Periodontitis is an inflammatory disease affecting the tooth supporting tissues (periodontium) and associated with chronic diseases such as cardiovascular disease and insulin resistance. However, there has been no nation-wide population based epidemiologic study regarding any association between periodontitis and serum IgE. Among the 8,958 participants in the 2010 Korean National Health and Nutrition Examination Survey (KNHANES V-1), 1,731 adults aged 19 to 64 who had measured serum IgE were included in the analysis. Dentists examined the periodontal status of the participants. Multiple logistic regression analyses were used to evaluate the odds ratio of periodontitis in association with total IgE and specific IgE to cockroach and house dust mite. In males, total IgE showed a positive correlation with the presence of periodontitis. The participants in the highest tertile of cockroach specific IgE  had a significantly increased risk of periodontitis . In females, the inverse association occurred between total IgE and periodontitis . The present study firstly demonstrated the association between periodontitis and serum IgE, using the Korean nationwide, population-based, cross-sectional health examination and survey. This study suggested a positive correlation between periodontitis and cockroach-specific IgE in Korean male adults. Porphyromonas gingivalis, Aggregatibacter Actinomycetemcomitans, Capnocytophaga spp, Eikenella corrodens, Prevotella intermedia, Campylobacter rectus, Fusobacterium nucleatum, and Treponema denticolaPeriodontitis is a common chronic inflammatory disease and a major cause of tooth loss2Helicobacter pylori infectionet al. reported that oral immunization by bacterial antigens may account for systemic immune response and oral colonization lead to systemic inflammationset al. reported that periodontal pathogen A. Actinomycetemcomitans is a candidate bacterial trigger of rheumatoid arthritisPeriodontitis has been considered to be associated with chronic diseases. Several studies have revealed the association of periodontitis with insulin resistance5et al. reported that there was a negative association between periodontitis and respiratory allergies12Allergic diseases have been revealed to have an inverse association with periodontitis. Friedrich et al. reported an inverse relationship between periodontal disease and an allergy-related outcomeet al. reported associations between serum Immunoglobulin G (IgG) antibody levels to A. actinomycetemcomitans and P. gingivalis and subject-reported asthma, wheezing, and hay fever among the US population aged 12 years and older. The higher concentrations of IgG antibody to P. gingivalis were significantly associated with the lower prevalence of asthma, wheeze, and hay fever. Higher concentrations of IgG to A. actinomycetemcomitans were significantly associated with a lower prevalence of wheezeThere are several reports that supports hygiene hypothesis of periodontitis to allergic disease. The detection of serum antibodies to oral pathogens in early childhood has provided evidence of an early immune response to these bacteria, and has shown a protective effect over allergic diseasesIn this study, we aimed to evaluate the association between periodontitis and the level of serum Immunoglobulin E (IgE) in general population. IgE is associated mainly with allergic reactions. An allergen-specific IgE test is done to check whether a person is allergic to a particular substance. In Korea, house dust mite, cockroach, mugwort, oak, Japanese hop, ragweed, and dog dander are important inhalant allergensThe characteristics of the study participants are summarized in The periodontitis group presented the higher percentage of ‘once or less tooth brushing times per day’, and a lower percentage of ‘three or more brushing times per day’ when compared to the control group. A remaining tooth count of more than 28 was significantly lower in the periodontitis group.2) and waist circumferences (83.5 ± 0.6 cm) were significantly higher than the control group . The difference in white blood cell counts was statistically significant between the periodontitis group  and the control group .The mean age of the periodontitis group (48.1 ± 0.6 years) was significantly higher than that of the control group . In the periodontitis group, BMI (24.3 ± 0.2 kg/mBecause levels of IgE showed wide ranges (0–5000 kU/L), comparing the mean value of IgE does not seem to be appropriate to find out the association between levels of IgE and periodontis. Subjects were categorized into three groups according to the levels of total serum IgE, house dust mite-specific IgE, and cockroach-specific IgE.In female, the cut-off levels between Tertile1 (T1) and Tertile2 (T2), and between Tertile2 (T2) and Tertile3 (T3) were 31.6 kU/L and 94.9 kU/L for total IgE; 0.03 kU/L and 0.09 kU/L for cockroach-specific IgE; and 0.03 kU/L and 0.3 kU/L for house dust mite-specific IgE, respectively. In male, the cut-off levels between Tertile1 (T1) and Tertile2 (T2), and between Tertile2 (T2) and Tertile3 (T3) were 67.3 kU/L and 269 kU/L for total IgE; 0.05 kU/L and 0.26 kU/L for cockroach-specific IgE; and 0.09 kU/L and 1.06 kU/L for house dust mite-specific IgE, respectively. The results of the logistic regression analyses between periodontitis and allergic sensitization were shown in In males, total IgE and allergic sensitization to the cockroach allergen showed a positive correlation with periodontitis. In model 1, the ORs of periodontitis in the middle Tertile  of total IgE was 2.067 (95% CI 1.269–3.367) compared to T1 . After adjusting for age, BMI, smoking and alcohol consumption status, exercise, income, education, metabolic syndrome, and white blood cell count, the OR in model 2 was 1.999 (95% CI 1.163–3.435) in males compared to total serum IgE (T1) in males. The highest tertile (T3) of cockroach-specific IgE in male showed increased ORs of 1.75 , 2.038 , and 2.108 (95% CI 1.233–3.606) respectively in three models of males. However, there was no association shown between periodontitis and house dust mite sensitization in males.Conversely, in females, inverse associations between total serum IgE and periodontitis were shown . In femaTo determine the effect of the hygiene hypothesis in Korean adults, we used the population-based database, KNHANES V-1. This study presented the association between both total IgE and specific IgE, and periodontitis in adult groups. The periodontitis group was significantly related to smoking, alcohol consumption, lower educational status, smaller numbers of remaining teeth, lower tooth brushing frequency, older age, BMI, waist circumferences, and metabolic syndrome . The welUnexpectedly, in males, the second tertile group of total IgE presented positive correlations with periodontitis in models 1 and 2 . AdditioThe gender difference in results was suspected that men had higher smoking rate than women and seemed to be less hygienic than women. Another explanation is that men had higher level of total and allergen specific IgE than women  and Tertile2 (T2), and between Tertile2 (T2) and Tertile3 (T3) were 31.6 kU/L and 94.9 kU/L in female, and 67.3 kU/L and 269 kU/L in male). However, the further studies of gender differences in association between serum IgE and periodontitis are needed to be evaluated.et al. suggested two pathologic mechanisms of cockroach allergen: serving as allergenic proteins and stimulating inflammatory cells through proteolytic activitieset al. demonstrated linkage of cockroach proteases to the activation of a variety of cells involved in the process of allergic airway inflammation, and in the role of PAR-2The discrepancy between house dust mite allergen and cockroach allergen might be explained by the specific reaction to cockroach allergen. Cockroach allergen is known to increase inflammatory cytokines, such as IL-8, MCP-1, CCL20, and GM-CSFPorphyromonas gingivalis and human gingival fibroblasts via PAR-2. Palm et al. revealed that the periodontal pathogen, P. gingivalis, facilitates periodontitis interaction with human gingival fibroblasts that activate PARThe pro-inflammatory mechanism of cockroach allergen through PAR-2 is similar to the inflammatory reaction between Another possible explanation can be that the cockroach-sensitized group might be different from the house dust mite-sensitized group in demographics. Several studies have demonstrated the geographical differences between house dust mite sensitization and cockroach sensitization28Our study did have several limitations. First, it was a cross-sectional study, which introduced difficulties in reasoning causality. Second, other specific allergens were not measured in this study. Third, the analysis of subgroups according to the specific IgE sensitization was not completed in this study. A difference between the house dust mite sensitized group and cockroach sensitized group was suspected. Fourth, gender differences were not further evaluated in this study. Fifth, the periodontitis definition (CPI) used in the present study does not take clinical attachment loss into consideration. Lastly, some response bias may have been present regarding the reporting of smoking and alcohol consumption status, since these data were collected through self-administered questionnaires.Despite these limitations, to the best of our knowledge, this is the first population-based study to demonstrate the association between serum IgE and periodontitis. This study provided meaningful evidence for the positive correlation between cockroach-specific IgE and periodontitis in Korean adult males. The positive correlation between cockroach-specific IgE and periodontitis in Korean male adults was also firstly revealed in this study that opposed the hygiene hypothesis of periodontitis. Additional research is needed to identify mechanisms linking cockroach sensitization and periodontitis.This study analyzed the data from the 5th Korean National Health and Nutrition Examination Survey (KNHANES V-1), which was conducted from January 2010 to December 2010 by the Korea Centers for Disease Control and Prevention. The study design followed the tenets of the Declaration of Helsinki for biomedical research. The survey was conducted after approval from the Institutional Review Board of the Korea Centers for Disease Control and Prevention (IRB No. 2010–02CON-21-C). Survey participants included 77.5% of the selected sample of 10,938 subjects in 2010.The study was conducted using a rolling sampling design that involved a complex, stratified, multistage, probability cluster survey of a representative sample of the civilian population of South Korea. A total of 192 sampling units were randomly selected from primary sampling units encompassing the target population. Each sampling unit contained 20 households; 3,800 households were surveyed in one year. The survey was conducted by four teams, and consisted of three parts: a health interview, a nutrition interview, and a health examination.All questionnaires were administered either by the physicians or by trained interviewers in person at the participants’ homes. According to the National Health Enhancement Act, subjects had the right to refuse participation. All who agreed to take part provided written informed consent. The Korea Centers for Disease Control and Prevention obtained consent from the participants to draw blood during the health interview survey and use samples for further research.Among 8,958 potential participants, those younger than 19 years (n = 2218) or older than 65 years (n = 1478) were excluded. In addition, 3,517 individuals were eliminated as participants due to lack of serum IgE measurements. After removing missing data (n = 14), the final study population was comprised of 1,731 participants with complete data sets .The health interviews and health behavior surveys included well-established questions to determine the demographic and socioeconomic characteristics of the subjects. The surveys included questions on age, sex, family income, education level, smoking and alcohol consumption status, exercise, and tooth brushing frequency. Smoking status was divided into three categories: current smoker, ex-smoker, or nonsmoker. Alcohol consumption status was categorized into no alcohol consumption and alcohol consumption more than once a month, and exercise status was divided into yes or no.Blood pressure was measured twice on the right arm at a 5-minute interval using a standard mercury sphygmomanometer  and recorded as an averaged value. Blood samples were appropriately processed, immediately refrigerated, and transported in cold storage to the Central Testing Institute . White blood cell counts were measured using laser low cytometry . Levels of glucose, high density lipoprotein cholesterol, and triglyceride were measured enzymatically using a Hitachi Automatic Analyzer 7600 .Metabolic syndrome is defined as the presence of any 3 of 5 risk factors; (1) large waist circumference ; (2) elevated triglycerides (≥150 mg/dL) or drug treatment for elevated triglycerides; (3) reduced high density lipoprotein cholesterol  or drug treatment for reduced high density lipoprotein cholesterol; (4) elevated blood pressure (systolic ≥130 and/or diastolic ≥85 mm Hg) or antihypertensive drug treatment and; (5) elevated fasting glucose (≥100 mg/dL) or drug treatment for elevated glucoseDermatophagoides farinae) and cockroach. We divided the subjects into three groups according to the serum levels: total IgE, cockroach-specific IgE, and house dust mite-specific IgE.The KNHANES randomly selected 12 people in one sampling unit by age  and gender . A total 2,400 participants were chosen annually for IgE measurement. Total IgE and allergen-specific IgE were analyzed using a 1,470 WIZARD γ-Counter analyzer  with an immunoradiometric assay . Two common indoor allergens were tested for house dust mite  community periodontal index (CPI) was used. The codes and criteria for CPI scoring are as follows: normal (CPI = 0), gingival bleeding present (CPI = 1), calculus felt during probing (CPI = 2), a periodontal pocket of 4–5 mm (CPI = 3), and a pocket of >6 mm (CPI = 4). Periodontal pocket depths were measured at the mesiobuccal, mid-buccal, distobuccal, distolingual, midlingual and mesiolingual sites per tooth with a WHO periodontal probe. Periodontitis was defined as a CPI value of 3 or 4. Trained dentists examined the periodontal status of the participants. Training was provided to minimize errors in the periodontal measurements. In the 2010 KNHANES, 36 dentists performed periodontal examinations. For the measurements of CPI, simulated patients were used for the training. The trainings were performed from four to five times per dentist. Average Kappa value for the fourth quarter of 2010 was 0.611 (0.473–0.768).t-tests or one-way analysis of variances were used to compare mean values for continuous variables; percentages were used for categorical variables, according to the presence of periodontitis. To estimate odds ratios (OR) of periodontitis according to total IgE levels and allergen-specific serum IgE levels, we conducted simple and multiple logistic regression analyses by using the generalized linear model for a complex survey design. The ORs and corresponding 95% confidence intervals (CIs) were calculated using a confounder adjustment for age (model 1); for age, BMI, waist circumference, smoking, alcohol consumption, exercise, income, education, white blood cell count (model 2); and for age, BMI, waist circumference, smoking, alcohol consumption, exercise, income, education, white blood cell count, frequencies of tooth-brushing, and self-reported oral status, number of remaining teeth (model 3). All analyses were performed using SAS .All continuous variables are presented as means and standard error. All categorical variables are presented as percentages. Logarithmic transformation was performed to achieve a normal distribution of the white blood cell count. Student How to cite this article: Hong, M. et al. Association between Cockroach-specific Immunoglobulin E and periodontitis in Korean male adults Based on Korean National Health and Nutrition Examination Survey. Sci. Rep.7, 46373; doi: 10.1038/srep46373 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Microplastics (MP) are recognized as a growing environmental hazard and have been identified as far as the remote Polar Regions, with particularly high concentrations of microplastics in sea ice. Little is known regarding the horizontal variability of MP within sea ice and how the underlying water body affects MP composition during sea ice growth. Here we show that sea ice MP has no uniform polymer composition and that, depending on the growth region and drift paths of the sea ice, unique MP patterns can be observed in different sea ice horizons. Thus even in remote regions such as the Arctic Ocean, certain MP indicate the presence of localized sources. Increasing exploitation of Arctic resources will likely lead to a higher MP load in the Arctic sea ice and will enhance the release of MP in the areas of strong seasonal sea ice melt and the outflow gateways. Microplastic (MP) pollution in polar regions is a growing environmental concern, yet little is known regarding the role of sea-ice as a sink and transport vector of MPs. Here, the authors show that MPs in sea-ice have no uniform polymer composition and observe unique MP patterns in different sea-ice horizons. Plastic accounts for 73% of marine debris globally and it has been estimated that about 8 million tons of plastic move from land into the ocean each year6. However, only 1% of this has been accounted for in terms of small plastic debris7, highlighting that some of the major sinks of oceanic plastic litter remains to be identified. The Arctic Ocean is now in a state of rapid transition that is best exemplified by the marked reduction in age, thickness and extent of the sea ice cover8. The European Arctic margin is influenced by drift ice formed on the Siberian shelves and carried to the Fram Strait via the Transpolar Drift9. In contrast, the Fram Strait is the gateway that transports warm Atlantic water, via the West Spitsbergen Current to the Central Arctic10, containing an anthropogenic imprint11. It is well known that regions of the Arctic Ocean are highly polluted owing to local sources and long-range atmospheric input12. In this context sea ice has been identified early on as a major means of transport for various pollutants14, with north and east Greenland as well as the Laptev Sea, being especially prone to contamination from several sources15. A useful method to study sea ice drift pattern is by using passive microwave satellite images combined with the motions of sea ice buoys17, which highlight the role of sea ice, e.g. spreading oil spills18. Recent studies stress the changes caused by the shift to first year ice resulting in the tendency of sea ice floes to diverge from the main drift pattern19 such as the Transpolar Drift, with complex effects on exchange processes of any contaminants between the exclusive economic zones (EEZ) of the various Arctic nations20. Despite the scant knowledge of Arctic ecosystems, the trend towards thinner sea ice and ice-free summers in the future has already stimulated increasing exploitation of its resources in terms of shipping, tourism, fisheries and hydrocarbon exploration21.Marine debris is a growing environmental concern as recent reports indicate that increasing quantities of litter disperse into secluded environments, including Polar Regions22. Particles < 5 mm are called microplastics (MP) and have recently featured in a strongly growing number of studies and publications23. MP raise particular concerns because plastic in this size category can be taken up by a much wider range of organisms with currently largely unknown health effects on marine life and humans25. Over the past decade, MP were identified from numerous marine ecosystems globally5, including the Arctic26 and the Southern Ocean3. High concentrations of MP also occur in the surface waters south-west of Svalbard26, but overall, MP origins, pathways and their compositional framework within Arctic sea ice remains unclear.Plastic degrades into smaller fragments under the influence of sunlight, temperature changes, mechanic abrasion and wave action28 (Imaging FTIR) and compared to a previous study with respect to MP in Arctic sea ice cores. Analyses of discrete ice core horizons allowed us to assess the spatial variability within sea ice and to reconstruct the location of MP incorporation. By computing drift trajectories, coupled to a thermodynamic ice growth model29, possible source regions of MP entrainments during ice growth were identified.Here, we analyzed the content and composition of MP from sea ice cores at five different locations along the Transpolar Drift to assess if sea ice is a sink and transport vector of MP. Ice cores were taken from one land-locked and four drifting ice floes to distinguish between local entrainment of MP and long-distance transport. MP composition of the cores was analyzed by focal plane array detector-based micro-fourier-transform infrared imagingPolarstern in spring 2014 and summer 2015 in the Fram Strait and Central Arctic  was detected in an ice core taken in the pack ice of Fram Strait . The MP load of core C and E, collected north of Svalbard and in the Nansen Basin respectively, varied between (2.9 ± 2.4) × 106 N m−3 and (2.4 ± 1.0) × 106 N m−3. The lowest concentration was found in core D (1.1 ± 0.8) × 106 N m−3; Fig. 2 (1.3–9.6) × 104 N m−3, values exclude rayon, for further details see method section), which can largely be explained by the different methodology used. In the previous study2, the filter area was first inspected by light microscopy and suspected MP particles were then analyzed individually by Fourier-transform infrared (FTIR) microscopy. In contrast, we used Imaging FTIR28, where entire areas were scanned. This excluded the human bias introduced by visual selection of particles .To quantify the MP concentration and composition we obtained ice cores during expeditions of the German research ice breaker tic Fig. , Table 1les Fig. . Imagingion Fig. . In cont35, also dominated the other core from the Fram Strait (A) and the cores retrieved north of Svalbard . The latter core was further characterized by almost 9% of CE-Alkylated 35.In total, 17 different polymer types were identified  with one of our cores (E), while the other cores can be related to the Beaufort Gyre (core Hc), the Chukchi Shelf (core Ha) and the East Siberian Sea , with a general L-shaped distribution pattern. Only the land-fast-ice core (A) had a maximum concentration at the top. Particulate organic carbon (POC) had a maximum of 1.34 mg L−1 and also showed an L-shaped distribution pattern ). The latter concentration was found in the surface horizon of core B originating from the Makarov Basin . The core originating from the Laptev Sea (E) displayed another MP maximum in the bottom horizon at the seawater–ice interface (4437 L−1), while core C was characterized by a sub-surface maximum  displayed significantly higher Chl a concentrations, salinities and C/N-ratios compared to A, B and E (SIMPROF group d). Still, POC, PON and temperature were significantly higher in cores A, B and E  surface water south and west of Svalbard26, but no clear transportation pathways of MP could be identified. In that study, water with a high melt fraction was rather low in MP particle load, suggesting a comparably low impact of sea ice originating MP. However, in our study we found several order of magnitude higher concentrations of MP in the sea ice and thus confirm the first study by Obbard et al. Particularly the abundance of the small particles (11 µm) are of concern, since they can be taken up within the microbial food web25. A recent modelling study, which suggested an active transport of plastic debris with the North Atlantic currents into the Central Arctic Ocean46 corroborates the notion that polar waters can no longer be considered free of plastic litter. However, owing to the different analytical approaches applied in MP concentration estimates, a direct comparison of the studies is hampered by the current lack of standards in MP research and thus only general inherent trends can be compared. Terrestrial MP sources in these sparsely populated high-latitude regions seem to have a negligible contribution to the MP load of Arctic waters as Lusher et al.26 reported extremely low MP concentrations close to shore. In contrast to other coastal (and more densely populated) areas, which are known to be much more contaminated with MP24, emissions from Arctic terrestrial sources may be considered to be low. In addition, nothing is known about the impact of MP coming from the large rivers entering the Arctic. However, results from a recent modelling study suggest that contaminates originating from the Lena and Mackenzie river mouths, lead to a rapid spreading of theses pollutants in the entire Arctic Ocean15.Overall, the sources and sinks of MP are currently not very well understood41. During sea ice growth, characteristic salt fingers are developed40 and enriching the particle concentration in the brine channels. In addition, coagulation with exopolymer particles excreted from sea ice algae47 might further enrich the concentrations of MP. An accumulation of sediment particles in the surface horizons, as has been described for multiyear ice41, due to constant surface melting, might explain the high MP concentration observed in the surface of the cores originating from the Makarov Basin and the Laptev Sea. It is however unlikely that this process redistributes MP in first year sea ice.Cores from east of Greenland (core A), close to Franz Josef Land (core D) and the Makarov Basin (core B) were further characterized by an abrupt change of MP composition in the various horizons. This suggests that the ice floe had passed through regions with fast changing MP compositions during the sea ice growth process. In analogy to previously described sediment entrainment into sea ice particularly frazil ice scavenged sediment particles48 or the Skagerrak49, which are the highest hitherto reported values in terms of reports per volume unit (www.litterbase.org). This peak consisted almost entirely of PE. Since PE has a low density particles are likely to float over long distances at the sea surface with the ocean currents before they eventually sink through ballasting50. The Canadian Basin is supplied with water originating from the northeast Pacific and transported through the Bering Strait51. From the southern part of the Chukchi Sea sea ice has a direct path via the Central Arctic towards the Fram Strait52. We thus speculate that the high PE concentrations in the core from the Makarov Basin might reflect remains from the so-called North Pacific Garbage Patch53, transported with the incoming Pacific inflow. A recent study by Desforges et al.54 showed quite high MP concentrations for the NE Pacific and highlights the role of oceanographic conditions for the accumulation patterns of MP’s54. Indeed, models project that on long time scales inter-ocean exchanges play a significant role in the distribution of marine debris enabling transport between accumulation areas53. Because of its widespread use and the low density, PE might nowadays, be considered to be a background MP even in surface water of the Central Arctic, analogous to the global distribution of certain persistent organic pollutants55.The highest concentration of MP ever determined in sea ice was found in core B, originating from the Makarov Basin. The core contained concentrations comparable to those from South Korean waters35 and to a lesser extent with ethylene vinyl acetate copolymer (EVA), a polymer, which is also used in antifouling paints for ships56. The occurrence of varnish and EVA can be attributed to ship traffic, which has increased between 2009 and 2014 in the Arctic58. PA, usually associated with fishing gear35, was found frequently in almost all sea ice cores. This polymer was the most abundant in the sea ice core originating from the Chukchi Shelf2. It accounted for 22% in the core originating from the deeper Nansen Basin, which is comparable to other reports (<20%)35. Overall, a high contribution of PA may be related to increasing commercial fishing efforts in the eastern Bering Sea, Barents Sea, north of Svalbard and north of Franz Josef Land58 implying local input. Fisheries accounts for a major share of the ship traffic in the Arctic Ocean58 and continuous reduction of sea ice is assumed to increase fisheries further, particularly in the high Arctic59. The above attribution of source regions is supported by the reconstruction of the location of MP incorporation into the ice by coupling the back-tracking approach with a one-dimensional thermodynamic sea ice growth model  and the core originating from the Laptev Sea (E). In the latter, varnish is present throughout the entire core and often associated with a high proportion of cellulose acetate, indicative of cigarette filters60, reflecting different source areas of the water, e.g., input from Lena river water or Pacific water. It is likely that parts of the MP, which are embedded in the sea ice, were transported by currents into these regions and that different oceanic realms (Pacific versus Atlantic) currently still have specific MP imprints. However, these imprints are altered by localized dispersal of MP in the Arctic, which need to be considered for future budgeting of global MP sources and sink estimates.Overall, this is the first detailed mapping of MP particle composition and size classes from sea ice cores obtained in the high Arctic with special emphasis on the vertical pattern of MP. The ice cores were characterized by various footprints of polymer composition resulting from different origins and pathways during the period of ice growth, although to prove this concept more data are needed. We identified unique footprints for different origin areas. This occurrence pattern is akin to data obtained for the presence of coloured dissolved organic matter4 km3 and 1.93×104 km3 (PIOMAS 2011–2016 based on ref. 61) large fractions of these particles are released. Basic calculations show the potential release of MP between a minimum of 7.2 × 1020 and a maximum of 8.7 × 1020 particles per year between 2011 and 2016, assuming the here-observed average MP values. The maximum values can be attributed to the sea ice record minimum low found in 2012. Since currently only a few studies focus on the occurrence of MP in Arctic waters, it remains speculative whether these potentially released MP remain in Arctic waters or are transported to lower latitudes. On the other hand, due to the co-occurrence of sticky exopolymer particles in sea ice62, a formation of hetero-aggregates might occur32, resulting in a change of buoyancy of MP63 and sedimentation to the seafloor. Indeed, very high numbers of MP were recently detected in deep-sea sediments of the HAUSGARTEN observatory in Fram Strait30. Highest MP concentrations occurred at the northern most stations, which are characterized by a long-lasting marginal sea ice zone area. Recent studies in the Central Arctic also showed that biogenic particles below 2 µm can contribute to the vertical flux64 due to particle coagulation. The process of brine circulation due to melt progression65 may redistribute MP in the Central Arctic Ocean as there is, for example, a high exchange of sea ice algae between the ice and the underlying water to depths of 40 m66. Many MP are in the same size range as sea ice algae, and may therefore also be transported far below the euphotic zone by brine convection.With respect to global climate change, large fractions of MP might be released from melting Arctic sea ice. Given a yearly melt of sea ice between 1.6×10We conclude that the MP distribution in the Central Arctic is more complex than previously considered, assuming only transport with high MP loads from the urban areas into the remote Polar Regions, although this undoubtedly constitutes the main point of entry. Our results also point to localized MP sources, which might become more pronounced as the exploitation of the Arctic progresses.67), the Barents Sea slope  and the Central Arctic . At each station, a designated coring site was assigned and if present, the snow was removed before drilling the sea ice cores. Nitrile gloves were used and cores were drilled with a Kovacs 9 cm diameter corer . The microplastic cores were immediately transferred into plastic bags (polyethylene tube films (LDPE) by Rische and Herfurth) and stored at −20 °C.Sea ice sampling has been carried out during three cruises with the ice breaker Polarstern in the Fram Strait . Ice drift data are provided by different institutions and have been widely used in various studies to investigate pathways and source areas of sea ice71. In this study, two different sets of ice drift products were used: During summer months (June–August), the Polar Pathfinder Sea Ice Motion product provided by the NSIDC provided on a 25 km grid72 was applied. During the rest of the year, tracking is forced with sea ice motion data provided by the Center for Satellite Exploitation and Research (CERSAT) at the Institut Français de Recherche pour l’Exploitation de la Mer (IFREMER). Motion data are available with a grid size of 62.5 km, using time intervals of 3 days for the period between September and May73.To determine drift trajectories and source areas of sampled sea ice we tracked the sampled ice backward using low-resolution ice drift and concentration products from passive microwave satellites after Krumpen et al.The tracking algorithm works using motion and concentration data. A specific ice area is tracked backwards until: the ice reaches a position next to a coastline, the ice concentration at a specific location reaches a threshold value of <15% when ice parcels are considered lost, or the tracking time exceeds 4 years. To quantify uncertainties of estimated sea ice trajectories using satellite sea ice motion and concentration data, pathways of 39 buoys were re-tracked. Buoy data were obtained from the SeaIcePortal.de and followed from their deployment position in a forward direction. On average, the displacement of virtual buoys during the first 150 days (around 1000 km of ice drift) is around 35 km. After one year (ice drift of more than 2500 km), the average displacement is around 150 km. For general details of the AWI ICETrack tool (Antarctic and Arctic Sea Ice Monitoring and Tracking Tool), please see Krumpen74, where the change in ice thickness Δh/Δt is given by:L, the thermal conductivities of ice κi and snow κs and the freezing point of seawater T0 are set to literature values according to74. Surface air temperature is extracted along the ice trajectory from NCEP reanalysis75, while the ocean heat flux is assumed to be constant at 2 W/m2 in agreement with Meyer et al.76 and earlier work77. Ice thickness is calculated along the trajectories at daily increments and is in reasonably good agreement with ice core length for such a simple model. The model was also validated against an ice-mass-balance buoy78 providing accuracy of few centimetres during the growth phase.Along the pathways derived from the back-tracking model sea ice trajectories, air temperatures  and snow depth (Warren climatology) and other atmospheric parameters were extracted as input for the thermodynamic ice growth model. The model was then used to estimate the location of MP incorporation into the respective ice sample (see below). To link the vertical distribution of MP within ice cores to the location, where MP particles were incorporated into the ice; we used a simplified one-dimensional thermodynamic model of sea ice growth. The model calculates sea ice growth based on surface air temperature, ocean heat flux and snow cover76 report tenfold increased heat fluxes for the sampling region with basal melt rates of up to 26 cm/day. This dramatic melting, which is strongly limited in time and space can generally not be reproduced by single point to point comparisons even with the most sophisticated thermodynamic sea ice models. The difference between our simple model and measured ice core lengths, on the order of 50 cm, can be caused by just a few days of melting. This does, however, not affect the growth phase of the respective sea ice, so that our simple thermodynamic model can still be used to estimate the location of MP incorporation into the ice.While such simple models perform very well on simple ice growth of typical Arctic sea ice, they are not suited to model strong regional melting features. Sampling locations of ice cores C and D, taken on the TRANSSIZ expedition in 2015, are strongly affected by small-scale abnormal basal melting in the inflow area of Atlantic water just north of Spitsbergen. Meyer et al.Using back-tracking . After filtering the melt water the filter was overlaid with 40 mL H2O2 and incubated at room temperature overnight. Lastly, the H2O2 was drained and the filters were flushed with approx. 750 mL MilliQ water. To remove the adhering material, the filtration funnel was further flushed with 30% ethanol  to reduce surface tension and thereby assure the concentration of all particles on the filter. The Anodisc filters were placed in glass petri dishes and dried at 30–40 °C in a drying cabinet  overnight.To prevent contamination of samples, handling and processing the sea ice cores was conducted under a clean bench . Ice cores were cut individually into horizons ranging from 10 to 35 cm using a bone saw. To exclude sample contamination from sampling the surface of the ice core horizon was removed by a stainless steel grater. Afterwards, it was washed with 1 L of MilliQ to remove the particles that would eventually adhere. Each horizon was weighed before being melted in glass-preserving jars at room temperature and then concentrated onto Anodisc filters . All samples were treated with of 35% HFor the blank tests, artificial ice cores were produced by freezing MilliQ water in a stainless steel beaker for one day. Afterwards, they were transferred into an ice core transportation bag and kept in the freezer for three days. Each day, the cores were rolled to simulate transport and then treated in the same manner as the sea ice core samples described above.27. The scan was run in transmittance mode with 6 co–added scans, a range of 3600–1250 cm−1 and a resolution of 8 cm−1. A 4 × 4 binning was selected to balance the amount of data and the analysis time. The whole system was flushed with compressed dry air and with a flow rate of approx. 200 L h−1 to prevent signals caused by air humidity and CO2. After drying, the Anodisc filter was placed on the FTIR microscope. The background was measured on the Anodisc surface without sample impurities. As it was not possible to analyze the whole filter cake of (36 mm) in diameter in a single measurement, three separate fields on the concentrated sample were measured as technical triplicates. Three grids of 70 × 70 FPA fields each were placed on the filter equalling 3,763,200 single spectra. The measurement took 12.25 h per grid resulting in a total analysis time of 36.75 h per filter.For the particle measurements, a Hyperion 3000 microscope (Bruker Optics) attached to a Tensor 27 (Bruker Optics) spectrometer was used. The microscope features a FPA detector with 64 × 64 detector elements. With a visual objective of ×4 magnification the whole filter area was photo-documented to obtain a sample overview. Afterwards, the IR measurement was performed via two 15× magnification Cassegrain lenses. The measurements and analyses were performed with the OPUS 7.5 software (Bruker). In previous studies, the optimal settings for the measurements were evaluated28. During this process, each spectrum was compared twice against a spectral library with different data handling. Each successful hit was stored together with the x, y and a quality factor into a csv file. Afterwards, the file was analyzed by image analysis to determine the polymer types, particle number per polymer and size distribution28. For each filter, the mean value NF and standard deviation of the three m technical triplicates were calculated. To extrapolate to the total area in contact with the sample, Eq. (N) numbers per litre melted ice were calculated from the mean value NF and the volume fraction of one measurement field VF from the overall volume. Particle numbers derived from blank samples were subtracted from NF. To estimate errors of this conversion an error propagation was performed.Each measurement field was subjected to the automated analysis by Primpke et al.N) values, Eq. 44N is theV, an error of 0.01 L was estimated due to the gravimetric determination. For ΔCF, an error value of 0.267 was found that includes the errors from the measurement field size determination and filter cake diameter.28. For image analysis, the following quality factor thresholds differing from 600 were used : Polyethylene type 1 = 1100, polyethylene type 2 = 1350, PE-Cl = 1310, PC = 700, PA = 1020, PVC = 800, PES = 800, quartz = 700, EVA = 900, rubber type 1 = 1190, rubber type 2 = 1300, polyethylene type 3 = 1070. In addition, polychloroprene had to be excluded due to the low hit qualities.To maintain a 95% confidence interval for the chosen type of sample purification, several fields were manually reanalyzedrayon is often included in the classification of MP found in the marine realm. For example, it accounted for up to 30% of the MP found in samples from the Arctic26. However, FTIR-based studies showed that 30% of suspected rayon fibres turned out to be cellulose, which is considered a natural product. Since cellulose and the semi-synthetic polymer rayon, have almost identical FTIR spectra45, we resigned from identifying this particular compound in our study. To compare ours with the previous study of MP in sea ice, we also excluded rayon from the MP identified in Obbard et al.2. We digitized the data from Fig. −3 for Fig. The polymer 26, which cannot be identified with our way of applying the FTIR spectra, since fibres are not distributed flat on the surface of the filter and regions out of focus of the IR-beam were hardly or not detectable. The typical diameter of fibres was around 10–20 µm and the increased scattering due to their shape was not suitable for identification with our analytical approach.The visible inspection classifies usually a large fraction of the MP as fibresav) were further used in ANOVAs for testing group differences of MP-related data and ancillary variables. Spearman rank correlations and ANOVAs were calculated by using non-transformed data.Multivariate analyses were performed by using the software package Primer 7.012 (Primer-E), and univariate analyses by using Statistica 11 (Statsoft). Polymer-specific MP numbers and numbers of particles in the different size classes were fourth root transformed; ancillary variables were normalized before multivariate analyses. For clustering (group average), Bray-Curtis similarities were used for MP-related data and Euclidean distances for ancillary variables. Calculation of diversity indices  were performed by using the PRIMER routine DIVERSE. The exploratory similarity profile test (SIMPROF) was applied to detect structures in the datasets. A significance level of 5% was used to test the SIMPROF statistic. SIMPROF groups (of ancillary variables; SIMPROFhttps://doi.pangaea.de/10.1594/PANGAEA.886593.The authors confirm that all data underlying this study are fully available without restriction. All data can be downloaded from the public repository PANGAEA; Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2


Protein kinases are major regulators of mitosis, with over 30% of the mitotic proteome phosphorylated on serines, threonines and tyrosines. The human genome encodes for 518 kinases that have a structurally conserved catalytic domain and includes about a dozen of cell division specific ones. Yet each kinase has unique structural features that allow their distinct substrate recognition and modes of regulation. These unique regulatory features determine their accurate spatio-temporal activation critical for correct progression through mitosis and are exploited for therapeutic purposes. In this review, we will discuss the principles of mitotic kinase activation and the structural determinants that underlie functional specificity. Protein phosphorylation is a key regulatory mechanism influencing various cellular processes such as cell growth, cell motility, cell differentiation and cell division. Most notably, protein phosphorylation peaks during mitosis and the timing coincides with the cell division-related chromosomal and cytoskeletal reorganization  and an α-helical C-terminal lobe  at each end  family . Though the activation loop auto-phosphorylation is sufficient for basal activity, facilitating the right conformation of the loop is required for full activation, and is achieved by the binding of TPX2 and INCENP to Aurora A and Aurora B kinases, respectively  and kinetochore-microtubule attachment Elowe, . Cdc20, CDK Activating Kinase belonging to the family of CDKs)  which is essential for their increased kinase activity  and the budding yeast Hrr25 (Casein kinase) critical for meiosis co-orientation of kinetochore do not require the activation loop phosphorylation and their kinase domains are constitutively active (Eswaran et al., Kinases achieve substrate specificity through multiple mechanisms in mitosis (Ubersax and Ferrell, in vitro and in vivo thus far has helped define kinase substrate specificity. Typically about 4-6 amino acids flanking the phospho-acceptor residue P can contribute to the selectivity of kinases for their substrate. The molecular basis for substrate recognition mainly comes from the structural work on CDK2/cyclin A bound to its substrate (Brown et al., Kinase substrate specificity is generally determined by the architecture of the substrate binding site, which might select negatively against certain residues flanking the phosphorylation site. The identification of substrates in vitro phosphorylation of kinetochore proteins by Bub1 followed by phosphorylation-directed staining and mass spectrometric analyses identified many prospective Bub1 substrates with a putative consensus motif ϕ-X5-S/T (Breit et al., The identification of multiple budding yeast kinetochore Aurora B kinase substrates, allowed to define an Aurora consensus phosphorylation sequences (Cheeseman et al., in vivo (Dephoure et al., The use of peptide libraries against kinases has greatly contributed to the identification of optimal peptide sequence motifs and “anti-motifs” for kinases (Hutti et al., Kinases may use docking sites or sites that are primed by another kinase to enhance their substrate selectivity. For example, to bind and to be phosphorylated by Plk1, a substrate generally needs to be primed by another kinase (Lee et al., CDK-cyclins also use docking sites to recognize and phosphorylate temporally their substrates. Certain cyclin partners have a hydrophobic docking patch that recognizes an “RXL” motif on substrates 40Å away from the catalytic site of the CDK active site (Schulman et al., Many mitotic kinases rely on spatial targeting to phosphorylate their specific substrates. This restricts the activity of the kinase to generate gradients of kinase activity. The most well characterized spatially-targeted kinases are Aurora A and B kinases and they appear to share the same substrate specificity (Fu et al., The molecular basis for the recruitment of Mps1 kinase to the outer kinetochore is also well established. Multiple kinases including CDK1, Aurora B, Plk1, and Mps1 itself are implicated in Mps1 kinetochore targeting (Morin et al., High resolution mechanistic understanding of kinase regulation is essential not only to define how kinases achieve error-free cell division, but also to exploit the differences in their regulatory mechanisms to specifically target them in mitosis-related human disorders. Structural studies of kinases thus far have provided key insights into the similarities and differences in the modes of activation and regulation of many mitotic kinases. Although kinases possess a broadly conserved catalytic core, their level of kinase activity and substrate specificity are determined by specific inter/intra molecular interactions and phosphorylation. In this review, we summarize how key structural regulatory elements such as the relative orientation of the C-helix, activation segment conformation and spatial regulatory elements responsible for correct kinase sub-cellular localization achieve accurate kinase function. However, there are still many open questions, particularly on factors determining the graded level of kinase activation and its implications on their mitotic role. More structural analyses of kinases in complex with their regulatory binding partners with and without bound substrates, and their functional implications in cells will undoubtedly further advance our mechanistic understanding of this essential class of mitotic regulators.JW and AJ have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


TRPM7 and TRPM6 were the first identified bifunctional channels to contain their own kinase domains, but how these channel-kinases are regulated is poorly understood. Previous studies identified numerous phosphorylation sites on TRPM7, but very little is known about TRPM6 phosphorylation or sites on TRPM7 transphosphorylated by TRPM6. Our mass spectrometric analysis of homomeric and heteromeric TRPM7 and TRPM6 channels identified phosphorylation sites on both proteins, as well as several prominent sites on TRPM7 that are commonly modified through autophosphorylation and transphosphorylation by TRPM6. We conducted a series of amino acid substitution analyses and identified S1777, in TRPM7’s catalytic domain, and S1565, in TRPM7’s exchange domain that mediates kinase dimerization, as potential regulatory sites. The phosphomimetic S1777D substitution disrupted catalytic activity, most likely by causing an electrostatic perturbation at the active site. The S1565D phosphomimetic substitution also inactivated the kinase but did so without interfering with kinase dimerization. Molecular modeling indicates that phosphorylation of S1565 is predicted to structurally affect TRPM7’s functionally conserved N/D loop, which is thought to influence the access of substrate to the active site pocket. We propose that phosphorylation of S1565 within the exchange domain functions as a regulatory switch to control TRPM7 catalytic activity. TRPM6 was first linked to vertebrate MgDictyostelium myosin heavy chain kinase A, B, C , which primarily phosphorylate their substrates within alpha helical domains rather than within flexible loops and turns, as generally done by conventional protein kinases2+ nucleotides152-terminal to the core catalytic domain17in vitro substrates, including non-muscle myosin heavy chain IIA, annexin I, phospholipase C gamma-2, and histones, suggesting that the TRPM7 kinase may be impacting a diverse range of physiological activities19202122The channel-kinases are also members of the atypical alpha-kinase family, so named after initial members of the family Dictyostelium MHCKs identified important autophosphorylation sites outside the catalytic core that regulate kinase activity26284Unlike other members of the alpha-kinase family and conventional protein kinases, TRPM7 has been shown to undergo extensive autophosphorylation within a serine/threonine-rich region proximal to the exchange domain of the kinase and the kinase’s catalytic core24While numerous studies have focused on regulation of the channel activity of TRPM7 and TRPM6, by comparison the functional role of these channels’ kinase domains or how they are regulated is poorly understood. In previous studies, a high number of phosphorylation sites were identified on TRPM7, either by performing mass spectrometry (MS) analysis of an ATP-stimulated COOH-terminal fragment of TRPM7 or of full length TRPM7 transiently expressed and purified from human embryonic kidney cells24in vivo and in vitro (in vitro via kinase assays using myelin basic protein (MBP) as a substrate  to identify residues phosphorylated on TRPM7 and TRPM6, using different constructs both in vitro . We firsubstrate . Unlike mulation . A totalmulation . We prevIn vitro kinase assays verified the respective kinase activity of SBP-TRPM7-K1646R and HA-TRPM6 proteins (282-terminus (S552)  .in vitro before MS analysis. A catalytically inactive mutant of TRPM7 kinase was also analyzed as a negative control  (Sumo-TRPM7-Kinase)  from bac control . In vitrentified , and in in vitro kinase assays. Our screen identified two autophosphorylation sites S1596 and S1777 on the kinase catalytic core domain that influenced catalytic activity , S1613, which was discovered on the constitutively expressed FLAG-TRPM7, and S1596, a phosphosite identified in a previous studyactivity . We founactivity . Omega-lactivity . S1777 iactivity , the invtivity 15. By conttivity 15. This reSubstitution of alanine or aspartate at the five other serine and threonine residues  did not cause a significant change in the catalytic activity. Close examination of the kinase structure found that these five serine and threonine residues are exposed at the protein’s surface , suggest16in vitro kinase assay. We found that PLC-β1 does not impact the kinase’s catalytic activity towards the MBP substrate   and investigated its ability to affinity purify GFP-TRPM7-Cterm WT and mutants from cell lysate   and 8a15–1577) 20. Mutatio–1577) 20. Previou mutants . To testl lysate . If dimeOne explanation for the catalytic defect observed in S1565D mutant comes from the observation that the side chain of S1565 is orientated towards a glycine-rich loop (a.a. 1783–1798) between the β15 sheet and the αE strand of the other monomer. This loop of alpha-kinases is referred to as the “N/D loop” due to the presence of invariant asparagine or aspartate residuein vivo and in vitro. One of our concerns was that which sites on TRPM7 are phosphorylated in vivo might vary depending on whether the full-length protein is present on the cell surface or located in intracellular compartments such as the ER, which is where the channel is predominantly found when transiently overexpressed in HEK-293T cells. Also, our previous studies found that overexpression of TRPM7 causes cell stress, which could also potentially influence the phosphorylation state of TRPM7242523With the aim of understanding how phosphorylation regulates the two unique channel-kinases TRPM6 and TRPM7, our study deployed LC-MS/MS to survey phosphorylation sites present on these two proteins using various constructs, examining phosphorylation Previous studies have reported that TRPM6 can cross-phosphorylate TRPM7 but not vice versa2942840To further understand how phosphorylation events could be controlling the catalytic activity of TRPM7, we closely examined multiple serine and threonine residues near or in the kinase domain and uncovered a number of autophosphorylated sites whose mutation affected catalytic activity. S1777 is highly conserved in TRPM7 and TRPM6  and located at the active site close to key catalytic residues. The addition of a phosphate group to S1777 is likely to break the existing hydrogen bond between S1777 and the key catalytic residue D1765 and introduce a negative charge in the vicinity of ATP. It is possible that S1777 phosphorylation functions as a stop signal for TRPM7 catalysis, though it is not clear whether this “off” signal could be easily reversed given its buried location. By contrast, S1565 is located outside of the TRPM7 catalytic core on the kinase’s exchange domain. Though phosphorylation of residues on the exchange domain does not affect TRPM7 kinase dimer formation, close examination of the kinase structure suggests a possible interaction between S1565 of one kinase monomer and the flexible N/D loop of the other monomer. The N/D loop of alpha-kinases is considered to be equivalent to the activation loop of conventional serine/threonine kinases, which is located at the bottom of large C-lobe facing toward the catalytic cleft152638Our current study has attempted to understand how regulation of TRPM6 and TRPM7 kinase activity differs from that of the other alpha-kinases such as MHCKs and eEF2K. A comparison between the crystal structures of MHCK A and TRPM7 shows a high degree of similarity in the core catalytic domain, but while TRPM6 and TRPM7 kinases form dimers, the kinase domain of MHCK A is a functional monomer and does not possess an exchange segment homologous to that of TRPM6 and TRPM7262627381538in vivo TRPM7 kinase activity can be controlled. Future studies will be directed at determining whether phosphorylation of S1565, as well as S1777, plays a functional role in regulating TRPM7 kinase activity in vivo. Now that phosphorylation sites on both TRPM6 and TRPM7 have been identified, we can also begin the work of teasing apart how phosphorylation of these unique channel-kinases impacts their functions.In this study, we performed a compressive analysis of phosphorylation sites present on TRPM6 and TRPM7 as a first step towards understanding the regulatory mechanisms of these channel-kinases. Indeed, our discovery that phosphorylation of TRPM7 S1565 inactivates kinase activity without affecting dimerization provides a unique mechanism by which BamHI/EcoRI sites of a pTrcHis2 A vector  modified to contain a NH2-terminal His6-Sumo-SBP tag between NcoI/BamH1. Site-directed point mutations were introduced into TRPM7 using the QuickChange mutagenesis kit . To generate the GST-fused exchange peptide of TRPM7, residues 1548–1576 of mouse TRPM7 were amplified by PCR and fused in-frame to GST by cloning into the BamHI and EcoRI cloning sites of the pGEX-6P3 vector . The kinase-inactive TRPM6-K1804R mutant was generated by site-directed mutagenesis  using the HA-tagged human TRPM6 as a template.The GFP-TRPM7-Cterm a.a. 1120–1863) containing a streptavidin binding protein (SBP) tag was generated in an earlier study20–1863 c2 incubator.The 293 T cell line (CRL-3216) was purchased from American Type Culture Collection . The HEK-293-TRPM7 cells expressing recombinant FLAG-tagged mouse TRPM7 was described in an earlier publicationE. Coli BL21-DE3 cells . Bacteria were grown at 37 °C to OD600 of 0.6–0.8, cooled to 16 °C and induced at 16 °C for 16–18 h with 1 mM isopropyl-beta-D-thiogalactopyranoside . Cells were lysed by sonication in ice-cold phosphate buffered saline (PBS) containing a final concentration 1 mM protease inhibitor PMSF and 1% Triton-X10. Sumo-TRPM7-Kinase was pulled down from the cell lysate supernatant by streptavidin agarose  and eluted with 10 mM Biotin . Before MS analysis, purified Sumo-TRPM7-Kinase WT and KR was stimulated with 0.5 mM ATP in kinase buffer (50 mM MOPS (pH 7.2), 100 mM NaCl, 2.5 mM MnCl2) at 30 °C for 20 min.To identify autophosphorylation sites of TRPM7, HA-TRPM7 WT and K1646R and GFP-TRPM7-Cterm WT and K1646R were transiently expressed in HEK-293T cells. Cells were lysed with lysis buffer containing 50 mM Tris (pH 7.4), 150 mM NaCl, 1% IGEPAL CA-630 , protease inhibitor cocktail , and phosphatase inhibitor cocktail . HA-TRPM7 proteins were immunoprecipitated by HA-agarose  and eluted with 1 mg/ml HA-peptide . The GFP-TRPM7-Cterm proteins containing an SBP tag was immunoprecipitated by streptavidin resin  and eluted with 10 mM biotin . FLAG-tagged TRPM7 was obtained from the HEK-293-TRPM7 cell line expressing recombinant mouse FLAG-TRPM7 at a basal level without tetracycline induction and immunoprecipitated by M2 FLAG-agarose For phosphorylation site identification, purified TRPM6 and TRPM7 were resolved in a Bis-Tris polyacrylamide gel, and each gel band was subjected to in-gel reduction, alkylation, tryptic digestion and peptide extraction with a standard protocol. Peptides were solubilized in 0.1% trifluoroacetic acid, and analyzed by Nano LC-MS/MS with Dionex Ultimate 3000 RLSC Nano System interfaced with a Velos-LTQ-Orbitrap  or a QExactive HF  based on instrument availability. Samples were loaded onto a self-packed 100 μm × 2 cm trap  and washed with Buffer A (0.2% formic acid) for 5 min with a flow rate of 10 μl/min. The trap was brought in-line with the analytical column  and peptides fractionated at 300 nL/min using a segmented linear gradient 4–15% Buffer B (0.2% formic acid in acetonitrile) in 35 min, 15–25% Buffer B in 65 min, 25–50% Buffer B in 55 min. Mass spectrometry data was acquired using a data-dependent acquisition procedure with a cyclic series of a full scan acquired with a resolution of 60,000 (Velos-LTQ-Orbitrap) or 120,000 (QExactive HF) followed by MS/MS of the 20 most intense ions and a dynamic exclusion duration of 30 sec for both instruments. Proteome Discoverer was used for database search and analysis. Data were searched against most updated SwissProt database using MASCOT (v 2.3). Precursor ion mass error tolerance was set to ±10 ppm (Velos-LTQ-Orbitrap) or +/− 7 ppm (QExactive HF) and fragment mass error tolerance to ±0.4 Da (Velos-LTQ-Orbitrap) and +/−20 ppm (QExactive HF). Cysteine carbamidomethylation was set as a complete modification, acetylation on N-terminus of protein, oxidation on methionine, phosphorylation on serine, threonine and tyrosine were set as variable modifications. Site localization was analyzed using PTMRS. Only spectra of high confidence (FDR were set at 0.01 for PSM) were reported. Interested sites were further validated manually.2, 0.5 mM ATP). The kinase reactions were performed at 30 °C for various times in the presence of 4 μCi of [γ-32P]ATP with 5 μg of myelin basic protein as a substrate. Reactions were stopped by the addition of SDS sample buffer, and the reaction mix was resolved by SDS-PAGE. Proteins were detected by Coomassie blue staining and gels were dried completely using a gel dryer . Incorporation of [γ-32P]ATP into substrates was analyzed by autoradiography using Cyclone Plus Phosphor Imager .Purified TRPM7 proteins were dialyzed into kinase buffer (50 mM MOPS (pH 7.2), 100 mM NaCl, 2.5 mM MnClE. Coli BL21-DE3 cells  and purified from cell lysates by incubating with glutathione agarose  at 4 °C for overnight. The resin was washed thoroughly with PBS with 1% Tween-20. For GST pull-down, HEK-293T cells lysate containing transiently expressed GFP-TRPM7-Cterm was incubated with GST-exchange peptide or GST proteins bound on glutathione agarose for overnight at 4 °C.Recombinant GST-exchange peptide and GST were expressed in For detection of proteins, the proteins resolved by SDS-PAGE and western blotting using standard protocols. A rat monoclonal antibody anti-HA antibody  was used to detect HA-tagged TRPM7 and TRPM6. Anti-FLAG M2 antibody  was used to detect FLAG-TRPM7. A mouse monoclonal antibody anti-SBP  and a rabbit polyclonal anti-TRPM7-C47 were used to detect SBP-TRPM7How to cite this article: Cai, N. et al. Mass Spectrometric Analysis of TRPM6 and TRPM7 Phosphorylation Reveals Regulatory Mechanisms of the Channel-Kinases. Sci. Rep.7, 42739; doi: 10.1038/srep42739 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Understanding how anthropogenic disturbance influences patterns of community composition and the reinforcing interactive processes that structure communities is important to mitigate threats to biodiversity. Competition is considered a primary reinforcing process, yet little is known concerning disturbance effects on competitive interaction networks. We examined how differences in ant community composition between undisturbed and disturbed Bornean rainforest, is potentially reflected by changes in competitive interactions over a food resource. Comparing 10 primary forest sites to 10 in selectively-logged forest, we found higher genus richness and diversity in the primary forest, with 18.5% and 13.0% of genera endemic to primary and logged respectively. From 180 hours of filming bait cards, we assessed ant-ant interactions, finding that despite considered aggression over food sources, the majority of ant interactions were neutral. Proportion of competitive interactions at bait cards did not differ between forest type, however, the rate and per capita number of competitive interactions was significantly lower in logged forest. Furthermore, the majority of genera showed large changes in aggression-score with often inverse relationships to their occupancy rank. This provides evidence of a shuffled competitive network, and these unexpected changes in aggressive relationships could be considered a type of competitive network re-wiring after disturbance. Human-modified landscapes have increasingly become a part of many ecosystems6 and mounting evidence supports that disturbance alters the interactive processes within communities and subsequent ecological function8. Understanding the effects of disturbance requires deep knowledge of how community composition changes10, and to link end-point patterns of change with the reinforcing interactive processes that structure communities12.Species assemblage has been realised as a major determinant of ecosystem processes and function14, and it is reasonable to presume that habitat disturbance will alter these interactions15. Indeed, studies on plant communities have shown that persistent anthropogenic disturbance can cause seemingly irreversible shifts in grassland competitive communities17, and the defoliation of dominant plant species can decrease interspecific competitive interaction intensity and importance18. Furthermore, community interaction network studies have reported a re-wiring of interactions following disturbance in soil microbes20, and following the removal of plants or pollinators in mutualistic plant-pollinator community networks23. However, experiments attempting to elucidate how the dynamics of competitive interactions across multi-node networks change after disturbance are limited24. Here, we aim to contribute to this paucity of data by examining how potential changes in the community composition of ants, found between undisturbed and disturbed sites of a lowland dipterocarp rainforest in Borneo, is reflected in a change to the observed competitive interactions over a food resource between the nodes of the ant community network.Competition between taxonomic and/or functional groups is considered an important interactive process determining community composition and structureAnt community in a disturbed forest of Borneo: The Indo-Malayan region of the tropics is a global hotspot of biodiversity25, but worryingly is experiencing some of the highest rates of forest loss compared with other tropical realms28. With nearly 80% of the land surface on Borneo having been affected by logging and oil palm conversion30, it is important we understand how communities are responding to such change8. Ants constitute an estimated 25% of animal biomass in tropical forests31, and play a number of critical functional roles in ecosystem processes, often acting as ecosystem engineers33. The ubiquity, functionality and competitive structuring in ant communities may make ants some of the most cost-effective indicators of tropical forest disturbance36.42, with interactions between certain taxonomic groups, when competing over a common resource, often showing consistent uni-directional aggressive behaviour(s) from one group to the other44. It has been proposed that such patterns in behaviour can dictate ant spatial distributions (occupancy)46, abundances47 and potentially even species richness49. Importantly, the removal of competitive groups in a community may create competitive release, changing the abundance or distribution of other groups by allowing them to newly access and exploit previously denied resources52. The abundance and/or occupancy of a taxonomic/functional group in the community is thus likely to be related to components of their competitive ability over other constituent groups. In other words, a change in frequency of one competitive node is likely to have a cascading or ripple effect across the competitive network, rather than just a ‘one-step effect’ on only the directly linked nodes.Competition among ants has been recognized as a key process in the structuring of their communitiesTesting the influence of disturbance on ant community composition and competition: The effect of anthropogenic forest disturbance on animal communities, such as ants, has been of interest to ecologists57, but despite their critical functional roles and apparent importance of competition for structuring their communities, studies specifically examining the effect of disturbance on competitive interactions within communities are relatively lacking. Here, we conducted a study that first investigated the difference in ant community composition between primary and selectively-logged sites in an extensive Bornean forest. Primary forest acted as the control because it had not undergone anthropogenic forest disturbance in the form of logging or clearing for agriculture58. Selectively-logged forest acted as the disturbed forest comparison, as the removal of specific trees from a forest area results in canopy gaps, destroyed undergrowth, and the presence of extensive road networks59. In identifying both the similarities and differences in community composition between the sites, we then set out to observe inter-genus interactions at bait cards, allowing us to explore how ant abundance and occupancy relates to variation in competitive interactions for the shared ant genera between the forest types. As a proxy for competitive ability we observed each genus-genus interaction on a bait card and scored whether it was an aggressive, neutral or submissive response for each individual. In the absence of prior experiments of this nature, we tested a null hypothesis in which aggression-scores among genera observed in primary forest would be the same in logged forest, regardless of any change in relative abundances or occupancy between forest types. Alternatively, changes in abundance or occupancy could positively correlate with aggression-score (intuitive hypothesis) causing a shuffling of dominance in the competitive network, as variations to the presence of numerically dominant ants has been shown to increase interspecific aggression in a previous study60.58. We established 10 control (undisturbed) sites in primary lowland dipterocarp rainforest within the Maliau Basin Conservation Area , and another 10 disturbed sites located in selectively-logged lowland dipterocarp rainforest within the Ulu Segama Forest Reserve . The primary forest had never been logged and has an average aboveground tree biomass of 350 t.ha−1, in contrast to the selectively-logged forest which was logged in the 1970’s and again in the 1990’s, removing an estimated 228 t.ha−1 of tree biomass61. The logged forest was characterized by a more open canopy with lower leaf area index and smaller trees61. The choice to use the Stability of Altered Forest Ecosystems project as a research location was important, as the design and location of study sites is considered to minimise the confounding factors that affect land-use change, such as latitude, slope and elevation58.Study sites were situated in the Malaysian state of Sabah, on the island of Borneo, at the site of the Stability of Altered Forest Ecosystems project63, ants were sampled for 2 hours from the first of the grids at 0800 h, the second grid at 1200 h and last grid at 1600 h.Field data focused on sampling ground dwelling ants collected between February-June 2016. An initial sampling site in each forest type was chosen at random, and the remaining nine sites were spaced sequentially along a transect at intervals of 60–100 m to ensure independence. At each sampling site, 27 sampling points were established using a 3 × 9 grid pattern design (composed of three sets of 3 × 3 connected grids) with each sampling point spaced 5 m from its nearest neighbour .For column 1, ant individuals were collected, and genus identified from leaf litter samples. We scraped up and collected all leaf litter within a 1 × 1 m quadrat at each sampling point71. To attract a range of ant genera we used tuna as a protein bait and cat food provides a carbohydrate nutrition base both of which have been highly effective in attracting ants in previous studies74. Data from only the video recordings were used to investigate ant competitive interactions.For column 2, a bait card was placed at each sampling point, with each card consisting of a sheet of graph paper (210 × 148.5 mm) placed flush with the ground and baited with two heaped teaspoons of a tuna and cat-food mix (mixed at a 15:1 weight ratio) Fig. . Ant genFor column 3, we again used a bait card, but this was monitored for 40 mins by a human observer and any ants that crawled on to the card were invasively hand collected, placed in 70% ethanol and later identified Fig. . CollectEach of the three grids at a sample site was split into three columns, each with a different sampling method Fig. . We used75 and photographs from online databases77. We used genus level identification because this is an efficient method of taxonomic sorting that ant community composition studies have used previously80. Moreover, ants can be separated into functional groups at the genus level82, and importantly these functional groups have been shown to display differing levels of dominance/aggression83. Given this, we felt that genus-level identification was sufficient to begin to unpick the competitive mechanisms within such a highly diverse ant community.Ants collected from columns 1 and 3 were identified to genus level under a stereo microscope with the help of a taxonomic identification key73. Interactions were categorized as neutral or competitive: neutral interactions were when the individuals of one genus did not change the behaviour of individuals in the other genus; competitive interactions were when individuals of one genus showed aggression toward individuals of another genus70. For all competitive interactions, genera were further classified as either aggressive, where individuals of that genus showed aggression and/or forced individuals of the other to retreat from the bait; or submissive, where an individual fled from the bait when confronted by another from a different genus.From the column 2 video recordings, we noted the time and order of arrival for each genus, and any direct interactions with individuals belonging to other ant genera; processes which have been shown to affect competitive ability in previous studiesRate of competitive interactions were defined as the total number of competitive interactions over the 40 min observation, and per capita number of competitive interactions was calculated by dividing the total number of interactions by the total abundance of ants on a bait card over the 40 min observation period. We assigned an aggression-score to each genus involved in a pairwise genus-genus interaction , and then calculated a mean score for each pairwise genus-genus combination. Consequently, we had multiple aggression-scores for each genus – one for each of the other genera that the target genus interacted with. Only genera that had interactions with >3 other genera were analysed. Scores were produced separately for interactions observed in the primary and logged forest, and the difference between forest-specific scores were calculated to represent an aggression-score change. Considering unequal representation of the genera in samples because of colony and sampling method variations, we weighted the aggression scores based on their sample size to encompass the variability. The mean of the differences in a genus’ aggression-score between forest types were also calculated to represent a change in an aspect of their competitive status between primary and logged forest. The mean of this competitive change was then compared to changes in occupancy to investigate whether variations in competitive interactions are associated with variations in community composition.84).All statistical analyses were carried out in R (R Development Core TeamH’) was also calculated and a linear regression used to compare ant genera community evenness between forest types85. Occupancy refers to the number of sampling points in which the focal genus was present at out of all sampling points (120 per site). We used occupancy rather than abundance to reduce any sampling bias that could be introduced if sampling was near or far away from a colony (nest) entrance86. Further Mann-Whitney U tests were used to compare the occupancy of genera in each sampling method. We used a Spearman’s rank correlation to compare changes to the rank occupancy of genera between forest types.A Generalised Linear Model (GLM) with quasipoisson error distribution was used to examine the effect of forest type on genus richness. Mean Shannon diversity , 0 = Neutral . GLMERs were also used to examine the effect of forest type on the proportion, the rate and the per capita number of competitive interactions at each bait card. The random effect of site, containing 10 levels per forest type, was included in the models to account for the nested structure of our sampling design. Following this, we used a Spearman’s rank correlation to compare changes in aggression-score with changes in occupancy rank between forest types.We used Mann-Whitney U tests to examine the ratio of neutral to competitive interactions in primary and logged forests, and we used a GLM with binomial error distribution to test the effect forest type had on this ratio. To assess whether ant interactions changed between forest type we employed a mixed-effects model (GLMER) using the R package lme4N = 37) of genera in common, with 18.5% (N = 10) being exclusive to primary forest and the remaining 13.0% (N = 7) exclusive to logged forest  this was not seen to the same degree in logged , with the difference between forest types close to being significantly different , despite very little difference in total ant abundance in the two forest types (Primary: 1659 vs. Logged: 1622). One hundred and sixty-three interactions were competitive and 452 neutral. Interestingly, whilst a significantly higher proportion of neutral interactions were found in primary forest  or increase in aggression-score  in the logged relative to primary forest  between forest types (Mean score change: −0.323). However, many genera showed contrary patterns of competitive score and occupancy changes, displaying idiosyncratic patterns  may alter the dominance of a genus or alter the position of species in an interactive network in ants95. Previous data showing idiosyncratic type responses of plant and animal communities to disturbance supports this105. For instance, in the logged forest, the reduction in occupancy of predatory and dominant genera like Odontomachus could have weakened any competitive exclusion they placed on other genera in the community, allowing others such as Odontoponera to increase in aggressive activities and thus dominate a resource. Nevertheless, we may not have detected a distinct change in aggression-score as a result of this cascading process. The reduced occupancy of these genera in logged forest may be due to equal declines in their food resources (e.g. termites) because of changes in vegetation structure and climate82. Previous studies showing lower predatory genera abundances in logged forest8, along with competitive release following the removal of dominant ant species supports the trends seen here107. Competitive release in logged forest may also explain why we see decreases in genus richness, given dominant species have been shown to promote species richness49.The idiosyncratic relationship we observed could be due to a form of dual process where the potential cascading effects of community compositional change, through physical changes to the environment, allows for a competitive advantage through an increase in overall competitive ability or competitive release, through changes in the competitive network, or vice versa95. In primary forest, Lophomyrmex shows aggressive dominance over Acanthomyrmex but in logged the roles are reversed. This respective switch in dominance is most likely a result of them competing for the same niche space in each forest type, as they are considered functionally equivalent82 and interestingly are the same size24. However, as the environment changes, different traits may become advantageous and the competitive status is reversed. The decrease in aggression-score of Lophomyrmex and Myrmicaria could also be explained by their increase in occupancy, allowing for greater opportunity to compete and be aggressively dominated in logged forest. Notably, genera that saw few changes in their score such as Pheidole or Nylanderia may be a result of their subdominant position in the competitive hierarchy in the community allowing them to still compete for patchy resources and remain relatively high in occupancy, despite changes in the genus showing high aggression or disturbance effects108.The change in environment between forest types may further induce cascading effects, with idiosyncratic changes in aggression between genera being seen as a result of competitive disadvantages32.In conclusion, we provide a new insight into how a competitive network can change as a result of disturbance which helps us to better understand the mechanistic processes that reinforce the difference in ‘end-point’ community structure. Future studies can also look at how altered competitive processes may impact on ecosystem function given the important functional role of ants in tropical forests, such as scavenging, seed dispersal, predation and soil turnoverwww.safeproject.net; Dataset ID: 1).The data used in this study is available on Zenodo (10.5281/zenodo.1198302) and can also be accessed through the S.A.F.E. project website (Supplementary Information