Self-regulation refers to the ability to monitor and modulate emotions, behavior, and cognition, which in turn allows us to achieve goals and adapt to ever changing circumstances. This trait develops from early infancy well into adulthood, and features both low-level executive functions such as reactive inhibition, as well as higher level executive functions such as proactive inhibition. Development of self-regulation is linked to brain maturation in adolescence and adulthood. However, how self-regulation in daily life relates to brain functioning in pre-adolescent children is not known. To this aim, we have analyzed data from 640 children aged 8–11, who performed a stop-signal anticipation task combined with functional magnetic resonance imaging, in addition to questionnaire data on self-regulation. We find that pre-adolescent boys and girls who display higher levels of self-regulation, are better able to employ proactive inhibitory control strategies, exhibit stronger frontal activation and more functional coupling between cortical and subcortical areas of the brain. Furthermore, we demonstrate that pre-adolescent children show significant activation in areas of the brain that were previously only associated with reactive and proactive inhibition in adults and adolescents. Thus, already in pre-adolescent children, frontal-striatal brain areas are active during self-regulatory behavior. •Children with higher levels of self-regulation employ more proactive inhibition.•During proactive inhibition, children aged 8–11 show activation in frontal-cortical areas.•Children higher in self-regulation exhibit more cortical-subcortical coupling.•Children aged 8–11 show similar brain activation as adults during inhibition. This capacity is commonly referred to as self-regulation. Self-regulation has been defined as the ability to monitor and modulate emotions, behavior, and cognition, that in turn allows us to achieve goals and adapt to changing circumstances . This caSelf-regulation can be studied across development in terms of executive functions . One sucIn the case of inhibition, it has been shown that while children at the end of childhood can inhibit prepotent responses, a low-level executive function, they further develop this skill during adolescence . This imThis integration of executive functions, which allows for proactive inhibitory control, has been theorized to depend upon the establishment of frontal control over the rest of the brain, in particular subcortical regions . The shiHowever, these previous studies included adolescents and young adults, and we therefore do not yet know if and how individual differences in the state of executive function development and brain maturation pre-adolescence are linked to levels of self-regulation. It may very well be that children who show higher levels of self-regulation are better able to engage relevant brain regions during the execution of executive functions. This may be coupled with increased functional coupling between regions that will begin to form brain networks. For instance, stronger frontostriatal connections have been linked to better delay of gratification . ConsequThe central hypothesis is that children who show high levels of self-regulation in daily life will also show higher levels of reactive and proactive inhibitory control. Behaviorally, we expect children scoring higher on self-regulation, to demonstrate more proactive inhibitory control during the task, resulting in the slowing down of responses in anticipation of a stop-signal on go trials . In the 22.1We requested the largest available data sample from the YOUth cohort study , which p2.2The full-scale Early Adolescent Temperament Questionnaire-Revised Short Form for parents (EATQ-R-SF: translated in Dutch by C.A. Hartman) is used to obtain a measure of self-regulatory capabilities . This qu2.3The Pubertal development questionnaire (PDS)  was used2.4We will use behavioral measures and functional MRI data acquired while subjects perform the Stop-Signal Anticipation Task (SSAT)  and success of stopping on stop trials. The SSRT was computed according to the integration method  and pooled across all stop-signal probability levels. This measure has been used as a behavioral indicator of inhibitory control , and has2.6The experiment was performed on a Philips  Ingenia 3.0 T MRI scanner at the UMC Utrecht. Functional images consisted of whole-brain, T2 * -weighted echo planar images with blood oxygen-dependent contrast  in a single run of 595 dynamic scans. A T1-weighted image from the same session was used for within-subject registration purposes.2.72.7.1http://www.fil.ion.ucl.ac.uk/spm/). Preprocessing included realignment to correct for head motion, where the time-series were registered by a least-square approach and a rigid-body transformation. Then slice timing correction was applied by interpolating all slices in time to the center slice. Even with short repetition times and multiband, slice timing correction has been demonstrated to benefit results  can result in holes inside the mask for some subjects. This was due to either significant movement (possibly exacerbated by the multiband sequence), or general scanner artefacts. It is difficult to assess retrospectively whether signal artefacts are primarily due to scanner issues or motion artefacts. Subjects with voxels below the signal threshold within the brain, excluding cerebellum, were removed from the analysis. The total number of subjects excluded with this method was 151 , leaving a dataset of 645 children . During the subsequent analyses, 5 children were excluded from the dataset by being either an outlier in terms of signal (n = 2) or behavior (n = 3), leaving a final dataset of 640 children. There were 86 left-handed children in our sample, however all were instructed to perform the task using the right hand. As we did not have specific hypotheses on how handedness affects inhibitory motor control during the task, we did not exclude these participants from our analyses. We have rerun all analyses with right-handed children only to ensure that left-handedness did not change the significance of our main findings. These analyses are added as a 2.7.3Functional images were submitted to a general linear model. Activation was time‐locked to the presentation of the cue and to the response period with a defined duration of 0 s, and was modeled using a hemodynamic response function based on stop‐signal probability. On average the inter‐trial interval was 1000 ms (ranging from 500 to 1500 ms), and served as an implicit baseline. Six realignment parameters were added as regressors of no interest to correct for residual signal changes related to head motion. All data were high‐pass filtered with a cut‐off of 128 s to control for low‐frequency drifts. For each participant, we computed two contrast images: (1) activation during successful stop trials versus failed stop trials (reactive inhibition), (2) activation during go trials with a stop-signal probability versus trials without (proactive inhibition). The first contrast is used to investigate the specific activation patterns associated with successful inhibition, based on previous research employing the same paradigm . The lat2.7.4t-test group-level analysis, resulting in two group-level brain maps. To determine effects of sex and age on activation in these contrasts, regression analyses were performed on predefined regions of interest (ROIs), created using the MarsBaR toolbox (http://marsbar.sourceforge.net). For proactive inhibition the regions are based on the activation patterns in young adults from t-test was used to test for significant activation in the selected ROI for the two contrasts. Mean activation levels of all ROI were subsequently subjected to a regression analysis with age as continuous predictor, and sex as a between-subject variable. No additional manipulations or corrections were performed on the independent variables. The statistical threshold for significance was set at p = 0.05/3 = 0.017, to correct for multiple comparisons (Bonferroni correction with three ROIs per contrast). Figures of the ROIs for proactive and reactive inhibition are included in the The two contrast images per subject were subjected to a one-sample 2.7.5Functional coupling analyses were performed using psychophysiological interaction (PPI)  to inves2.7.6To investigate potential activation patterns outside the predefined ROIs, an additional whole-brain group analysis was conducted on the contrasts defined in 33.1F = 19.37, p < 0.001, with motion being significantly lower in older than younger children. We performed additional Pearson's correlation tests to see whether movement during the task was related to our behavioral measures of reactive and proactive inhibition, or scores of self-regulation. Such an association was found in a previous fMRI study investigating inhibitory control  = 0.73, p = 0.39, but did show an effect of age  control , and thi3.2F = 104.84, p < 0.001 (r = −0.38), but not with sex F = 3.08, p = 0.08, indicating that older children where faster at inhibiting responses than younger children. Inhibition accuracy also improved with age F = 26.67, p < 0.001, regardless of sex F = 1.00, p = 0.32. Slowing down responses in anticipation of a stop-signal is a measure of proactive inhibition. Participants slowed their responses more with increasing stop-signal probability, F = 248.71; p < 0.001, regardless of sex, F = 2.52, p = 0.11. This proactive response slowing was not associated with age F = 2.97, p = 0.09, nor with sex F = 0.48, p = 0.49. While older children were both significantly faster and more accurate in response inhibition than younger children, they did not show an increase in response slowing.We then assessed effects of sex and age on reactive and proactive behavioral measures from the task. We found that reactive inhibition latency (SSRT) was significantly associated with age F = 6.48, p = 0.01, regardless of sex F = 0.54, p = 0.46  = 2.57, p = 0.11; nor sex, F = 2.59, p = 0.11; nor an interaction effect, F = 0.92, p = 0.34. To test our hypothesis that children scoring higher on this scale show better inhibitory control during the task, a regression analysis was conducted for reactive and proactive measures of inhibition. There was no significant main effect of the scores on SSRT (e.g. reactive inhibition), F = 0.43, p = 0.51. However, we did find a significant relation between self-regulation and proactive response slowing on the task, p = 0.46 .Fig. 2Pr3.33.3.1t-test was used to test for significant activation in the selected ROI. For reactive inhibition we found deactivation in the left motor cortex in the contrast of successful stop trials versus failed stop trials, t(639) = −2.39, p = 0.02, indicating suppression of the motor cortex during successful inhibition. However, this result does not survive correction for multiple comparisons (Bonferroni with p < 0.05/3 = 0.017). In addition, there was significant bilateral activation in the striatum, left t(639) = 10.67, p < 0.001, and right t(639) = 10.65, p < 0.001. For proactive inhibition, there was significant activation in the network associated with proactive inhibition: the mid frontal cortex, t(639) = 9.11; p < 0.001, the right parietal cortex, t(639) = 6.90; p < 0.001, and the right putamen t(639) = 4.42; p < 0.001. These results survive correction for multiple comparisons (p < 0.05/3 = 0.017). A linear regression analysis with age as a continuous variable and sex as a within subject variable yielded no significant effects, see the A one-sample , F = 6.37, p = 0.01 (r = 0.11), with no interaction effect for sex F = 0.07, p = 0.79   .Fig. 3Se3.3.2, F = 4.93, p = 0.03. There was no effect of sex, F = 1.71, p = 0.19, though there was an interaction effect between sex and age, F = 4.66, p = 0.03. A post-hoc regression analysis revealed that this association with age, was specifically present for girls F = 10.52, p < 0.01 (r = 0.17), but not for boys F = 0.01, p = 0.92 (r = 0.01); (Bonferroni corrected for multiple comparisons at p < 0.05/2 = 0.025). An additional analysis splitting the two sexes in groups based on pubertal development, revealed that boys with mid pubertal characteristics had significantly more coupling between the two ROI, than boys in pre- and early puberty t(205) = 2.95, p < 0.01. There was no such difference for girls.To investigate the degree to which areas of the brain are functionally connected, we tested for effects of sex and age on functional coupling between cortical and subcortical ROI of the brain. During reactive inhibition, there was an effect of age on functional coupling between the right striatum and the left motor cortexF = 7.21, p = 0.01. There was no effect for sex F = 2.13, p = 0.14, but there was an interaction effect between sex and age, F = 10.26, p < 0.001. A post-hoc regression analysis revealed that the association with age was specifically present for boys F = 15.56, p < 0.001 (r = 0.23), but not for girls F = 0.03, p = 0.85 (r = −0.01); (Bonferroni corrected for multiple comparisons at p < 0.05/2 = 0.025). There was no difference in coupling based on pubertal development, for either sex. For the right parietal cortex, there were no effects of age and sex altogether.During proactive inhibition, regression analyses showed that activation in the striatum was more strongly coupled with the mid frontal cortex for older than younger children, F = 4.18, p = 0.04; but no interaction with sex, F = 3.08, p = 0.08 , and proactive inhibition  in a cohort of 640 healthy children aged 8–11 years. Behaviorally, we find that even in the narrow age-range spanning 3 years, there are advances in inhibitory control speed and accuracy. Both boys and girls slowed down their responses in anticipation of a stop, demonstrating that proactive inhibitory control is already present. Notably, we found that an independent measure of self-regulation was associated with the amount of proactive response slowing on the task. In the brain, we found significant activation in brain regions associated with reactive and proactive inhibition. During reactive inhibition, there was increased activation in the bilateral striatum. During proactive inhibition, there was increased activation in the right mid frontal gyrus, the right inferior parietal lobe and the right putamen. Activation in these regions was not associated with age and did not vary between boys and girls. However, self-regulation scores were positively associated with activation in the frontal cortex during proactive inhibition. Finally, we found several age-related changes that differed between the sexes. In girls, functional coupling between the right striatum and the left motor cortex increased with age during reactive inhibition. In boys, fronto-striatal functional coupling  increased with age during proactive inhibition. In our sample, reactive inhibition improved significantly in terms of speed and accuracy in the span of three years. Both older boys and girls are more skilled at inhibiting responses than their younger counterparts, in line with other studies . NotablyDuring proactive inhibition, children in our sample predominantly exhibited activation in cortical areas such as the right parietal cortex and right mid frontal cortex, with the activation cluster extending into the striatum. Response inhibition studies have commonly reported an association between striatal activation and the anticipation of stop‐signals . The broWe saw a significant association with age and functional coupling of the right striatum and the right mid frontal cortex, specifically for boys. Previous research has shown increases in functional connectivity between these regions in an older sample of children . During Our aim was to determine whether children who show high levels of self-regulation also show high levels of reactive and proactive inhibitory control. We found that children with higher self-regulation scores demonstrated more response slowing during the task. It is presumed that the improvement in self-regulation in adolescence is in part due to the effective integration and coordination of executive functions, leading to the rise of proactive response strategies that allow for a more efficient processing by engaging inhibitory functions prior to having to inhibit responses . In term4.1A number of limitations need to be considered. First, our results are based on an fMRI paradigm in children. In an adult sample this specific task has a moderate reliability , and datHead motion can produce spurious signal fluctuations that may confound measures of functional coupling . While w4.2Our data shows for the first time in children, that self-regulation is related to behavioral and neural correlates of inhibitory control. First, we showed that even children at a young age exhibit proactive inhibitory control over their actions, while reactive inhibition improved with age. Children scoring higher on self-regulation demonstrated more proactive inhibitory control in terms of slowing down their responses, higher activation in the mid frontal cortex and more functional coupling between subcortical and cortical areas. This paper does not provide a definitive answer to how increases in self-regulation during childhood relate to changes on a neural level, however, this cross-sectional data does shed light on several neural correlates that may be of importance in development. The associations between self-regulation and neural underpinnings in our sample undoubtably are limited in size, as such this data may benefit from optimizing methods of reducing noise that may be present in both questionnaire and brain data. When cohort data from a second wave will be made available, future research can employ longitudinal designs to further investigate the neural aspects of self-regulation. In theory, the state of self-regulation in the brain at a young age could subsequently be used to make predictions on well-being, school results and drug usage in adolescence.Data is accessible under restriction as outlined in the YOUth Data Access Protocol on the data access page of the YOUth website (https://www.uu.nl/en/research/youth-cohort-study/data-access). Access to the data used in the current publication for verification purposes is possible, and requests should be directed at the corresponding author.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Pimelia latreillei inhabiting the polluted site at Zawya Abd El- Qader, Alexandria, Egypt. Beetles were collected from the vicinity of five factories. The genotoxic effects of environmental exposures to industrial heavy metals were monitored using a broad range of assays, including energy-dispersive X ray microanalysis and X-ray diffraction (SEM and EDX)), qRT-PCR gene expression assay, micronuclei formation, and transmission electron microscope (TEM). Energy dispersive X-ray microanalysis for the soil and testicular tissues of beetles collected from the polluted site revealed a higher percentage of heavy metals than the beetles collected from the reference site . To analyze/monitor genotoxicity in P. latreillei sampled from the polluted site, the transcription levels of levels of heat shock proteins (Hsps) and accessory gland seminal fluid protein (AcPC01) in testicular tissues were recorded. The incidence of micronuclei (MN) formation in the testicular cells was also observed. Quantitative RT-PCR (RT-qPCR) analysis was carried out to detect the changes in the gene expression of the aforementioned proteins. Genes encoding heat shock proteins  were significantly overexpressed (> 2-fold) in specimens sampled from the polluted site; however, AcPC01 gene expression was under-expressed (<1.5-folds). The incidence of MN was significantly increased in specimens sampled from the polluted site. Ultrastructure anomalies (nuclear and cytoplasmic disruption) were also observed in the testicular cells of the beetles sampled from the polluted site compared to those sampled from the unpolluted site. Our results, therefore, advocate a need for adequate measures to reduce increasing environmental pollution in the urban-industrial areas.The present research aims to evaluate the impact of industrial processes and anthropogenic activities on the beetle  Heavy metals released from industrial processes and anthropogenic activities have an adverse effect on humans and the ecosystem , 2. The As metal ions traverse cell barriers, the balance of extracellular and intercellular ions is interrupted, which affects membrane permeability . TherefoGenotoxic agents can induce several health disorders, such as structural abnormalities and growth retardation . ConsequThe physiological response of an organism exposed to a stressor triggers the synthesis of specific proteins to repair possible damage caused by such exposure. These proteins are named molecular chaperones or heat shock proteins (Hsps) , 24. TheIn insects, seminal fluid proteins (SFPs) are produced by the accessory glands (AGs), vesicula seminalis, ejaculatory duct, ejaculatory bulb, and testes. The SFPs include protease inhibitors, lectins, prohormones, peptides, and protective proteins, such as anti-oxidants present in the ejaculate of all eukaryotes . During Micronuclei (MNs) are biomarkers used to monitor genotoxicity . They arThe ultrastructure of the internal organs of insects is a competent tool in determining the effect of toxins. The bioaccumulation of heavy metals into insects can be used as a monitor for environmental pollution. Insects possess special structures, spherites for accumulating trace metals . AccumulPimelia latreillei, this study clarified the genotoxic effect of heavy metals originating from anthropogenic sources and industrial effluents. We also observed the ultrastructure damages to the testicular cells, which may be caused by heavy-metal pollution.Using a biomonitoring beetle, The ethical rules for animal regulations were followed and approved by Faculty of Science, Alexandria University committee in March 2018 (Alex-01-2018). All animal procedures were conducted in accordance with the local Guiding Principles for the Care and Use of Laboratory Animals as adopted and promulgated by Alexandria University.Two sites were chosen for sampling the coleopteran insects. The sample locations were in public areas. Site A at Sidi Kirier, north coast of Alexandria, Egypt (latitude 31.016250°N and longitude 29.635663°E), was considered the reference site. Some ornamental plants, grasses, and shrubs were cultivated at this site. Site B at Zawya Abd El-Qader, southwest Alexandria, Egypt (latitudes 30° 33’ - 31° 30’ N and longitudes 29° 50’ - 30° 45’ E), was considered as the polluted site. This area covered a vast cultivated land representing most Abis and El-Nahada farms. These lands were subjected to aerosol deposition from various industrial activities located in the western part of Alexandria city . From meteorological data, the wind direction was found to be northwest (average speed between 2.75 m/s and 7.14 m/s), which might accelerate the delivery of contaminants over a long distance.P. latreillei were collected randomly from ten sampling areas (1 m2 each) at each site in June 2018. Simultaneously with the beetle collection, soil samples were collected at a depth of 25 cm below the surface from the mentioned sites. The ten areas at Zawya Abd El Qader (the polluted site) were selected near the aforementioned companies (two areas around each company). The mean air temperature in June ranged from 28°C to 36°C and the mean relative humidity was 65%, with nearly no differences between the two sites. About 200 insects were collected from each site. The specimens were sexed, and about 90 males were preserved alive in local soil and plants in glass containers until processing. Beetles were anaesthetized with absolute ethanol (95%), then dissected under a dissecting microscope in a drop of Ringer’s physiological solution. The abdominal cavity was opened and the testes were extracted.Live specimens of Pimelia latreillei. The studied insect belonged to Tenebrionid beetles.The specimens were identified at the Faculty of Agriculture, Alexandria University (Department of Entomology) as Energy-dispersive X-ray microanalysis (EDX) was used to determine the percentages of different metals in the sieved soil and testicular tissues. This analysis was applied using a JEOL (JSM-5300) scanning microscope at the Electron Microscope Unit (E.M.), Faculty of Science, Alexandria University, Egypt. The accuracy of the analytical results was determined using eight samples of soil from each site and testicular tissues obtained from eight male beetles.The identity of each peak was assigned automatically by the SEM EDX software. Line intensity was measured for each element in the sample and for the same elements in calibration standards of known composition. At X500, a stationary spot was analyzed at random for 110 s.P. latreillei with TRIzol® Reagent . To ensure DNA digestion, 1 U of RQ1 RNAse-free DNAse  was added to the RNA, and the mixture was re-suspended in DEPC-treated water. Total RNA purity was assessed by the 260/280 nm ratio (between 1.8 and 2.1). To ensure integrity, ethidium bromide stain analysis of 28S and 18S bands by formaldehyde-containing agarose gel electrophoresis was performed. Aliquots were used for reverse transcription (RT).Total RNA was isolated from eight samples of testicular tissues and accessory glands of male P. latreillei was reverse transcribed into cDNA in a total volume of 20 μl using Revert AidTM First Strand cDNA Synthesis Kit . From the total RNA, 5 μg was used with a master mix (MM) consisting of 50 mM MgCl2, 5x reverse transcription (RT) buffer , 10 mM of dNTP, 50 μM oligo-dT primer, 20 U ribonuclease inhibitor (50 kDa recombinant enzyme to inhibit RNase activity), and 50 UM- MuLV reverse transcriptase. Each sample mixture was centrifuged for 30 s at 1000 g. The mixture was then transferred to the thermo-cycler . The RT reaction started at 25°C for 10 min, continued at 42°C for 1 h, and was stopped after heating at 99°C for 5 min, followed by cooling in an ice chamber.Poly (A) + RNA isolated from testicular tissues and accessory glands of Step One™ Real-Time PCR System from Biosystems  was used to determine the beetles’ cDNA copy number. PCR reactions were set up in 25 ml reaction mixtures containing 12.5 ml 1× SYBR® Premix Ex TaqTM , 0.5 ml 0.2 mM sense primer, 0.5 ml 0.2 mM antisense primer, 6.5 ml distilled water, and 5 ml of cDNA template.−ΔΔCT methods.The reaction program was divided into 3 steps. Step (1) was at 95.0°C for 3 min. Step (2) consisted of 40 cycles in which each cycle was subdivided into 3 steps: (a) at 95.0°C for 15 s; (b) at 55.0°C for 30 s; and (c) at 72.0°C for 30 s. Step (3) consisted of 71 cycles which started at 60.0°C and then increased about 0.5°C every 10 s up to 95.0°C. Primer quality was measured using melting curve analysis that was executed at the end of each RT-qPCR . Each exSamples of beetle testes were prepared for MN analysis. The testes were immersed in saline solution , incubated in tap water as a hypotonic treatment for 50 min to let the cells swell, allowing the mononuclear and binuclear to separate. 3 μg/ml of cytochalasin B was used to block cytokinesis. Testis was spread on coded slides, fixed in Water: Ethanol: Acetic Acid by vol (4:3:3) for 20 min, Ethanol: Acetic Acid,1:1(v/v) for 30 min, and Acetic Acid (100%) for 24 h, air dried, stained with Giemsa dye 1M diluted in 30 M buffer  for 10 min. About 1000 testicular cells were scored for each slide under a light microscope at a magnification of 1000× to determine the frequency of MN , 44. OthMicronuclei (MN) are illustrated in 4F1G) in 0.1 M phosphate buffer solution (pH 7.2) at 4°C for 3 h, followed by post-fixation with 2% osmium tetroxide (OsO4) in the same buffer for 2 h. A buffer was used to wash the samples, which were dehydrated at 4°C through a graded series of ethanol, then embedded in Epon-Araldite mixture in labeled beam capsules. Ultrathin sections (0.06–0.07 μm thick) were cut from the testes for examination under a transmission electron microscope (TEM). The ultra-thin sections were placed on 200 mesh copper grids, which were double-stained with uranyl acetate for 30 min and lead citrate for 20–30 min (Reynolds 1963). Electron micrographs were taken at several magnifications. Scoping and photographing the grids were achieved by JEOL 100 CX TEM, at Electron Microscope Unit, Faculty of Science, Alexandria University, Egypt.Testes were fixed immediately in 4% formaldehyde and 1% glutaraldehyde  . The ShaP. latreillei sampled from the inspected sites  and eight elements in the samples from site B . A significant elevation in the percentages of Ca, Na, Zn, Cu, and Al was observed in the testicular tissue of beetles collected from the site B compared with those at site A, except for K (not detected), with detection of Fe, Pb, and Cd . A significant elevation in the percentages of metals was reported at the site B compared with those at site A, except for K, with detection of Pb and Cd . However, and Cd .P. latreillei. The Hsp60 , Hsp70 , and Hsp90  transcripts were detected to be highly significant, being more than 2-fold in the testicular tissues of beetles collected from the polluted site in comparison with the expression observed in the testicular tissues of beetles collected from the reference site. In particular, relatively high mRNA expression levels of Hsp70 were observed in samples from the polluted site  transcript level, being less than 1.5-fold, was observed in the accessory glands of male P. latreillei collected from the polluted site, compared with that of the reference site  showed euchromatic spermatogonia with a large spherical nucleus, one or two dense nucleoli, and a regular nuclear envelope. Their cytoplasm contained mitochondria distributed around the nucleus. Rough endoplasmic reticulum, Golgi complex, and free ribosomes were also observed  [Hsp mRNA levels were upregulated in the tested insect sampled from the polluted site, particularly Hsp70 gene. Hsp70 protein is the most dominant protein found in the early instars of insects and helps them to overcome adverse conditions [Drosophila melanogaster to different concentrations of metal mixture . They reported that the expression of Hsp genes was altered by increasing the exposure time and that Hsp70 was the more expressed gene. Moreover, Braeckman et al. (1997a), Braeckman et al. (1997b), and Kafel et al. (2012) [Aedes albopictus and Spodoptera exigua exposed to cadmium. Joshi and Tiwari (2000) [Lucilia cuprina.RT-qPCR primers were used to amplify homologous sequences in the available coleopteran species , 43. The. (2011)  and Zhao. (2011) . Inducti. (2011) , 58, 59,nditions . It alsonditions , who exp. (2012) –65 obseri (2000)  noticed SFP analysis gives the perception of evolutionary patterns of reproductive traits . UnderstTribolium (Coleoptera) [P. latreillei is considered a model organism to evaluate the environmental impacts on the tested SFPs. In this study, a primer set was designed from the sequence of the tiger beetle’s AcPC01 protein available from Genbank [SFPs have been described in several insect orders, such as honeybees (Hymenoptera), field crickets (Orthoptera), flies and mosquitoes (Diptera), moths and butterflies (Lepidoptera), and genus eoptera) –71. To d Genbank .D. melanogaster treated with organophosphate compounds, dichlorvos and chlorpyrifos. They reported that the chemicals might either inhibit the regulation of AcPs or cause damage to the cells producing them.Accessory glands of adult male insects are considered the main organs for producing the non-cellular portion of the sperm . SecretoDreissena polymorpha, collected from four monitoring sites in river Drava, with different pollution intensities. They reported that MN formation stayed persistent in the cell until the end of its lifespan. Increased numbers of micronuclei indicate a mutagenic and carcinogenic effect in organisms [The results obtained from MN in the testicular cells of insects collected from the polluted site indicated the intensity of DNA damage. The polluted site possessed significantly higher frequencies of MN than the reference site. The MN illustrate major damage to DNA that cannot be effectively repaired , 76. Klorganisms , 79. Offrganisms  stated trganisms , 82. Therganisms , 83. TheP. latreillei, which represents the same structure as most of the ground beetles among the coleopteran insects. The testes appeared packed with germinal cysts [No pathological features were observed in the male reproductive system of al cysts , 14, 35.P. latreillei are homologous to tenebrionid sperms. They consist of a conoid acrosome, slender nucleus, centriole, and flagellum with a 9+9+2 pattern. There are two similar mitochondrial derivatives and accessory bodies on each side of the axoneme [Our electron micrographs illustrated sperm differentiation, starting from spermatogonia, which exhibited a round nucleus and nucleolus, and a cytoplasm packed with cytoplasmic organelles. Spermatocytes were seen to have a larger nucleus and aggregated mitochondria, preparing for nebenkern formation. There was chromatin condensation in spermatids and dimensioning in the head size through sperm maturation. Similar features were described previously by several researchers , 37, 84. axoneme , 35, 85.At the polluted site, morphological changes in the nucleus and cytoplasm of testicular cells were noticed in most spermatogenic stages. These pathological signs are a consequence of DNA, protein damage, and dysfunction of membranes due to the action of heavy metals , 86, 87.We noticed some degeneration of the flagellar components of spermatids through spermiogenesis, such as axonemal and mitochondrial degeneration. Axonemal degeneration affects sperm motility, which is based on the movement of axonemal microtubules . MitochoThe presence of dense vesicles and vacuoles in the cytoplasm was another pathological feature in our electron micrographs. High levels of heavy metals can be sequestered as dense vesicles of the lysosomal system . Also, tThe function of the parietal cells in insects is similar to the function of Sertoli cells in mammals, which are being responsible for the nourishment of sperm and phagocytosis of the residual cytoplasm , 95. HenP. latreillei is a good biomonitoring insect for evaluating heavy metal toxicity.Finally, heavy metals sequester in particular compartments, such as the nucleus, mitochondria, and ER, which leads to cellular damage associated with changes in gene expression and DNA damage. Thus, Humans benefit from ground beetles because they are active decomposers, recycling and removing feces. They also play a critical role as nutrient recyclers, returning organic matter to the soil via multitrophic interactions. Because they are long-lived and maintain a stable population, they are used in biomonitoring programs to monitor adverse environmental conditions. Genotoxic compounds are found in urban areas featuring industrial activities. Heavy metals are one of the possible genotoxic agents that may induce DNA and protein damage as well as ultrastructure anomalies in testicular cells. These aberrations can affect testicular functions. This study advocates a need for proper measures to be taken to lessen increasing environmental pollution in the urban industrial areas.


Escherichia coli has recently been developed. While this system was able to produce fully modified mersacidin precursor peptide that could be activated by Bacillus amyloliquefaciens supernatant and showed that mersacidin was activated in an additional proteolytic step after transportation out of the cell, it lacked a mechanism for clean and straightforward leader processing. Here, the protease responsible for activating mersacidin was identified and heterologously produced in E. coli, improving the previously reported heterologous expression system. By screening multiple proteases, the stringency of proteolytic activity directly next to a very small lanthionine ring is demonstrated, and the full two-step proteolytic activation of mersacidin was elucidated. Additionally, the effect of partial leader processing on diffusion and antimicrobial activity is assessed, shedding light on the function of two-step leader processing.The ribosomally synthesized and post-translationally modified peptide mersacidin is a class II lanthipeptide with good activity against Gram-positive bacteria. The intramolecular lanthionine rings, that give mersacidin its stability and antimicrobial activity, are specific structures with potential applications in synthetic biology. To add the mersacidin modification enzymes to the synthetic biology toolbox, a heterologous expression system for mersacidin in  The class II lanthipeptide mersacidin is a ribosomally synthesized and post-translationally modified peptide RiPP; . LanthipStaphylococcus aureus  attached to the core peptide. GDMEAA-mersacidin is not active until matured by a protease from the supernatant in a second proteolytic step.Because mersacidin has an unusual and very interesting first ring structure, with potential applications in synthetic biology, a heterologous expression system for the mersacidin biosynthetic genes MrsAMD in eveloped . Using tE. coli. Cleaving of the mersacidin leader with a single purified protease would allow for a more accurate digestion of any products produced in E. coli using the mersacidin biosynthetic genes. Additionally, purification and analysis of digested samples are more straightforward in the absence of compounds from B. amyloliquefaciens supernatant. More fundamentally, identification of the mersacidin leader protease is one of the last steps of mersacidin biosynthesis that remains to be described. Finally, because of the unusual ring structure directly downstream of the leader cleavage site, any protease able to cleave at this unusual position might be of interest for synthetic biology and other purposes.Identification of the protease responsible for cleaving the mersacidin leader would greatly improve the previously described expression system in Mersacidin leader processing deviates from that of comparable class II lanthipeptides . The conB. subtilis ATCC 6633 proteases  at 37°C at 225 RPM. When pACYC was present, E. coli strains were grown with 15μg/ml chloramphenicol, unless stated otherwise. Al transformed strains were grown on LB agar at 37°C. E. coli strains containing pACYC were grown with 15μg/ml chloramphenicol. Strains transformed with pDR111 were grown with 100μg/ml ampicillin (E. coli) or 50μg/ml spectinomycin (PG10).When grown in liquid medium, all strains used in this study, B. amyloliquefaciens BH072 AprE-His production, the aprE gene was amplified from BH072 with Eco31I restriction-site overhangs and cloned into shuttle vector pDR111  promoter, which was amplified by PCR to introduce compatible Eco31I overhangs, in the case of BH072 AprE introducing a C-terminal His-tag. The mersacidin leader peptide was amplified from pACYC His-MrsA .Molecular cloning was performed as previously described , adjuster pDR111 , amplifilis PG10 . All cloHis-MrsA  and clonHis-MrsA . For pro2 chemically competent E. coli TOP10. Overnight cultures were made from transformants colonies, after which the Plasmid DNA was isolated using a “NucleoSpin Plasmid EasyPure” kit (Macherey-Nagel) and confirmed by sequencing .All oligonucleotides used in this study were obtained from Biolegio . PCRs were performed using Phusion (Thermo Scientific) polymerase, which were subsequently cleaned using a “NucleoSpin Gel and PCR Clean-up” kit (Macherey-Nagel). The cleaned PCR products were digested with FastDigest Eco31I (Thermo Scientific), followed by an additional cleaning step. After restriction and cleanup, the respective compatible vector and insert fragments were joined using T4 ligase (Thermo Scientific). This mixture was subsequently used to transform CaCl600=0.075 and grown ca. 3h to OD600=0.5. Then, expression was induced by the addition of 1mm IPTG. After 4h, the cells were spun down, and the supernatant was harvested.Good PG10 transformants were grown overnight in an Erlenmeyer flask containing 50ml LB. The cultures were diluted to ODPer expression, several fresh BL21(DE3) colonies were picked up in LB medium +15μg/ml chloramphenicol and grown overnight. The cultures were diluted 50 times in fresh LB medium containing 10μg/ml chloramphenicol and grown for 2h and 15min. Then, the cultures were cooled down to 16°C in ice water and induced with a final concentration of 1mm IPTG. The induced cultures were grown for 16h at 16°C at 225 RPM, after which the cells were harvested.E. coli BL21(DE3)+pACYC-duet to detect any antimicrobial activity caused by the purification method.Expression of the His-mersacidin leader was done identical to that of His-AprE up to the point of induction. The expression cultures were kept at 37°C, induced with 1mm IPTG and grown for 4h until the cells were harvested. As a control for the activity test, a similar expression was done using ca. 10ml binding buffer (20mm H2NaPO4 (Merck), 0.5M NaCl (VWR), 20mm Imidazole (Merck), pH 7.4) and sonicated until visible lysed. The sonicated samples were centrifuged for 1h at 10.000 × g, after which the supernatant was loaded onto the column. In case of purification from the expression culture supernatant, supernatant was loaded directly onto the column. After loading, the column was washed with 10 column volumes (CV) binding buffer, followed by an additional wash with five CV wash buffer . Elution from the column was done using 1.8ml 250mm imidazole elution buffer  in case of enzymes and 500mm imidazole elution buffer in case of peptides.All His-tagged peptides were purified using 1ml Ni-NTA slurry (Qiagen) in an open column, using manufacturer’s instructions. In case of purification from the cell pellet, the pellet was resuspended in ca. 6ml). The column was wetted using 2 CV acetonitrile +0.1% TFA and then equilibrated using 5 CV Milli-Q+0.1% TFA, after which the acidified samples were loaded. The column was washed with 5 CV 20% ACN+0.1% TFA, after which samples were eluted from the column using 5 CV of 50% ACN+0.1% TFA. The eluted samples were freeze-dried and stored at −20°C until use.His6-mersacidin leader and the control expression were purified by C18 open column, using 0.25 gram (CV=1ml) of 55–105μm C18 resin (Waters). The 1.8ml His-tag elution samples were acidified using Milli-Q 0.5% trifluoroacetic acid  until a pH of <4 was reached  MrsMD modified His6-MrsA +7.5μl Milli-Q water was digested. For the respective digestions, 1.5μl was added of each of the His-tag purified AprE-His samples. As negative controls 1.5μl of elution buffer (250mm Imidazole) and a His-tag purification of a PG10+empty pDR111 control expression were added.All strains were grown for 20h, after which the cells were spun down, and the supernatant was filtered (0.2μm). Of each supernatant, 5μl was added to 2μl 16mg/ml (pre-HPLC) MrsMD modified His6-MrsA or in case of the negative control 2μl Milli-Q water. To each sample, 3μl Milli-Q water was added. All samples were incubated for 2h at 37°C and subsequently spotted.E. coli), or 1μl MrsT150-His , 1μl AprE-His , and, respectively, 0, 1, 3, or 6μl of freeze-dried His-mersacidin leader or pACYCduet purification control, dissolved in 100μl Milli-Q  were prepared as described previously . Two ideMALDI-TOF MS was performed as previously described . Of digeThe freeze-dried activatable fraction and non-activatable fraction purified by HPLC, from 1.5 Liter expression volume His-MrsA + MrsM + MrsD , were diaprE in B. subtilis 168, pJOE8999 was used containing the cas9 gene under control of the B. subtilis mannose-inducible promoter (aprE was designed using the CRISPR Guide Design Software of Benchling (aaagtagctgttatcgacag) and cloned into pJOE8999 via Eco31I digestion. To enable homologous recombination, up- and downstream flanking regions were obtained from the genomic DNA of B. subtilis 168 using primer pairs aprE-up-fw + aprE-up-rv (upstream) and aprE-down-fw+aprE-down-rv (downstream). To obtain the final pJOE_ΔaprE vector, flanking regions were digested with SfiI followed by ligation into similarly digested pJOE8999 vector with the sgRNA-encoding sequence. Deletion of aprE and loss of pJOE_ΔaprE in B. subtilis 168 was achieved as described previously  was able to activate mersacidin . AprE-His expressed in both PG10 and BL21(DE3) was purified by Ni-NTA affinity chromatography, in PG10 from the supernatant, and in BL21(DE3) from the cell pellet. The AprE homologs from both Bacillus strains were able to activate mersacidin, either produced in BL21(DE3) or PG10 . The ability of BH072 AprE to activate mersacidin confirms that this is a major protease responsible for activating mersacidin in natural conditions.To verify that AprE from  or PG10 . The app or PG10 . BH072 ABacillus subtilis 168 Δ aprE strain was used to confirm that no other proteases from B. subtilis can activate mersacidin. MrsMD modified His6-MrsA was digested with the supernatant of multiple Bacillus strains, that is, B. amyloliquefaciens BH072, B. subtilis 168, B. subtilis 168 Δ aprE, and PG10. While B. subtilis 168 supernatant could activate mersacidin, the aprE knockout strain supernatant was unable to  as described previously . To testAprE-His . It was E. coli BL21. AT was supported by a grant from European Union’s Horizon 2020 Research and Innovation Program (Grant Agreement No. 720776).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.


Lichen Sclerosus et Atrophicus (LSA) is a chronic inflammatory, invalidating disorder mainly involving the anogenital skin. Extragenital lesions are uncommon, occurring as multiple, oval, porcelain-white macules, or papules. When present, they are mostly observed on the superior trunk, axillae, buttocks, and extremities, following Blaschko lines . In the We report the case of a 70-year-old woman who presented bilateral symmetrical itchy lesions affecting the inner thighs, appearing as wrinkled, porcelain-white color plaques with cigarette-paper-like texture and measuring 4 cm × 4 cm . The lesDermoscopy of cutaneous lesions revealed widespread whitish patches, comedo-like openings, and peppering patterns . On dermThe differential diagnosis of the skin patches included morphea and extragenital LSA, due to their clinical morphology and distribution and to the association with anogenital lesions . A punchExtragenital LSA affects about 15–20% of patients with genital LSA. It is generally asymptomatic and usually affects neck, shoulders, and upper trunk, presenting as flat, white papules or slight atrophic white plaques. The diagnosis is mainly clinical and is confirmed by histopathology.Clinically, our patient showed a specific skin lesions that made us hypothesize an inflammatory disease, such as morphea or extragenital LSA, but due to symmetrical distribution and the peculiar size, the lesions were not pathognomonic for any disease.The uncertainty in diagnosing extragenital LSA was due to the uncommon sites of the lesions, very close to anogenital LSA, rather than on the trunk or sites of pressure. On the contrary, dermoscopy added features suggesting the hypothesis of extragenital LSA, showing well-demarcated, whitish structureless areas, and comedo-like openings . DermoscFurther cases of extragenital LSA need to be reported and collected, to deepen the understanding of this rare disease’s dermoscopic features, confirming the presence of peppering as clue for differential diagnosis.


In addition, casein kinase CK2α1 was found to phosphorylate Ser104, although this was not a major phosphorylation site in cultivated HEK293 cells. The evaluation of the effects of phosphorylation revealed that the phosphorylation mimic mutants S11/727E exhibit only 20% reduction in PLA1 activity. However, the phosphorylation mimics were mainly localized to focal adhesions, whereas the phosphorylation-resistant mutants S11/727A were not. This suggested that phosphorylation alters the subcellular localization of DDHD1 without greatly affecting its PLA1 activity.Phospholipase A1 (PLA1) hydrolyzes the fatty acids of glycerophospholipids, which are structural components of the cellular membrane. Genetic mutations in DDHD1, an intracellular PLA1, result in hereditary spastic paraplegia (HSP) in humans. However, the regulation of DDHD1 activity has not yet been elucidated in detail. In the present study, we examined the phosphorylation of DDHD1 and identified the responsible protein kinases. We performed MALDI-TOF MS/MS analysis and Phos-tag SDS-PAGE in alanine-substitution mutants in HEK293 cells and revealed multiple phosphorylation sites in human DDHD1, primarily Ser8, Ser11, Ser723, and Ser727. The treatment of cells with a protein phosphatase inhibitor induced the hyperphosphorylation of DDHD1, suggesting that multisite phosphorylation occurred not only at these major, but also at minor sites. Site-specific kinase-substrate prediction algorithms and  In mammmembrane  and membmembrane , 9. In cmembrane , 11, 12 membrane  and p125membrane . DDHD-tyn detail . DDHD1 wn detail , 11, 12.Distinct from secreted/extracellular PA-PLA1 isoforms that function in outside of the plasma membrane, DDHD-type PLA1 enzymes locate in the cytoplasm , 5, 6.SPG28 (SPG54 subtype (via the hydrolysis of PA (SPG28 subtype) and LPI/GPR55 has not yet been elucidated and the underlying pathogenic mechanisms remain unclear.Several mutations in the human DDHD1 gene have recently been reported in patients with autosomal-recessive forms of hereditary spastic paraplegia (HSP), termed SPG28 , 19, 20. subtype . HSP is  subtype . Mitocho subtype . Recent is of PA . We previs of PA . We alsois of PA , 26, 27;Posttranslational modifications play a key role in many cellular processes such as signaling and regulatory processes . ProteinIn the present study, we examined an important posttranslational modification, the “phosphorylation” of human DDHD1. We identified multisite phosphorylated serine and threonine residues using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), Phos-tag SDS-PAGE, and systematic alanine-substituted mutagenesis . In addihttp://www.cbs.dtu.dk/services/NetPhos/), and analyses revealed multiple phosphorylation sites in human DDHD1. Phosphoserines, S8, S11, S104, S130, S139, S332, S723, S727, S738, and S806 are predicted with a high score (over 0.500)  . CDK5 anding tag .A, the inhibition of endogenous phosphatase activity with okadaic acid altered the mobility of DDHD1 in Phos-tag SDS-PAGE followed by immunoblot analysis; many slower bands were detected by the anti-FLAG M2 antibody. In addition, even when cells were cultivated in normal growth medium with 10% FBS and 25 mM glucose, DDHD1 was phosphorylated because treatment with lambda protein phosphatase (λPP) increased mobility . Therefore, human DDHD1 was suggested to be highly phosphorylated and may be reversibly regulated in phosphorylation–dephosphorylation states by protein kinases and phosphatases.After FLAG-tagged human DDHD1 was expressed in HEK293 cells, cells were treated with okadaic acid, an inhibitor of protein phosphatases 1 and 2A in growth medium containing 10% fetal bovine serum (FBS). As shown in Figure 12), zirconium dioxide (ZrO2), or TiO2/ZrO2 affinity chromatography. Peptides were analyzed by MALDI-TOF MS/MS.We attempted to identify phosphorylation sites in human DDHD1 using MALDI-TOF MS/MS analysis. FLAG-DDHD1-expressing HEK293 or PANC1 cells were treated with okadaic acid, and FLAG-DDHD1 was purified by immunoprecipitation and SDS-PAGE. After the in-gel digestion of purified FLAG-DDHD1 with trypsin or Asp-N, the resultant phosphopeptides were further purified by immobilized metal affinity chromatography (IMAC) or titanium dioxide (TiO2NY…GS28 was phosphorylated at serine 8 (Ser8) and Ser11 (A). On the other hand, the peptide 708EP…SR732, containing six serines and three threonines, was phosphorylated at Ser723 and threonine 726 (Thr726) (B). Single-phosphorylated peptides at only Ser8, Ser11, or Ser723 were also detected, but not at Thr726 . The phosphorylation of DDHD1 at Ser8, Ser11, and Ser723 was also predicted using a protein phosphorylation site predictor; however, the software implied a greater potential for phosphorylation at Ser727 than at Thr726 (B). We considered the phosphorylation of Ser727 to be sensitive to dephosphorylation by phosphatase or the detection process of MALDI-TOF MS/MS. Alternately, we considered the possibility that Ser727 cannot be phosphorylated when Thr726 is already phosphorylated.The Mascot analysis using the database of the human SwissProt 2016_07 , 2016_08 , or 2017_04 , or FLAG-tagged human DDHD1 sequence revealed more than ten phosphopeptides of DDHD1 with significant scores . These pnd Ser11 A. On the(Thr726) B. Singlet Thr726 . Therefot Thr726 B. We conB). With the mutant enzymes, S11A , S723A, T726A, and S727A, there were faster migrating bands and fewer slower bands than with WT. This demonstrated that the amino acid residues Ser11, Ser723, and Thr726 were phosphorylated and confirmed the results of MALDI-TOF MS/MS. Although the phosphorylation of Ser727 was not observed by MALDI-TOF MS/MS, Phos-tag SDS-PAGE of the S727A mutant revealed its phosphorylation.To confirm the phosphorylation sites of DDHD1, we created several site-directed mutants in which phosphorylation sites identified by MALDI-TOF MS/MS  were chaFig. 1B). These results again indicated that Ser8, Ser11, Ser723, Thr726, and Ser727 were all phosphorylated. The phosphorylation of Ser8 is easily detectable based on comparison of the mobility of S11/727A  and S8/11/727A . The mobility of the bands of the S8/11/727A mutant was similar to that of the bands of the λPP-treated WT enzyme ; however, doublet bands were observed with the S8/11/727A mutant. In addition, the mobility of the bands of the S8/11/727A mutant was similar to that of S8/11/723/727A , suggesting that the degree of phosphorylation at Ser723 was low. Therefore, Ser8, Ser11, and Ser727 are the major phosphorylation sites of DDHD1 in HEK293 cells.Phos-tag SDS-PAGE of DDHD1 with multiple mutations revealed that its migration was generally faster than that of WT and the single and double/triple mutants B. These B, lane 13). Comparison with S8/11A  revealed that the degree of phosphorylation at Thr726 is high because migration was increased by mutation at Thr726. In contrast, the fast migrating band of S8/11/T726A was broader upward than that of S8/11/727A , suggesting a greater degree of phosphorylation at Ser727 than at Thr726, whereas Ser8 and Ser11 were not phosphorylated.The fast migrating band was broader in the Phos-tag SDS-PAGE of S8/11/T726A . As the front of the broader bands migrated faster than that of λPP-treated WT, the mutation at T726 may affect not only the inhibition of phosphorylation, but also conformational changes in the 3D structure of DDHD1.The inhibition of phosphorylation at Thr726 may suppress that of other serine, threonine, and tyrosine residues (or the activation of dephosphorylation) because very fast migrating bands were observed in the Phos-tag SDS-PAGE of the T726A mutant B, lane 6B, lanes 2 and 3). However, based on comparison of the mobility of S727A  and S8/727A , the intensity of the fast migrating band decreased, whereas that of slower migrating ones, which were (hyper-) phosphorylated, markedly increased when Ser8 and Ser727 were not phosphorylated. Thus, the phosphorylation of Ser8 affected the phosphorylation of other sites. In contrast, there were more fast migrating bands and fewer slower bands in S8/11A  than in S11A ; however, very slow migrating bands, which were (hyper-) phosphorylated, were also observed. These results again suggested that phosphorylation is increased when Ser8 and Ser11 are not phosphorylated.However, detailed comparisons suggested that the degree of phosphorylation differed at each serine or threonine. The phosphorylation of Ser8 was not prominent because the mobility of S8A was not as affected as that of WT  to phospholipase A2. We confirmed this assay to be accurate and reliable to distinguish the small difference in activity because it can quantitatively measure linear changes in 50 ng of DDHD1 for 10 min (A and B).The PLA1 activity of DDHD1 was measured by a method employing a fluorescent substrate (PED-A1). PED-A1 is a probe specific to PLA1 or lipase activities because the BODIPY FL acyl chain esterifies the r 10 min , A and BA), which may have been due to the offset caused by the multisite phosphorylation of DDHD1, which means that DDHD1 includes a mix of many major or minor phosphorylation sites up- or downregulating the PLA1 activity of DDHD1. Accordingly, the effects of the phosphorylation of individual sites need to be investigated.To assess the effects of phosphorylation on PLA1 activity, purified FLAG-DDHD1 was treated with λPP. λPP did not markedly affect the PLA1 activity of WT A, which As assessing the effects of the phosphorylation of individual sites in multisite phosphorylated proteins is difficult, we created several glutamic acid mutants . The subB). In contrast, PLA1 activity was not affected by the substitution of Ser8 or Ser723 to glutamic acid . As such, the phosphorylation of Ser11 and S727, but not Ser8 or Ser723, reduced the PLA1 activity of DDHD1. However, the impact on PLA1 activity by phosphorylation was less than 25%.The substitutions of Ser11, Ser727, and both by glutamic acid  reduced PLA1 activity B. In conThe PLA1 activity of the phosphorylation-resistant form of DDHD1  was not markedly different from that of WT . These rC). Compared with the enzymes not treated with λPP (B), the effects of substitution to glutamic acid were slightly attenuated by λPP. Therefore, the phosphorylation of Ser11 and Ser727 may negatively control the PLA1 activity of DDHD1 in coordination with the phosphorylation state at other sites influenced by them.To investigate the relationship between the phosphorylation mimics at Ser11/Ser727 and the phosphorylation of other sites, PLA1 activity was measured after WT and the phosphorylation mimic mutants of DDHD1 were treated with λPP C. Comparwith λPP B, the efTaken together, the impact of phosphorylation on PLA1 activity was suggested to be less than 20%.A). We then confirmed if this localization pattern was associated with the phosphorylation status of DDHD1. Of note, the apparent concentration of WT at focal adhesions was also observed with the phospho-mimic form S11/727E , but not with the phosphorylation-resistant mutant S11/S727A (left). A similar difference was noted when the alanine mutant expression profile was compared with that of WT . These findings are consistent with our observation that Ser11 and Ser727 of DDHD1 are nearly always phosphorylated (B). These results suggested that the phosphorylation at Ser11 and Ser727 regulates the targeting of DDHD1 to focal contacts.Next, the effects of phosphorylation on the subcellular localization of DDHD1 were examined. When the cellular localization of DDHD1 was examined in COS-7 cells that were coated with a fibronectin fragment, retronectin, we noticed that the DDHD1 (WT) was located at the cellular contact sites attaching to the glass. Coexpression of DDHD1 with a focal adhesion marker, paxillin α , revealeFig. 4orylated B. These https://scansite4.mit.edu/4.0/#home), and iGPS (http://igps.biocuckoo.org/). These software programs predicted several protein kinases, including cyclin-dependent kinases (CDKs) and glycogen synthase kinase-3 (GSK-3), with relatively high scores  resulted in faster migrating bands corresponding to partially unphosphorylated forms , lane 4.As relatively high doses of inhibitors of protein kinases were required to reduce the phosphorylation of DDHD1, the specificity of the inhibitors was of concern. Therefore, we investigated the effects of knockdown of GSK3β or CDK1 using miRNA expression vectors. miRNA for GSK3β or CDK1 reduced the expression of the protein kinases; however, the knockdown did not affect the phosphorylation of DDHD1 in HEK293 cells . This suin vitro kinase assay employing purified recombinant protein kinases. We selected CDKs and GSK3 because they were predicted to be involved kinases (A). When CDK1 was used as the candidate kinase, up-shifted bands of DDHD1 were observed in the presence of cyclin A2 ; however, a new and slow-migrating band was very faint . In contrast, a very strong band shift was observed when cyclin-dependent kinase 5 (CDK5) was used as the candidate kinase in the presence of p35 . In both cases, these up-shifted bands were not observed in the absence of cyclin A2 and p35, respectively . Cyclin A2 and p35 themselves have no kinase activity. Therefore, DDHD1 was phosphorylated by activated CDK1 and CDK5 because cyclin A2 and p35 are activators of CDK1 and CDK5, respectively. In addition, CDK5/p35 more strongly phosphorylated DDHD1 than CDK1/cyclin A2 with the same amount of kinase/activator .To obtain clearer evidence, we conducted an  kinases . After t kinases A. When Cyclin A2 A, left; ry faint A, lane 4e of p35 A, lane 8Changes in the migration of DDHD1 were not observed when DDHD1 was used without pretreatment with λPP as a substrate. The underlying reason may be that Ser8, Ser11, and Ser727 of DDHD1 were already phosphorylated in HEK293 cells . CDK1/cyB) because CK was another predicted candidate. When λPP-untreated DDHD1 was used as a substrate, up-shifted bands were observed by CK2α1 , but not by the kinase-inactive isoform CK2α1 K68M (lane 4) in Phos-tag SDS-PAGE. Thus, site(s) phosphorylated by CK2α1 may differ from those in DDHD1 by other kinases, including CDK1/cyclin A2 and CDK5/p35, under the growth conditions of HEK293 cells.A similar analysis was conducted using casein kinase 2, alpha 1 (CK2α1) B becauseby CK2α1 B, lane 5B, lanes 3 and 6), whereas that with CK2α1 induced an up-shift of the bands of DDHD1 ; however, kinase-inactive isoform CK2α1 K68M did not (lane 7). Furthermore, CK2α1 phosphorylated DDHD1, but treatment with CK2α1 did not reverse the phosphorylation state before the pretreatment with λPP, again suggesting that the site(s) phosphorylated by CK2α1 differ from those in DDHD1 by kinases under the growth conditions of HEK293 cells.The pretreatment with λPP increased the mobility of DDHD1 , although a high dose of the GSK-3 inhibitor CHIR99021 resulted in faster migrating bands, as described before. As such, GSK may phosphorylate DDHD1 in vivo, but not in vitro, which may have been due to priming phosphorylation being necessary for the phosphorylation of GSK-3β (B and C). These results suggest that ERK2 and p38 need to be phosphorylated by upstream protein kinases . However, when S8/11/727A was used as a substrate, the bands up-shifted by CDK1/cyclin A2 disappeared , suggesting that CDK1/cyclin A2 phosphorylated DDHD1 at Ser8, Ser11, or Ser727. When the S8/11A, S8/727A, or S11/727A mutant was used, up-shifted bands were observed . As Ser727, Ser11, and Ser8 are intact in the S8/11A, S8/727A, and S11/727A mutants, respectively, CDK1/cyclin A2 phosphorylated the intact serine. However, the degrees of phosphorylation by CDK1/cyclin A2 differed at each serine. The intensity of up-shifted bands was high with the S8/727A mutant , whereas only small bands were detected with the S8/11A and S11/727A mutants . These results strongly suggest that CDK1/cyclin A2 prefers to phosphorylate Ser11 over Ser8 and Ser727 in DDHD1.We next investigated the phosphorylation site(s) of DDHD1 by each protein kinase. We performed an ted band A, lane 2B). When WT DDHD1 was used, up-shifted bands were observed in the presence of CDK5/p35 and ATP . However, when S11/727A and S8/11/727A were used, the up-shifted bands disappeared , suggesting that CDK5/p35 phosphorylated DDHD1 at Ser11 and Ser727. Based on the intensity of the up-shifted bands for each mutant , CDK5/p35 prefers to phosphorylate Ser11 over Ser727 in DDHD1. These results reflect differences in the specificity of the phosphorylation site by each CDK isoform. However, as Ser11 and Ser727 were both preferred phosphorylation sites over Ser8 because the fast migrating band increased with the S11/727A mutant  compared with that of S727A and S8/727A mutants , the physiology of DDHD1 affected by CDK1 or CDK5 in HEK293 cells may mainly be due to a difference in the strength of kinase activity.Similar analyses employing CDK5/p35 and each DDHD1 mutant were conducted B. When W and ATP B, lane 2A and B, lanes 9–12), CDK1/cyclin A2 and CDK5/p35 both phosphorylated Ser727, but not Thr726, consistent with the results shown in Figure 1B.When the behaviors of S8/11/T726A and S8/11/727A were compared . Similar results were observed when the S8/11/727A mutant was employed as a substrate , suggesting that CK2α1 phosphorylated DDHD1 at serine/threonine residue(s) other than Ser8, Ser11, and Ser727. Therefore, we considered potential phosphorylation site(s) based on the MALDI-TOF MS/MS analysis , suggesting that CK2α1 phosphorylated the Ser104 residue of DDHD1. However, the Mascot ion score of peptides containing single-phosphorylated Ser104 was not significant. Therefore, Ser104 is a novel, but minor phosphorylation site in HEK293 cells. This was consistent with the migration of the S104A mutant in Phos-tag SDS-PAGE not being markedly different from that of WT under the growth conditions of HEK293 cells.Treatment of the dephosphorylated form of WT with CK2α1 and ATP resulted in an up-shifted band  and functions as a molecular switch for their regulation . This mo complex . In addi complex . CDK1 an complex ; howeverin vitro . Even Ser104 may be a minor phosphorylation site because Phos-tag SDS-PAGE of S104A did not markedly alter mobility. On the other hand, Ser730 in the bovine enzyme was phosphorylated by ERK2, whereas the corresponding Ser727 in the human enzyme was phosphorylated by CDKs (A and B) and not ERK2  were identified in both HEK293 and PANC1 cells . Althoug723SPVTSP728 may be one of the phosphorylation sites. However, we were unable to confirm the phosphorylation of human DDHD1 in an in vitro kinase assay employing recombinant GSK-3β (As the inhibitor of GSK-3β (CHIR99021) up-shifted bands in Phos-tag SDS-PAGE, we considered GSK-3β to also be a responsible kinase for human DDHD1 . The cont GSK-3β . Primed t GSK-3β . Kinasest GSK-3β  and S6.A). We employed phosphorylation mimic mutants in which an individual serine was substituted to glutamic acid because this mutation gives a negative charge and is hypothesized to mimic a constitutively phosphorylated state. The PLA1 activity of S11E, S727E, and S11/727E was lower than that of WT DDHD1 (B), suggesting that the phosphorylation(s) of Ser11 and S727 reduced this activity. Reduced activity was significant, but the potency was not large and the degree was less than 20%.We examined the effects of phosphorylation(s) on PLA1 activity. Precisely evaluating phosphorylation is difficult because human DDHD1 is phosphorylated at multiple sites, even in cells cultivated in growth medium, and multisite phosphorylation(s) may exert offset effects on PLA1 activity. The nonselective dephosphorylation of purified DDHD1 by λPP did not markedly alter the PLA1 activity A. We empWT DDHD1 B, suggesin vitro kinase reaction by CDK5/p35. Approximately 64.2% of DDHD1 was phosphorylated by the kinase reaction, and the activity of the 100% phosphorylated form was calculated to be 70.1% of the dephosphorylated form (third bar graph) in comparison with the activity of CDK5/p35-treated DDHD1 without ATP as a control (We next assessed the relationship between the phosphorylation(s) of Ser11/Ser727 and PLA1 activity using the  control . The ext control . This su control .SPG28 subtype) (As phosphorylation(s) did not markedly affect PLA1 activity, phosphorylation(s) may affect other properties of DDHD1. We thus examined the effects of phosphorylation on its subcellular localization. Phosphorylation at Ser11 and Ser727 was strongly suggested to facilitate localization of the enzyme to focal adhesions  and 9. Fsubtype) , 19, 20,Oligonucleotides for the expression of the epitope-tagged DDHD1 mutant in HEK293 and PNAC1 cells described below were synthesized by Invitrogen. Sequencing-grade modified trypsin and AspN were purchased from Promega. High-purity MS grade 2, 5-dihydroxybenzoic acid (DHB) was from Shimadzu. α-Cyano-4-hydroxycinnamic acid (α-CHCA) was from Sigma. Phos-tag acrylamide was from Wako. The mixture of protease inhibitors containing 4-(2-aminoethyl) benzenesulfonyl fluoride, aprotinin, bestatin, E-64, leupeptin, and pepstatin A was from Calbiochem. Olomoucine was from Sigma. CHIR99021 was from Wako. Anti-mouse IgG antibodies conjugated with horseradish peroxidase were from Dako. All other reagents were from Wako, unless otherwise mentioned. All other compounds were of reagent grade or higher. The expression plasmid for paxillin α  was a gegag and pol genes of vesicular stomatitis virus, were maintained in D-MEM containing 10% fetal calf serum, 1% penicillin/streptomycin, 4 mM L-glutamine, and 1 mM sodium pyruvate. Cells were grown on a monolayer at 37 °C in a humidified atmosphere with 5% CO2.HEK293, COS7, and PANC1 cells were maintained in high-glucose Dulbecco’s modified Eagle’s medium  containing 10% fetal calf serum and 1% penicillin/streptomycin (Gibco). Retroviral package GP2-293 cells, which stably express the in vitro kinase assay, the cDNA encoding human CDK1, cyclin A2, CDK5, p35, or CK2α1 with a FLAG-tag was amplified by PCR using cDNA derived from HeLa cells as a template  according to the manufacturer’s instructions using pcDNA4/TO/FLAG-DDHD1 and pcDNA4/TO/FLAG-CK2α1 plasmids as templates, respectively. The primer sets utilized are described in The pcDNA4/TO-based epitope-tagged human DDHD1, protein kinases, or their mutant expression vectors were transfected into HEK293 or PANC1 cells using Lipofectamine 2000 (Invitrogen) or Calfectin (SignaGen) according to the manufacturer’s protocol. The pQCXIP-based human FLAG-DDHD1 expression vector was cotransfected with pVSV-G (Clontech) into GP2-293 cells to produce the retrovirus. After being incubated in medium containing retroviral particles for 2 to 3 days, the target cells were treated with puromycin (Sigma) for 2 weeks to select cells stably expressing DDHD1 according to the manufacturer’s protocol. The stable DDHD1-expressing cell lines by retroviral vector transfection were mainly used in MALDI-TOF MS/MS and Phos-tag SDS-PAGE experiments with protein kinase inhibitors.7 cells expressing FLAG-tagged proteins were harvested and lysed in ice-cold immunoprecipitation buffer  NP-40, and protease inhibitors) at 4 °C. The lysate was centrifuged for 30 min at 15,000 rpm. The resulting supernatant with anti-FLAG M2 affinity gel (Sigma) was incubated with gentle rocking at 4 °C overnight. The gel was washed three times with TBS buffer, pH 8.0, and the enzyme was eluted from the gel by competitive replacement with 100 μg/ml of FLAG peptide (Sigma) according to the manufacturer’s instructions. The amount of purified protein was measured using Bicinchoninic Acid Solution reagent (Pierce). Purified proteins were used to assess phospholipase enzymatic activity or in the in vitro kinase assay as described below.1 × 107) by attaching the enzyme to anti-FLAG M2 affinity gels, washing them with TBS buffer, at pH 8.0 three times, and incubating them at 30 °C for 1 h with an excess amount of lambda protein phosphatase . After the incubation, enzyme-containing gels were washed three times with TBS buffer, at pH 8.0 to remove λPP, and the enzyme was eluted as described above.Prior to examining the phosphorylation of recombinant DDHD1 or its mutants (in most experiments), we removed the esterified phosphate groups introduced into HEK293 cells (1 × 107 cells expressing FLAG-DDHD1 with or without 1 μM okadaic acid (Sigma) at 37 °C for 4 h, we used SDS-PAGE to purify the DDHD1 protein immunoprecipitated with anti-DYKDDDDK (FLAG) monoclonal antibody  conjugated to Dynabeads protein G (Invitrogen) and then digested aliquots of the purified enzyme with trypsin or AspN using a procedure modified from a previously published protocol (4HCO3 containing trypsin (10 μg/ml) or AspN (10 μg/ml). The temperature was increased to 37 °C and the incubation was continued overnight. After the incubation, digested DDHD1 was extracted from gel pieces three times using 0.1% trifluoroacetic acid (TFA) in 50% ACN. The extracted peptides were pooled, dried, and then dissolved in 0.1% TFA or 300 mg/ml of DHB in 80% ACN/0.1% TFA. Phosphopeptides in the former and latter solvents were further enriched with the Magnetic Phosphopeptide Enrichment Kit (Clontech) based on IMAC and Nutips (Glygen) consisting of TiO2, ZrO2, or a mixture of both, respectively, according to the manufacturer’s instructions, but with slight modification. The phosphopeptide solutions were dried, reconstituted in 0.1% TFA, and desalted using ZipTip C18 tips (Millipore). Purified peptides were released in 50% ACN/0.1% TFA, which was mixed with an equal amount of 10 mg/ml of α-CHCA or 20 mg/ml of DHB matrix solution in 50% ACN/0.1% TFA containing 1% phosphoric acid (Sigma) for analysis by MALDI-TOF MS on AXIMA Performance (Shimadzu). The instrument was calibrated using a standard of bradykinin fragment 1 to 7 , N-acetyl-renin substrate , and ACTH fragment 7 to 38  for MS and MS/MS. MS and MS/MS analyses were performed in the positive reflector mode using Shimadzu Biotech MALDI–MS Launchpad v. 2.8.4. Mono and average isotopic peak lists were generated by MALDI-MS software. MS data obtained from the purified phosphopeptides of DDHD1 were compared with a theoretical peptide mass fingerprint of DDHD1 with phosphorylated serine and threonine sites by MASCOT website (http://www.matrixscience.com/) or software . Peptides matching the masses of predicted phosphopeptides were preferentially selected for fragmentation by a form of postsource decay without using collision gas. Initial MS/MS data were examined for the presence of a neutral loss of 98 Da corresponding to the phosphate moiety and selected phosphopeptides were directed to collect more thorough data to identify the phosphorylation sites of DDHD1. The search parameters in MASCOT were the following: number of missed and/or nonspecific cleavages permitted: 1; list of all fixed modifications (including residue specificity) considered: None; list of all variable modifications (including residue specificity) considered: Phospho (ST); Mass tolerance for precursor ions: ±0.9 to 1.4 Da; Mass tolerance for fragment ions: ±1.3 to 2.0 Da. To prevent the hydrolysis of phosphate groups, all solutions used in this process were adjusted to below pH 8.3.After treating 6 × 107 cells were also lysed using the same RIPA buffer without EDTA. Laemmli SDS-PAGE was performed with 10% polyacrylamide gels. Proteins were transferred to nitrocellulose membranes (Wako) using a semidry blotting apparatus . Zn2+-Phos-tag SDS-PAGE was performed using the Tris-AcOH (acetic acid) system with a 3% polyacrylamide gel strengthened with 0.5% agarose H (Wako) using a procedure modified from a previously published protocol  NP-40, 0.1% (w/v) SDS, and 0.5% sodium deoxycholate) supplemented with protease inhibitors. Regarding Phos-tag PAGE, 1 × 10protocol , 38. We sn-1 position and a dinitrophenyl quencher-modified head group. The cleavage of the BODIPY FL-labeled acid at the sn-1 position by PLA1 reduces quenching efficiency and increases fluorescence emission detected at approximately 515 nm. Mixed phospholipid micelles were prepared as PED-A1/dioleoylphosphatidylcholine (DOPC)/dioleoylphosphatidylglycerol (DOPG)  in 50 mM Tris-HCl (pH 7.4), 140 mM NaCl, and 2 mM CaCl2. The substrate concentration in the micelles was 36.7 μM (3.33 μM PED-A1). Reactions were initiated by the addition of 50 ng of purified FLAG-DDHD1 and its mutants and were conducted at room temperature for 10 to 30 min. The fluorescent cleavage product was measured  by a Powerscan HT multidetection microplate reader (DS Pharma).PLA1 activity was measured using the EnzChek Phospholipase A1 assay kit (Thermo Fisher Scientific) according to the manufacturer’s protocol. PED-A1 is a glycerophosphoethanolamine with BODIPY FL pentanoic acid at the We confirmed that activity monitored by 515-nm emission was dependent on the amount of FLAG-DDHD1 and the incubation period. In addition, the incubation with the inactive mutant, in which the serine 537 residue involved in PLA1 activity was substituted to alanine, did not increase the 515-nm emission .6 tag at the C-terminus was synthesized (Integrated DNA Technologies), in vitro assembled with cDNA of cfSGFP2 (The anti-ALFA nanobody cDNA containing a poly (Asp) cfSGFP2  or tdTom cfSGFP2  as a N-t cfSGFP2 , was useCells transfected with plasmids plated onto retronectin (Takara)-coated cover glasses  were fixed with glyoxal fixative  and bloc2) containing 1 μM ATP, 50 μM DTT, and 0.1 to 1 mg/ml of BSA together with either kinases, kinase complexes, or kinase mutants. Reaction mixtures were incubated at 25 °C for 150, 180, or 360 min. The reaction was stopped by the addition of Laemmli sample buffer, followed by Phos-tag SDS–PAGE.Purified FLAG-tagged DDHD1 (WT or mutant) was resuspended in kinase assay buffer (40 mM Tris-HCl, pH 7.4, and 20 mM MgClvia the jPOST partner repository with the data set identifier PXD023208.The MS/MS data were deposited into the ProteomeXchange Consortium This article contains The authors declare that they have no conflict of interest regarding the content of this article.


The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.Earth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO We present a bi‐directionally coupled ice sheet and Earth system model including advanced representation of surface snow/ice processesThe surface mass balance is calculated in the land component with an energy balance scheme and downscaled to the ice‐sheet component via elevation classesIce sheet meltwater and solid discharge are passed to the ocean component; changes in ice sheet area and topography to land and atmosphere Once laThe modeling of ice‐sheet response to climate change, and the response of the Earth System to ice sheet change, is an active, challenging area of research  for present‐day ice sheet configurations has been done byfor example, Lipscomb et al. , LofversHere, we present the coupling between the Community Earth System Model version 2 (CESM2) and the Community Ice Sheet Model version 2 (CISM2). This work extends preliminary coupling efforts with CESM1 and the Glimmer‐CISM ice sheet model  . With atmosphere, land, ocean, sea‐ice, and ice sheet components that interactively exchange state information at runtime, CESM2 allows for realistic simulations of Earth's climate , using a finite‐volume dynamical core  that allow for a variety of crop and vegetation types, including bare ground.Land processes are simulated by the Community Land Model Version 5 . In areas with perennial snow cover, this depth allows the development of a firn layer that is sufficiently deep for firn hydrological processes, such as refreezing and storage of surface melt water. From fresh snow accumulation, the model simulates compaction of snow into firn, with prognostic density and “pore” space, considering the effects of snow mass overburden, snow metamorphism, and enhanced wind‐driven surface compaction  model, which accounts for vertically resolved solar absorption, snow grain size evolution, and snow with impurities from aerosols . Model sensitivity to the lapse rate choice was assessed in Sellevold et al.  elevation is set as the mean of all CISM grid cell surface elevations falling within it. Typically, one or two elevation classes are sufficient to represent the distribution of ice sheet elevations within a CLM5 grid cell in the relatively flat regions of the ice sheet interior. Conversely, more elevation classes are needed to capture topographic variation on the steep ice sheet margins. The remaining ECs in a grid cell are virtual; that is, their area fraction is zero. SMB calculations in virtual ECs allow to realistically initialize a temperature profile when an EC first acquires a nonzero area value. The elevation classes calculations are done in a predefined domain. Figure Physically, the interface between snow and ice is characterized as the point at which densities of solid ice are reached, and no additional snow compaction as a result of overburden pressure can occur. In CLM5, the conversion of snow to ice is based on depth; any snow accumulation exceeding a prescribed threshold (10 mWE by default) is assumed to turn to ice. In CESM simulations without interactive ice sheets, this ice is sent to the ocean as a solid runoff flux, but in coupled CESM‐CISM runs, it is sent to the ice sheet model as accumulation . An equal amount of mass is then removed from the lowest snow layer in CLM5 to allow refreshing of surface snow density and albedo. Mass variations in snow and firn layers are only considered in the land model, while variations in ice mass “belong” to the ice sheet model. Therefore, the SMB sent from CLM5 to CISM2 is defined as the difference between  ice accumulation and ablation. Accumulation is the sum of snowfall and refrozen rain wherever the maximum allowed CLM5 snow depth is reached (10 mWE by default). An equal amount of mass is then removed from the lowest snow layer to allow refreshing of surface density and albedo. The annual integrated melt that takes place on bare ice (which may be exposed after the snow pack has disappeared) is passed to the ice sheet model as ablation . In ice‐free regions of CISM2, negative SMB from CLM5 is ignored. The SMB definition used in the ice sheet‐land model coupling does not take into account variations of mass within the snow and firn pack. Thus, the SMB received by CISM reflects long‐term changes in ice thickness, but not seasonal‐to‐interannual variations in snow depth. This approximation is valid for equilibrated climate and SMB, but introduces a bias during transient climates, especially in the vicinity of the equilibrium line altitude (ELA). The reason is a delay in the transition from positive or negative SMB, or vice versa, when using SMB that includes snow pack changes, versus using SMB as the difference between ice accumulation and ice ablation.The CESM2 coupler (the interface between the land and ice‐sheet models) accumulates and averages the SMB in each land model grid cell over the coupling interval .SMB in each EC is  bilinearly interpolated from the land model to the ice‐sheet model grid.In each ice‐sheet grid cell, the SMB is linearly interpolated in the vertical between adjacent ECs to the appropriate surface elevation in the ice‐sheet model.Mass discrepancy (%) following these interpolations is quantified by separately evaluating the total area‐weighted accumulation and ablation on the source grid  and destination grid . This results in two normalization factors, one for the accumulation region and one for the ablation region. For the coupled GrIS simulations described here, the mass discrepancy usually is less than 10%, and thus the normalization factors fall between 0.9 and 1.1.In each ice‐sheet grid cell, the SMB is multiplied by the appropriate normalization factor to ensure mass conservation.After annual SMB is accumulated in CLM5 for each glacier‐covered EC, the SMB is remapped from the coarse land model grid to the higher‐resolution ice sheet model grid through trilinear interpolation and renormalization. The remapping procedure targets (a) local accuracy, (b) smooth SMB gradients without any imprint of the coarse land model grid, (c) preservation of the spatial distribution of accumulation and ablation areas, and (d) conservation of mass. To reach all these targets, the downscaling algorithm proceeds as follows:3.2Surface runoff, ice discharge, and basal melt comprise the freshwater flux from the ice sheet to the ocean. Marine‐terminating glaciers discharge ice directly to the ocean. Thus, the coupling is only from ice to ocean, and no information is passed from the ocean to the ice sheet. As a result, CESM does not yet simulate ocean‐forced melting of marine‐terminating glaciers, as described by Goelzer et al.  and SlatThe relevant aspects of water fluxes to the ocean, from a coupling perspective, are the source , timing, and phase . Surface runoff fluxes are calculated in the land model and coupled to the ocean on hourly time scales. The ice sheet model, on the other hand, computes annual ice discharge and basal melting rates, which are supplied to the ocean at a constant rate throughout the following year . Solid ice fluxes from ice discharge are melted instantaneously (temperature of ice is assumed to be 0°), and the energy for the phase change is extracted from the global surface ocean. For liquid fluxes, the temperature difference between the liquid‐phase water flux and the ocean temperature is assumed to be negligible, such that no net heat transfer occurs. Since the water volume in POP2 is fixed, the ocean model converts freshwater fluxes to virtual salinity fluxes.Water flux routing depends on the model component. Surface runoff from the land model is routed downhill by the river transport model (MOSART) to the ocean. Once on the ocean grid, the water is distributed in the upper three model levels (upper 30 m) using an estuary box model , which in turn impacts the full range of surface processes. Each CLM5 grid cell can represent several different land units  at the same time. Ice‐sheet/climate coupling thus requires accommodation for dynamic (interactive or time‐evolving) land units, as the ice sheet margin changes.Dynamic land units are implemented as follows. In each CLM5 grid cell, glacier elevation classes are initialized in accordance with the topography in CISM2. As the ice‐sheet topography evolves, the coupler remaps the new ice‐sheet geometry from CISM2 to CLM5. The coupler also uses the ice sheet extent in CISM2 to recompute the fractional glacier coverage (in each elevation class) in each CLM5 grid cell that overlaps the CISM2 domain. Adjustments are made to the total glacier area of the grid cell, as well as the glacier area and mean topographic height in each elevation class. CLM5 land units are updated at the CISM2 coupling frequency .The transition from vegetated to glaciated land unit when the ice sheet margin advances  requires conservation of mass and energy in each CLM5 grid cell. As the total glacier area in each CLM5 grid cell changes, the area of each subgrid column  also changes. Each column in CLM5 has a different subsurface water, energy, carbon, and nitrogen content. Specifically, vegetated columns have soil layers, while glacier columns have subsurface ice layers. CLM5 does not adjust the below‐ground states for water and energy when the fractional areas of land units change. Instead, correction fluxes are applied to ensure conservation of mass and energy. Runoff fluxes (either positive or negative) are generated to conserve liquid water and ice, and sensible heat fluxes are generated to conserve energy. These correction fluxes are typically small compared to the physical fluxes of water and energy, and they are distributed evenly throughout the following year to MOSART and CAM6, respectively. Regarding soil carbon and nitrogen, glacier land units typically do not track this. When the ice sheet retreats, it is assumed to contribute zero carbon and nitrogen to the newly vegetated land unit's soil column. When the ice sheet advances, however, the glacier land unit will store the carbon and nitrogen from the previously vegetated land unit. The carbon and nitrogen contents remain unchanged until the area deglaciates again. Further details can be found in Leguy et al. , SectionWhen the ice sheet retreats, the vegetation types that regrow on deglaciated land are determined by the input map of PFTs. The default PFT distribution in CESM2 is based on present‐day observations  global Digital Elevation Model (DEM) from USGS on a rectilinear latitude‐longitude grid ; the standard deviation of large subgrid‐scale topography ; and the standard deviation of small subgrid‐scale topography . The latter two variables estimate subgrid surface roughness, and are used in the CAM6 parameterizations of orographic gravity wave drag and the Beljaars turbulent orographic form drag, respectively.The NCAR topography generation software for unstructured grids . The idealized high‐CO2 scenario (hereafter hCO2) is a 350‐year simulation that starts with a transient component in which the atmospheric CO2 concentration increases by 1% per year for 140 years , after which it is held fixed until model year 350. The experimental set‐up is described in detail in Nowicki et al.  steady‐state simulation is designed following the CMIP6 guidelines as specified in Eyring et al. , with a i et al. .Both simulations are initialized from the spun‐up pre‐industrial climate/ice‐sheet state described in Lofverstrom et al. . In thisThe model configuration used here is the same as in CESM2 without an evolving GrIS, except for several minor modifications, as permitted by the ISMIP6 guidelines . In this segment, the climate has warmed significantly and ice sheet changes are noticeable. The global mean surface temperature is 7 K warmer than pre‐industrial. The GrIS area and volume are 7% and 3.8% smaller than pre‐industrial, respectively (Table –220. In 4.2.1μ [σ]: −1.16 [0.95] Gt day−1), and the summer mean snowfall of 1.73 [0.55] Gt day−1 is slightly less than the annual value of 1.97 [0.27] Gt day−1). Refreezing of meltwater within the snow and firn layers contributes substantially to net SMB (2.71 [0.88] Gt day−1). However, the sum of melt and sublimation  is larger than the sum of snowfall and refreezing, resulting in the slightly negative net SMB.Figure 2 simulation, the number of months with a positive SMB decreases to seven, and the annual mean SMB is negative (Table −1), with melt as the main contributor (35.78 [2.89] Gt day−1). Not all additional melt water contributes to the surface mass loss, as the amount that refreezes increases as well (to 7.44 [0.98] Gt day−1). Snowfall decreases in the summer months, and increases in the fall and early winter. Sublimation decreases in the summer and increases during the rest of the year.In the hCOve Table . The ext−1 in July was modeled by MAR for the period 1958–2011, with a maximum of about 16 Gt day−1. The modeled extreme melt in 2012 was 22 Gt day−1, with is less negative than the CESM2.1 July average in hCO2, but far more negative than PI values.The range of melting in these simulations agrees with a recent study by Tedesco et al. , which pFigure −1 . The spatial pattern of runoff corresponds closely with the ablation simulation in Figure 2. Figures 2, respectively. Consistent with the largest increases in ablation area and magnitude, the largest runoff increases in the hCO2 are found along the western and southeastern coasts.The PI annual average runoff is 351 45] Gt year5 Gt year4.2.32 and PI is −0.15 × 106 km2 (−7.6%)  and the energy exchange with the atmosphere in the deglaciated areas   surface elevation variance  ESM that accounts for simulated changes in ice sheet area, elevation, and freshwater fluxes to the ocean. The coupled model conserves mass and energy, an important feature for robust long‐term simulations of climate and ice sheet changes . The simulations presented here were run on the Cheyenne high‐performance computer, using 2,160 processors with a load‐balanced processor layout. The model cost is around 3,500 processor‐hours for one simulated year, with throughput of about 17.5 simulated years per wall‐clock day; see Table 6Energy‐balance and SMB calculations in the land model, with SMB remapped to the higher‐resolution ice sheet grid.Solid ice discharge from the ice sheet model to the ocean model.Dynamic surface types in the land model as the ice sheet advances or retreats.Evolution of the land‐atmosphere boundary with changing ice‐sheet surface topography.This study describes and demonstrates the interactive coupling of CESM2 with CISM2. The current coupling is bi‐directional throughout the ice sheet‐snow‐climate domain, and uni‐directional through the ice sheet‐ocean interface. This paper covers four primary aspects of the coupling:2 simulation. In the warmer climate, the GrIS‐integrated SMB becomes negative for the annual mean, has a much larger amplitude in the seasonal cycle, and expanded ablation zones. With greater melt in low‐elevation regions, the ice sheet margins thin. This results in steeper topographic gradients near the ELA, enhancing ice flow from the interior to the margins (Figures We demonstrated the capabilities of the new model by comparing a preindustrial simulation with a transient, high‐CO Figures  and 6b. 2 simulations (Muntjewerf, Sellevold, et al., CESM2‐CISM2 is one of a small number of coupled ice sheet‐climate models participating in the CMIP6‐endorsed ISMIP6 experiments (Nowicki et al.,