline, described previously , with mihttp://qiime.org/scripts/pick_open_reference_otus.html, accessed on 17 February 2022). This script clusters reads against the Greengenes v13_8 database [http://qiime.org/scripts/identify_chimeric_seqs.html, accessed on 17 February 2022) against the qiime-default-reference (85_otus.pynast.fasta). The OTUs were taxonomically classified using the Ribosomal Database Project Classifier [http://qiime.org/scripts/single_rarefaction.html, accessed on 17 February 2022) at a value of 10,298 sequences, based on the minimum number of sequences found in the most indigent sample in the dataset. For successive statistical analysis OTUs, sequences were used to construct a phylogeny tree using make_phylogeny.py  using FastTree [Bacterial Tag-Encoded FLX Amplicon Pyrosequencing (bTEFAP) for Microbiome Studies  was appldatabase . Chimeriassifier  against assifier . SamplesFastTree  with defhttp://qiime.org/scripts/alpha_diversity.html, accessed on 17 February 2022). The script beta_diversity_through_plots.py  was used to analyze statistical differences between samples (beta diversity) and generate Principal Coordinate Analysis (PCoA) plots. Hierarchical Cluster analysis  was applied on a Bray–Curtis similarity matrix obtained from the rarefied OTU abundance table within PAST PAleontological STatistics V3.25 . The same OTU table and the same program were used to calculate the contribution of single OTUs to the observed difference between samples (SIMPER test) and the ANOSIM  [Within-community diversity  was calculated using observed OTUs, Chao1 and Shannon indexes, with 10 sampling repetitions at each sampling depth, using alpha_diversity.py (arities)  to assesAll sequence data obtained in this study are freely available at the European Nucleotide Archive (ENA)/NCBI under the accession number PRJNA807589.top and APIbottom layers of Terra Nova Bay annual pack ice were used for the enrichment and cultivation of anaerobic microorganisms that decompose compatible solutes. For this purpose, the ONR7 a mineral basic medium [−1 and 40 g L−1 NaCl, respectively. After autoclave sterilization, 1 mL L−1 of acidic trace metal solution, 1 mL L−1 of vitamin mix [−1 of yeast extract were added to the ONR7, a base media. For enrichment with psychrophilic anaerobes that decompose compatible solutes, stock solutions of choline and dimethyl sulfide (DMS)  were filter sterilized and added to medium at a final concentration of 20 mM. Serum bottles of 120 mL were filled with 90 mL of sterile medium, and after adding 10 mL of each brine sample, anaerobic conditions were achieved by the addition of 0.05 mM cysteine . The bottles were further subjected to three cycles of evacuation/flushing with sterile argon. Incubation was carried out at 0 °C in the dark for 6 months without shaking. All cultivations were performed in triplicates.Brine samples obtained from the APIc medium  was adjuamin mix , alkalinamin mix  and 50 mtop horizons, and −4.7 °C, 78 psu for the APIbottom horizons). Considering that, at the time of sampling, the station was covered with a thick layer of snow (mean 12.5 cm), efficiently isolating the pack ice from cold air, but not from solar heating, meant that such differences in temperature measured at different depths of pack ice were evident. At both depths, the ice was permeable with a relative brine content of approximately 3–5% calculated as a function of temperature and salinity [Amphiphora and Nitschia, further visualized in the laboratory using microscopy analysis of the brine samples. On the contrary, with salinity and pH ranges close to those of pack ice, all the analyzed horizons of the simulated fast ice represent a micro-oxic environment with an oxygen content of no more than 3.1 mg L−1. This depletion of oxygen was most likely associated with the exposure of fast ice to the dark, which stimulated algae death, followed by their decomposition by aerobic bacterial heterotrophs, which is an oxygen-consuming process. The bottom-most SFI layers were more oxygenated than the upper horizons, probably due to their higher salinity, which somehow interfered with the metabolic activity of the bacteria.With direct field measurements of temperature and salinity, the brine samples taken from the same horizons of twin cores turned out to be identical ; (ii) platelet ice interstitial water (PLI); (iii) under-ice seawater, collected directly below pack ice (UISW); and (iv) six layers of simulated fast ice (SFIL1-SFIL6), taken from the bottom to the middle part of the core  brine samples taken from different horizons of annual pack ice (APIthe core . After qthe core .bottom) , ACE, Chao1, Shannon, Simpson and Dominance indexes were calculated. The number of species observed indicates that the greatest diversity was found in natural samples, regardless of whether they were less (UISW) or more saline (APIbottom) .−1 found in the SFIL3 horizon.The smallest number of ASVs and, accordingly, the least prokaryotic diversity were found in all SFI samples, with a general trend of decreasing diversity towards the middle horizons of the analyzed SFI core . As alreL1 and SFIL2 with an oxygen content of 2.3–3.1 mg L−1; and (iii) the most oxygen-depleted upper horizons of the SFI core, respectively (p = 0.0165).As above, beta diversity analyses showed a clear separation of microbial biodiversity between natural samples and simulated fast-ice samples. The unweighted uniFrac distance takes into account the presence and absence of different ASVs along with their phylogenetic distance, while the weighted uniFrac distance also considers the relative abundance of the different ASVs identified in each sample . The difectively . A similectively . In additop pack ice brine. UISW and APIbottom were intermediate, with 48.51% and 44.87% chloroplast-derived SSUs among all the reads analyzed, respectively  and the phylum year ice ,52,53,54ribacter .Gammaproteobacteria ASVs, namely the genera Pseudomonas (2.838 Av.dissim.) and Paraglaciecola (1.054 Av.dissim.), covered 22.23% and 9.61% of all APIbottom and APItop SSU gene reads, respectively. The atypical prevalence of Pseudomonas-related reads can be somehow explained by the presence of a significant amount of Pleuragramma antarctica (silverfish) eggs observed at the bottom of both pack ice cores during brine sampling. Indeed, the most similar (98.54% of identity) SSU gene sequence, found in the NCBI database, belongs to Pseudomonas sp. S8 (accession number KT223376), isolated from the eggs of Atlantic salmon  [Colwellia dominated the UISW bacterial community, accounting for 9.57% of all reads, while their contributions to microbial diversity in other natural samples were minimal (less than 0.5%). Notably, despite covering nearly 6% of all reads, no dominant group (≥2%) among the 59 ASVs affiliated with the class Gammaproteobacteria was found in the platelet-ice interstitial water , and an alpha-proteobacterial ASV belonging to Loktanella —both typical Antarctic bacteria associated with diatom bloom [After SIMPER analysis at the genus level, the two dominant o salar) . Represeal water . As prevom bloom —were amoIn contrast to spring and summer, the activities of sea-ice bacteria during the Antarctic winter are poorly understood, and their community dynamics have not been yet described, since the information available is limited to isolated bacterial strains . In ordeAs mentioned above, the simulated fast ice showed low microbial diversity, with the number of species being half that observed in natural samples . BesidesColwellia were also detected in the initial seawater, recruiting almost a tenth of the UISW reads. However, few of these sequences were found also in platelet ice and annual pack-ice samples. Interestingly, Colwellia dominated the saltiest SFIL1 and SFIL2 bottom horizons  and were found to be 99% identical to organisms previously found in bottom ice during the sea ice formation experiment, conducted in a mesocosm with organic-enriched waters of the North Sea [Colwelliaceae family are characterized as facultative anaerobic bacteria [Among the dominant bacteria , only Gammaproteobacteria of the genus orth Sea . In addibacteria , which cOleispira antarcica-related ASVs in all analyzed SFI samples. Whereas only a few of such sequences (<0.04%) were found in the original seawater and platelet ice, they peaked at 23.95% of all reads derived from the upper SFIL6 layer. These organisms belong to the group of obligate marine hydrocarbon-degrading bacteria [15-C18 hydrocarbons released by decaying diatoms [Of special interest was the finding of bacteria ,64,65 an diatoms ,67.Epsilonproteobacteraeota ; Bacteroidia (genus Marinifilum); and, quite unexpectedly, by strict anaerobic microorganisms belonging to Deltaproteobacteria , Fusobacteria (genus Psychrilyobacter) and Clostridia . Since they all have different metabolic preferences, their uneven distribution over different horizons of the simulated winter-ice core may indirectly indicate the predominance of one type of catabolism or another occurring there. Namely, the less saline (≤51 psu) SFI layers were dominated by both sulfate-reducing Desulforhopalus and sulfur-oxidizing ε-proteobacteria, suggesting that, under suitable conditions, sulfur-containing compounds may be actively transformed in winter sea-ice. In addition to seawater, sulfate and sulfur-containing amino acids; dimethylsulfoniopropionate (DMSP), a known compatible solute, produced in large quantities by polar ice diatoms as an osmo- and cryoprotectant [dddY-like genes, encoding periplasmic DMSP lyase, were found in various Arcobacter strains [2 and H2 S as the end-products of their oxidation [L6 layer analyzed (39 psu). Representatives of the genus Desulforhopalus were found in the next three lower layers and reached their maximum  in SFIL5, indicating an active sulfate reduction there.Apart from these bacterial taxa, the SFI ice samples showed a predominance of atypical sea-ice bacterial groups, represented by facultatively anaerobic otectant ,69,70; a strains . Moreovexidation . Thus, bPsychrilyobacter  and spore-forming clostridia of the genus Caminicella . The discovery of representatives of the latter genus among the main microorganisms involved in the rapid mineralization of organic matter was intriguing. Although originally described as thermophilic, they are often found on the cold seafloor of the Arctic [Octadecabacter [In turn, the most saline near-bottom part of the SFI core was a zone predominantly enriched in hydrolytic, and fermenting strictly anaerobic psychrotolerant representatives of the genus e Arctic . In addicabacter , meaningcabacter .Desulforhopalus, along with sulfur-oxidizing Arcobacter and Sulfurospirillum, was observed in the middle section of a winter pack-ice core taken from the Weddel Sea, which had a strong hydrogen sulfide odor indicative of anoxic conditions. Unfortunately, based on the limited current data, we are not only unable to deduce how common anaerobic bacteria are in Antarctic winter pack-ice, but we are also unable to draw a conclusion about their origin. However, firstly, the presented data indicate that, under certain conditions, these key anaerobic bacteria can become locally predominant in winter pack-ice; secondly, such a striking similarity of the structures of the microbial community in the anoxic pack ice of Weddel Sea, with the community observed by us in the SFI, as the proof of concept, confirms the feasibility of our method for modelling winter sea-ice formation.To our knowledge, apart from previous evidence of transient anoxic conditions and anaerobic reactions such as denitrification in the Arctic ice , there iN,N,N-trimethylglycine) and DMSP, mentioned above, are the most common and widespread in the marine environment [top and APIbottom brine samples. Given that anaerobic bacterial communities, including potential sulphate-reducing bacteria, were recently tracked in Antarctic winter pack-ice [top enrichment (43 psu) turned black and gave off a strong smell of hydrogen sulfide, indicating the growth of sulfate reducers. For this reason, only this one was further processed for high throughput sequencing of SSU genes.Many bacteria and diatoms associated with sea ice are adapted to thrive in sea-ice brines by producing increased amounts of secondary metabolites known as osmolytes . When stironment . Considepack-ice , specialtop enrichment was dominated by sulfate-reducing bacteria belonging to the genera Desulforhopalus  and Desulfosporosinus (5.33%), followed by the facultatively anaerobic fermenting Marinifilum (18.23%), sulfur-oxidizing ε-proteobacteria of the genus Arcobacter  and strictly anaerobic psychrotolerant representatives of the genus Psychrilyobacter . Although the spore-forming clostridia of the genus Caminicella do not belong to the group of dominating organisms , they were also present in enrichment, accounting for 1.54% of all sequences. Is it worth noting that all of these dominant microorganisms appear to represent the so-called ‘dark part’ of the pack-ice microbial community, as they were not detected by Illumina’s deep sequencing of the original brine samples. It can be seen from this list that our enrichment approach created a microbial community strikingly similar to those we observed in the upper layers of the simulated winter ice, despite the fact that they originated from different natural sources . Following this finding, we can state that the Antarctic pack-ice and surrounding ambient are likely to be very dynamic and can quickly respond to environmental changes caused by the seasonal fluctuations, such as lack of sunlight in winter. Given the size of the Antarctic pack-ice, even in total darkness and cessation of photosynthesis, its ecosystem appears to remain active, continuing to take part in global carbon and sulfur cycling.The results of this analysis indicated that the microbial community of APIPolaribacter (the phylum Bacteriodetes) dominate the bacterial communities along with copiotrophic Gammaproteobacteria (the genera Paraglaciecola and Pseudomonas) and Alphaproteobacteria (the family Rhodobacteraceae). It is well known that sea-ice microbial community is highly dependent on a number of abiotic factors such as temperature, salinity and, in particular, light and oxygen content [Epsilonproteobacteraeota ; Bacteroidia (genus Marinifilum); and strictly anaerobic microorganisms belonging to Deltaproteobacteria , Fusobacteria (genus Psychrilyobacter) and Clostridia . The structure of the SFI microbial community was strikingly similar to that obtained by us in anaerobic enrichment with the addition of compatible solutes (choline and DMS). This finding suggests that both oxygen depletion and the presence of algae-derived organic compounds are likely key factors that shape the microbial population in sea ice during the dark winter season.Our late spring study of the microbial community inhabiting the annual pack ice of Terra Nova Bay is consistent with most studies conducted during the same period. It has been shown that widespread sea-ice-associated copiotrophic bacteria of the genera  content ,82,83,84As a general outcome, it seems that in spite of harsh environmental conditions appearing during the dark, cold winter months, the microbial community of Antarctic pack-ice continues to operate and participate in global carbon and sulfur cycling. Overall, our results indicate that sea-ice-associated microbial communities can remain dynamic throughout winter if physical conditions are favorable, and if the algal-derived organics are high enough to support the activity of both aerobic and, as we found out, anaerobic bacteria.


Tourette disorder (TD) is characterized by tics, which are sudden repetitive involuntary movements or vocalizations. Deficits in inhibitory control in TD patients remain inconclusive from the traditional method of estimating the ability to stop an impending action, which requires careful interpretation of a metric derived from race model. One possible explanation for these inconsistencies is that race model’s assumptions of independent and stochastic rise of GO and STOP process to a fixed threshold are often violated, making the classical metric to assess inhibitory control less robust. Here, we used a pair of metrics derived from a recent alternative model to address why stopping performance in TD is unaffected despite atypical neural circuitry. These new metrics distinguish between proactive and reactive inhibitory control and estimate them separately. When these metrics in adult TD group were contrasted with healthy controls (HC), we identified robust deficits in reactive control, but not in proactive control in TD. The TD group exhibited difficulty in slowing down the speed of movement preparation, which they rectified by their intact ability to postpone the movement. Whereas the process of outright withholding/cancelation of a planned unwanted movement  when instructed is referred to as reactive inhibitory control4. The dual mechanisms framework of cognitive control associates proactive control with the maintenance of goal-relevant information and sustained attention in anticipation of upcoming event(s), and reactive control with transient late correction in response to the appearance of specific stimuli5. A successful inhibition of action is the outcome of the interplay between both proactive and reactive inhibitory control .The ability to regulate and/or inhibit unwanted movements is one of the prerequisites for flexible goal-directed behavior. For example, driving through a busy street warrants more alertness, precaution, and preparedness of the driver to react to sudden appearance of a pedestrian or vehicle on the collision course by pressing the brake to avoid an accident. The process of adjusting attentional setting to detect the critical signals  or strategic adjustment in ones’ response (driving at slow speed) to optimize success in goal-directed behavior  is referred to as proactive control9. In a Go/No-Go task, the requirement for the elicitation (or inhibition) of a movement in a stipulated time is indicated at the beginning of each trial by a go (or no-go) signal. Infrequent presentation of the no-go signal and random interleaving of go and no-go trials make the task difficult. The frequency of errantly eliciting a response in no-go trials is referred to commission error rate, which is widely used as a metric of proactive inhibitory control10. Less the commission error, better the proactive inhibitory control. In contrast, participants generate a primary motor response following a go-signal in the majority of trials in a countermanding  task, but they are instructed to cancel the pre-planned response in randomly interleaved trials when a stop-signal appears after a variable delay from the go-signal, called stop-signal delay. In ideal situation, error in inhibition increases monotonically with the increase in stop-signal delay. Race model3 describes performance in the stop-signal task as an outcome of a competition between a preparatory GO and an inhibitory STOP process. Each process independently rises at a stochastic rate to reach a common fixed threshold. If the STOP process reaches the threshold before the GO, the movement is inhibited; the movement is generated otherwise. Race model provides methods to estimate the average time taken by the STOP process called stop-signal response time (SSRT). SSRT is used as a metric of reactive inhibitory control. The shorter the SSRT, the better the reactive inhibitory control.In laboratory, proactive and reactive inhibitory control are often assessed using tasks like Go/No-Go task, AX version of continuous performance task (AX-CPT), cued stop-signal task and classical countermanding task12, schizophrenia15, obsessive–compulsive disorder (OCD)17, attention-deficit hyperactivity disorder (ADHD)19, and Tourette disorder (TD)21. Tourette disorder (TD) represents a relevant model of inhibition impairment due to its major clinical sign: tics. Usually, they corresponded to sudden, repetitive, non-rhythmic, involuntary or semi-voluntary movements and/ or vocalization23 and are frequently considered as “fragments of motor behavior that escape voluntary motor control”, related to a deficiency in inhibitory control of actions25. However, studies did not find a consistent significant difference between TD and HC either in the commission error rates28 or in SSRT29. A recent study30 examined volitional (proactive and reactive) and automatic inhibition in primary tic disorder using conditional stop-signal and masked priming task respectively. They found that proactive control was intact and automatic inhibition was impaired. Though they found longer SSRT in the overall tic group than HC, it was associated with the presence of OCD. There was no significant difference in SSRT between tic without OCD group and HC. It led authors to speculate that inconsistent findings of difference in SSRT may be an outcome of no accounting for comorbidities in TD. Another possible explanation for the inconsistent findings of difference in SSRT is that SSRT might not be an appropriate measure of inhibitory control when the context independence assumption  is violated, especially at short SSDs32. The violation is pervasive and has a severe effect on the estimation of SSRT. For example, if trials with short intervals between the go and stop signal are removed from SSRT estimation, the difference reported in published studies between HC and disorder groups mostly disappears35.The average SSRT in patients population has been contrasted with healthy control (HC) to identify the propensity of impairment in inhibitory control in the populations with motor and cognitive deficits like Parkinson’s disease36, which is an alternative to race model, does not assume a race between GO and STOP. In its original form, this model advocates that the inhibition of a pre-planned movement is determined by the efficiency of the detection process and magnitude of deceleration. After the stop-signal appears, deceleration in the build-up activity of GO is triggered. If the magnitude of deceleration determined by the detectability of the stop-signal is sufficient, the impending movement is inhibited. We and others35 have recently shown that cancellable rise-to-threshold model can explain the behavior in stop-signal task better than race model. To assess the contributions of both proactive and reactive control in movement inhibition without independence assumption, we derived a pair of metrics on the foundation of CRTT framework of countermanding, which we referred to as ‘proactive delay’ and ‘log-attenuation rate’, respectively36. The former estimates the time consumed in postponing the response in expectation of the stop-signal to increase the odds of successful inhibition, whereas the latter estimates the dynamics of decelerated preparatory build-up activity triggered by the onset of the stop-signal. Since CRTT metrics are independent of the race model’s assumptions and sensitive to deficits in proactive and reactive inhibitory control independently, we revisited the deficits in inhibitory control in adult TD patients21.The cancellable rise-to-threshold model (CRTT)9. In the current study we tried to characterize inhibitory control in TD in the CRTT framework. Given the deficiency in inhibitory control of actions in TD25, we expected that both the CRTT metrics, i.e. log-attenuation rate and proactive delay, would be less in TD in comparison to HC. However, we found that the TD group rectified the deficiency in reactive control by judicious exertion of intact proactive control.Previously we showed that the efficacy of inhibitory control depends on both deceleration in the speed of movement preparation in response to the stop signal, and strategic postponement of movement initiation21 , which required them to refrain from pressing a key in response to an infrequent stop-signalsee Fig. ”.Figure t (81) = 0.596, p (two-tailed) = 0.553, d = 0.136, BF01 = 3.624]; education level ; or gender  between the TD and HC groups. Out of 53 TD patients, 19 were taking antipsychotic medication, 23 had ADHD, and 11 had OCD. The mean (SD) tic severity was 16.321(7.076) as measured by YGTSS/50.Table F  = 14.628, p < 0.001, F  = 47.261, p < 0.001, p = 0.003, d = 0.871) and from 3rd to 4th bin  but a non-significant increase from 2nd to 3rd bin  in HC group. Similarly, the mean error increased significantly from 1st to 2nd , from 2nd to 3rd bin , and from 3rd to 4th bin . in the TD group. It shows the error monotonically increased as predicted by the race model in both groups (except error from 2nd to 3rd bin in HC).No significant differences were found between HC and TD on all behavioral performances  = 22.03, p < 0.001, d = 4.164, BF+0 > 100] and TD . Subsequently, to test whether noncancelled RT increased with the increase in SSD, we plotted mean noncancelled RT against the midpoint of each SSD bin  = 129.717, p < 0.001, F  = 95.29, p < 0.001, ps <  = 0.009, all ds >  = 0.493) reflecting the replication of the predictions of the race model. In short, noncancelled RT increased monotonically as a function of SSD in both groups as predicted by the race model. These results were majorly in line with the race model’s prediction allowing estimation of SSRT.No-stop RT was significantly longer than non-cancelled stop RT in both HC , TD . SSRT estimated by median method had positive significant correlation with error in HC  and non-significant in TD . SSRT by mean method was also positively correlated in HC  and non-significant in TD . A significant positive correlation between SSRT and error in inhibition demonstrates that the estimated SSRT was in compliance with race model. However, the model does not show a difference in mean SSRT between TD and HC, suggesting that TD patients do not have compromised inhibitory process.We estimated SSRT by three methods to rule out any bias due to the choice of estimation method. Using the three previously described SSRT estimationsHC Table . Subsequp (one-tailed) = 0.006, d = −0.616] . However, no significant difference was observed for the mean proactive delay  . These results suggest that the TD group had a deficit in reactive control, but proactive control was intact, in comparison to the HC group.Using CRTT metrics, we found that the mean log-attenuation rate was significantly less in TD than HC  Fig. C. This dr (25) = −0.514, p (one-tailed) = 0.003, R2 = 0.264, BF-0 = 16.183] and TD . However, Bayesian statistics suggests this relationship was ‘anecdotal’ (1 ≤ BF < 3) for TD, but ‘strong’ (10 ≤ BF < 100) for HC. Pearson’s coefficient indicates that the magnitude of coupling between log-attenuation rate and error in HC was almost numerically twice the magnitude of coupling in TD. However, a follow-up Fisher’s z test estimated by cocor package39 showed that the magnitude of correlations of log-attenuation rate and error between HC and TD was not significantly different . Proactive delay was also significantly correlated with error in both HC  and TD . Bayesian statistics suggests this relationship was ‘decisive’ (BF ≥ 100) for both groups.Theoretically, log-attenuation rate and proactive delay, each should have a negative correlation with the overall error in inhibition. We tested the correlation of log-attenuation rate and proactive delay with overall error in inhibition for both groups. Log-attenuation rate was significantly correlated with error in both HC . (2) The mean (± SEM) proactive delay in TD with ADHD (384 ± 15 ms) and TD without ADHD (384 ± 12 ms) was not significantly different . (3) The mean (± SEM) inhibition error in TD with ADHD (44.07 ± 1.42%) and TD without ADHD (44.65 ± 0.99%) was not significantly different . (4) The mean (± SEM) log-attenuation rate in medicated TD (0.0086 ± 0.0003) and un-medicated TD (0.0089 ± 0.0003) was not significantly different . (5) The mean (± SEM) proactive delay in medicated TD (366 ± 16 ms) and un-medicated TD (395 ± 11 ms) was not significantly different . (6) The mean (± SEM) inhibition error in medicated TD (45.89 ± 1.51%) and un-medicated TD (43.48 ± 0.91%) was not significantly different . These results indicate that the difference found in log-attenuation rate and proactive delay in HC and TD might not be due to medication or presence of ADHD. We did not consider OCD due to small sample size (n = 11) and lack of prior link between CRTT metrics and OCD.Since we found a link between deceleration rate and attention in Indrajeet and Ray (2019) and effect of medication on SSRT in Atkinson-Clement et al3 and relatively recent CRTT model9 to assess the inhibitory control in the TD group in comparison to HC participants. Not surprisingly, like earlier studies we also observed that neither stopping behavior nor the metric derived from race model was able to distinguish between TD and HC. On the contrary, our new method based on CRTT model teased apart contributions from proactive and reactive control in stopping a manual movement. While the ability to postpone an action by TD was comparable to HC, the log-attenuation rate that estimates the strength of deceleration in GO process following the stop signal was significantly less in TD than HC. Our study also suggests that the CRTT metrics, which were originally derived to study countermanding saccades, can be generalized to variants of stop-signal task with different effectors (eye / hand) and stop-signal adjustment methods (randomization/staircasing). These results are consistent with a recent meta-analysis study indicating possible impairment in reactive but not in proactive inhibitory control in TD40, and critical from the clinical point of view to identify differences in neural circuitry causing deficiency in one type of control sparing the other.In this study, we applied both traditional race model51 and dysfunctional cortico-basal ganglia pathways underlie TD55. Interestingly, inhibition of preplanned action entails an engagement of fronto-cortical basal ganglia pathways51, which is somehow compromised in TD55. A simplified description suggests that on the direct pathway in basal ganglia, the dorsal striatum that receives projection from the frontal cortex inhibits the substantia nigra pars reticulata (SNr) causing disinhibition of the thalamus, which is attributed to an underlying neural mechanism of the GO process, whereas the subthalamic nucleus (STN) exerts an excitatory influence on SNr acting similar to pressing the brake in a car57. The dorsal striatum consists of two structures: caudate nucleus (CN) and putamen (Pu). Striatum and STN are also interconnected via globus pallidus external (GPe) on the indirect pathway59. Imaging studies have found an abnormality in cortico-basal ganglia-thalamocortical motor loop and supplementary motor area in TD60. TD patients exhibited increased activation in the right supplementary motor area and the inferior parietal cortex, but decreased activation in the dorsal pre-motor cortex while performing a stop-signal task61. Furthermore, Ganos et al. (2014) showed that the activation of supplementary motor area (SMA) on correct stop trials were correlated with the frequency of tics.What might be a feasible physiological explanation of weak attenuation on GO process, but intact ability of strategic adjustment of the time of process initiation (postpone the movement) in the TD group? Studies have advocated that the strength of the fronto-basal ganglia connectivity largely determines the efficacy of the inhibitory control64, was diminished in TD patients in comparison to HC65. However, P300 as a marker of response inhibition is debated66 and may reflect other processes e.g., infrequent stimulus detection as well68. Additionally, EEG studies in TD  doesn’t consistently show diminished P30069 and it is not always attributed to impaired inhibitory process. For example, reduced amplitude of P3b in TD was linked to altered allocation of attentional resources70. Some studies have shown that P300 linked to no-go is shifted over anterior  from central electrodes in TD72 but no difference in P300 amplitude between TD and HC72, and even enhance P3b amplitude at parietal electrodes73 or delayed P300 onset in TD in incompatible condition in Simon task74. Error related negativity amplitudes were not significantly different between TD and HC implying intact error detection76 (for a review of ERPs in TD refer to Morand-Beaulieu and Lavoie 201969). Since we have previously shown a link between detectability of stop-signal and attenuation rate32, it may be an interesting idea to explore the relationship between ERP components  and CRTT metrics in future. Interestingly, despite the differential neural activity in brain areas critical for response inhibition, none of these studies found a significant difference in SSRT or other behavioural performance between TD and HC. At the structural level, the volume of the caudate nucleus (CN), putamen (Pu), and globus pallidus (GPe) are reduced in TD adults78. Single neuron’s activity recordings have shown a link between neuronal activity in the caudate nucleus in monkeys79 and GPe neurons in rats56 in reactive inhibition. GPe neurons activity in rats is also linked to proactive control during stop-signal tasks80. We speculate that SSRT is not always a reliable metric to identify some of the differences found at the neural level in TD that might be explained by CRTT metrics.Similarly, some EEG studies have shown that the amplitude of fronto-central P300, considered as a marker of response inhibition81. Also, presence, severity, and capacity to inhibit premonitory urges could be relevant to the present results83. Further studies are warranted to address these caveats. Recent studies have shown impairment in inhibition in TD is not purely motor but also linked to perceptual and cognitive processes, e.g., altered perception–action integration85, attention86, etc. (for a viewpoint refer to review87). Additional studies which measure perceptual and cognitive processes with the inhibition are warranted to show a wholistic view of the nature of impairment in TD. Further, like many other clinical sample studies, comorbidities and medication might be issues. However, we found that CRTT metrics were not different between TD with and without ADHD, or un-medicated and medicated TD. Having said that caution should be taken interpreting no statistical difference, because effects were analyzed separately ignoring the effect of other factors. Despite these limitations, our study is a methodological advancement in the assessment of deficits in inhibitory control in TD.Our study suffers from a few limitations. For example, CRTT metrics could not be computed for each emotion category and for each participant due to a smaller number of noncancelled trials in each emotion condition. It would be interesting to test whether CRTT metrics are sensitive enough to detect modulation of the inhibitory process in an emotional context and able to resolve the contradictory findings regarding the effect of emotion on inhibitory control. In addition, some recent studies showed that the neurocognitive measures of inhibitory control were not always the best predictors of tics severity as did the subjective tics suppressibilityA total of 63 TD and 34 HC were recruited for the original project. The HC group was matched with the TD group for age, gender, and acquired education, keeping the ratio between the healthy control and TD patients ~ 1:2. The exclusion criteria for all participants were based on satisfying any of the following conditions: (1) incapable to provide consent, (2) history of substance (except nicotine) addiction or psychosis, (3) neurological condition except tics, (4) history of any psychiatric condition for HC. All participants were informed about the procedure and protocol of the study and gave their informed consent. Monetary compensation (50 Euros) was provided for participation.https://clinicaltrials.gov/show/NCT02960698). All participants gave their informed consent. All procedures comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.The study was approved by the Comité de protection des personnes (CCP) of Sorbonne Université (CCP16163/C16-07) and preregistered prior to the research being conducted on ClinicalTrial 89 for impulse-control related disorders, and the Barratt Impulsivity Scale (BIS)-1190 for impulsivity. For TD patients, the Yale Global Tic Severity Scale (YGTSS)91 was used to assess the severity of tics. Each patient underwent a psychiatric evaluation and a medical history check-up to assess for psychiatric comorbidities.All participants were assessed using the Mini-International Neuropsychiatric Interview (MINI)92 were selected from the international affective picture system and were from three groups of equal size . Positive or negative emotional content images were of moderate emotional intensity and arousal. Thus, in a total of 405 trials, each image was presented thrice. However, we could not fit the CRTT model for each emotion condition due to insufficient number of error stop trials with positive PPT. Therefore, all trials in each emotion condition were combined for this study. After a blank black display for a 1–2 s from the image, letter ‘O’ in green appeared at the centre of black display acting as a go-signal . Participants were instructed to press the ENTER key ‘as soon as possible’ in these trials. However, in 33% of the total trials, after a variable delay from the go-signal , letter ‘X’ painted in red appeared at the centre acting as a stop-signal . Participants were instructed to refrain from pressing the Enter key in these trials. For a detailed description of the task e.g., staircasing of SSD, refer to supplementary material. Details of scene image selection and categorization, and inhibitory control in induced emotional context can be found elsewhere21.As shown in Fig. E-prime software  created and displayed all stimuli and stored the critical task parameters and responses made by participants. All stimuli were displayed on a monitor at a 60 Hz refresh rate. The ENTER key of the keyboard was assigned for response input. The pre-processing and basic analysis  of the data was carried out by using Matlab® . Matlab® Statistical Toolbox  , JASP software  (Bayesian statistics) and SigmaStat  (ANOVAs and post-hoc tests) was used for statistical analysis. Curve Fitting Toolbox™ of Matlab® was used for fitting curves.36. We previously extended the CRTT model to show an exponential increase in reaction time (RT) in unsuccessful stop trials, as parallel processing time (PPT) increased32. PPT is defined as the maximum time duration, for which the stop-signal and the go signal can be processed in parallel before the elicitation of a response. Empirically, it was calculated by subtracting SSD from RT in error stop trials . PPT was grouped in bins and mean PPT and corresponding mean noncancelled RT was calculated for each bin. Noncancelled RT was plotted against PPT, and the plot was fitted with an exponential function  for HC and TD groups. P-values of t-tests (to compare mean SSRT between HC and TD) and correlations (between SSRT and error in inhibition) were adjusted for multiple comparisons using Holm method93 using R software .The criterion of significance α was fixed at 0.05 level, except for the tests of normality and equivalence of variance where a lenient criterion was used (α = 0.01). Linear Pearson product–moment correlation method was performed to calculate correlations . SSRT was estimated by three methodsData may be shared in its raw form for review purpose or other reasonable scholarly use.Supplementary Information.


These findings reveal how PDGFRβ engages and phosphorylates Abl2 leading to activation of the kinase, providing a framework to understand how growth factor receptors engage and activate Abl family kinases.Abl family kinases are nonreceptor tyrosine kinases activated by diverse cellular stimuli that regulate cytoskeleton organization, morphogenesis, and adhesion. The catalytic activity of Abl family kinases is tightly regulated in cells by a complex set of intramolecular and intermolecular interactions and post-translational modifications. For example, the platelet-derived growth factor receptor beta (PDGFRβ), important for cell proliferation and chemotaxis, is a potent activator of Abl family kinases. However, the molecular mechanism by which PDGFRβ engages and activates Abl family kinases is not known. We show here that the Abl2 Src homology 2 domain directly binds to phosphotyrosine Y771 in the PDGFRβ cytoplasmic domain. PDGFRβ directly phosphorylates multiple novel sites on the N-terminal half of Abl2, including Y116, Y139, and Y161 within the Src homology 3 domain, and Y299, Y303, and Y310 on the kinase domain. Y116, Y161, Y272, and Y310 are all located at or near the Src homology 3/Src homology 2-kinase linker interface, which helps maintain Abl family kinases in an autoinhibited conformation. We also found that PDGFRβ-mediated phosphorylation of Abl2  Abl family nonreceptor tyrosine kinases, comprised of Abl1 and Abl2 in vertebrates, translate signals from growth factors and adhesion receptors to regulate cytoskeleton organization and remodeling, which is essential to many cellular processes including cell morphogenesis, adhesion, and migration , 7, 8, 9via an autoinhibitory mechanism, in which the kinase domain is held in a rigid conformation through intramolecular interactions with the Src homology 3 (SH3) and Src homology 2 (SH2) domains  , 21, 23.in vitro and in cells. We also identified several novel tyrosine (Y) phosphorylation sites on Abl2 including Y116, Y139, and Y161 on the SH3 domain and Y299, Y303, and Y310 on the kinase domain. Of notable interest, Y116, Y161, Y272, and Y310 are all located near the SH3/SH2–kinase linker interface, which is crucial for keeping Abl2 in an autoinhibited conformation. Mutation of Y116, Y161, Y272, and Y310 to phenylalanine abrogated PDGFRβ-mediated activation on Abl2. These findings provide a mechanism to understand how Abl family kinases are regulated by receptor tyrosine kinases through different phosphorylation events.Here, we report the molecular mechanism by which PDGFRβ interacts with, phosphorylates, and activates Abl2 kinase. We found that PDGFRβ binds and phosphorylates Abl2 both Previous work demonstrated that Abl2 coimmunoprecipitates with PDGFRβ from cell lysates , but wheB). In parallel, the kinase-inactive PDGFRβ point mutant (K634R) did not undergo PDGF-stimulated autophosphorylation and was not retained on Abl2 SH2 beads (A and B). These data indicate that autophosphorylated PDGFRβ in cell lysates can bind the Abl2 SH2 domain.PDGFRβ was expressed in human embryonic kidney 293 (HEK293) cells and activated by stimulation with PDGF-BB (PDGF). Following stimulation, we found that PDGFRβ could be retained on Abl2 SH2 domain–containing agarose beads but not on beads containing the Abl2 SH2 R198K point mutation that disrupts SH2 binding to phosphotyrosine-containing binding partners , 35 FigB. In parH2 beads , A and BC and D). Binding of PDGFRβ Y751F was also reduced but only by 10% relative to WT controls (C and D). These data suggest that phospho-Y771 in PDGFRβ is required to interact with the Abl2 SH2 domain.PDGFRβ is phosphorylated at multiple sites in cells, some or all of which could be binding interfaces for the Abl2 SH2 domain, but previous studies have not resolved which phosphotyrosine (pY) residue(s) of PDGFRβ serve as binding sites for the Abl2 SH2 domain. To address this, we mutated specific tyrosine residues in the PDGFRβ CD to phenylalanine and expressed the mutants in HEK293 cells. All mutants were expressed at similar levels and underwent significant tyrosine phosphorylation following PDGF-BB treatment, but binding of the PDGFRβ Y771F mutant to Abl2 SH2 domain beads was reduced by 90% relative to WT PDGFRβ or any of the other Y to F single-substitution mutants of PDGFRβ , C and Dcontrols , C and Din vitro using phage lambda phosphatase, and repurified the dephosphorylated PDGFRβ CD (A). We incubated PDGFRβ CD in the presence of saturating Mg2+ and ATP for 2 h to enable it to autophosphorylate to completion (A). Purified autophosphorylated PDGFRβ CD bound to the Abl2 SH2 domain beads with submicromolar affinity (Kd = 0.26 B). As in experiments using cell-derived PDGFRβ (B), the binding-defective Abl2 SH2 domain R198K mutant completely abolished binding to autophosphorylated PDGFRβ CD (C). While the PDGFRβ CD Y771F mutant was able to autophosphorylate in vitro, the amount of protein binding to Abl2 SH2 domain–containing beads was greatly reduced compared with WT . The Abl2 SH2 domain might bind to other minor phosphorylated tyrosine(s) in the Y771F PDGFR construct, which could explain the small amount of residual PDGFRβ CD Y771F pulled down by SH2 beads (D). Together, our data indicate that the Abl2 SH2 domain binds directly to phosphorylated Y771 interface on the PDGFR CD.We next used purified recombinant Abl2 SH2 domain and PDGFRβ CD to test whether the proteins interact directly and to measure the affinity and specificity of this interaction. The PDGFRβ CD was comprised of the residues spanning from the C-terminal end of the transmembrane region to the C terminus of the protein (554M-1106L). We purified 6XHis-tagged PDGFRβ CD following baculovirus-mediated expression in insect cells, fully dephosphorylated it DGFRβ CD A. We incmpletion A. Purifi binding B. As in d PDGFRβ B, the biDGFRβ CD C. While H2 beads D. Togethin vitro kinase assay to measure whether purified recombinant PDGFRβ CD phosphorylates Abl2. We expressed maltose-binding protein (MBP)-Abl2 full length (encompassing the first common exon to C terminus), MBP-Abl2 C terminus  and a 6XHis-tagged Abl2 N terminus  in insect cells and purified them (A). The Abl2 kinase domain–containing constructs carried two inactivating mutations (D307N and K317M) in the kinase domain, which eliminates possible Abl2 autophosphorylation. In the presence of Mg2+ and ATP, 5 nM of recombinant PDGFRβ CD directly phosphorylated full-length Abl2 and the Abl2N but only very weakly the Abl2 C terminus (B). We next investigated whether PDGFR/Abl2 direct interaction is required for PDGFR to phosphorylate Abl2. PDGFRβ CD phosphorylation of the Abl2N (R198K) SH2 domain mutant, defective in binding, was greatly reduced relative to WT Abl2N (C). These results suggest that SH2 domain–mediated Abl2 recruitment to PDGFR is required for its phosphorylation.Abl2 kinase activity is activated by phosphorylation . We usedied them A. The Abterminus B. We nexWT Abl2N C. These via phosphorylation of those homologous sites (kcat (6.8 versus 7.3 min−1) and KM (1.6 versus 2.8 μM) as compared with WT, suggesting that the PDGFRβ CD phosphorylates one or more novel sites in Abl2 (D).Phosphorylation of Abl2 at Y272 in the SH2 domain-kinase linker and Y439 in the kinase activation loop can activate its kinase activity, and Abl1 is similarly activated us sites , 26. We  in Abl2 D.A, top panel). Phos-tag SDS-PAGE successfully separated unphosphorylated Abl2N and resolved multiple phosphorylated Abl2N species in the PDGFRβ CD-treated samples. As kinase reaction time increases, the intensity increases for higher phosphorylated states of Abl2N, whereas the intensity decreases for lower phosphorylated states and nonphosphorylated Abl2N . The phosphorylated Abl2N was used to perform phosphopeptide mapping by MS to locate potential new phosphotyrosine residues. We attempted to limit nonspecific phosphorylation as much as possible by reducing both the kinase concentration and time of phosphorylation. MS analysis identified seven tyrosine phosphorylation sites , including phospho-Y439, which was previously identified as an Src family kinase (SFK)–mediated phosphorylation site  and several novel sites including phospho-Y161 .In order to identify the novel phosphorylation sites, we performed phosphopeptide mapping with MS. Abl2N purified from insect cells was treated with a mix of Lambda protein phosphatase and YopH for dephosphorylation. Abl2N phosphorylated by PDGFRβ CD was monitored for phosphorylation status at different time points. Samples immunoblotted for phosphotyrosine show phosphorylation intensity saturates at a reaction time of 2 h . Mutation of tyrosine 272 (Y272F) on the SH2–kinase linker completely abrogated Abl2 SH2 domain phosphorylation by PDGFR, whereas the other triple mutant constructs did not reduce phosphorylation (B). Mutation of three tyrosines in the SH3 domain  greatly reduces SH3–SH2 domain phosphorylation by PDGFR (C). Mutations of four tyrosines in the kinase domain  also significantly reduced its phosphorylation (D). Our mutagenesis kinase assay was consistent with MS findings. Interestingly, there are several novel phosphorylated tyrosine residues  located at or near the SH3/SH2–kinase linker interface, which has an important regulatory role of keeping Abl family kinases in an autoinhibited conformation (E) . W. WA). Muin vitro, using purified proteins (A). We first incubated 1 μM of Abl2N with 10 nM of PDGFRβ and Mg2+/ATP in a 1-h activation reaction, during which we achieved significant tyrosine phosphorylation (B). Control preparations include PDGFRβ only, Abl2N without PDGFRβ/ATP (nonactivated), and Abl2N with ATP-only (autoactivated) condition. Following these preincubations, we used 1 nM of Abl2N in kinase reactions to phosphorylate CrkII, and KM and kcat for the reaction were measured. The catalytic efficiency (kcat/KM) value for the nonactivated Abl2N was determined to be 0.55 μM−1 min−1, and autophosphorylated Abl2 had a kcat/KM = 0.83 μM−1 min−1, whereas the PDGFR-activated condition was 3.15 μM−1 min−1. This result suggests that PDGFR phosphorylation on Abl2N promotes a 5.7-fold activation over baseline and a 3.8-fold activation over autophosphorylated Abl2N (B and D).Autophosphorylation of Y272 in Abl2 and phosphorylation of Y439 by SFKs promotes Abl2 kinase activity . We testproteins A. We firrylation B. Controed Abl2N , B and DC and D). SFK–mediated phosphorylation of Abl2 on Y439 phosphorylation within its activation loop promotes kinase activation (C and D). Using an Abl2 pY439-specific antibody, we found that PDGFRβ does not phosphorylate Tyr439 on the Abl2N 4YF mutant construct, whereas it significantly phosphorylates the WT Abl2N (A). We also found that autophosphorylation of the Abl2N 4YF protein does not lead to increased kinase activity (B and C). These data suggest that PDGFR phosphorylation on one or more of the additional sites, Y116, Y161, Y272, and Y310, contributes to activation of Abl2N kinase activity.To determine which tyrosine phosphorylation events contribute to Abl2 kinase activation, we selected five tyrosine residues to mutate that were suggested to be most relevant to Abl2 kinase activation , by structural modeling, to create the Abl2N 5YF construct. Incubation with the PDGFRβ CD did not result in Abl2N 5YF activation , C and Dtivation . Hence, tivation , C and DWT Abl2N A. We alsactivity , B and CA). Only WT PDGFRβ underwent significant tyrosine phosphorylation following PDGF treatment (A). We then immunoprecipitated Abl2 and measured Abl2 tyrosine phosphorylation levels. In cells expressing WT PDGFRβ, PDGF stimulation significantly increased Abl2 tyrosine phosphorylation levels by 2.2-fold, but similar increases in Abl2 tyrosine phosphorylation were not observed in PDGF-stimulated cells expressing kinase-inactive PDGFRβ (B and C). Similarly, stimulation of the PDGFRβ did not increase tyrosine phosphorylation of the PDGFRβ-binding defective Abl2 R198K mutant. In fact, the basal tyrosine phosphorylation of the Abl2 R198K mutant was significantly lower than WT Abl2. PDGFRβ also coimmunoprecipitated with Abl2 after PDGF stimulation, but complexes were not detected in transfections expressing either the PDGFR kinase inactive mutant or the R198K Abl2 mutant. These data suggest that PDGFRβ signaling promotes Abl2 tyrosine phosphorylation and PDGFRβ/Abl2 interaction.We next investigated whether PDGFRβ binds and phosphorylates Abl2 in cells. PDGFRβ and Abl2-HA (hemagglutinin) tag were coexpressed in HEK293 cells, stimulated with PDGF. Both WT and kinase-inactive PDGFRβ and WT and R198K Abl2-HA expressed at similar levels A. Only Wreatment A. We thee PDGFRβ , B and CB). Stimulation of WT mouse fibroblasts with PDGF leads to an eightfold increase in phosphorylation of the Abl1/Abl2 substrate CrkII (A), but this was significantly abrogated in Abl1/Abl2 CRISPR double KO (DKO) cells. However, we ascribe the small increase of CrkII phosphorylation after PDGF stimulation to this residual Abl1/Abl2 level in the DKO cells.We next addressed whether PDGFRβ activation leads to Abl2-mediated signaling events in cells. We used CRISPR in WT mouse 3T3 fibroblast cells to achieve 90% reduction in Abl1 levels and 88% reduction in Abl2 levels B. Stimulte CrkII A, but thin vitro and in cells via the Abl2 SH2/PDGFRβ phospho-Y771 interface. Abl2 recruitment results in PDGFRβ directly phosphorylating the Abl2N on multiple sites. Using both kinase assays with Tyr to Phe substitution and phosphopeptide mapping with MS, we identified up to eight phosphotyrosine sites on Abl2. We demonstrated that PDGFRβ phosphorylation of Abl2 results in Abl2 kinase activation both in vitro and in cells. These findings provide a molecular mechanism to understand how receptor tyrosine kinases activate Abl family kinases through different phosphorylation events.We report here the molecular mechanisms by which PDGFRβ binds, phosphorylates, and activates the Abl2 kinase. We provide evidence that Abl2 binds to autophosphorylated PDGFRβ both trans, which also promotes kinase activation   . EngagemD) , 49, 50.tivation , 26.in vitro. Mutation of Y116, Y161, Y272, Y310, and Y439 (5YF) abrogated PDGFRβ-mediated activation of Abl2 kinase activity. Surprisingly, an Abl2N mutant in which Y439 was restored  could not undergo activation by PDGFRβ. PDGFRβ does not phosphorylate Tyr439 on the Abl2N 4YF mutant construct. Our data may be consistent with a model in which Abl2 Y439 is not efficiently phosphorylated when Abl2 is in a less phosphorylated and possibly more “autoinhibited” conformation. Our model may provide some insight that activation loop phosphorylation and kinase activation may be regulated by N-terminal domain conformation.Phosphorylation of Abl2 at Y439 (Y412 on Abl1) in the kinase activation loop is a critical step for full kinase activation of Abl family kinases , 48. HowOur work adds to a growing body of data indicating that Abl kinases are not simply switched between a closed autoinhibited state and an open active state through a one-step process , 26, 29.Full-length Abl2 (residues 74–1182), Abl2 N terminus (residues 74–557), Abl2 kinase domain (residues 288–539), and PDGFRβ CD (residues 554–1106) were cloned with an N-terminal 6XHis tag into the pFastBac1 vector (Invitrogen), as previously described . All AblS-transferase (GST) into the pGEX-6P-1 vector, and GST-Abl2-SH3-SH2 and GST-Abl2-SH2 fusion proteins were purified from BL21 (DE3) Escherichia coli cells (Millipore Sigma) on glutathione 4B beads . The GST tags were cleaved using PreScission protease , as previously described , as previously described (The Abl2 SH3–SH2 and SH2 domains were cloned in frame with glutathione-escribed . GST-Crkescribed . Before AminoLink (Thermo Fisher Scientific) beads were used to covalently link Abl2 SH2 domain following purification . BrieflyKd values, an increasing concentration gradient of PDGFRβ CD constructs from 0 to 2 μM was used. Binding reactions were incubated for 1 h at 4 °C before washing and resuspending in Laemmli sample buffer (LSB). Bead-associated material were boiled and separated on SDS-PAGE gels. Gel bands were resolved with Coomassie blue silver stain, and densities were quantified using ImageJ   . For mea2, 5 mM MnCl2, 1 mM sodium pervanadate, and 1 mM DTT for 5 min at 32 °C before initiating reactions with 5 μM ATP with 0.75 μCi of [γ-32P] ATP for 10 min before terminating with LSB, running on gels, and exposing to a phosphor-imaging screen. Screens were scanned using a Personal Molecular Imager (Bio-Rad), and band densities were quantified using ImageJ software , 1 nM of preincubated Abl2 kinase proteins, 5 μM ATP, and 0.5 μCi of [γ-32P] ATP. All reactions were quenched with 1× LSB after 10 min, boiled, and separated on 10% SDS-PAGE gels. Gels were stained with Blue Silver G-250 Coomassie for 30 min to visualize GST-CrkII protein bands. Bands were cut out, along with background regions within the same lane, and scintillation counted along with a 1 μl sample from the kinase assay. The number of counts per minute was calculated, and KM and kcat values were determined as previously  targeting the seventh exon of Abl2 was inserted into lentiCRISPRv2 plasmid (Addgene Plasmid #52961), then transfected into HEK293T cells to generate Abl2sg1 lentivirus. WT mouse 3T3 fibroblast cells were infected with the generated Abl2sg1 lentivirus and then selected with 2 μg/ml puromycin for 72 h to generate abl2−/− 3T3 cells. Another guide sequence of 5′-GTTAGTTCACCATCACTCCA-3′ with a protospacer adjacent motif (CGG) targeting the fourth exon of Abl1 was inserted into lentiCRISPRv2 neo plasmid (Addgene Plasmid #98292), then transfected into HEK293T cells to generate Abl1sg1 lentivirus. WT mouse 3T3 fibroblast cells were infected with the generated Abl2sg1 lentivirus and Abl1sg1 lentivirus simultaneously and then selected with 2 μg/ml puromycin and 800 μg/ml G418 to generate abl1−/−abl2−/− DKO 3T3 cells.Experiments were performed in HEK293 cells (American Type Culture Collection) and The following antibodies were used for this study: phosphotyrosine , (P)-Y751 PDGFRβ , CrkII , (P)-Y439 Abl2 (Thermo Fisher Scientific), (P)-Y221 CrkII , Abl2 , HA (12CA5 purified from hybridomas), PR4, a rabbit polyclonal antiserum recognizing the C-terminal 13 amino acids of the human PDGFRβ was a generous gift from Daniel Dimaio .HEK293 cells were transiently transfected with WT or mutant full-length PDGFRβ using polyethylenimine transfection. At 48 h after transfection, cells were serum starved overnight with Dulbecco's modified Eagle's-only medium. PDGFRβ was then stimulated with 100 nM of PDGF-BB for 10 min. Cells were lysed in radioimmunoprecipitation assay buffer . Lysates (500 μg) were incubated with 1 μM of Abl2 SH2-linked beads in a 500-μl reaction overnight before washing and resuspending in LSB. Pulldown products were boiled, separated by SDS-PAGE, and then immunoblotted for PDGFRβ.Abl2-HA was immunoprecipitated from HEK298 cells lysed in Triton lysis buffer . Cell lysate  was precleared with 20 μl of Protein A/G Plus Agarose bead (Thermo Fisher Scientific) for 1 h at 4 °C. The precleared supernatant was incubated with 20 μl of beads that had been incubated overnight with anti-HA antibody (12CA5) for 1 h at 4 °C. Immunoprecipitates were washed three times with 0.5 ml of lysis buffer, suspended in 40 μl of LSB, and separated by SDS-PAGE for immunoblot analysis.abl1−/−abl2−/− DKO KO mouse 3T3 fibroblasts were serum starved overnight before stimulation with 100 nM of PDGF-BB for 10 min. Cells were lysed in radioimmunoprecipitation assay buffer . Lysate (40 μg) in LSB was boiled, separated by SDS-PAGE, and then blotted for CrkII, (P)-Y221 CrkII, PDGFRβ, and (P)-Y751 PDGFRβ. About 500 μg of cell lysate was precleared with A/G-agarose beads (Pierce Protein Biology) and incubated overnight at 4 °C with Ar11 antibody beads to immunoprecipitate Abl2. Immunocomplexes were incubated with protein A/G-agarose beads for 1 h at 4 °C before spinning down, washing, and resuspending in LSB. Pulldown products were boiled, separated by SDS-PAGE, transferred, and then immunoblotted for Abl2 and phosphotyrosine.WT and In vitro phosphorylated Abl2 (50 mg) was reduced with DTT , alkylated with iodoacetamide , and then digested with trypsin in a trypsin-to-protein ratio of 1:20 at 37 °C overnight. The reaction was quenched by 1% formic acid . The resulting peptides were dried using a SpeedVac , desalted with Pierce C18 tips (Thermo), and the phosphopeptides were enriched by Titansphere Phos-TiO Kit (GL Science) according to the manufacturer's protocol.E. coli database  using the Sequest HT algorithm. The Proteome Discoverer, version 2.5 (Thermo Fisher Scientific) was used for database search with the following parameters: enzyme, trypsin (full); parent mass error tolerance, 10 ppm; fragment mass error tolerance, 0.6 Da (monoisotopic); maximum number of missed cleavage sites, two; variable modifications of +15.995 Da (oxidation) on methionine, and +79.996 Da (phosphorylation) on serine, threonine, and tyrosine; fixed modification of +57.021 Da (carbamidomethylation) on cysteine. Identified peptides were validated through the false discovery rate, for which thresholds were 0.01 and 0.05 for strict and relaxed target false discovery rate, respectively.The enriched phosphopeptides were analyzed by MS using a Dionex Ultimate 3000 nano-UHPLC system LC coupled with a Thermo Scientific Orbitrap Velos Pro mass spectrometer. The Dionex Ultimate 3000 system was equipped with an Acclaim PepMap 100  trap column and an Acclaim PepMap RSLC  analytical column. Chromatographic separation of the phosphopeptides was achieved using a linear gradient consisted of ultrapure water  with 0.1% FA and acetonitrile  with 0.1% FA, where the gradient was from 5% B at 0 min to 40% B at 105 min. The source voltage was set in 2.1 kV, and the capillary temperature was set at 320 °C. The MS analysis was performed using a top-10 data-dependent analysis in the positive ion mode with dynamic exclusion option enabled for 30 s. MS/MS spectra were collected using collision-induced dissociation. Data were searched against a custom-made database, which included the sequence of recombinant Abl2 in the background of via the PRIDE (All data are contained within the article and the he PRIDE  partner This article contains The authors declare that they have no conflicts of interest with the contents of this article.


Dear Editor,In this study, measurement of target inhibition of lysyl oxidase‐like 2 (LOXL2) in a high throughput manner from tissue lysates and blood was achieved by the tailored design of an activity‐based probe (ABP), PXS‐5878. Effective inhibition of LOXL2 enzymatic activity in vitro, in vivo and in a phase 1 study in healthy humans was demonstrated by a novel small molecule, PXS‐5338. In contrast to the encouraging results obtained with PXS‐5338, our study also revealed the inability of a LOXL2 antibody (AB0023) to effectively inhibit the target, thereby providing a plausible explanation for the failure of the corresponding humanised antibody, simtuzumab, in the clinic.Lysyl oxidases are a family of five enzymes critically responsible for the formation of cross‐linked collagen and elastin, the hallmarks of fibrosis and stroma.PXS‐5878 Figure , a novel50 of 35 nM after 30 min pre‐incubation and full inhibition achieved at concentrations above 300 nM  and the PXS‐5878/Simoa® platform used to measure enzymatic activity ex vivo. As in plasma, almost complete inhibition of LOXL2 activity in the lung occurred at 4 h Figure , confirmca. 80% of enzyme activity returning within 24 h. At doses of 200 or 400 mg, PXS‐5338 achieved complete inhibition at 4 h, with 50% or 70% inhibition remaining at 24 h, respectively. These results tallied with the pharmacokinetic profile of PXS‐5338 at the different dose levels (Figure 50, enabling target engagement (Figure To confirm the therapeutic potential of the anti‐fibrotic PXS‐5338 Figure  in humans Figure , with drt Figure . Taken tOur work underscores the importance of understanding both the target engagement properties of an inhibitor, as well as target resynthesis rate following inhibition, to enable an accurate and successful translation of preclinical data to clinical efficacy. In the case of simtuzumab it seems reasonable to suggest insufficient antibody concentrations, and low target inhibition, caused the clinical failures. The development of a bespoke ABP, PXS‐5878, enabled accurate measurement of the inhibition achieved by LOXL2 inhibitor PXS‐5338, as well as the rate of resynthesis of the enzyme. Moving forwards this knowledge will prove crucial for effective drug discovery and development efforts focussed on this important class of enzymes.All authors are current or former employees of Pharmaxis except Mary Brock and Christina Raso who are employees of Quanterix. All authors have read and approved the manuscript.Supporting informationClick here for additional data file.


The next section describes the neurophysiological evidence that linguistic negation interacts with response inhibition, along with the suggestion that both functions share inhibitory mechanisms. Finally, the manuscript concludes that the functional relation between negation and inhibition observed at the mechanistic level could be easily integrated with predominant cognitive models of negation processing.Negation is known to have inhibitory consequences for the information under its scope. However, how it produces such effects remains poorly understood. Recently, it has been proposed that negation processing might be implemented at the neural level by the recruitment of inhibitory and cognitive control mechanisms. On this line, this manuscript offers the hypothesis that negation reuses general-domain mechanisms that subserve inhibition in other non-linguistic cognitive functions. The first two sections describe the inhibitory effects of negation on conceptual representations and its  In contrast, the inclusion of a negative marker in the same sentence (The flower is not yellow) calls for representing both the negated situation (a yellow flower) and what might be the factual situation . Thus, according to this theory, negation is representationally more complex because it requires two instead of only one mental representation.Negation markers such as To arbitrate between the above two general explanations, most cognitive research on negation has mainly focused on figuring out how it gets represented during comprehension. In contrast, little attention has been paid to other crucial elements for a complete cognitive model of negation: the processes and mechanisms that guide and implement these representations. Certainly, the two-step simulation theory does assume that the transition between simulations implies processes that guarantee the suppression of the negated situation, as well as its replacement by the factual one. Yet, the specific details of these processes have generally not been provided. Notably, this situation has changed in the last years. Several groups have started to independently emphasize the relevance of general-domain cognitive control mechanisms for negation processing, connecting in this way the study of negation with broader conceptualizations in psychology and neuroscience of language  the BOLD signal from premotor and motor cortical areas , which is performed after sentence completion and presumably reflects the activation level of the concept within the simulation of the whole sentence. In contrast, cortico-spinal reactivity and motor action interference are indirect, and to some extent automatic measures, which do not require explicit judgments on the negated information, possibly indexing early meaning processing. Therefore, embodied effects are not snapshots of the working memory status for the whole sentence representation, but reflect the low-level mechanisms that serve the integration of lexical meaning . Children and adults produce such negative expressions to reject an object, or to somehow stop or prevent an imminent action, establishing thereby a strong association between the verbal markers of negation and the rejection and prevention of an action. Moreover, in this early stage of linguistic development, children often talk to themselves using negative expressions as self-prohibition commands, showing that they have already internalized negation as an important tool for self-regulation  derive from previously acquired functions, with the formers being just logically and metacognitively sophisticated versions of rejection , with disagreement expressions as ontogenetically bridging between them , the tendency is generated directly on each trial, wherein a cue is first displayed instructing the participant to select one out of the two possible responses, followed in some trials by a signal presented with a short and variable delay requiring them to stop the selected response. Thus, similar to negation-induced suppression, response inhibition requires firstly the activation of a response program which would later be stopped or suppressed if inhibition is to be successful. To some extent, this means that both can be considered functionally equivalent, but falls short of demonstrating that negation shares inhibitory mechanisms with response inhibition. Empirical evidence in two directions is needed: first, directly demonstrating that negation and inhibition activate similar brain networks independently; second, finding mutual influences between them when they are executed simultaneously, which could be manifested in behavioral facilitation or interference, or interactions at the neurophysiological level.The creation of a strong tendency to respond is the critical process in response inhibition tasks. For the Go/NoGo task, this tendency is settled by presenting, in fast succession, a larger number of response  than inhibition  trials. In the In sum, both the ontogenetic trajectory and the neural reuse theory are arguments in favor of the hypothesis that negation reuses the basic and domain-general inhibitory mechanisms frequently associated with response inhibition. More broadly, this conclusion is also consistent with other phylogenetic conceptualizations of language origin, especially those arguing that language co-opted and co-evolved with already existing complex motor functions, which were there to support planning in the face of lithic technology  or to prohibit the action in NoGo trials . Therefore, the interaction between negation and response inhibition in prior studies might well be caused by this close similarity in functions and meanings between the negative imperative sentences of the comprehension task and the mental representations of the NoGo cue for the inhibition task. To rule out this alternative account, Liu et al. (in preparation) employed a dual-task Go/NoGo paradigm with existential instead of imperative sentences as stimuli, for example, “There are already/no apples in the fridge”. For these sentences, the Go/NoGo cues appeared 300 ms after the presentation of the object noun . The results showed again an interaction between Go/NoGo cue and sentence polarity. In this case, the interaction arose in the P3 component of the fronto-central N2-P3 ERP complex, which shows generally larger amplitudes for NoGo than Go trials  tested this prediction by adapting the original Go/NoGo dual task paradigm. The main change consisted in the relocation of the Go/NoGo cues within the trial. So, instead of appearing shortly after the verb onset, the cues were presented 1200 ms before the onset of the first sentential word. This allowed to analyze the influence of the Go and NoGo cues on the ERP waveforms elicited by the word-by-word sentence comprehension. As predicted, they found an interaction between Go/NoGo cue and sentence polarity. Again, there was no difference between affirmative and negative sentences after the Go cue (response). In contrast, after the NoGo cue (inhibition), there was a sustained ERP amplitude difference between affirmative and negative sentences, which started just after the polarity marker onset. Negative sentences following NoGo cues showed more negative waveforms than all the other conditions. In addition, brain sources analysis identified two inhibition-related brain regions as the likely origin of this interaction, the right inferior frontal gyrus (rIFG) and left middle frontal gyrus (lMFG). In both sources, negative sentences after NoGo cues showed stronger activations than all the other conditions. The sustained ERP effect of this study cannot be directly interpreted as a neural signature of inhibitory mechanisms. The is reason is that, unlike the fronto-central theta power and N2-P3 ERP complex, it does not result from comparing inhibitory with non-inhibitory trials in the context of a response inhibition task. Nonetheless, this ERP effect reveals an interaction in the predicted direction, which encourages the idea that linguistic negation reuses inhibitory processes; an interpretation that is strengthened by the source-localization of the interaction at regions that are core components of the inhibitory neural network ; in contrast, negation has no effect when these mechanisms remain in a dormant state . Secondly, it indicates that the processing of negative sentences is affected by prior activations of inhibitory mechanisms, but not by the prior delivering of a response. Thus, it shows that negation and response inhibition modulate each other in a rather specific way. Finally, it is worth noting that the reuse hypothesis could have been readily disproved if other results had emerged in the above research. For example, main effects of either polarity or response inhibition, without any interaction between them, had spoken against a sharing of neural resources. And similar doubts had arisen as well from interactions driven by either an effect of polarity on response trials, instead of an effect on inhibition trials, or an effect of trial type (either response or inhibition) on affirmative sentences, but not on negatives.Although negation modulated the SSRT in the SST, all the studies using the Go/NoGo task failed to find behavioral evidence of negation-to-inhibition influence. The lack of modulation in these studies is likely due to the fact that both response execution (Go) and inhibition (NoGo) showed a virtual ceiling effect. In the standard Go/NoGo task, a short inter-trial interval is normally implemented to increase the errors rate  the semantic relatedness effect that is typically obtained for the N400 component  with repetitive TMS before asking participants to complete a linguistic comprehension task, and examining whether, as predicted, the inactivation has functional consequences for the comprehension of negative sentences. Another avenue for further research might be to test the generalizability of the interaction between negation and inhibition, exploring how negation interacts not only with response inhibition tasks but also with cognitive inhibition tasks, or analyzing whether the inhibitory hypothesis of negation can be extended to functional types of negation other than imperative and existential sentences. Reasonable predictions here are that negation will influence the inhibitory processes triggered by more cognitively-oriented inhibition tasks (e.g., direct suppression of memory retrieval, Engen & Anderson,