The effects of climate change constitute a major concern in Arctic waters due to the rapid decline of sea ice, which may strongly alter the movements and habitat availability of Arctic marine mammals. We tracked 98 bowhead whales by satellite over an 11-year period (2001–2011) in Baffin Bay - West Greenland to investigate the environmental drivers  involved in bowhead whale’s movements. Movement patterns differed according to season, with aggregations of whales found at higher latitudes during spring and summer likely in response to sea-ice retreat and increasing sea temperature (SST) facilitated by the warm West Greenland Current. In contrast, the whales moved further south in response to sea temperature decrease during autumn and winter. Statistical models indicated that the whales targeted a narrow range of SSTs from −0.5 to 2 °C. Sea surface temperatures are predicted to undergo a marked increase in the Arctic, which could expose bowhead whales to both thermal stress and altered stratification and vertical transport of water masses. With such profound changes, bowhead whales may face extensive habitat loss. Our results highlight the need for closer investigation and monitoring in order to predict the extent of future distribution changes. This is especially true for species inhabiting Arctic regions, where the effects of climate change are of major concern due to the decline of sea ice, i.e. a decrease of 3 to 4% per decade highlighted in the past 29 years5. Among the marine species that year-round inhabit Arctic waters, 11 are marine mammals 8. Sea ice provides access to air and platforms for haul-out, making some of these Arctic marine mammals strongly dependent on sea ice to support their life-history events8. For example, ribbon, spotted, harp and hooded seals breed on pack ice11, whereas ringed and bearded seals use stable ice for raising their pups and molting13.In response to climate change, modifications of the environmental conditions encountered by marine species might strongly alter their movements and consequently their habitat14. Heide-Jørgensen et al.15 have shown that sea-ice loss has an effect on beluga whales’ distribution in West Greenland, as with sea-ice retreat, beluga whales abandon the coastal ice-free areas and follow the retreating sea-ice to the west. Additionally, several studies conducted in the Bering Sea have concluded that bowhead whales are associated with areas of high sea-ice concentration (e.g. up to >90%19). However, unlike seals, polar bear and walrus, Arctic cetaceans  are not “sea-ice obligates”. They have evolved to deal with high concentrations of sea ice and they do not necessarily depend on sea ice, and in some cases, sea ice acts more like a barrier to potential feeding grounds. By structuring the ecosystem and therefore influencing prey availability7, the effect of sea ice on the movements of Arctic cetaceans is probably indirect, and the distribution of these species might be more influenced by thermal conditions and their cascading effects on the food chain rather than on the sea ice per se. In this study we address this question directly and attempt to determine which of a suite of habitat predictors best predict bowhead whale distributions.Associations between sea ice and their movements have also been highlighted for Artic cetaceans. The narwhal population of Davis Strait and Baffin Bay performs seasonal movements that are directly related to the retreat and advance of sea ice22, the relationships between Arctic cetaceans and this variable have been poorly investigated, with only a few studies focusing on beluga and bowhead whales. From May to July, most beluga whales move into lagoons and estuaries in warmer waters to feed, bear their calves and moult25. Beyond the summer season, Bailleul et al.26 have demonstrated that the timing of migration in this species was related to sea surface temperatures (SSTs) conditions, with a later summer departure during summers with warmers SSTs. Regarding bowhead whales, a recent study conducted on the Pacific stock has demonstrated an avoidance of warmer waters coming from the Alaskan Coastal current27.Although the main factor influencing the geographical range of many lower latitude cetaceans is water temperature28, the population of Baffin Bay-Davis Strait occupies a wide geographical range spreading from the Canadian High Arctic to West Greenland31. Several studies involving satellite tracking of individuals from this population have shown migratory patterns for this species, and noted that an aggregation occurs in Disko Bay, West Greenland, from February to June32. In this area, the strong inter-annual site fidelity of bowhead whales can be partly explained by high concentrations of copepods, making this site an important foraging ground35. However, the local biomass of their preferred prey peaks in June36, indicating that the whales leave the foraging ground of Disko Bay prior to the peak availability of copepods. The reason for this mismatch is unclear, and it has been proposed that ocean temperature may be involved, either by being outside the range commonly used by this species or by forcing water column stratification in spring, which subsequently changes the density of prey37. Given that the West Greenland Current brings warm North Atlantic waters to Disko Bay in spring40, and that the water masses on the West Greenland Shelf increase in temperature from April41, we expect that bowhead whales adapted to cold temperatures will avoid the increase spring temperature in Disko Bay.Among the five stocks of bowhead whalesTo test this hypothesis, we used tracking data from 98 bowhead whales originating from the same population of Baffin Bay-Davis Strait over an 11 year-time-series (2001–2011), to investigate the role played by either the SST and/or sea ice in driving their seasonal movements. Track lines or dive data from some of the whales have been presented in previous publications .The 98 bowhead whales from the Baffin Bay-Davis Strait population were tracked from three different locations. We obtained 826 ± 821 (mean ± SD) locations per whale (range: 2–4129), for a tracking duration ranging from 1 day (#6335_11) to 489 days  – see Supplementary Information Table Sp < 0,001). The estimated length of the whales differed significantly according to the tagging location, being longer for those tagged in Disko Bay , than those tagged in Foxe Basin , or in Cumberland Sound .The estimated length of the tagged whales ranged from 8.5 to 18 m, measuring on average (mean ± SD) 14.5 ± 2.0 m. The males were slightly but significantly longer  than the females  dispersed largely across Baffin Bay, all around Baffin Island and within the fjords of the Canadian Arctic Archipelago , the whales remained within Baffin Bay, aggregating close to Disko Bay Fig. . In summSeasonal patterns in latitudinal movements were observed across both years and according to tagging location Fig. . GloballAssociations between the whales’ movements and the SST were observed over the 10 tracking years. As warmer surface waters moved from the south-western part of Greenland in March, whales departed from Disko Bay and headed west across Baffin Bay Fig. . In JulyWith the autumn advance of sea ice and the decreased SST, the whales moved further south along the east coast of Baffin Island Fig. . OverallThe relationships between the whales’ movements and the SST front are shown in Figs March is the coldest month where annual sea-ice concentrations (SIC) in Baffin Bat (including Disko Bay) reaches values between 62 and 100% Fig. . From MaDuring summer (July to September), the whales used waters associated with lower SIC in Disko Bay and Cumberland Sound Fig. , pushingThe whales from Disko Bay tended to follow the sea-ice edge (defined as 50% isoline of SIC) during spring and winter Fig.  top. In For the habitat suitability, explained deviances ranged between 32% in autumn to 58% in winter  decreased with the distance to SST front Fig. , meaningDistance to sea-ice edge was a significant explanatory variable in spring, summer and winter. There was a positive relationship between the distance to sea-ice edge and the whale’s density in summer Fig. , with thThe SST variable was retained in the four seasonal models. Except in summer, when there was a negative relationship between SST and bowhead whale’s density Fig. , for theThe use of a large tracking dataset (n = 98) together with environmental covariates provided novel information on the crucial role played by the SST in driving the movements of a cetacean that resides year-round in Arctic waters. These results have also important implications for predicting the likely extent and distribution of habitat due to climate change.42. This is in accordance with a previous study conducted in this area showing that the population of Disko Bay is dominated by females (78%) larger than 14 m32. On contrast, the whales from Foxe Basin were composed of large individuals (15–18 m) associated with smaller, and likely immature whales (10–11 m). Heide-Jørgensen et al.32 found similar results using skin samples, and several studies suggested that Foxe Basin may be an important nursing ground in late summer and early autumn for this species44. Finally, the whales originating from Cumberland Sound were composed of smaller individuals (8–11 m), presumably immature whales. Given that sexual maturity is reached at 12–14 m in length in this species45, we assume that immature whales might not be ready to travel to Disko Bay to utilize the relatively deep waters in the bay compared to more shallow areas in Foxe Basin and Cumberland Sound. Despite the unequal sample size between the three tagging locations, the present tracking dataset confirmed that bowhead whales segregate by sex, age and reproductive status. For the first time, this large tracking dataset was analysed by combining the three different tagging locations in Baffin Bay, providing a reliable picture of the bowhead whale’s movements in this region as well as highlighting pronounced seasonal patterns.The satellite tracking of the 98 bowhead whales showed different spatial patterns based on where they were tagged. The whales tagged in Disko Bay dispersed much more widely and used a broader geographical range than the whales tagged in Foxe Basin or Cumberland Sound. The whales tagged in Disko Bay were mainly adult females (range: 12–18 m), some of which might have been pregnant, and may have given birth during the spring migrationet al.44, we have shown that the whales tagged in Foxe Basin were associated with lower ice concentrations during autumn-winter (mean SIC: 44%) compared to summer (mean SIC: 62%). The selection of areas characterized by less ice concentration, thinner ice and smaller floes in winter might reduce the risk of ice entrapment and provide protection from killer whales44, especially for immature individuals that are dominant in Foxe Basin. A similar trend was observed for the whales tagged in Disko Bay which experienced lower concentrations of sea ice during autumn (mean SIC: 18%) than during summer (35%). Despite their ability to break thick ice (up to 60 cm thick46), bowhead whales in Baffin Bay generally followed the sea-ice edge, especially those departing from Disko Bay to reach Baffin Island. Although the marginal ice zone is known to be one of the most productive areas in the Arctic Ocean47, the bowhead whales were more associated with particular values of SST rather than the sea-ice edge, suggesting that the sea-ice edge is unlikely to be used as a foraging area by this species. Many studies conducted in Disko Bay reinforce this assumption as they showed a high biomass of copepods Calanus during spring49, which is the main prey of adult bowhead whales.The seasonal pattern revealed by the whales’ tracks was characterized by north-south movements independent of tagging location. Despite the decreasing sample size through months (higher in spring and summer), all individuals reveal the same migration pattern, moving further north during the warm season (spring and summer), and moving south to lower latitudes during autumn and winter. This pattern is reinforced irrespective of tagging location, and is not an artefact of tag loss. In agreement with the study of Ferguson 31, and n = 27 from Foxe Basin44), and so far no study has tried to relate such a behaviour to sea surface temperature. The departure of bowhead whales from Disko Bay coincides with the inflow of warm waters coming from the Atlantic and transferred by the West Greenland Current40. Despite the sea-ice retreat removing the physical barrier for whales crossing Baffin Bay, it may be that an affinity for colder waters could explain the whales’ departure as SST increases. This hypothesis is supported by our findings from the habitat models that show a consistent relationship between SST and bowhead whale densities for all seasons, highlighting an optimum temperature varying from −0.5 °C in spring to 2 °C in autumn. A similar behaviour was observed for the bowhead whales from the Bering-Chukchi-Beaufort Sea population which apparently avoid the warm Alaskan Coastal Current27, although the authors suggest it was the lower densities of zooplankton in the warm waters that spurred the movements of the bowhead whales. In contrast, the bowhead whales in Baffin Bay abandon highly productive waters in Disko Bay just prior to the peak zooplankton bloom in the area36. This supports the observation that the whales’ departure from Disko Bay is not related to the availability of their prey but rather the preference to remain in cooler waters. Bowhead whales have extremely thick blubber layers, that in Disko Bay has been measured up to 36 cm50, providing insulation adequate to maintain steady thermal state in external temperatures as low as liquid oxygen51. This indicates that potential heat-stress or hyperthermia from swimming activity is likely a key factor influencing the bowhead whales’ movements away from warm water despite dense zooplankton concentrations. The whales capitalize on the zooplankton production in Disko Bay to increase the blubber layer as a protection against leaner periods, but the increased metabolism, with ensuing heat dissipation, required for long-distance movements drives the whales away from the area before the increase in water temperatures. The narrow range of surface temperature experienced by the whales (means: −1.6 to 2.7 °C) compare to the range observed in Disko Bay (means: −1.7 to 9 °C) supports this assumption. For bowhead whales with limited heat exchanging appendages  it seems unlikely that they can avoid hyperthermia in sea water of 9 °C (summer temperature in Disko Bay) without lowering metabolic rates to unrealistically low levels51.The migratory behaviour of bowhead whales has already been evidenced by previous studies on this population but for fewer individuals . The diving and foraging behaviour of bowhead whales might explain such low percentages of explained deviance; whales follow the vertical migrations of copepods and can either feed on pelagic or hibernating zooplankton aggregations close to the sea floor35. Variability of the diving behaviour adds complexity to the environmental drivers and may limit the explanatory power of the additive models. Two studies have focused on the diving behaviour of bowhead whales in Baffin Bay35, but these were restricted to limited tracking durations (<30 d) and to Disko Bay. To better understand the three dimensional habitat use by this species during a complete migratory cycle (one year), additional diving data, together with in situ variables  to relate their diving behaviour to the properties of the water column are needed.Although the values of the explained deviances from the GAMs were comparable to what is commonly found in the literature when relating cetacean’s densities to environmental variables, e.g.55. Copepods species like C. hyperboreus are hibernating at depths below those reached by the bowhead whales for most of the year where a pycnocline is also present33. The nutrient rich copepod C. hyperboreus has a very strict seasonal timing of vertical migrations and presence in the upper part of the water column accessible to bowheads56. In the Baffin Bay area, the other copepod species, C. finmarchicus is present throughout the winter at depths accessible to bowhead whales, but the larger and the more lipid rich C. hyperboreus is only available for a short period in late spring57. The main prey of bowhead whales – C. hyperboreus – hibernates at great depths and is only available to bowhead whales during spring when they make vertical migrations to the strictly seasonal phytoplankton bloom. It is therefore an important observation that bowhead whales in Baffin Bay abandon the Disko Bay feeding ground when sea temperature increases and before the peak abundance of C. hyperboreus.Given the complexity of the vertical processes occurring in the water column, the SST cannot alone explain the movements of bowhead whales and their departure from Disko Bay, but SST should however be considered as a proxy for what drives the movements of this arctic species in Baffin Bay. In essence, SST is used as a variable to capture both the thermal stress bowheads are exposed to, and the changes in stratification of the water masses. Simultaneous with the increase in SST, a distinct stratification of the otherwise well mixed water column takes place59. In the current study this is evidenced by the variable selection of summering grounds either east or west of Baffin Island, a flexibility that is not observed for the two other Arctic cetaceans , that both have fairly predictable migratory patterns and high matrilineally driven site-fidelity61. Despite their relative plasticity in movement patterns, bowhead whales also function under strict environmental and physiological restraints. Evidently the sea ice should not be so thick that it prevents the whales from reaching the surface for breathing, sea ice appears to act more like a barrier restricting access to foraging areas rather than an asset for the whales. In some parts of their range in Baffin Bay, the bowhead whales will summer in areas that are completely devoid of sea ice (e.g. Isabella Bay) or have only scattered ice (15–50% coverage) as observed in most areas. What appears to be more important is that the sea surface temperature should be below 2 °C, which, in this region, often coincides with areas that have sea ice in winter and spring. The productive feeding area in Disko Bay35 is abandoned in late spring when the temperature rises and nothing suggests that prey availability is a driver for the departure from the bay. Our data are consistent with Disko Bay being used for spring feeding excursions for mainly mature females without calves while the core area used by the rest of the bowhead whale population (from Foxe Basin and Cumberland Sound) is around the Canadian Arctic Archipelago. However, feeding in Disko Bay by mature whales comes with the price that the area must be abandoned before sea temperatures rises and the whales, with replenished blubber deposits, will suffer from thermal stress. Long movements with high level of muscle activity will likely increase the risk of hyperthermia and travels across Baffin Bay may need to be initiated well in advance of the rising sea temperatures.Of the three Arctic cetaceans occurring in Baffin Bay, the bowhead whale undoubtedly has the greatest flexibility in movement patterns and habitat selection62) were instrumented with satellite transmitters during March to May in 2001, 2002, 2003, 2005, 2006, and between 2008 and 2011 from Qeqertarsuaq . See Supplementary Information Table et al.31 and Nielsen et al.63 for a description of the tag configurations. The study was conducted under the general permission from the Government of Greenland to the Greenland Institute of Natural Resources for tagging baleen whales. The protocol for tagging of bowhead whales was reviewed and approved by the Danish Animal Welfare Committee (IACUC), Faculty of Health Sciences, University of Copenhagen.Adult bowhead whales  from small (6 m) boats with outboard engines (150 hp). As soon as a whale was spotted, the boats quickly moved close to the whale, and while the whale was diving, the boats spread out and waited for the whale to reappear. This procedure was repeated until it was possible to get close enough to apply the tag from the boats. Tagging was done either by using a custom-made 8 m long fiberglass pole or a pneumatic gun65. The filtering approach of Albertsen et al.66 was applied to the tracking data in order to improve the Argos locations. We then used the General Bathymetric Chart of the Oceans (GEBCO) database  to discard any remaining locations on land (2.8%). We also discarded the Argos locations associated with a speed of over 10 km.h−1 (0.05%), as well as “type Z”  locations (0.01%).Data were relayed through the Argos Data Collection and Location System and decoded using Argos Message Decoder . All statistical analyses were performed using R software version 3.4.3Global Ocean Physics Reanalysis Glorys S2V4 product (PHYS 001-025) at a resolution of 0.25° (from E.U. Copernicus Marine Service Information). Distance from sea-ice edge was calculated as the minimum distance between each whale location and the 50% sea ice concentration isoline  derived from the SST over the whole study area. To identify the locations of oceanic fronts based on SST gradient, we used the areas with the highest SSTgrad magnitude (≥quantile 0.99) and calculated the distance between each whale position and the closest frontal zone identified.We extracted two environmental variables from both remote sensed data and model simulations to characterize the habitat of bowhead whales at their tracking locations. At each whale location, we extracted the daily associated Sea surface temperature (SST), sea ice concentration (hereafter SIC) from the 68.To assess seasonal patterns, one habitat use map per season was generated from tracking data by cumulating the number of days each individual had crossed each grid cell of 0.5 × 0.5 decimal degree. Seasons were defined as follow: spring from April to June, summer from July to September, autumn from October to December and winter from January to March. Indeed, the bowhead whales generally arrive in West Greenland between January and March, they spend April to mid-June in Disko Bay and abandon West Greenland after July. During July-September they roam widely in the CAA before moving towards their wintering ground Hudson Strait in October-December40, we assumed that the whales wintering in Disko Bay would be more exposed to large changes in temperature and sea ice. For that reason, tracks from whales tagged in Foxe Basin and Cumberland Sound were not included in the habitat modelling analysis. To investigate whether SST or sea ice had an effect on bowhead whale movements, we constructed a series of Generalized Additive Models (GAMs) using the mgcv package in R70. The response variable was the number of bowhead whales that crossed each pixel of 0.5 × 0.5 decimal degree. Monthly grids of presence data (i.e. from the tracking data) were generated by aggregating the whale’s tracks for each month of each tracking year. The monthly averaged SST and SIC were extracted in each monthly grid cell, and the distance to the closest SST front and to the sea-ice edge were derived following the method described above. The response variable was over-dispersed counts. Accordingly, we employed GAMs with a Negative Binomial error distribution. Such a distribution can provide good fits when dealing with over-dispersed count data71. Four environmental predictors were used: SST, SIC, distance to sea-ice edge and distance to the closest SST front. For each season, the models with all possible combinations were compared using the Akaike Information Criterion (AIC) and their explained deviance, and including the variables with a Variance Inflation Factor below three to avoid collinearity72. Temporal autocorrelation was then tested for each selected model using the acf function in R. To account for spatial autocorrelation, spatial coordinates (i.e. longitude and latitude) were included in each model as an explanatory variable, and the tracking year was included as a factor to account for potential inter-annual effect.Given that the eastern part of Baffin Bay is more influenced by the warm waters coming from the North Atlantic than the western partSummary of the horizontal movements of the 98 bowhead whales (Table S1) and AIC results showing all possible combinations for the seasonal GAMs (Table S2).


This study evaluated the technical adequacy of trans-articular sacroiliac joint (SIJ) fusion using three screws for non-traumatic SIJ pain, considering different grades of sacral dysplasia.Cadaveric CT data of unilateral sacropelvic complexes for 72 individuals (53.4 ± 8.4 years) were selected. A 3D model was reformatted into the plain lateral radiograph to mark the articular surface of the SIJ. Subjects were classified into dysplastic (DYS) and non-dysplastic sacrum (NDS) groups. Proximal (PS), middle (MS), and distal screws (DS) with 10-mm diameter were virtually introduced to the iliac bone and the SIJ on the lateral image with a 5-mm safety margin. On a corresponding axial image, each screw was advanced vertically to the sagittal plane with the same safety margin. The entry points for each screw to the endplate of S1 (S2) and to the corresponding anterior sacral margin on the lateral image were measured, along with the maximal screw lengths on the axial image. Whether each screw passed through the SIJ was determined. Different types of sacral dysplasia and screws were compared statistically.Thirty-eight (26.4%) cases were DYS, and 106 (73.6%) were NDS. The entry points of all screws were significantly more distal in DYS than in NDS groups. The PS and MS screw lengths differed significantly between the 2 groups. Incidences of short sacral fixation (< 10 mm) were significantly higher for the DS in both NDS (38.7%) and DYS (39.5%) groups. Incidences of screw pass were lowest for the MS in both NDS (43.4%) and DYS (47.4%) groups.Sacral dysplasia locates the SIJ more distally and therefore affects the entry point locations and screw lengths for all screws in trans-articular SIJ fusion, compared with a non-dysplastic sacrum. Moreover, three-screw fixation risks the development of unstable DS fixation and a high extra-articular fixation rate in MS. Pain from the sacroiliac joint (SIJ) is mostly in the buttock, lower back, and inguinal region and is similar to pain from the lumbosacral region –3. The iTrans-iliosacral fixation is performed in patients with traumatic sacroiliac dissociation using two long screws unilaterally or bilaterally to pass the midline of the sacrum , 11. DurTrans-iliosacral fixation techniques for non-traumatic SIJ pain differ from those for traumatic cases by using trans-articular fixation for SIJ fusion, mostly unilateral fixation, and two or three shorter screws –17. HoweThe objectives of this study were to establish a proper technique for percutaneous trans-articular iliosacral fixation for SIJ fusion and to define the clinical implications of sacral dysplasia for non-traumatic SIJ pain by determining the entry point and maximal screw length available when using 3 screws with maximally available screw diameter and conventional trajectory and maintaining 5 mm-safety margins to the adjacent sacral cortex in the presence of sacral dysplasia.Cadaveric CT data for 144 unilateral sacropelvic complexes from 72 individuals  were selected from the registration of the Catholic digital human library; the chosen subjects had no deformities, fractures, or surgeries to the lumbo-sacropelvic bones , 19. TheA 3D model of each sacropelvic bone complex was reconstructed from the CT data using the Mimics  software . In the In the software, three virtual screws were made with 10-mm cylinders and applied to the reconstructed sagittal images , 21. TheAfter establishing the entry points on the sagittal image, each screw was inserted vertically from the lateral margin of the iliac bone to the mid-sagittal plane on the corresponding axial image and stopped at the point required to maintain the 5-mm safety margin from the lateral margin of the canal without violating the margins of the anterior sacrum, canal, or foramens Fig. .Fig. 3MThe entry point of each screw was measured on the sagittal image. For the PS, the entry point for the proximal-to-distal distance was measured as the shortest distance from the center of the PS to the upper endplate of S1. For the MS and DS, the entry points for the proximal-to-distal distance were measured from the center of each screw to the upper endplate of S2. The entry point for the anterior-to-posterior distance for the PS was measured as the distance from the center of the screw to the anterior margin of the mid-sagittal image on the line parallel to the upper endplate of S1. For the MS and DS, the entry point for the anterior-to-posterior distance was measured as the distance from the center of each screw to the anterior margin of the mid-sagittal image on the line parallel to the upper endplate of S2  and that passing just the sacrum  were measured on the corresponding axial image Fig. . Both aupass. If the screw circle occupied ≤50%, it was categorized as no-pass.Whether the screw passed through the SIJ was determined by the percentage of the screw circle occupying the articular surface on the axial image. If the screw circle occupied > 50%, it was categorized as Using a previously published guideline , a dysplTo compare demographic data between the two-sacrum (NDS and DYS) groups, a student t-test was performed for age, and a chi-square test was performed for the sex ratio Table .The entry points of the proximal-to-distal and anterior-to-posterior distances for each screw were compared between the groups using one-way ANOVA, with the entry point as the dependent variable and the sacrum group as an independent variable Table .One-way ANOVA were also performed to compare the total and sacral screw lengths between the groups, with the screw length as the dependent variable and the sacrum group as an independent variable. Within each group, the total and sacral screw lengths between screws  were compared by one-way ANOVA, with the screw length as the dependent variable and the screw as an independent variable. When significance was found on the screw variable, post-hoc analyses were used to analyze the differences between the screws Tables  and 4. AChi-square tests were performed to compare the incidence of short (< 10 mm) sacral screw length Table  and screThe NDS and DYS groups contained 106 (73.6%) and 38 (26.4%) unilateral sacropelvic complexes, respectively. The age of the two groups did not differ significantly. However, the sex ratio of the two groups did differ significantly: the NDS group contained more females, and the DYS group contained more males , and that of the MS was significantly longer in DYS (40.2 mm) than in NDS groups (36.9 mm) (P <  0.001). The total screw lengths of the DS did not differ significantly between the groups. The total screw length of the PS, MS, and DS became significantly longer in the NDS group in that order. In the DYS group, the total screw lengths of the PS and MS were significantly longer than that of the DS, but the PS and MS did not differ significantly from each other  than in DYS (40.6 mm) (S groups 6.9 mm (PP = 0.009). The sacral screw lengths of the DS did not differ significantly between the groups. The sacral screw lengths of the PS, MS and DS became significantly longer in that order in both groups  than in DYS (19.8 mm) (P <  0.001), and that of the MS was significantly longer in DYS (16.3 mm) than in NDS groups 14.2 mm)  for the PS, MS, and DS did not differ significantly between the groups. The incidence for the DS , MS [12 (11.4%)], and PS [0 (0%)] was significantly higher in that order in NDS group. The incidence for the DS [15 (39.5%)] was significantly higher than that for the PS [0 (0%)] and MS [3 (8.6%)], but the differences between the PS and MS were not significant in DYS group , 46 (43.4%); 67 (63.2%); 104 (98.1%)] and DYS groups , respectively  were observed in our study population of 144 subjects. The prevalence of sacral dysplasia in this study is similar to previous studies (30 to 50%); it is not uncommon . Sacral These findings of sacral dysplasia were preventing the safe passage of a trans-iliosacral screw to S1 in surgeries for sacropelvic injuries, because the obliquely shaped alar anatomy restricts the area for screw fixation . The narHowever, screw fixation for dysplastic upper sacrum in non-traumatic SIJ fusion does not necessarily cross the sacral foramen from the sacroiliac articulation, because fusion occurs through the relatively stable but degenerative SIJ using multiple shorter screws under fluoroscopic guidance . TherefoThe ICD identified on the lateral image of the sacrum indicates the proximal margin of the SIJ. The proximal and distal margins of the SIJ can be identified on the AP view of the sacrum or the pelvic outlet view. The anterior and posterior margins of the SIJ cannot be clearly delineated on plain radiographs of the sacrum and pelvis, but they can be identified on a CT scan. Even with a CT scan, the anterior and posterior margins of the SIJ can be identified only partially on each axial view  because the sacrum contains the geographically complex sacral canal and foramens, causing unclearly delineated articulating margin of the SIJ on plain radiographs , 30–33. Unlike surgery to stabilize unstable sacropelvic injuries, trans-iliosacral fixation for non-traumatic SIJ pain demands trans-articular fixation for SIJ fusion , 15, 17.Two-screw fixation for trans-articular SIJ fixation in Asians may reduce iatrogenic complications . However, the effects of race and ethnicity on iatrogenic complications following trans-articular SIJ fusion were not investigated in this study.Sacral dysplasia locates the SIJ more distally than seen in non-dysplastic sacrum, which affects the entry points and screw lengths for all screws in trans-articular SIJ fusion for non-traumatic SIJ pain. Three-screw fixation risks unstable distal screw fixation and high rates of extra-articular fixation in the middle screw.


Adverse reactions (ARs) to drugs administered during general anesthesia may be very severe and life-threatening, with a mortality rate ranging from 3 to 9%. The adverse reactions to drugs may be IgE and non-IgE-mediated. Neuromuscular blocking agents (NMBA) represent the first cause of perioperative reactions during general anesthesia followed by latex, antibiotics, hypnotic agents, opioids, colloids, dyes and antiseptics (chlorhexidine). All these substances  may cause severe systemic non-IgE-mediated reactions or fatal anaphylactic events even in the absence of any evident risk factor in the patient’s anamnesis. For this reason, in order to minimize perioperative anaphylactic reactions, it is important to have rapid, specific, sensitive in vitro diagnostic tests able to confirm the clinical diagnosis of acute anaphylaxis. The potential occurrence of hypersensitivity reactions (IgE-mediated or non-IgE-mediated) is a great concern for anesthesiologists, because adverse reactions (ARs) may be very severe and life-threatening, with a mortality rate ranging from 3 to 9% . Fatal aThe individuation of the culprit agent is very difficult because of the several drugs administered during general anesthesia. Neuromuscular blocking agents (NMBA), latex, antibiotics, induction agents and opiates are the most common substances incriminated in perioperative anaphylaxis –6. PerioThe incidence of anaphylaxis is estimated between 1 in 10,000 and 1 in 20,000 anesthetic procedures . HoweverAn IgE-mediated mechanism has been confirmed in 40–70% of cases . GeneralIn recent decades perioperative adverse reactions had more attention and the general view is that immediate-type hypersensitivity reactions are largely under reported and causes remain often unknown. In addition, the extremely variable rate of reactions is due to the lack of homogeneity of clinical criteria and diagnostic tests, and the diversity of the populations studied .In case of IgE-mediated perioperative anaphylaxis, NMBA represent the first cause whereas latex is the second responsible allergen, followed by antibiotics –15. AbouNMBA (muscle relaxants) are responsible for 60–70% of anaphylactic episodes during general anesthesia or in the postoperative setting , 12, thuUnfortunately, quaternary ammonium groups are ubiquitous epitopes, which are contained in other drugs or disinfectants, so such reactive groups are responsible for cross-reactivity phenomenon with other drugs.The presence in NMBA of ubiquitous epitopes such as a substituted ammonium group (that are likely the immunodominant determinant recognized by IgE) is responsible for high cross-reactivity among these drugs  , but croPholcodine, for instance, is a potentially sensitizing antitussive agent with similar structure to morphine and NMBAs, which was able to induce the production of IgE antibodies cross-reacting with suxamethonium . In addiIn the light of these findings, previous exposure to non-anesthetic drugs or other substances may induce a hidden sensitization to muscle-relaxing agents, resulting in reactions among patients without prior anesthesia.The commonest triggers of NMBA reactions were found to be the suxamethonium (the most involved), followed by rocuronium, and then in descending order by vecuronium, pancuronium and atracurium . SeveralHevea brasiliensis) is a long-lasting, resistant and elastic product, which allows to maintain good tactile sensitivity and it protects against diseases transmitted through body fluids, so latex-derived products are largely present in hospital setting  [Latex (andages) , 25. Latandages)  because andages) , 25, 27.andages) . The risandages) , housewiandages) . Obstetrandages) .As latex allergy is suspected by clinical history , patients have to undergo skin prick test (SPT) and serum-specific IgE tests. SPTs are usually performed with several commercial extracts and with extemporary preparations at various dilutions obtained from high allergens content latex gloves and represents the gold standard in the diagnosis of latex allergy, characterized by high sensitivity and specificity .Serum-specific IgE can be detected through molecular diagnosis by ImmunoCAP/ISAC method  that is able to distinguish between a true sensitization and an asymptomatic cross-reactivity. Latex allergens Hev b 1, Hev b 3, Hev b 5 and Hev b 6 are currently considered markers of genuine latex sensitization , 34. On In sensitized patients, the exposure to NRL proteins can provoke a type I IgE-mediated hypersensitivity reaction and a type IV reaction (not life threatening) responsible for a contact dermatitis that elicits slow-onset eczematous reactions. IgE-mediated reactions may involve various organs and systems, even simultaneously. Clinical manifestations, that occur within a few minutes after contact with NRL proteins, include urticaria, angioedema, conjunctivitis, allergic rhinitis, asthma and anaphylaxis. Immediate reactions, such as anaphylaxis, can be life threatening , 35 and Airborne exposure to latex may also cause a contact dermatitis. It is a non-immune-mediate reaction that appears at the side of contact and cause itching, redness, blisters .Primary prevention is the avoidance of sensitization in at-risk population whereas secondary prevention means avoiding the onset of the allergic reaction in previously sensitized patients by establishing a “latex-free environment” not only in operating rooms, but also in all recovery rooms –39. SevePenicillins and cephalosporins are responsible for 70% of perioperative anaphylactic reactions induced by antibiotics . The reaBetalactam antibiotics, vancomycin and quinolones are frequently implicated in adverse reactions during perioperative period representing the third cause of anaphylactic reactions in the surgical patients .Heterogeneous and various mechanisms are involved in adverse drug reactions due to penicillins and other betalactams such as cephalosporins both IgE-mediated and non IgE-mediated in addition to unknown mechanisms.l-lysine (PPL) and so-called minor determinants mixture (MDM), including amoxicillin (AX) and ampicillin (AMP) [According to EAACI interest group on drug hypersensitivity, the diagnostic protocol for allergic reactions to b-lactam  contemplin (AMP) , 13.Provocation tests with b-lactam antibiotics should be performed only in patients with a positive clinical history but negative IgE and skin test investigations .Vancomycin, a glycopeptide antibiotic usually used for treatment of Gram positive resistant organisms and for patients with penicillin allergy, may provoke reactions both IgE-mediated and non IgE-mediated. Typically Vancomycin is responsible for “red man syndrome” consisting in non-IgE-mediated hypersensitivity reactions with flushing, pruritus, an erythematous rash of the head and upper torso, and arterial hypotension. These non-immunologic reactions are associated with a rapid infusion of the drug at the first dose , 51. SomQuinolones represent the third most important group of antibiotics involved in perioperative anaphylaxis . They caAmong the barbiturate anesthetics, in the past years, thiopental was in the most frequent agent responsible for anaphylaxis during anesthesia, but in more recent surveys, anaphylaxis from thiopental sodium is only rarely described because of the its less intensive application .Generally, although their frequent application, anaphylaxis from non-barbiturate hypnotics is rare .Propofol is a hypnotic agent that has been associated with anaphylactic reactions . DespitePropofol allergy has been diagnosed by skin tests, by sIgE and by histamine-release tests, although propofol can induce also a direct release of histamine concentration-dependent .Yet, benzodiazepines are rarely a cause of immediate hypersensitivity reactions. Among this drug class, midazolam is the main causative agent in the perioperative setting , 46, andIn the perioperative period patients are exposed to many substances  to ensure maximum safety and best care. All these substances may cause severe systemic non-IgE-mediated reactions or fatal anaphylactic events even in the absence of any evident risk factor in the patient’s anamnesis. It is important to keep in mind that is not always possible to detect certainly the culprit agent of a perioperative anaphylaxis because the cause-effect relationship is often difficult to demonstrate. In addition the diagnosis is not easy to make in an anesthetized patient because there are technical objective difficulties to recognize a hypersensitivity reaction in a perioperative setting. Firstly, the patient is unconscious and uncompliant, so anesthetists may only control vital signs and sudden changes in cardiac rate, a drop in blood pressure or a desaturation in pulse-oxymetry is not sufficient to suspect the onset of an immediate type hypersensitivity because such modifications may be associated with other pathologic conditions, i.e., a spontaneous pneumothorax, myocardial infarction or severe arrhythmia, which an anesthetists must consider rapidly.Muscle relaxants, NRL and antibiotics are the most common anesthetic drugs or substances that may be involved in anaphylaxis.To prevent successive anaphylaxis events, it is important to document every ARs and, above all, substances and/or drugs used during anesthesia, so that the identification of the causative drug by allergist can be simpler. Once the diagnosis has been made, the patient must be informed about symptoms during the anesthesia, the drugs that have been responsible for the reaction and must be provided with a bracelet or a tag that shows in detail the drugs to which he is allergic.Prevention is an important component to decrease the incidence of anaphylaxis especially for latex which is the second cause of anaphylactic reactions in perioperative period. Often this is underestimated because when ARs occur, the drugs are considered mainly responsible . PeriopeIn realty, the greatest necessity, in order to minimize perioperative anaphylactic reactions, is to have rapid, specific, sensitive in vitro diagnostic tests able to confirm the clinical diagnosis of acute anaphylaxis.


AMP-activated protein kinase (AMPK) is a key regulator of cellular energy homeostasis. Although AMPK has been studied extensively in cellular processes, understanding of its substrates and downstream functional network, and their contributions to cell fate and disease development, remains incomplete. To elucidate the AMPK-dependent signaling pathways, we performed global quantitative phosphoproteomic analysis using wild-type and AMPKα1/α2-double knockout cells and discovered 160 AMPK-dependent phosphorylation sites. Further analysis using an AMPK consensus phosphorylation motif indicated that 32 of these sites are likely direct AMPK phosphorylation sites. We validated one uncharacterized protein, ARMC10, and demonstrated that the S45 site of ARMC10 can be phosphorylated by AMPK both in vitro and in vivo. Moreover, ARMC10 overexpression was sufficient to promote mitochondrial fission, whereas ARMC10 knockout prevented AMPK-mediated mitochondrial fission. These results demonstrate that ARMC10 is an effector of AMPK that participates in dynamic regulation of mitochondrial fission and fusion. AMPK is regulates cellular energy and has been extensively studied, although our knowledge of downstream substrates is incomplete. Here, Chen et al. perform global quantitative analysis for AMPK-dependent sites and validate one hit, ARMC10, as a direct AMPK effector of mitochondrial dynamics. AMPK also phosphorylates 3-hydroxy-3-methyl-glutaryl–coenzyme A reductase and glycerol-3-phosphate acyltransferase to block the synthesis of sterols and triglycerides, respectively2. These regulatory actions by AMPK ensure increased cellular ATP supplies and decreased ATP consumption. AMPK also modifies the mammalian target of rapamycin complex, which functions as the master switch in controlling cell proliferation and fate by inhibiting autophagy and apoptosis4.AMP-activated protein kinase (AMPK) is a kinase complex that acts as a central regulator of cellular energy homeostasis in eukaryotes. It monitors ATP levels in cells. When the ratios of AMP:ATP and ADP:ATP increase, AMPK is activated and controls the activities of enzymes in a variety of pathways to ensure energy homeostasis. It switches on the glucose uptake and other catabolic pathways to generate ATP, while switching off the anabolic pathways to prevent the consumption of ATP, such as the conversion of glucose to glycogen7. Moreover, several compounds that have become therapeutic centerpieces seem to produce their protective and therapeutic effects by modulating AMPK signaling. For example, investigators are testing metformin and other agents that activate AMPK in the clinic as potential anticancer agents8.As a key regulator of many cellular processes, AMPK plays a central role in a variety of human diseases. Studies of AMPK in cancer, diabetes, and other human diseases verified its important roles in disease development11. Also, Brunet and colleagues combined a chemical genetic screen and peptide capture technique to identify AMPK phosphorylation sites12. James and colleagues reported on their global phosphoproteomic analysis of acute exercise signaling in human skeletal muscle and performed additional targeted AMPK assays and bioinformatics analysis to predict AMPK substrates13. Furthermore, Sakamoto and colleagues used an anti-AMPK motif antibody to discover AMPK targets14. Although these experimental approaches identified many AMPK substrates, defining the AMPK-dependent signaling network remains challenging because of the high background or noise level. Bioinformatics analysis is one way to filter data and uncover bona fide AMPK substrates. In this study, we reduced background by using AMPKα1/α2-double knockout (DKO) cells as controls.Discovery of AMPK substrates is critical for understanding AMPK functions and its applications in disease treatment. Several groups have used different strategies to identify AMPK substrates. For example, Shaw and colleagues, using 14-3-3 binding and AMPK substrate motif searching, identified several important AMPK substrates, such as ULK1, Raptor, and mitochondrial fission factor (MFF)17 allows knockout (KO) of target genes and study of their biological functions in human cells. This straightforward and highly efficient approach is ideal for phosphoproteomic studies, as it greatly reduces the background. In the study described here, we combined the CRISPR-Cas9 technique and global quantitative phosphoproteomic analysis to discover new members in the AMPK-dependent signaling network. We generated AMPK-deficient HEK293A cells by doubly knocking out two functionally redundant AMPK catalytic subunits: AMPKα1 and AMPKα2. These function-deficient cells are ideal controls for global phosphoproteomic analysis. By using this procedure, we identified 109 phosphosites with markedly higher phosphorylation levels in HEK293A AMPK wild-type (WT) cells after AMPK activation than those in AMPKα1/α2-DKO cells. Another 51 phosphosites were found to be phosphorylated at lower levels in AMPK WT cells than those in AMPKα1/α2-DKO cells, suggesting that these are likely phosphorylation events that are negatively and probably indirectly regulated by AMPK expression. Further analysis of the 109 upregulated phosphosites using known conserved AMPK phosphorylation motifs revealed 32 potential AMPK phosphorylation sites, 24 of which are newly discovered, previously unreported sites. We subsequently validated the phosphorylation site S45 of Armadillo repeat-containing protein 10  as an AMPK substrate site. Overexpression of ARMC10 promoted mitochondrial fission. Conversely, KO of ARMC10 prevented AMPK-mediated mitochondrial fission. Thus, we uncovered additional components of the AMPK-dependent signaling network and revealed ARMC10 as a novel AMPK substrate and effector involved in the dynamic regulation of mitochondrial fission and fusion.The recently developed CRISPR-Cas9 genome editing technologyTo identify new AMPK substrates, we combined the CRISPR-Cas9 genome-editing technology and quantitative phosphoproteomic in our workflow Fig. . We desi2 beads and analyzed them by using an LTQ Orbitrap Elite mass spectrometer   Fig. . We condMA) Fig. .19. In total, we acquired 9122 phosphopeptides  for the quantification of phosphopeptides. These analyses revealed 109 phosphosites with higher phosphorylation levels in WT cells than those in AMPKα1/α2-DKO cells  in WT cells than those in AMPKα1/α2-DKO cells  data and calculated the ratio between WT and AMPKα1/α2-DKO for the phosphopeptidesn = 32) . These sites may be regulated by the AMPK-dependent signaling pathways but are not directly phosphorylated by AMPK. The 51 phosphorylation sites that had higher levels of phosphorylation in AMPKα1/α2-DKO cells than in WT cells were classified as group 3. For these phosphosites, the motif analysis identified only one conserved amino acid P at the site right after the phosphosite, which is a potential phosphorylation site for cyclin/cdks and/or MAPK , MTFR1L S238 (reported at S103), AHNAK S135 (reported at S572), and ABLIM1 S706 (reported at S450|S452). For these four AMPK-dependent substrates, we identified different phosphosites than that previously reported. This may indicate that multiple AMPK phosphorylation sites exist in these proteins. These four sites and the remaining 20 sites are potentially novel AMPK phosphorylation sites, as indicated by our phosphoproteomic and bioinformatics analysis  at S539 and S582 is required for the association of the KLC interaction scaffolding protein 14-3-322, and it is crucial for PI3K transportation23. Because the protein sequence identity between KLC2 and KLC4 is 67.19%, and the sequence surrounding the KLC4 S590 site  is very similar to the sequence surrounding the KLC2 S582 site , we speculate that AMPK-dependent phosphorylation of KLC4 may participate in a similar or related function.In our data set, we identified a KLC family protein (KLC4) that is potentially phosphorylated by AMPK at S590, which agrees with the results of a previous high-throughput studyp value. Furthermore, we identified two different peptides for ARMC10 S45, which differ only by an alternative splicing site two residues after the phosphorylation site. REEP1 S152 and REEP2 S150 are from the same protein family, and the phosphorylation sites are within the same region with high sequence similarity . As already mentioned, the KLC4 S590 site is conserved and shares extensive sequence similarity with known AMPK phosphorylation site S582 in KLC2. MFF S172 is a control, which was reported as an AMPK phosphorylation site11. The six peptides for these five phosphorylation sites (ARMC10 S45_1 and ARMC10 S45_2 are two peptides but the same phosphorylation site from different isoforms) consistently showed stronger signals in AMPK WT cells than in AMPKα1/α2-DKO cells  in group 1 for further analysis. ARMC10 S45 is at the top of the list when ranked by lls Fig. .Fig. 3VaThe cDNAs of these genes were fused with S protein, Flag, streptavidin-binding peptide (SFB) tags and transiently expressed in AMPKα1/α2-DKO or WT cells. We harvested cells after treatment with 100 μM A769662 for 24 h, pulled down the overexpressed proteins with streptavidin beads, and analyzed them via Western blotting with an anti-phospho-Ser antibody and phospho-AMPK substrate motif antibody, respectively. We found that signals for ARMC10, KLC4, and REEP2 were higher in AMPK WT cells than in AMPKα1/α2-DKO cells as detected using the anti-phospho-Ser antibody Fig. . We did Our phosphoproteomics study identified the ARMC10 phosphorylation site S45 with two different peptides, both of which had considerably higher phosphorylation levels in AMPK WT cells than those in AMPKα1/α2-DKO cells Fig. . These tTo determine whether phosphorylation of the ARMC10 S45 site is regulated by AMPK, we first confirmed the specific interaction between AMPK and ARMC10 by pulldown assay. ARMC10 interacted only with AMPKα1 and AMPKα2, not with LKB1 or CAMKKβ Fig. . The twoWe detected phosphorylation only in the short isoform of ARMC10 Fig. . This ma24. We confirmed the mitochondrial localization of ARMC10 in HEK293T by using immunostaining  staining as a marker of autophagy. As shown in Supplementary Figures ARMC10 can induce changes in mitochondrial morphology and alter mitochondrial distribution, which may also cause mild mitochondrial aggregation36. We generated stable BioID2-tagged ARMC10-expressing HEK293T cells lines and performed BioID2-MS experiments with these cell lines six times. We used two controls—a BioID2 tag only and a BioID2 tag fused with another protein—for comparison. The candidate ARMC10 interactome comprised many proteins involved in mitochondrial fission and mitophagy  for pulldown experiments to test for potential interactions with ARMC10 in the regulation of mitochondrial dynamics. We found that ARMC10 can interact with two mitochondrial fission proteins, MFF and FIS1, that are important in mediating Drp1 recruitment during mitochondrial fissionPA1 Fig. . We furtPA1 Fig. . As MFF PA1 Fig. .In the present study, we performed global quantitative phosphoproteomic analysis and discovered 160 AMPK-dependent phosphorylation sites, and 32 of these sites are likely direct AMPK phosphorylation sites. We validated one uncharacterized protein, ARMC10, and demonstrated that the S45 site of ARMC10 can be phosphorylated by AMPK. According to our study, ARMC10 is an effector of AMPK that participates in dynamic regulation of mitochondrial fission and fusion in response to energy stress.-AMPK motif antibody or 14-3-3 protein and comparisons of samples treated or not treated with an AMPK activator or inhibitor. These strategies worked well and led to the discovery of more AMPK substrates with diverse cellular functions14. With these strategies, however, the basal activity of endogenous AMPK could increase the background signals, thereby complicating the identification of bona fide AMPK-dependent phosphorylation events. The well-developed CRISPR-Cas9 genome-editing technology greatly facilitates our ability to disrupt a target gene and thus completely abolish the function of this target protein. Therefore, we combined the CRISPR-Cas9 technology and global quantitative phosphoproteomic in this study to set up a workflow for the identification of AMPK substrates. We successfully discovered 32 phosphosites regulated by AMPK kinase, 24 of which are novel, indicating that the combination of CRISPR-Cas9−mediated KO cells and global quantitative phosphoproteomic is suitable as a general approach for the identification of kinase substrates. Moreover, this strategy does not require specific phosphorylation motif antibodies or any extensive knowledge of the particular kinase under investigation. We will continue to use this general approach to study kinase-dependent signaling pathways, especially the ones that have not yet been studied extensively.Identifying kinase substrates is critical to understanding the functions of a given protein kinase. However, this is an extremely challenging task because of the lack of a universal approach for discovery of kinase substrates. Previous studies have used several well-designed and specific strategies to identify AMPK substrates, including pulldown assays with a specific anti2 enrichment, which enriches all the phosphorylated peptides. The phosphosites regulated by the particular kinase of interest comprise just a very small fraction of the global phosphoproteome. Many of the phospho-substrates will be missed in such screens because of the relatively limited coverage of current phosphoproteomics. For example, we identified eight known AMPK substrates but missed many other well-known AMPK substrates. Second, the strategy of comparing kinase KO cells with WT cells may have intrinsic problems. KO of a particular protein kinase may cause compensation and/or cellular stress, which in theory can lead to some unpredictable events in the cell that may impede the discovery of true physiological substrates of the kinase of interest. Third, since the strategy we use is a global phosphoproteomics approach, many of the phosphopeptides with higher phosphorylation levels in WT but not in KO cells are not direct substrates of the kinase but are indirectly regulated by the kinase. We used the well-known conserved AMPK substrate motif to identify the ones that may be directly phosphorylated by AMPK. But for many kinases without any known substrate motif, it will be challenging to pick out the real direct kinase substrates. Fourth, our approach relies on the generation of kinase deficient/KO cells, which will not work for many protein kinases that are essential for cell survival. For these essential kinases, the alternative approaches are the use of knockdown cells or kinase inhibitors as the control, but these alternatives are not as efficient as KO since they cannot completely block the kinase activity.There are some drawbacks to this approach for the discovery of kinase phospho-substrate relationship. First, it is a global phosphoproteomics approach with only TiO42. Two different AMPK substrate screening studies identified MTFR1L13, indicating that MTFR1L is also likely a direct AMPK substrate. In this study, we validated ARMC10 as a newly discovered AMPK substrate that participates in mitochondrial fission. Thus, AMPK may have important roles in regulating mitochondrial dynamics via phosphorylating several components in this process. Its functions in mitochondria regulation need to be further elucidated.Our functional analysis of the three groups of proteins regulated by AMPK confirmed the diverse functions of this kinase, especially its roles in metabolism and signaling pathways. Notably, our study revealed several mitochondrial proteins, such as MFF, MTFR1L, and ARMC10, to be AMPK substrates. Indeed, Shaw and colleagues recently reported that MFF is an AMPK substrate that functions in the regulation of mitochondrial fusion and fissionWe identified a number of proteins with phosphosites that differed considerably between control and AMPKα1/α2-DKO cells but did not have the conserved AMPK substrate motif in their protein sequences (groups 2 and 3). We speculated that these proteins are indirectly regulated by AMPK. By using bioinformatics functional analysis, we found that these phosphoproteins have highly enriched nuclear functions. Many of them function in transcriptional and translational regulation. Groups 2 and 3 are also enriched in cell-cycle progression, DNA repair and nuclear organization. We suspect that phosphorylation of these nuclear proteins, which may be indirectly regulated by AMPK, enables AMPK to participate in the regulation of transcriptional and translational processes and thus ensure energy balance by increasing the capacity of cells to produce ATP but reduce ATP consumption. AMPK signaling may also promote cell survival via inhibition of cell-cycle progression and cell proliferation.From our list of candidate AMPK substrates, we identified two ARMC10 phosphopeptides for the same phosphorylation site, S45, strongly suggesting that ARMC10 is phosphorylated in vivo by AMPK at this site. The results of the subsequent functional studies suggest that ARMC10 is likely an important AMPK substrate involved in the regulation of mitochondrial functions. Moreover, we showed that ARMC10 is a key mediator involved in AMPK-dependent regulation of mitochondrial fusion and fission, and it relies on AMPK and AMPK-dependent phosphorylation at S45. Taken together, these findings suggest that ARMC10 is a key AMPK substrate that functions in mitochondrial fission.The mitochondria represent the primary site of ATP production. Given that AMPK function is directly regulated by AMP:ATP or ADP:ATP ratio, and AMPK is the key kinase regulating energy homeostasis, it is not surprising that AMPK participates directly in the control of mitochondrial dynamics and functions. We speculate that ARMC10 directly facilitates mitochondrial fission and contributes to mitophagy.41, whereas Drp1 mediates membrane fission by wrapping around and constricting mitochondrial tubules44. We further demonstrated an association between ARMC10 and Drp1, indicating that ARMC10 may work together with MFF, FIS1, and Drp1 to mediate mitochondrial fission. The details of the underlying mechanisms remain to be elucidated.ARMC10 is located at the outer membrane of the mitochondria. We validated the binding between ARMC10 and two mitochondria fission proteins, MFF and FIS1, which have been reported as receptors that recruit Drp1 to the mitochondrial surfaceThis and previous studies indicate that AMPK has important roles in the regulation of mitochondrial dynamics and other processes that are critical for cellular response to energy stress. We are still at the early stages of understanding the detailed mechanisms underlying AMPK-dependent regulation of many cellular processes involved in energy consumption and generation. We expect that our unbiased global phosphoproteomic analysis of AMPK-dependent phosphorylation events will enable us to gain a better understanding of the AMPK-dependent signaling network.2 (v/v). AMPKα1/α2-DKO HEK293A-derived, ARMC10-KO HEK293A-derived, and U2OS-derived cells were generated by the CRISPR-Cas9 system. The KO cells were validated by Sanger sequencing and immunoblotting as shown in Supplementary Figures HEK293A, HEK293T and U2OS cells were purchased from ATCC  and maintained in Dulbecco modified Eagle medium supplemented with 10% fetal bovine serum, 1% penicillin and streptomycin at 37 °C in 5% COFor plasmid transfection, cells were seeded in 6-well plates. The next day, a mixture of 2 µg DNA, 10 µL of polyethylenimines and 200 µL Opti-MEM  was added into one well of each plate. After incubation for 16–24 h, cells were collected or treated as indicated.N- or C-terminal-tagged fusion proteins. PCR-mediated site-directed mutagenesis was used to generate serial point mutations as indicated. The human codon-optimized Cas9 construct and target gRNA expression construct were obtained from Addgene.Constructs were generated via polymerase chain reaction (PCR) and subcloned into a pDONOR201 vector using Gateway Technology  for use as the entry clones. As needed, the entry clones were subsequently recombined into Gateway-compatible destination vectors for the expression of Anti-ARMC10 S45 phospho-specific antibody (1:500) was raised against KLH-conjugated phospho-peptide GIRSSK(phospho-S)AED. Antisera were precleared with non-phosphopeptide with the same sequence and then affinity-purified by using the AminoLink Plus immobilization and purification kit . Anti-AMPKα1 (2795 S), anti-AMPKα2 (2757 S), anti-AMPKα (5831 S), anti-ACC1 (3676 S), anti-phospho-AMPK T172 (2535 S), anti-phospho-ULK1 S555 (5869 S), anti-phospho-ACC1 S79 (11818), and anti-COX IV (4850 S) were purchased from Cell Signaling Technology  and used at 1:1000 dilution. Anti-phospho-Ser antibody was purchased from Santa Cruz Biotechnology  and used at 1:200 dilution. Anti-α-tubulin (T6199-200UL) and anti-Flag (M2) (F3165-5MG) monoclonal antibodies were purchased from Sigma-Aldrich  and used at 1:5000 dilution. Anti-ARMC10 (20506-1-AP) was purchased from Protentech  and used at 1:500 dilution. Anti-TOM20 (sc-11415) was purchased from Santa Cruz Biotechnology and used at 1:500 dilution in immunofluorescence analysis.gRNA sequences were introduced into an expression construct using site-directed mutagenesis via PCR. The gRNA sequences for the indicated genes were as follows:AMPKα1, 5′-TCCTGTTACAGATTGTATGC AGG-3′;AMPKα2, 5′-ACGTTATTTAAGAAGATCCG AGG-3′;ARMC10, 5′-TTACCTGCTGGAGTCAACGG AGG-3′.Constructs encoding Cas9 and gRNA were cotransfected with pCDNA3-enhanced green fluorescent protein (GFP) into HEK293A or U2OS cells by using polyethylenimine transfection. Cells were sorted based on their GFP signals, and KO clones were screened by Western blotting with corresponding antibodies and confirmed by sequencing.l-arginine (Arg 0) and l-lysine (Lys 0) (“light”) or l-arginine-U-13C615N4 (Arg 10) and l-lysine-U-13C615N2 (Lys 8) (“heavy”). The medium was supplemented with 10% dialyzed fetal bovine serum. Labeling efficiency was tested periodically using MS. Cells in light or heavy medium were treated or not treated with 100 μM A769662 for 24 h. Cells were collected and mixed immediately.For SILAC experiments, AMPKα1/α2-DKO HEK293A and parental HEK293A cells were labeled via passaging for up to eight cell divisions in Dulbecco modified Eagle medium containing g at 4 °C. Supernatants were placed in a clean tube and reduced in 5 mM dithiothreitol for 1 hour at 56 °C followed by alkylation with 20 mM iodoacetamide for 45 min at room temperature in the dark. Volumes (4×) of −20 °C acetone were added to precipitate the protein overnight. Precipitated protein was collected via centrifugation for 20 min at 2000 × g at 4 °C. Pellets were washed twice with −20 °C 80% acetone and air-dried. Pellets were resuspended in 8 M urea in 50 mM NH4HCO3 buffer with sonication at 4 °C for 5 min. After proteins were quantified by using a Bradford assay, 2 mg of each protein was placed in a new tube, and the urea was diluted with 50 mM NH4HCO3 buffer to reduce the concentration of urea to <1 M. The proteins were then digested in trypsin (1:100) for 18 h at 37 °C (1000 × g).Cells were solubilized in GdmCl lysis buffer . Cells were then subjected to sonication and centrifugation for 30 min at 4000 × 45. After digestion, 150 μL of 3.2 M KCl, 55 μL of 150 mM KH2PO4, 800 μL of acetonitrile (ACN), and 95 μL of trifluoroacetic acid were added to the digested peptides. Peptides were mixed at room temperature for 1 min at 2000 × g, cleared via centrifugation and transferred to a clean tube.The phosphopeptides were enriched according to a published protocol2 beads were added to peptides at a bead:protein ratio of 10:1, suspended in 80% ACN/6% trifluoroacetic acid and incubated at 40 °C for 5 min at 2000 × g. The beads were then pelleted via centrifugation for 1 min at 3500 × g, and the supernatant (containing non-phosphopeptides) was aspirated and discarded. The beads were suspended in a wash buffer (60% ACN and 1% trifluoroacetic acid), transferred to a clean tube and washed four more times with 1 mL of wash buffer each time. After the final wash, the beads were suspended in 100 μL of a transfer buffer (80% ACN and 0.5% acetic acid), transferred onto the top of a C18 StageTip (ThermoFisher Scientific) and subjected to centrifugation for 5 min at 500 × g or until no liquid remained on the StageTip. Bound phosphopeptides were eluted twice with 30 μL of an elution buffer  and collected via centrifugation into clean PCR tubes. Samples of the phosphopeptides were concentrated in a SpeedVac for 15 min.TiO46. Vacuum-dried peptides were dissolved in pH 10 buffer  and subjected to pH 10 C18 reverse-phase column chromatography. Peptides were eluted with a step gradient of 150 μL each of 6, 9, 12, 15, 18, 21, 25, 30, and 35% ACN (pH 10), pooled into six pools and vacuum-dried for nano-high-performance liquid chromatography-tandem MS.Phosphopeptide samples were fractionated followed a described protocolm/z (2 × 106 AGC target), and the 25 strongest ions were fragmented via collision-induced dissociation with 35 normalized collision energy and 1 m/z isolation width and detected by using an ion trap with 30 s of dynamic exclusion time, 1 × 104 AGC target, and 100 ms of maximum injection time.Peptides were loaded onto a 10-cm column with a 150-μM inner diameter, packed in-house with 1.9 μM C18, and subjected to nano-high-performance liquid chromatography-tandem MS analysis by using a nano-LC 1000 coupled with an Orbitrap Elite mass spectrometer (ThermoFisher Scientific). The peptides were separated with a 75-min discontinuous gradient of 2–24%, 4–24%, or 8–26% ACN/0.1% formic acid at a flow rate of 800 nL/minute. The mass spectrometer was set to data-dependent mode, the precursor MS spectrum was scanned at 375–1300 m/z with 240k resolution at 400 t-tests. The differentially expressed phosphopeptides were subsequently filtered for median fold-change >1.5 and p value < 0.05 (t-test). A site localization probability of 0.7 was used as the cut-off for localization of phosphorylation sites. Conserved motif analysis figures for the changed phosphosites were generated using WebLogo47. Function annotation was done by Ingenuity Pathway Analysis software  and reference mining.Raw MS data were processed by the MaxQuant software program  with a false-discovery rate <0.01 at the protein, peptide, and modification level using default settings with the following minor changes: multiplicity was set to 2 with light and heavy labeling; oxidation of methionine, acetylation of N-term, and Phospho (STY) were selected as variable modifications; carbamidomethyl(C) was selected as a fixed modification; and the minimum peptide length was 7 amino acids. Proteins and peptides were identified by using a target-decoy approach with a reversed database. The Human UniProt FASTA database (October 2015) containing 70,097 entries was searched. Peptides and proteins were quantified by using MaxQuant. Bioinformatics analysis of the proteomics results was done with Microsoft Excel and R statistical computing software. Significance was assessed with 32P-ATP  in a kinase buffer . These samples were incubated at 30 °C for 15 min. The reactions were stopped via boiling, and proteins were separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The gel was dried, and it was imaged by using the PhosphorImager software program10.Recombinant WT ARMC10 and the ARMC10 S45A mutant were expressed in bacteria and purified with use of a maltose-binding protein tag. Both recombinant proteins were mixed with active recombinant AMPK  and γ-7 cells were subjected to lysis with NETN buffer on ice for 30 min. The lysates were incubated with 20 μL of conjugated streptavidin beads or S-beads (for SFB-tagged pulldown) or with 20 μL of protein A/G agarose together with indicated antibodies for 2 h at 4 °C. Beads were washed three times with NETN buffer and boiled in 2× Laemmli buffer before Western blot analysis48. Uncropped scans of all Western blots are included in Supplementary Figure For pulldown and immunoprecipitation assays, 1 × 10Cells cultured on coverslips were fixed in 3% paraformaldehyde for 10 min at room temperature and then extracted with a 0.5% Triton X-100 solution for 5 min. After blocking with a Tris-buffered saline/Tween 20 solution containing 1% bovine serum albumin, cells were incubated with the indicated primary antibodies for 1 hour at room temperature. After that, cells were washed and incubated with fluorescein isothiocyanate or rhodamine-conjugated second primary antibodies  for 1 hour. Cells were counterstained with 100 ng/mL 4′-6-diamidino-2-phenylindole for 2 min to visualize nuclear DNA. The coverslips were mounted onto glass slides with anti-fade solution and visualized using an Eclipse E800 fluorescent microscope with a Plan Fluor 60× oil objective lens .11. In brief, the quantification was scored from more than 150 cells with three replicates, and it was done by a person who was blinded to genotype and treatment of the samples. Morphology was scored as follows: “fragmented”, the majority of mitochondria were spherical; “short”, the majority of mitochondria were less than ~10 μm; “long”, the majority of mitochondria were more than ~10 μm; and “fused”, highly interconnected mitochondria with fewer than 4–5 free ends.Quantification of mitochondrial morphology followed the strategy reported elsewhereN-terminus and inserted into a pDonor vector. After a subsequent reaction, BioID2-bait pDEST constructs were obtained (Gateway cloning protocols). The constructs were transfected into HEK293T cells by using polyethylenimine. HEK293T cell lines with stable expression of tagged proteins were validated with Western blotting after puromycin selection. For the BioID pulldown experiment, 4 × 107 cells were collected after incubation with 50 μM biotin for 16 h. Cells were subjected to lysis and cleared via centrifugation. The supernatants were incubated with 100 μl of streptavidin agarose beads overnight. After extensive washing, the samples were eluted by boiling with 80 μl of 2× Laemmli buffer, then separated by SDS-PAGE and visualized by Coomassie Blue staining.BioID2 (Addgene) cDNA was amplified with ARMC10 at the The gel band containing the entire sample was excised into small pieces and destained completely before digested with trypsin at 37 °C overnight. The peptides were extracted with acetonitrile and vacuum dried. The mass spectrometry analysis setting is similar to the method part of mass spectrometry analysis with a few changes. The samples were subjected to nanoscale liquid chromatography  coupled to tandem mass spectrometry  analysis. The peptides were separated with a 75-min discontinuous gradient of 4–24% ACN/0.1% formic acid at a flow rate of 800 nl/minute. The MS raw data were searched in Proteome Discoverer 1.4 (ThermoFisher) with Mascot algorithm 2.4 (Matrix Science). The identified peptides and proteins were filtered by false discovery rate <1%.t-tests.Six repeats of the BioID2-tagged ARMC10 experiment were performed for the bait, and eight repeats were performed for the controls, which included BioID2 tag fused with mitochondria localization sequence (two repeats) or fused with a nonrelated bait protein, SLX4IP (six repeats). To identify the significantly enriched proteins, we compared the identification list from BioID2-tagged ARMC10 to the list from control groups. The results for samples and controls were compared via t-test or two-way analysis of variance with the Tukey multiple comparisons test. P values < 0.05 were considered statistically significant.Each experiment was repeated two or more times unless otherwise noted. Differences between groups were analyzed by using the Student’s Supplementary InformationSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Description of Additional Supplementary FilesPeer Review File


Over the past decades, the Arctic has been warming more than any other region in the world with profound socio-economic consequences. One of the key elements for understanding this rapid climate change is the surface energy budget. However, in the Arctic this budget is not consistently described across the various climate models, reanalyses and observation products. Recognising the physical causes of these inconsistencies is highly relevant for improving climate predictions and projections. Here we show that a 5 to 10 °C warm bias of the sea-ice surface temperature in global atmospheric reanalyses and weather forecasts is mainly caused by a missing representation of the snow layer on top of the sea-ice. Due to the low thermal conductivity of snow compared to sea-ice, a thin snow layer reduces the conductive heat flux much more efficiently than sea-ice, and thus insulates the cold atmosphere from the relatively warm ocean. Contemporary atmospheric reanalysis and forecast systems often neglect the snow layer on top of the sea ice. This can result in a 5 to 10 °C warm bias of the sea-ice surface temperature and thus, in a misrepresentation of the surface energy budget. Currently, weather and climate models are subjected to having various systematic errors, which induce large spread in results of different climate models2 and have a significant impact on the local and mid-latitude prediction skill3. Also, contemporary global reanalysis products, often used in climate research in order to monitor climate change and variability, or to evaluate climate model systems4, have large biases in temperature, humidity and wind speed in the Arctic7.There is a growing demand for a more accurate prediction and understanding of Arctic weather and climate, which puts great expectations on the global and regional forecasting and reanalysis systems4. Within the coupled atmosphere, ocean, snow, and sea-ice system, this energy balance controls the growth and melt of sea-ice, as well, as the thermal stratification of the lower atmosphere. Thus, the accurate simulation of the Arctic surface energy budget is key for improving our understanding of the rapid climate change in the Arctic, as well as, advancing long term prediction of sea-ice properties in the future.Specifically, in the Arctic surface energy balance significant deviations between climate models are found9. In addition, in sea-ice covered regions the ocean moderates the low temperatures during CSEs in contrast to the land surfaces, where minimum temperatures of −50 to −60 °C occur8.During Arctic winter clear-sky events (CSE) over sea-ice, with the absence of solar radiation and the strong longwave radiative cooling, the air temperatures can drop to −40 °C. Studies of the winter Arctic surface energy budget show that the radiative cooling of the troposphere is balanced by the advection of heat from lower latitudes10 and a pan-Arctic sea-ice surface temperature satellite product. We find a warm bias in almost all analysed model systems and show that it is induced by a missing representation of snow on sea-ice. Furthermore, the simplistic representation of sea-ice thickness and concentration in the analysed model systems contribute to inconsistencies in the simulation of sea-ice surface temperatures.In the present study, we investigate the ability of contemporary regional and global weather prediction systems and global reanalysis systems to simulate the low temperatures observed during CSEs. We use the in-situ data set from the N-ICE 2015 drift campaign13. Several CSE have been observed during N-ICE campaign13. In addition, we utilise a pan-Arctic sea-ice surface temperature satellite product14 based on infrared data from AVHRR instruments in order to extend our results to the pan-Arctic scale. More details on the use of the observations are given in the Methods section.We use the observational in situ data set of atmospheric, snow, sea-ice and ocean observations which is available from the N-ICE 2015 campaign and taken during the four subsequent drifts of a research vessel in between January and June 2015 , and global reanalysis systems  to simulate those low temperature events. For HARMONIE-AROME two configurations of the sea-ice parameterisation scheme are studied. First, the control experiment (AA) which resembles sea-ice handling in IFS-HRES and has a snow-free sea-ice layer of uniform and fixed thickness. Second, the sensitivity experiment (AA-snow) which uses extended sea-ice parameterisation scheme that includes a prognostic sea-ice thickness and snow layer model (see the Methods section for further details). General overview of the model systems discussed in the present study is provided in the Table We investigate the ability of regional and global weather prediction systems  during the CSE-1, where all models show a consistent representation of the clear sky conditions in terms of the simulated low LWThe conductive heat flux in the observations is mentclass2pt{minimThe overestimation in We conclude that the missing snow layer on top of the sea-ice results in the overestimated conductive heat flux from the ocean to the atmosphere, which is compensated by an increase in outgoing longwave radiation and too high surface temperatures. The resulting bias in the net surface radiation budget , the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-218), the Japanese 55-year Reanalysis (JRA-5519), and the National Centers for Environmental Prediction Reanalysis 2 (NCEP-220).We analyse a suite of global reanalyses, i.e., two configurations of the ECMWF model system (ERA-Interim16), as well as, two experimental configurations of the regional convective scale model HARMONIE-AROME15. The first of these configurations (AA) covers the same domain as the operational numerical weather prediction system AROME Arctic26 and has the same representation of the sea-ice cover. The second experimental configuration of HARMONIE-AROME (AA-snow) is similar to AA, but incorporates the parameterisations for the sea-ice mass-balance and snow layer on top of the sea-ice. The model domain for AA-snow is smaller than that one in the AA experiment (see the Fig. We also include the operational ECMWF global deterministic weather forecasting system (IFS-HRES27.Relevant features of the models, which were used to produce forecast and reanalysis products, are given in Table To extend the existing sea-ice parameterisation of HARMONIE-AROME with ice mass-balance calculations, we added the representation of the following processes: ice growth and melting from the bottom, and surface melting. The more complex processes of internal melting and snow-ice formation were not considered.28:The interface between the sea-ice bottom and the underlying water body is governed by the balance between the sea-ice and ocean heat fluxes. When these fluxes are not in equilibrium state, the residual heat flux leads to growth or melting of the ice layer28:The processes of surface melting is parameterised in the following way. At the first step, the ice surface temperature is calculated from the thermal balance of the surface layer of sea-ice. Then, if the obtained temperature is higher than the melting temperature of sea-ice, it is set to be equal this melting temperature and the residual heat flux 21.The AA-snow experiment, which uses the updated sea-ice parameterisation scheme, shows simulated snow depths between 0.45 and 0.7 m and sea-ice thickness between 1.4 and 1.7 m. This is consistent with the observed snow and sea-ice thickness of We compare the model’s mentclass2pt{minimmentclass2pt{minim13The energy budget of the surface layer, or the net-energy transfer If we assume that a variation Peer Review File


Prostate cancer (PCa), the second most mortal cancer from developed countries, presents a high level of chemoresistance. There is emerging evidence underscores the critical role of autophagy in the onset, progression, and chemoresistance of PCa. In the present study, we investigated the possible role of a novel autophagy regulator, activating molecule in beclin1-regulated autophagy1 (Ambra1), a novel ATG gene in the sensitivity or PCa cells to cisplatin. We explored the regulation by the Ambra1 manipulation on the induction of apoptosis and autophagy in human PCa DU145 cells in the presence of cisplatin, via up- or down-regulating Ambra1 expression. In addition, we examined the colony forming of DU145 cells post cisplatin treatment and Ambra1 manipulation. Our results demonstrated that the Ambra1 up-regulation reduced, whereas Ambra1 knockdown increased the cisplatin-induced apoptosis, caspase 3 cleavage, and poly ADP-ribose polymerase (PARP) cleavage. Interestingly, we also found significant autophagy induction in the cisplatin-treated DU145 cells, with increased autophagic vesicles, up-regulated autophagy-related markers. However, the cisplatin-induced autophagy was up-regulated by the Ambra1 overexpression or was down-regulated by the Ambra1 knockdown. In addition, the colony forming was also positively regulated by Ambra1 in DU145 cells post cisplatin treatment. In conclusion, Ambra1 negatively regulates the cisplatin-induced apoptosis and the cisplatin-mediated growth reduction in DU145 cells, in association with the Ambra1-mediated autophagy promotion. It implies that Ambra1-mediated autophagy might be an important mechanism underlining the sensitivity reduction of PCa cells. Prostate cancer (PCa) is the second most mortal cancer after lung cancer in men from developed countries . Though Cisplatin is a widely used agent for chemotherapy. It can also induce autophagy in various types of cancers, such as endometrial cancer cells , malignaIn the present study, we investigated the possible role of Ambra1, a novel ATG gene, on the cisplatin-induced apoptosis and cisplatin-mediated growth reduction in human PCa DU145 cells. Our study found the negative regulation by Ambra1 on the cisplatin-induced apoptosis and cisplatin-mediated growth reduction in DU145 cells, in associating with the Ambra1-mediated autophagy promotion. It implies that Ambra1-mediated autophagy might be an important mechanism underlining the sensitivity reduction of PCa cells.2 at 37°C. DU145 cells were divided when growing to more than 85% confluence. For the Ambra1 overexpression, 85% confluent DU145 cells in six-well (approximately 8 × 105 cells per well) or 12-well plate (approximately 4 × 105 cells per well), without antibiotics, were transfected with Ambra1-pcDNA3.1(+) (with CAT-pcDNA3.1(+) as control) using Lipofectamine 2000 reagent . For the Ambra1 knockdown, 85% confluent cells without antibiotics were transfected with siRNA-Ambra1 or siRNA-Control  using Lipofectamine RNAiMax . For cisplatin treatment, 85% confluent DU145 cells, with Ambra1 overexpressed or knockdown, were treated with 10 μM cisplatin  and were incubated with RPMI-1640 medium/2% FBS in a humidified chamber at 5% CO2 at 37°C.Human PCa DU145 cells  were cultured in RPMI-1640 medium , being supplemented with 10% (v/v) fetal bovine serum  (or 2% FBS for cell maintaining) in a humidified chamber at 5% COCt) values of Ambra1 mRNA were normalized to β-actin from the same sample as relative mRNA levels.mRNA sample from DU145 cells was extracted with TRIzol reagent  according to the product’s manual. Takara One Step real time PCR (RT-PCR) kit  was utilized to relatively quantify the Ambra1 mRNA level to β-actin in a 7500 Fast PCR instrument . The cycle threshold , were separated with 10% SDS polyacrylamide gel, and then were electrophoretically transferred to nitrocellulose membrane . Then the membrane was subject to blocking overnight at 4°C with 5% non-fatty milk in 1× phosphate buffered saline Tween-20 (PBST). Then the membrane was incubated at 4°C for 2 h with rabbit monoclonal antibody against Ambra1, β-actin, caspase 3 (reactive to both pro- and cleaved caspase 3), poly ADP-ribose polymerase (PARP), p62, A and B subunits of microtubule-associated protein1 light chain 3 (LC3-A/B), Atg7, or Beclin1. Finally, the specific binding of antigen and antibody was detected post another incubation at 4°C for 1 h with the secondary HRP-conjugated antibody and the last incubation with enhanced chemiluminescence . Three-time washing with PBST was performed before each incubation. Each band was quantified using Image J software.Treated cells were lyzed with ice-cold lysis buffer  for 20 min; cell lysate was centrifugated at 13000 g at 4°C), and then were suspended in the 500–1000 μl 1× binding buffer (1 × 106 cells/ml). Finally, 5–10 μl Annexin V-FITC and propidium iodide (PI) were added on turn into cell suspension for approximately 10 min incubation at room temperature at dark. The flow cyometry analysis was performed on a FACScan flow cytometer .The apoptosis of DU145 cells was examined by FACScan flow cytometer as following. Post staining with Annexin V-FITC Apoptosis Detection Kit  according to the guidance of the kit’s manual. Treated or control DU145 cells were trypsinized with 0.25% trypsin  and were immediately washed once with ice-cold PBS , and was adjusted to 50–200 µg per 50 µl Cell Lysis Buffer for each assay (well). Then each cell well was added with 50 µl of 2× Reaction Buffer (containing 10 mM DTT) and with 5 μl of the 4 mM DEVD-p-NA substrate  for an incubation at 37°C for 60–120 min. Then the plate was measured for the OD400-405 nm on a microplate reader . The caspase 3 activity was presented as a relative level to control.The caspase 3 activity in DU145 cells was examined using Caspase 3 Assay Kit (Colorimetric) . The pellet of 1–5 × 10The autophagic vesicles in DU145 cells was visualized and quantified with a green fluorescence protein (GFP)-LC3B reporter, pGM-CMV-GFP-hLC3 . Briefly, approximately 85% confluent DU145 cells were transfected with the pGM-CMV-GFP-hLC3 reporter plasmid with Lipofectamine 2000 . Post an incubation for 24 h, DU145 cells were updated with RPMI-1640 medium supplemented with 2% FBS. Then the GFP-positive vesicles were visualized and counted under Hitachi Medical Systems Fluorescence F-2000 .2. Then cells were treated with 10 μM cisplatin for another 24 h. Post another incubation for 5–8 days at 37°C under 5% CO2, the DU145-formed colonies were stained Crystal Violet (0.005%) for 20 min and were counted.The regulation by cisplatin, or by the Ambra1 manipulation on the growth of DU145 cells was evaluated by colony forming assay. In brief, 200-300 blank DU145 cells or the DU145 cells post Ambra1 up- or down-regulation were seeded in six-well plates and were incubated for 24 h, at 37°C under 5% COt test was performed. A P value of 0.05 or much less was considered significant.Results are presented as mean ± standard error of the mean (SE). For the analysis between two groups, the Student’s P<0.001) (Ambra1 pcDNA3.1(+), first column), compared with the control group of DU145 cells, which were transfected with CAT-pcDNA3.1(+) (Ctrl pcDNA3.1(+), second column) at either 24- or 48-h post transfection. The Ambra1 mRNA promotion lasted from 24 to 48 h, though there was unrecognizable reduction of it at 48-h post transfection. Of course, there was no significant difference in the mRNA level of Ambra1 between CAT-pcDNA3.1(+)-transfected and blank (third column) DU145 cells. In the other experiment, we knocked down the Ambra1 expression with RNAi technology. In contrast with the siRNA-Ctrl (control)-transfected DU145 cells , the transfection with siRNA-Ambra1 markedly reduced Ambra1 expression in DU145 cells  (P<0.01). The up-regulation by Ambra1-pcDNA3.1(+) or the down-regulation with siRNA-Ambra1 was also confirmed in protein level by Western blotting assay. P<0.01 respectively).To investigate the regulatory role of Ambra1 in the cisplatin-induced apoptosis in DU145 cells, we manipulated the Ambra1 expression in DU145 cells, and then evaluated the apoptosis in DU145 cells, post cisplatin treatment. As indicated in P<0.0001, P<0.01), reducing the apoptosis induction to approximately 12% (P<0.05). Detailed counting of apoptotic DU145 cells was indicated in Then the DU145 cells, with Ambra1 overexpressing or knocking down were treated with 0 or 10 μM cisplatin for 48 h, and the apoptosis was assessed by flow cytometry post Annexin V-FITC/PI staining. tely 12% F. On thetely 12% G, compartely 12% H  was markedly reduced in the Ambra1 pcDNA3.1(+) DU145 cells ). On the other side, it was significantly aggravated in the siRNA Ambra1 DU145 cells, compared with siRNA CTRL cells (P<0.01). Similar regulatory effect was also found in the lysis of PARP .Acidic vesicular organelles (AVOs) symbolize autophagy formation . The micP<0.001, P<0.001, P<0.05, P<0.05 or P<0.01). Taken together, we confirmed the promotion by Ambra1 on the autophagy in the cisplatin-treated DU145 cells.Western blotting was also performed to examine the expression of Atgs, such as LC3, Atg7, and Beclin1. P<0.01, column 2 vs column 1, P<0.05, column 4 vs column 3, P<0.05, column 6 vs column 5). Therefore, Ambra1 ameliorates the growth of cisplatin-treated DU145 cells.We also explored the regulation by Ambra1 on the growth of cisplatin-treated DU145 cells with colony forming assay. It was shown in Ambra1 has recently been recognized to promote the formation of autophagosomes and thus regulate autophagy ,17. It wConsidering the important role of autophagy in the regulation on cell survival and cell death, it is critical for evaluating autophagy as a cancer therapy strategy to understand the signaling pathways underlying autophagy in response to various conditions in cancer. The autophagosome elongation-related Atgs, such as Atg5 , P21 2727, UNC-5in vitro sensitizes PCa cells to Src tyrosine kinase inhibitors [Accumulating evidence has revealed that autophagy involves in the cancer therapeutic responsiveness ,22. Autohibitors . Our stuhibitors . In addihibitors . Our resIn summary, our study found the negative regulation by Ambra1 on the cisplatin-induced apoptosis and cisplatin-mediated growth reduction in DU145 cells, such negative regulation was associated with the Ambra1-mediated autophagy promotion, regardless of p62 signaling pathway. It implies that Ambra1-mediated autophagy might be an important mechanism underlining the sensitivity reduction of PCa cells.