In North America and Asia, extreme cold weather characterized the winter of 2017–18. At the same time, the Pacific, the Bering Sea, and the Atlantic Arctic regions experienced anomalously low sea ice extent in the early winter. The jet stream dividing cold Arctic air from warm air deviated from normal zonal patterns northward into the ice-free areas north of the Bering Strait. Large southward jet stream pathways formed over Asia and America, allowing cold air to spread into Asia and the southern areas of North America. We hypothesise that the late autumn Bering Strait sea-ice anomaly and Pacific atmospheric rivers were partially responsible for the cold winter. We used data analyses and numerical experiments to test this hypothesis. We propose a positive feedback mechanism between the sea ice anomaly and atmospheric river activity, with anomalous south winds toward the sea ice anomaly potentially leading to more warm water injected by the wind-driven current through the Bering Strait. Our findings suggest that Poleward propagation of the atmospheric rivers made upper air warm, leading to their upgliding, which further heated the overlying air, causing poleward jet meanders. As a part of this response the jet stream meandered southward over Asia and North America, resulting in cold intrusions. We speculate that the positive feedback mechanism observed during the 2017–18 winter could recur in future years when the sea-ice reduction in the Pacific Arctic interacts with enhanced atmospheric river activity. This cold winter cannot be accounted for by a single cold wave event, which typically do not last throughout the winter. The negative phase of the Arctic Oscillation (AO), which is equivalent to a weak jet stream, is a good measure for hemispheric cold weather2. In this case, the AO was persistently in its negative phase from mid-November through mid-February. A weak jet is usually accompanied by large meanders5, in the same way that a slow-flowing fluvial river meanders. Negative AO does not specify where the southward meander travels, but in this case, the southward meander was locked in Eastern Canada and East Asia. This persistent southward meander allowed cold air to spread southward. Understanding the reason for this large persistent meander, with regional focal areas, yields explanations for the extreme cold weather in 2017–18. La Niña is also known as a cause of extreme weather, but because La Niña occurs approximately every four years, and because it was weak in this particular season, La Niña6 alone does not explain the cold weather of 2017–18.The winter of 2017–18 was abnormally cold over Eastern Canada and East Asia. Likewise, both Korea and Japan also experienced record-breaking winter cold. Data from the Japanese Meteorological Agency reveal that the seasonal mean temperature in western Japan was the lowest recorded since 1985–869. It has been shown that anomalous heat flux from an ice-free ocean excites large-scale atmospheric stationary waves that travel eastward over Eurasia, causing cold weather in East Asia7. Ice reduction in the Barents Sea is also known to strengthen the downward influence of the stratosphere12, making the phase of AO negative and resulting in cold mid-latitudes. However, influence of the Barents Sea ice reduction mechanism has not been widely accepted yet. Numerical simulations need many ensemble runs in order to arrive at a statistically significant level to show the influence of the Barents Sea ice12. This is because the variability of the jet meanders owing to atmospheric internal fluctuation is much larger than that owing to surface conditions such as sea ice9. Barents Sea ice was not exceptionally low in the 2017–18 winter compared with recent years. Since Barents Sea ice has been extremely low during the last ten years, it should have been an extremely cold winter every year, which was not the case. The downward influence of the stratosphere12 was also not predominant in the 2017–18 winter, as stratospheric sudden warming, which tends to make the tropospheric mid-latitudes cold, had not occurred until late winter. Direct explanations for this severe winter thus remain unclear. In addition to the anomalous upward heat flux from an ice-free ocean, horizontal moisture flux injecting into the Arctic, such as atmospheric rivers, makes the Arctic warm17. Although both the upward and horizontal fluxes may excite large-scale atmospheric stationary waves that resultantly make mid-latitudes cold, no previous studies have demonstrated the influence of the horizontal flux upon the mid-latitudes.One other possible explanation for the cold winter of 2017–18 is the reduction in sea ice extent off the northern coast of Norway, specifically the Barents Sea ice extent has been extremely low during the last decade. This semi-permanent ice reduction tends to make Eurasia cold18 of recent decades, resulting in the cold 2017–18 winter. The present study demonstrates that the sea ice in the Pacific Arctic was a chief cause of the cold winter in mid latitudes.Here we propose a new candidate: The Arctic Ocean Pacific sector, including the Chukchi Sea and Bering Sea, which experienced the lowest sea ice coverageWe first describe the anomalous jet meander and anomalous sea-ice coverage in winter 2017–18 from the global-scale viewpoint. Next, we show that sea-ice retreat over the Pacific Arctic sector was responsible for the anomalous winter by using atmospheric numerical experiments. We show how this area modulated the overlying atmosphere as viewed from a local atmosphere-ice-ocean feedback system.The 2017–18 winter was abnormally cold over wide areas in the mid latitudes in the Northern Hemisphere, in particular in Japan, Western Europe, and Eastern Canada; whereas near the Bering Strait, the winter was historically warm Fig. . These cSea ice concentration in the Chukchi Sea was at an historical minimum in November, and closed at the end of December Fig. . Freeze-20.Over the Bering Strait warm hole, the temperature was historically highest from the surface to the upper air Fig. . The warIn order to identify the atmospheric response to the sea-ice reductions of individual areas, i.e., the warm hole in the Pacific sector of the Arctic, the Barents Sea, and other areas, atmospheric numerical experiments were performed. In order to see the difference we executed the following numerical experiments: one forced with largely ice-free boundary conditions observed in 2017–2018, and the other with sea ice corresponding to the high-ice period in 1983–1984.An experiment under ice-free conditions in the Pacific side of the Arctic successfully simulated a cold East Asia and North America in the lower troposphere Fig. . This exFigure The numerical experiments have shown that the warm hole in the Pacific sector played a role in forming a cold Asia and warm Arctic from the view point of large-scale atmospheric circulation. We focus on the area of the warm hole in order to understand how the warm hole promotes the jet meander. Figure 13. In addition, anomalous upward heat flux from the area of the warm hole to the atmosphere assisted atmospheric warming , central Siberia (reddish area) and East Asia (bluish area) seen in Fig. 5. We speculate that the wave from Europe was partially enhanced by the retreat of Barents Sea ice, as pointed out by many studies12, and that this Eurasian wave was also a necessary condition for the extreme winter. The Barents sea-ice anomaly in the winter worked on a more or less permanent basis for about ten years, with repeatedly cold winters in Eurasia. This year was very unusual; the exceptionally strong anomaly on the other side of the Arctic  may have ‘reinforced’ the effect of the ‘semi-permanent’ anomaly in the Barents region. Some resonant effects may have occurred as well. Atmospheric numerical experiments under an ice-free condition in the Chukchi area successfully simulated a cold East Asia and North America 32 was used in this study. The SV NAM, a leading mode of EOF analysis applying vertically and zonally averaged atmospheric geopotential height fields poleward of 40°N, is able to identify the overall atmospheric pressure contrast between the Arctic region and the mid-latitude region better than the well-known AO index. In addition, SV NAM is a good indicator for the strength of the polar jet stream. The SV NAM index is available at http://www.bio.mie-u.ac.jp/kankyo/shizen/lab1/AOindex.htm. Figure We used the gridded atmospheric reanalysis dataset of the Japanese 55-year Reanalysis (JRA-55), supplied by the Japanese Meteorological Agency30. Atmospheric rivers are detected by identifying contiguous regions ≥2000 km in length with IVTs ≥ 250 kg m−1 s−1 in mid-latitude regions29, and IVTs ≥ 200 kg m−1 s−1, IVTs ≥ 150 kg m−1 s−1, or IVTs ≥ 100 kg m−1 s−1 for high-latitude regions34. Figure Arrows in Fig. 35, supplied by the European Centre for Medium-Range Weather Forecasts from 1981 through 2018. The sea ice concentration shown in Fig. For sea ice data, we used ERA-Interim36. Its horizontal resolution is 1 × 1 degrees with 50 vertical layers. Time resolution for this product is every ten days. The definition of the anomaly is the deviation from long-term mean values from 1981 through 2010. Figure The ocean reanalysis product used in the present report is the Multivariate Ocean Variational Estimation system/Meteorological Research Institute Community Ocean Model (MOVE/MRI-G2)37 for this experiment, and the simulation area covers most of the area to the North of 10°N. The simulation domain is gridded into 150 × 150 points, with a horizontal grid spacing of 100 km. There are thirty atmospheric layers vertically, with the top of atmosphere set to 10 hPa. There are five ensemble members for each group of sensitivity tests; the first ensemble member starts on 1 August 2017, and ends on 30 April 2018. The other four members start respectively on 30 July, 31 Jul, 2 August, and 3 August, and all end on the same date as the first member.We employed Weather Research and Forecasting (WRF) version 3.9.138 data is employed as the forcing, and provide atmospheric background as lateral boundary conditions and surface cover, including SST/sea ice conditions for surface boundary condition. Three zones of interest are identified, for which the original sea ice cover (2017–2018) is replaced with sea ice values from 1983–1984 for sensitivity simulations for each ensemble member. Zone 1 is delimited by 135°E and 135°W longitude, containing the oceanic region of the East Siberia Sea, the Beaufort Sea, and the Chukchi Sea. Zone 2 is delimited by 45°W and 90°E, containing the North Atlantic Ocean, the Barents Sea, and the Kara Sea. The third zone has the boundaries of 135°W and 45°W in longitude, which basically covers the oceanic area in the North of Canada, as well as to the West of Greenland.NCEP/NCAR reanalysis (NNRP)All runs included in the analysis are forced by the 2017–2018 atmospheric boundary conditions (from NNRP). Low sea ice runs are forced by 2017–2018 sea ice conditions, and high sea ice runs are forced by the 1983–1984 sea ice conditions. The sea ice conditions are also from NNRP. The anomalies are calculated by subtracting variables  of reference high sea ice cases from low sea ice cases. The sea ice conditions are imported into WRF as 6-hourly sea ice extent at the surface boundary. Thus the sea ice extent changes through time rather than being fixed.SUPPLEMENTARY INFORMATION


Despite many studies on Adélie penguin breeding phenology, understanding the drivers of clutch initiation dates  is limited or lacks consensus. Here, we investigated Adélie penguin CIDs over 25 years (1991–2016) on two neighboring islands, Torgersen and Humble (<1 km apart), in a rapidly warming region near Palmer Station, Antarctica. We found that sea ice was the primary large‐scale driver of CIDs and precipitation was a secondary small‐scale driver that fine‐tunes CID to island‐specific nesting habitat geomorphology. In general, CIDs were earlier (later) when the spring sea ice retreat was earlier (later) and when the preceding annual ice season was shorter (longer). Island‐specific effects related to precipitation and island geomorphology caused greater snow accumulation and delayed CIDs by ~2 days on Torgersen compared to Humble Island. When CIDs on the islands were similar, conditions were mild with less snow across breeding sites. At Torgersen Island, the negative relationship between CID and breeding success highlights detrimental effects of delayed breeding and/or snow on penguin fitness. Past phenological studies reported a relationship between air temperature and CID, assumed to be related to precipitation, but we found air temperature was more highly correlated to sea ice, revealing a misinterpretation of temperature effects. Finally, contrasting trends in CIDs based on temporal shifts in regional sea ice patterns revealed trends toward earlier CIDs (4–6 day advance) from 1979 to 2009 as the annual ice season shortened, and later CIDs (7–10 day delay) from 2010 to 2016 as the annual ice season lengthened. Adélie penguins tracked environmental conditions with flexible breeding phenology, but their life history remains vulnerable to subpolar weather conditions that can delay CIDs and decrease breeding success, especially on landscapes where geomorphology facilitates snow accumulation. The abiPygoscelis adeliae) along the Western Antarctic Peninsula (WAP) inhabit one of the most rapidly warming regions on Earth  of Adélie penguin breeding phenology data to investigate and reveal the environmental drivers of clutch initiation date (CID), and the subsequent consequences to breeding success near Palmer Station, Anvers Island, WAP. We investigated the drivers of CID on two neighboring islands that are <1 km apart but differ significantly in landscape attributes that may affect breeding habitat quality. We hypothesized that ambiguity in previous findings could be related to the influence of island‐specific geomorphology on nest site microclimate  and Humble  islands near Palmer Station, Antarctica Figure . The TORAdélie penguins return annually to these rocky islands to begin nesting in mid‐October, with egg laying beginning in mid‐November. Adélie penguins typically lay two eggs Ainley, . In the Weather and sea ice conditions often prevented small boats from accessing the study sites. For this reason, lay and hatch dates were divided into two categories, true and estimated. For true dates, weather and ice did not impede daily checks, hence the exact timing of all nesting events were confirmed. However, if weather and ice induced gaps in daily checks, then lay and hatch dates at the next possible nest check were recorded as estimated because the exact dates were unknown. For all records with true dates, we calculated the mean and standard deviation in the lay date of egg 1 and egg 2, the days between these lay dates, the hatch date of chick 1 and chick 2, the days between these hatch dates, and the days between lay and hatch dates (incubation period). We determined whether there were significant differences between phenology at HUM and TOR using a linear mixed model (LMM) fit by maximum likelihood using lmer in the lme4 and lmerTest packages . For this linear regression between lay and hatch dates, 91% of the predicted lay dates were within ±2.5 days of the true lay dates, 83% were within ±2 days and 70% were within ±1.5 days. An error range of ~2 days may seem considerable but it should be noted that a 1.5‐day interval was within our measurement resolution . Therefore, we used this linear regression model to adjust estimated lay dates and dates where the true/estimated identifier was not recorded. The latter was especially true for dates prior to 1995, or before protocols were refined to accommodate the environmental conditions that might affect island access and thus how date‐specific data were interpreted. Thus, prior to 1995, we used the hatch dates to check the lay dates, and if the predicted lay date was within ±2.5 days of the recorded lay date, the record was retained (95% of the data) and all others were removed from further analysis. Similarly, after 1995, if both lay and hatch dates were estimated, we only retained records if the predicted and recorded lay dates were within ±2.5 days (57% of the data).Because Adélie penguins have an incubation period of approximately 30–40 days Ainley, , there it test with the Benjamini–Hochberg false discovery rate used as a correction for multiple testing  for each year to test for differences between island means using all CID records within that year. Additionally, for each island, we calculated the anomaly in the mean CIDs by subtracting the time series CID mean from each season's mean CID.We computed mean CIDs for each island for each year. We removed 2013 (for HUM and TOR) and 2005 (for HUM) from further analysis due to low sample sizes resulting from unusually poor weather or sea ice conditions. For both years, <35% of the data had a true hatch or lay date, and the number of trues was <5. For all other years, we compared adjusted and unadjusted mean CIDs by island using Pearson's correlation to determine the strength of the correlation. We tested whether the CIDs differed between sites and years using a LMM as described above with CID as the response variable, site as fixed effect and year as a random effect. Further, to identify which years had significantly different CIDs between sites, we used a separate Welch two sample Adélie penguin chick fledging mass was measured at HUM as chicks gathered on beaches . We also calculated the number of days with precipitation (rain or snow >0 cm) in October to compare with observations at nearby Faraday/Vernadsky Station (discussed below).We aimed to understand if CID was related to environmental drivers. Adélie penguins generally return to their colonies in October for courtship and nest building prior to laying eggs in November. Therefore, conditions in the late austral winter and early spring may influence CIDs. Other studies have shown that CID is related to October air temperature, hypothesized to be indicative of snow on the ground , because these may influence access to the colony, access to open water from the colony, be related to wintering locations, parental condition, and/or migration distance/timing of arrival. Sea ice retreat day within 200 km of Anvers Island . Nino3.4 reflects warm El Niño (high Nino3.4) and cold La Niña (low Nino3.4) conditions in the equatorial Pacific .Climate indices may be related to CID through teleconnections due to both sea ice and weather being linked to the El Niño Southern Oscillation (ENSO) Renwick, . We obtaWhen the breeding/phenology monitoring sites on HUM and TOR were established in late October or early November from 1998 to 2016, snow depth was usually measured at the colony edge near the groups of monitored nests. This measurement was taken before the mean CID and was an indication of snow depth at the sites before clutch initiation. We used these data to investigate the difference in snow depth between the two locations, which was likely related to the influence of island‐specific geomorphology on snow accumulation Figure . We calchttps://legacy.bas.ac.uk/cgi-bin/metdb-form-1.pl?table_prefix=U_WMC,U_MET&acct=cmet). Precipitation information was recorded as part of routine synoptic observations under “Present weather,” which refers to weather at the time of observation. Observations every 3 hr were recorded as numerical codes  acquired by the British Antarctic Survey . A separate linear regression was run for each environmental variable.We hypothesized that in years without significant differences in mean CIDs  identified the models that accounted for the most variation, selected the model with the best balance between bias and precision, and avoided over fitting  mean annual CID at TOR, (b) mean annual CID at HUM, and (c) an average of mean CIDs at HUM and TOR as response variables, with a combination of predictor variables. We report all models with ΔAICc < 10. For each GAM, the effect of each environmental predictor was plotted to visually inspect the functional form to confirm the same relationship was seen within and across the three model suites. This general approach has been used in many studies to look at the environmental drivers of seabird demographics  using the “mgcv” package in R. The smoothness parameter (s) was estimated using generalized cross‐validation Wood, . GAMs arAs studies often report no trends in seabird phenology over short time series  and November 15 (day 46) for HUM and TOR  and had the same variability over time . The overall mean lay date for all adjusted mean CIDs was November 14 and 16 for HUM and TOR. Anomalies across years in mean CIDs ranged from approximately ±5.6 and ±7.6 days for HUM and TOR . While there was overlap in the values of most environmental parameters between significant and nonsignificant years , and a significant negative relationship with ice retreat day , November ice area , and El Niño indices . Interestingly, there was no significant relationship between the difference in mean CID and air temperature .There were 19 years where CIDs were significantly different between islands Figure a and onls Figure b–d, thers Figure a. SimilaR = .78, p = .0006), but there were years of noticeably more snow on TOR . In the five years when the mean CID was not significantly different between islands  performed well and explained most of the variance for HUM (R2 = ~.6), TOR (R2 = ~.77) and the average of HUM and TOR CIDs (R2 = ~.7)  and sea ice conditions (R = .6–.7); air temperature was generally negatively related to sea ice variables (R = .5–.8). In contrast, snow depth was not strongly related to any environmental variables  than during other years at TOR but not significantly different at HUM (p = .7). At both islands, however, breeding success was relatively high (>1.2 chicks/pair) in those five years , model B , and CID observations . From 2010 to 2015/16, a positive trend was present in expected CID over time, which was significant or marginally significant for model A , model B , and model 2 . The slope describing the positive trend for CID observations from 2010 to 2016 was 0.99 ± 0.67 days/year (p = .2). While the modeled and observed CID did not always have statistically significant trends, the trend lines across all time series were very similar and in the same direction  correlate with spring temperatures  and variable environments  with the greatest snow depths had some of the lowest breeding success values and latest CIDs; this pattern was also noted at the Copacabana colony , we suggest that phenological data should be matched along the same time scales to long‐term climate data to determine whether a trend can be expected and detected. It is also important to recognize the impact of landscape geomorphology at a study site to understand how weather  may differentiate impacts on colonies located in close or distant proximity. This is especially relevant when looking at phenology across latitudes, where a delay in phenology at southerly latitudes could be amplified or reduced by landscape effects (e.g., Lynch et al., The authors declare no competing interests.WRF designed the data collection methodology. WRF and DPF collected the data. MAC and WRF developed the research questions. MAC analyzed the data, and MAC wrote the initial manuscript with contributions from WRF. SS analyzed the sea ice data. All authors contributed to data interpretation, edited, and reviewed the manuscript. Click here for additional data file.


The clinical benefit of allergen-specific immunotherapy (AIT) involves induction of blocking antibodies. It is not clear if these antibodies function via steric hindrance alone or a combination of levels, avidities, and epitope specificities, and clinical outcome cannot be predicted. We aim to in-depth characterize serum antibody profiles during birch pollen AIT, investigate therapy-induced antibodies for their capacity to block IgE binding to Bet v 1 and correlate data with clinical outcomes.Immune responses of five birch pollen allergic patients were monitored during the first year of AIT by nasal provocation tests (NPTs), ImmunoCAP, immunoblots, direct and avidity enzyme-linked immunosorbent assays, mediator release assays, facilitated antigen binding (FAB) assays, and inhibition mediator release assays.There was no correlation between NPT results and therapy-induced changes in levels , avidities, or mediator release potency of Bet v 1-specific antibodies. In FAB assays, blocking antibodies initiated upon AIT were shown to prevent formation of Bet v 1-IgE complexes of an indicator serum pool and significantly correlated with clinical readout. Inhibition mediator release assays using patient-specific IgE for passive sensitization revealed therapy-induced blocking capacities with very good correlation to NPT results. Notably, this assay was the only one to detect a non-responder during treatment in this pilot study.Clinical outcome of AIT depends on induction of blocking antibodies able to prevent the patient’s own IgE from allergen binding. Monitoring of clinical efficacy seems to be best achieved using the inhibition mediator release assay, as development of relevant blocking antibodies can be verified in a patient-tailored manner.The online version of this article (10.1186/s13601-018-0226-7) contains supplementary material, which is available to authorized users. The enormous global increase in allergic diseases over the last few decades has become a major public health concern . Having At the B cell level, serum IgE levels are initially boosted by AIT but then decline during treatment. However, the decrease occurs too long after the start of treatment to be associated with clinical efficacy. Induction of high levels of serum IgG  during AIT does not correlate with IgE reduction or treatment efficacy , 11. SomBetula verrucosa contains a complex mixture of proteins, more than 95% of birch pollen allergic patients are sensitized to the major allergen Bet v 1 and 60% demonstrate exclusive reactivity [Recent studies indicate that not only serum antibody subclass levels but rather their functional roles are important for successful therapy. The ability of IgG4 to block IgE-allergen binding was explained by the development of similar epitope specificities , 23. Antactivity . The potIn this pilot study, we extensively characterized Bet v 1 serum antibody responses during the early course of AIT in five birch pollen allergic patients. Antibody subclasses were analysed regarding levels, avidity, epitope specificities, and blocking capacities and correlated with rhino-conjunctivitis total symptom scores (RTSS) throughout the study. By integrating quantity and quality, as well as AIT-induced alterations of antibody-allergen interactions, we aimed to explain the therapy-related antibody blocking concept in more detail, and to monitor the allergic state of the patients throughout the first year of treatment.Birch pollen-allergic patients qualifying for AIT in the routine clinical setting were selected according to case history, positive in vivo as well as in vitro diagnosis (n = 5) Table . InclusiSubcutaneous immunotherapy was performed using Alutard SQ Birch  with 11–13 injections at intervals of 1–2 weeks during the up-dosing phase starting with 100 SQ according to the manufacturer’s protocol  reconstituted in 5 ml AllergoPharma solvent. If negative to saline challenge, NPT was performed with increasing concentrations of birch pollen extract  at 15-min intervals . Sneezing, rhinorrhea, nasal pruritus, nasal obstruction and congestion, as well as ocular symptoms were recorded and a RTSS ranging from 0 to 18 was established, where each symptom was assessed on a four-point scale  according to published protocols .E. coli BL21 Star (DE3) using the pET28b vector system and purified from the soluble fraction by standard chromatographic procedures. The endotoxin level determined by limulus amoebocyte lysate cell assay was < 0.3 ng/ml.Aqueous pollen extract was prepared by rapid agitation of 2 mg birch pollen  dissolved in 10 ml distilled water for 4 h at room temperature. After centrifugation and 0.45 µm filtration, the protein concentration was measured by Bradford assay  and Bet v 1 concentration determined as 0.76 mg/ml by a sandwich ELISA. Production and characterization of recombinant Bet v 1.0101 was performed according to published methods . In shor3 and cut into stripes which were incubated with 1:10 diluted sera overnight at 4 °C while shaking. Bound allergen-specific IgE, IgG1, IgG4, IgA, as well as IgM was detected using AP-conjugated monoclonal anti-human IgE , IgG1, IgG4, IgA or IgM antibodies , respectively. Furthermore, a staining solution consisting of 10 ml AP buffer , 30 µl BCIP (stock: 50 mg/ml in dimethylformamide) and 30 µl NBT  was used. After staining, membranes were washed with distilled water and air-dried.Birch pollen extracts were separated by preparative 15% polyacrylamide gels and blotted onto nitrocellulose membranes . Blots were blocked for 1 h with a buffer containing 25 mM Tris/Cl, pH 7.5, 150 mM NaCl, 0.5% (v/v) Tween, 0.5% (w/v) BSA, 0.05% (w/v) NaN405/492 of 0.5 and 1 where the titration curves were not in the plateau; 1:10 for IgE, 1:40 for IgG4 and IgG1, 1:160 for IgA and IgM) for detection of the reactivity of antibody subclasses before and after heat inactivation overnight at 4 °C. Bound allergen-specific immunoglobulins were detected with alkaline phosphatase (AP)-conjugated monoclonal anti-human IgE , IgG1, IgG4, IgA or IgM antibodies , respectively, after incubation for 1 h at 37 °C and for 1 h at 4 °C. For colorimetric detection 10 mM PNPP  was used as substrate and OD measurements were performed on a Tecan Sunrise  plate reader at 405/492 nm. Measurements were performed as duplicates and results are shown as mean values. For calculation of endpoint titer, the LOD (Limit of Detection) was used as cutoff value which is calculated as three times the standard deviation.For direct ELISA experiments, Maxisorp plates  were coated with 100 ng Bet v 1/well in PBS overnight at 4 °C. After washing with TBS, pH 7.4, 0.05% (v/v) Tween, plates were blocked with TBS, pH 7.4, 0.05% (v/v) Tween, 0.5% (w/v) BSA for 1 h at room temperature. They were either incubated with serial dilutions of sera  for endpoint titer determination or with just one dilution of patients’ sera . After an incubation step overnight at 4 °C, 50 µl/well sodium thiocyanate (NaSCN) (Applichem) solution was added to the wells in concentrations ranging from 0 M to 3 M NaSCN  and plates left at room temperature for 15 min. Bound allergen-specific IgE, IgG1, IgG4, IgA or IgM was detected with AP-conjugated monoclonal antibodies and a coloritmetric substrate as indicated above. Avidity indices were calculated from the NaSCN-concentration at which 50% of the bound antibodies were detached. Measurements were performed as duplicates and mean values are given.For avidity ELISA experiments, Bet v 1 was coated on Maxisorp plates and washed as indicated above. 50 µl diluted sera were pipetted in duplicates into 12 wells each (same amount of serum in each well). The serum dilution for each serum was chosen between an OD5 EBV transformed B-cells (in 5 µl) were added for 1 h at 4 °C. IgE complexes bound to the low affinity IgE receptor FcεRII on B-cells were stained with FITC-labelled affinity purified goat-anti human IgE antibody  and measured on a FACS Canto II flow cytometer . The blocking capacity of AIT-induced antibodies was expressed as 100% minus percentage of cells carrying IgE-allergen complexes.The capacity of birch pollen AIT-induced antibodies to block IgE antibody binding to Bet v 1 was monitored using a FAB assay which was performed according to slightly modified published methods , 33. In 2 [Mediator release assays were performed using RBL-2H3 rat basophilic leukemia cells transfected with the alpha chain of the human IgE receptor FcεRI, which were passively sensitized with the allergic patients’ sera. Sera were diluted 1:20 in tissue culture medium and incubated overnight at 37 °C and 7% CO2 . After sInhibition RBL assays were performed according to published methods  with minFor inhibition RBL assays used to monitor the AIT-induced blocking antibody responses on a patient-by patient basis, rat basophilic leukemia cells were passively sensitized with IgE from T0 serum samples at a final dilution of 1:20 in tissue culture medium overnight and the assay was performed as described above. Supernatants were analyzed for remaining β-hexosaminidase release. Results are expressed as percentage of inhibition in relation to the total β-hexosaminidase release obtained by addition of 10% Triton X-100. For statistical analysis, curve-representative inhibition values at inhibition serum dilutions of 1:10 were chosen.P values < .05 were considered statistically significant. Pearson’s correlation of antibody and clinical data was calculated and displayed by regression lines. Pearson r (rho) values of ≥ 0.5 or ≤ − 0.5 were considered statistically significant.GraphPad Prism software 5 was used for statistical analysis. Friedman test with Dunns post test was used for comparison of the three AIT time points. In this pilot study, the antibody response of five birch pollen allergic patients  undergoing AIT was monitored (Fig. To monitor therapy-related changes of antibody profiles towards whole birch pollen extract, we performed immunoblot experiments Fig. . PatientSince substantial therapy-related changes towards Bet v 1 were revealed by immunoblot, subsequent experiments focused on this clinically relevant allergen. First, we determined antibody titer by ELISA using individual sera Fig. . Four ouWe performed mediator release assays to determine the allergenic activity of patients’ sera triggered by IgE receptor cross-linking and subsequent β-hexosaminidase release (Additional file We used ELISA to measure avidity indices of Bet v 1-specific antibody subclasses and calculated these as the NaSCN-concentration at which 50% of the bound antibodies were eluted off (Fig. Next, we performed FAB assays to study the capacity of AIT-induced antibodies to prevent Bet v 1-IgE complex formation in an indicator serum pool containing high amounts of IgE Fig. a. WhereaInhibition mediator release assays were performed investigating the combined effect of antibody avidity, epitope specificity, and considering the subsequent functional consequence in terms of mediator release. Thereby, RBL cells were passively sensitized with IgE from T0 serum samples Fig. b or indiWhereas inhibition at the beginning of therapy was low, it was significantly higher at T1 for all patients and remained at similar levels for four out of five patients Fig. . For P3,In this study, we fully characterized serum antibody profiles during birch pollen AIT and monitored antibody blocking and immunotherapy-related changes. We thereby intended to uncover parameters influencing blocking capacity to evaluate AIT progress. NPTs were performed to obtain measurable parameters for therapy outcome. Clinical results after 1 year AIT demonstrated beneficial treatment for four subjects, whereas one patient showed a worsening in clinical parameters. Our study clearly focused on monitoring antibody responses during the first year of therapy rather than testing the clinical efficacy of a birch pollen AIT product. For this and ethical reasons which would not justify the application of a placebo, this preliminary antibody monitoring study was conducted within the setting of routine birch pollen AIT in the clinics.To obtain an initial overview of antibody subclass reactivity towards birch pollen extract, we performed immunoblot assays. Changes in profiles during AIT mostly affected IgE and IgG reactivity to Bet v 1. De novo IgE to Bet v 2 and potentially Bet v 6, Bet v 4, Bet v 7, and Bet v 3 was induced only in P4. After 1 year, novel IgG4 antibodies against Bet v 1 and other proteins were detected in all patients. IgA and IgM did not present relevant changes in antibody reactivity, but control sera generally showed a more complex profile towards those antibody subclasses.To track Bet v 1-related changes of antibody subclass levels, we performed ELISA experiments. We detected an initial increase in Bet v 1-specific IgE accompanied by an increase in IgG4, which was however lacking in P3. This in turn resulted in an unaltered IgE/IgG4 ratio, while all other patients presented a significantly decreased ratio during AIT. Analogous to previous studies, none of the antibody subclass levels correlated with treatment outcome , 35, 36.To additionally address epitope specificities of AIT-induced antibodies, FAB and inhibition mediator release assays were performed. FAB assays revealed that all patients developed blocking antibodies against Bet v 1 during AIT. P2 and P5 had pre-existing Bet v 1-specific IgG but those were only partially able to block IgE-allergen binding. The blocking effect developed during AIT suggests a change in epitope recognition . SimilarBased on a modified protocol, we performed inhibition mediator release assays to monitor the AIT-induced blocking antibody responses towards the patients’ own IgE epitope specificities and to measure the functional consequence of IgE-allergen binding for mediator release. We showed that low mediator release inhibition before therapy was due to no or low IgG titers. Inhibition significantly increased during therapy revealing that AIT-induced IgG gained the ability to block IgE-specific epitopes , 38, 39.The use of patient-tailored inhibition mediator release assays has so far been reported in two studies , 39; howAdditional file 1. Table of patients’ birch pollen allergen antibody titer and total IgE determined by ImmunoCAP.Additional file 2. Table of Bet v 1-specific serum antibody subclass titer.Additional file 3. Correlation of ImmunoCAP values with antibody titer, RTSS and mediator release.Additional file 4. Mediator release curves of RBL-2H3 cells during birch pollen AIT and correlation with antibody titer.Additional file 5. Table of Bet v 1-specific serum antibody subclass avidity indices.Additional file 6. Correlation of Bet v 1-specific serum antibody titer with percent inhibition of IgE-Bet v 1 complex formation measured by FAB assay.Additional file 7. Reactivity of serum antibody subclasses before and after heat inactivation.Additional file 8. Inhibition mediator release curves and correlation with antibody titer using cells passively sensitized with T0 sera.Additional file 9. Inhibition mediator release curves and correlation with antibody titer using cells passively sensitized with indicator serum pool.


Mining is the extraction of materials of economic importance from the earth. It is an important source of employment and economic development. However, mining activities can impact on biodiversity, the environment, and human health, mainly through the emission of large quantities of heavy metals. Our objective was to investigate the impacts of gold mining on the Balochistan gerbil, a rodent that inhabits the natural environments of Saudi Arabia. Our results demonstrate the accumulation of heavy metals in the soil, in Arabian boxthorn plants, and in the different tissues of the gerbils. In addition, the gerbils exhibited liver, kidney, and lung injury associated with decreased antioxidants. These data may be of public interest and may call attention to the evaluation of the impacts of gold mining on the environment and nearby communities.Gerbillus nanus, in relation to organ dysfunction and redox imbalance. Soil samples, Lycium shawii, and G. nanus were collected from a site near a mining plant, and a control site. Soil and L. shawii samples from the mining site showed significantly higher cadmium (Cd), copper (Cu), mercury (Hg), arsenic (As), zinc (Zn), lead (Pb), and vanadium (V) levels. Hepatic, renal, and pulmonary Cd, Pb, Hg, Zn, Cu, Fe, As, and V concentrations were significantly higher in G. nanus from the mining site. Markers of liver and kidney function were elevated in serum, and several histological manifestations were observed in the liver, kidney, and lung of G. nanus from the mining site. Malondialdehyde and nitric oxide levels increased, and glutathione and antioxidant enzymes decreased in the liver and kidney of G. nanus. In conclusion, mining practices trigger tissue damage and oxidative stress in G. nanus that live close to the mining site. These findings can represent a scientific basis for evaluating the environmental and health impacts of mining on nearby communities.Mining can impact the environment, biodiversity, and human health through direct and indirect practices. This study investigated the effects of gold mining on  Mining refers to the extraction of geological materials such as minerals, coal, limestone, and other materials of economic interest from the earth. Mining activities include both small- and large-scale activities, and have a significant contribution to economic growth and development. However, mining activities can impact the environmental and social systems, living standards, health, and traditional practices of nearby communities ,2,3. EroThe widespread contamination of the environment with heavy metals (HMs) is one of the main consequences of mining . Owing tGerbillus nanus) in Riyadh (Saudi Arabia). G. nanus belongs to the murid subfamily Gerbillinae [Given the hazardous impact of mining, and the resulting HM waste on the environment, society, and health, we investigated the effect of mining on the Balochistan gerbil . This city is one of the large governorates in Saudi Arabia, and hence selected for the study.Site 1 (Mining): Located 500 m away from the gold mine, between E45° 05′ and N23° 47′.Site 2 (Control): Located 20,000 m away from the gold mine, between E45° 06′ and N23° 36′.The investigated gold mine site is located southwest of Al-Quway’iyah city. The samples were collected from two sites, as follows :Site 1 (n = 8) and Lycium shawii (Arabian boxthorn) (n = 8) were collected from both sites for the determination of HMs. Eight G. nanus were collected from each site with the help of specific rodent traps and transferred to the laboratory. The animals were sacrificed under anesthesia, and blood and tissue samples were collected for analysis. The protocol and procedures were approved by the institutional animal ethics committee of King Saud University (No. KSU-20165).Samples of the soil at 20 cm depth .The concentrations of HMs were determined in the soil, Serum alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), creatinine, urea, and uric acid were measured using Biomerieux  reagent kits, following the manufacturer’s instructions.Samples from the liver and kidney were homogenized in phosphate buffered saline (10% w/v) and centrifuged, and the supernatant was used for the assays. Malondialdehyde (MDA) , nitric G. nanus were fixed with 10% neutral buffered formalin and processed for paraffin embedding. 5 μm sections were cut, stained with hematoxylin and eosin (H&E), and examined using a light microscope.Samples from the kidneys, liver, and lungs of t-test, and a p value <0.05 was considered significant.Data were analyzed using GraphPad Prism 7  and expressed as means ± standard error of means (SEM). All statistical comparisons were performed using p < 0.05) at the mining site, when compared with the control site  when compared with the corresponding control site animals  in G. nanus from the mining site , NO, and cellular antioxidants in the liver and kidney. G. nanus from the mining site showed a remarkable increase of hepatic (p < 0.001) and renal (p < 0.01) LPO (p < 0.01) in G. nanus from the mining site  LPO A. Similaing site B. When cG. nanus, with an emphasis on HM accumulation and redox imbalance. To evaluate the emission and distribution of HMs at the mining site, we determined the concentrations of Pb, V, Cu, As, Zn, Cd, Fe, and Hg in soil, L. shawii samples, and different organs of G. nanus. Pb, V, Cu, As, Cd, and Hg were increased in both the collected samples of soil and L. shawii. Fe and Zn concentrations were not significantly increased in soil and L. shawii, respectively. These findings show the effect of mining on the soil profile, as well as on plants growing in the areas nearby.This study evaluated the impact of mining activities in Al-Quway’iyah, Riyadh (Saudi Arabia) on G. nanus. Besides their environmental impact, these HMs have proven to be a major threat to the body and its proper functioning [G. nanus were observed. These hazardous effects are directly connected to the accumulation of HMs in different tissues of G. nanus.Despite their negative impact on the ecosystem and adverse health effects, exposure to HMs continues to increase in many regions . Here, Pctioning . AccordiPb contamination [G. nanus from the mining site. The accumulation of Pb in the liver and kidney elevated transaminases, ALP, and renal function markers, along with the histopathological changes indicated by the injury of liver and kidney tissues. In this context, in vivo studies have demonstrated both hepato- and nephrotoxicity in rodents exposed to low concentrations of Pb [G. nanus, demonstrating an oxidative stress status. Furthermore, Pb concentration was increased in the lungs of G. nanus, which showed dilation of alveoli, infiltration of inflammatory cells, and congestions. The relationship between lung injury and Pb accumulation was supported by the findings of Li et al., who demonstrated increased Pb concentration in the lungs of rats following exposure to atmospheric fine particulate matter [Pb, Cd, As, and Hg were demonstrated to be common HM pollutants produced through various human activities, including mining, and are all hazardous to human health. Pb is a highly toxic HM whose widespread use has resulted in health problems as well as environmental contamination. It has been estimated that 540,000 deaths per year, particularly in developing countries, occur due to mination  and thatmination . The mosmination , and thins of Pb ,33,34. Tns of Pb . It can ns of Pb . In addins of Pb . Accordie matter .L. shawii samples from the mining site. In addition, Cd concentrations were increased in different tissues of G. nanus, and its accumulation was associated with oxidative stress, hepato-/nephrotoxicity, and lung injury. Although the exact mechanisms of Cd toxicity have not been fully elucidated, the role of oxidative stress has been well-acknowledged. Cd produces hydrogen peroxide, which acts as a source of free radicals generated via Fenton reaction [G. nanus from the mining site, and was a result of the binding of Cd with the thiol groups of these enzymes [G. nanus showed lung injury associated with elevated Cd concentrations. The potential of Cd to provoke pulmonary toxicity has been supported by studies reporting bronchial and pulmonary irritation, transient bronchial inflammation [Cd is a highly toxic, nonessential HM and a serious environmental pollutant. When released into the environment, Cd can remain for several decades in the soil and sediment because of its lack of degradability ,40. It hreaction . Its toxreaction ,44. Uponreaction . Within reaction . Cd bindreaction . The act enzymes . In addi enzymes . The obs enzymes . Furtherammation , diminisammation , and priammation  followinL. shawii, and different tissues of G. nanus collected from the mining site. As is extensively available in different forms and possesses toxic and carcinogenic effects [G. nanus has a role in the observed oxidative stress and hepato-/nephrotoxicity. Recent reports have shown As-induced hepatic, renal, and pulmonary manifestations in experimental animals [Mining is one of the major sources of As and Hg pollution. Accordingly, As and Hg were found in high concentrations in the soil,  effects . The tox effects . The tox effects . Therefo animals ,56,57.G. nanus contributes, at least in part, to liver and kidney injury and redox imbalance.Hg is a well-known HM pollutant, and its toxicity is commonly responsible for acute HM poisoning. Although neurotoxicity is the most common effect of Hg and methylmercury, which induces LPO and cell death , it can L. shawii, and different tissues of G. nanus from the mining site. V is an environmental pollutant that possesses hazardous effects, and the inhalation of vanadium pentoxide dust has caused occupational toxicity [G. nanus that live close to the mining site.V, Cu, Zn, and Fe were the other HMs shown to accumulate in the soil, toxicity . Liver itoxicity , and inhtoxicity ,64. Cu etoxicity . Zn is atoxicity . Iron istoxicity , as welltoxicity  and nephtoxicity . TherefoL. shawii from the mining site, which demonstrates the negative environmental impact of mining. G. nanus living at the mining site exhibit hepato- and nephrotoxicity, and lung manifestations. The deleterious effects of mining activities on G. nanus were associated with oxidative stress and the depletion of antioxidants. These results demonstrate the environmental and health impacts of mining and can provide a scientific basis for evaluating the effects of mining on nearby communities.These findings highlight the hazardous effects of mining activities on soil, plants, and animals. HM concentrations were higher in the soil and


Dehalococcoides as most predominated OHRB, and Dehalogenimonas and Geobacter as other known OHRB. In sediment-free enrichments obtained from the EA and EB cultures, dechlorination of 1,2-DCA was inhibited in the presence of the same concentrations of either PCE, vinyl chloride (VC), or 1,2-DCP; however, concurrent dechlorination of dual chlorinated compounds was achieved. In contrast, 1,2-DCA dechlorination completely ceased in the presence of cis-dichloroethene (cDCE) and only occurred after cDCE was fully dechlorinated. In turn, 1,2-DCA did not affect dechlorination of PCE, cDCE, VC, and 1,2-DCP. In sediment-free enrichments obtained from the EA culture, Dehalogenimonas 16S rRNA gene copy numbers decreased 1–3 orders of magnitude likely due to an inhibitory effect of chloroethenes. Dechlorination with and without competitive inhibition fit Michaelis-Menten kinetics and confirmed the inhibitory effect of chloroethenes and 1,2-DCP on 1,2-DCA dechlorination. This study reinforces that the type of chlorinated substrate drives the selection of specific OHRB, and indicates that removal of chloroethenes and in particular cDCE might be necessary before effective removal of 1,2-DCA at sites contaminated with mixed chlorinated solvents.1,2-Dichloroethane  is one of the most abundant manmade chlorinated organic contaminants in the world. Reductive dechlorination of 1,2-DCA by organohalide-respiring bacteria (OHRB) can be impacted by other chlorinated contaminants such as chloroethenes and chloropropanes that can co-exist with 1,2-DCA at contaminated sites. The aim of this study was to evaluate the effect of chloroethenes and 1,2-dichloropropane  on 1,2-DCA dechlorination using sediment cultures enriched with 1,2-DCA as the sole chlorinated compound (EA culture) or with 1,2-DCA and tetrachloroethene (PCE) (EB culture), and to model dechlorination kinetics. Both cultures contained The online version of this article (10.1007/s00253-019-09985-8) contains supplementary material, which is available to authorized users. Chloroflexi , Firmicutes , and Proteobacteria   reductive dehalogenase gene (vcrA)-containing Dehalococcoides to trichloroethene (TCE) reductive dehalogenase gene (tceA)-containing Dehalococcoides, leading to diminished VC transforming ability , and efficient 1,2-DCA dechlorination occurred only when cDCE was completely dechlorinated to VC , cDCE, VC, or 1,2-DCP), the impact of co-contaminants on OHRB was investigated by quantifying 16S ribosomal RNA (rRNA) genes of known OHRB. The dechlorination reactions were approximated with Michaelis-Menten kinetics taking into account competitive inhibition. Parameter estimation was performed using AMALGAM (Vrugt and Robinson dl-lactate solution (Sigma-Aldrich). Other organic and inorganic chemicals were of analytical grade and were used without further purification.1,2-DCA, chloroethenes, 1,2-DCP, ethene, and propene were purchased from Sigma-Aldrich, and were used directly in the following experiments. Lactate stock solution (1 M) was prepared from 60% sodium 2S·9H2O (0.48 g/L) were added as redox indicator and reducing reagent, respectively. The headspace of the bottles was exchanged with N2 and CO2 . Lactate (3 mM) was used as the carbon source and electron donor. The electron acceptors for the sediment cultures were PCE  and PCE plus 1,2-DCA . The bottles were sealed with Teflon lined butyl rubber stoppers and aluminum crimp caps  and incubated statically in the dark at 20 °C. The EA and EB sediment cultures were spiked 21 times with their respective chlorinated electron acceptors during enrichment. After dechlorination of each spike of the chlorinated substrates to ethene, the headspace of the cultures was flushed with N2 and CO2 (80:20%) for three times (3 min for each run and 10 min rest in between each flushing cycle) before re-amendment of the respective chlorinated substrate(s). In the last three spikes, the concentration of each chlorinated substrate(s) was increased stepwise from 10 μmol/bottle to 25 and 40 μmol/bottle. To avoid toxicity of the chlorinated compounds in the following experiments, each single chlorinated substrate was added at 25 μmol/bottle unless otherwise stated.Surface sediment samples (down to 15 cm below surface) were collected from a wetland in Estarreja, Portugal. This site has a long history of contamination with agrochemical and fine chemistry effluents  and single or double chlorinated substrates, i.e., 1,2-DCA either alone or with PCE, cDCE, or VC Fig. . Each trThe dechlorination pattern of the last (third) spike of chlorinated substrates(s) .After dechlorination of each spike of the chlorinated compounds during the last three spikes  in the EA and EB sediment cultures Fig.  and OHRB−1. The inlet temperature was 100 °C. The split ratio was 30. The temperature program of the column was 40 °C hold for 1 min, followed by an increase at 40 °C min−1 to 260 °C and hold for 1.5 min.Chloroethenes, 1,2-DCA, 1,2-DCP, ethene, and propene were analyzed using a gas chromatograph-mass spectrometer (GC-MS) composed of a Trace GC Ultra  equipped with an Rt®-Q-BOND column  and a DSQ MS (Thermo Fisher Scientific). Helium was used as a carrier gas with a flow rate of 2 ml minrn (μM d−1) is the dechlorination rate that depends on the respective chlorinated compound, knmax, (μM d−1) is the compound-specific maximum utilization rate or degradation constant, Kns, (μM) is the compound-specific half-velocity constant, In (μM) is the compound-specific competitive inhibition rate, and Cn (μM) is the aqueous concentration of the chlorinated compounds. The index i represents the number of parent compounds considered in the dechlorination during competitive inhibition that varied with enrichment set-up.Reductive dechlorination of the chloroethenes in cultures shown in Fig. Dihaloelimination of 1,2-DCA to ethene and of 1,2-DCP to propene were also modeled using Eq. (1). In the enrichment cultures containing both chloroethenes/1,2-DCP and 1,2-DCA, competitive inhibition between 1,2-DCA and the other compounds was also included in the models.n-dimensional space, where n is the number of culture-specific objectives. Using a compromise solution  were modeled, and subsequently model complexity was gradually increased by including additional dechlorination reactions . Following this procedure, additional prior information could be used for more complex models to decrease the parameter space (defined by user-set upper and lower boundaries) from which AMALGAM retrieves optimal solutions. Initial boundary values were based on literature , Geobacter (~ 108 16S rRNA gene copies/mL), and Dehalogenimonas (106–107 16S rRNA gene copies/mL) were the predominant OHRB in the EA culture  was the predominant OHRB in the EB culture, and Geobacter and Dehalogenimonas numbers were ~ 107 and 104 16S rRNA gene copies/mL, respectively  was stoichiometrically converted to ethene in the EA and EB sediment cultures without production of any chlorinated intermediates indicating 1,2-DCA dihaloelimination Fig. . Besidesure Fig. . In contely Fig. . The 16Sber Fig.  and d. Tber Fig.  and d. H1,2-DCA dechlorination was maintained in the EA and EB sediment-free transfer cultures  than in the cultures fed only PCE or cDCE , Geobacter (~ 107 16S rRNA gene copies/mL), and Dehalogenimonas (106–107 16S rRNA gene copies/mL) were the predominant known OHRB in these transfer cultures, similar to EA transfer cultures amended with 1,2-DCA and chloroethenes  to fresh media containing only 1,2-DCP (10 μmol/bottle). During 70 days of incubation, more than 90% of the 1,2-DCP in the EA transfer culture was dechlorinated to propene Fig. , whereases Figs.  and 5d.FKs and I values of the chloroethenes are in the same range as in the previous studies listed in Table kmax is less straight forward as many studies provide kmax in units related to the bacterial cell or protein mass. kmax estimates for PCE and TCE obtained here are similar to those in Haston and McCarty  but likely lost during incubation in the presence of 1,2-DCA plus PCE (EB culture). This suggests that 1,2-DCA but not PCE was also a growth substrate for the 1,2-DCP dechlorinating Dehalococcoides population, whereas PCE was likely a substrate for the other Dehalococcoides population. The EA transfer cultures were also able to dechlorinate PCE  . As soon as cDCE concentrations drop by a factor ≥ 10, inhibition of 1,2-DCA dechlorination by cDCE becomes much less important. The calibrated inhibition constants suggest that VC is a stronger inhibitor on 1,2-DCA dechlorination than cDCE in all cultures except EB-T2 . However, IVC is largest in cultures EA-T4 and EB-T4 where no higher chlorinated compounds were present. A higher competitive inhibition constant indicates a smaller inhibitive effect. The parameter for VC probably lumps inhibition effects from higher chlorinated parent products when present, resulting in a higher simulated inhibition effect of VC in mixed compound tests.An interpretation of competitive inhibition is not straightforward from the obtained inhibition constants I Table . For exaKs and kmax values for chloroethenes and 1,2-DCP in cultures with and without 1,2-DCA. In contrast, kmax,DCA values decreased and Ks,DCA values increased in multi-compound cultures compared with the cultures amended with 1,2-DCA only. This hints towards an effect of the chloroethenes and 1,2-DCP on 1,2-DCA dechlorination. However, the best parameter combination did not put this effect in the inhibition constants, but rather in the dechlorination constants of 1,2-DCA itself. Another example is culture EA-T9: a small Ks of 1,2-DCA is counteracted by a small inhibition constant of 1,2-DCP in the duplicate cultures. In other words, the obtained parameters suggest that dechlorination of 1,2-DCA could occur at a maximal rate at low substrate concentration, but would then be more inhibited by 1,2-DCP; or in contrast, the maximal dechlorination rate of 1,2-DCA is not attained under the current experimental conditions but its dechlorination would be less inhibited by 1,2-DCP. However, both parameter combinations would yield a proper fit of the experimental observations, proving the non-uniqueness of the solution  obtained from cultures with multiple chlorinated compounds proved challenging, as strong cross-correlation exists among the parameters of the Michaelis-Menten kinetics. For example, we observed comparable on Beven .The use of results from less complex culture set-ups in the refinement of the parameter space, from which AMALGAM choses viable solutions for more complex set-ups , allowed us to reduce the uncertainty on the parameter estimates. However, the problem of non-uniqueness still remains, e.g., the existence of multiple parameter combinations producing an equally good fit. Uncertainty on the parameter estimates arises due to incomplete or insufficient information on the dechlorination processes in the individual cultures .Dehalococcoides and Dehalogenimonas populations. Further studies are needed to better understand the inhibitory mechanisms. Possible experimental approaches include identification of the genes and enzymes involved in 1,2-DCA dichlorination, study the transcriptional regulation of these genes, and assess potential competitive inhibition of the enzymes. Theoretical modeling experiments that more rigorously look into the effect of the size of the parameter space or the use of different estimation algorithms could further improve our understanding of parameter/model uncertainty.In conclusion, the inhibitory effect of chloroethenes and 1,2-DCP on 1,2-DCA dechlorination identified in this study has important implications for understanding the persistence of 1,2-DCA at many contaminated sites. For effective bioremediation of such contaminated sites, it will be necessary to first remove potential inhibitors such as cDCE as well as its parent compounds PCE and TCE, which can delay 1,2-DCA dechlorination and even cause loss of 1,2-DCA/1,2-DCP dechlorinating ESM 1(PDF 2535 kb)ESM 2(XLSX 24 kb)


Switching the site-selectivity of C–H activation in aryl sulfonamides containing strongly coordinating N-heterocycles was achieved using a RhIII-catalyst. iii) catalyst. The site-selectivity of C–H carbenoid functionalization at the ortho position relative to either the sulfonamide or N-heterocycle directing groups was elegantly switched using solvents of different polarities and different additive concentrations. Importantly, sulfonamide-group-directed ortho-C–H carbenoid functionalization tolerated strongly coordinating N-heterocycles, including pyridine, pyrrole, thiazole, pyrimidine, and pyrazine. Density functional theory (DFT) calculations were performed to rationalize the reaction mechanisms and the influence of reaction polarity.The limitations of arene C–H functionalization of aryl sulfonamides containing strongly coordinating N-heterocycles were overcome using a Rh( It was worth noting that product 3 was isolated as the major product and the 3/3′ ratio could reach 33 : 1 when the reaction was carried out in toluene at 0.01 M concentration (iii)-catalyzed site-selective C–H carbenoid functionalization . In contrast, increasing the reaction concentration led to increase of the thiazole-directed product 3′, which also well reflected the significant solvent effect of this site-selective C–H carbenoid functionalization (3/3′ ratio (entries 13 and 14), which reached <1 : 99 when the amount of AgOAc was 8- and 12-fold that of [RhCp*Cl2]2 respectively. It is worth noting that 2.5 mol% [RhCp*Cl2]2 and 60 mol% AgOAc loading amount could guarantee an excellent site-selectivity of 3′ . These results showed that increasing the amount of AgOAc favored C–H functionalization at the thiazole ortho-position. It may be possible that changing the AgOAc concentration affected the polarity of the reaction environment, influencing the site-selectivity. It is also possible that AgOAc plays the role of a Lewis acid which could bind to an N-heterocycle or diazo compound and affect the site-selectivity.ortho-position of sulfonamide and N-heterocycle were chosen respectively (entries 9 and 15). These two methods not only gave good yields, but more importantly excellent site-selectivities.Initially, this Rh at 60 °C, affording excellent site-selectivity (4–14). In addition to phenyl sulfonamides, thienyl sulfonamides also showed excellent site-selectivity (15 and 16), while substrates containing phosphate ester and sulfone ester diazo groups instead of dimethyl 2-diazomalonate also gave satisfactory results (17 and 18). Notably, C–H di-activation at the ortho-positions relative to the sulfonamide group afforded the major product when para-heterocycle-substituted benzenesulfonamide was used (19–22). As shown in 2]2 catalyst and 60 mol% AgOAc as the additive at 60 °C, with good yields and excellent site-selectivity . A 1,2-disubstituted substrate was also tried, but no desired carbenoid functionalization product was obtained, which may be the result of a bidentate coordination, impeding the free coordination site for cyclometallation.With the two optimal conditions in hand, sulfonamide substrates containing various N-heterocycles in a competitive position were further investigated, including thiazole, pyrazole, imidazole, pyridine, pyrimidine, and pyrazine substrates . As expeIntermolecular competition experiments were conducted to explore the unique chemoselectivity of difunctional sulfonamides containing N-heterocycle substrates . NotablyN-acetyl sulfonamide (1a) by method A and B in the presence of [D4]-MeOD showed that reversible processes for sulfonamide and thiazole directed C–H activation were involved under method A and B conditions.ortho position of the thiazole group using [D4]-MeOD as a co-solvent in the method A catalytic system, implying weak reversible properties. As shown in The mechanism of the site-selective aryl C–H carbenoid functionalization between sulfonamide and N-heterocycles was further investigated by experimental studies and theoretical calculations. The mechanism of directing group oriented aryl C–H carbenoid functionalization has been illustrated in the previous literature, and three major steps including C–H activation, metal–carbene formation and final C–C bond formation process were proposed to take place.2 complex was commonly considered as the active catalyst under the conditions of [RhCp*Cl2]2 with an abundant AgOAc additive.2 were similar to those catalyzed by RhCp*Cl2/AgOAc, which proved that RhCp*(OAc)2 was an active catalyst for the C–H carbenoid functionalization  center adjacent to the ortho-C–H bond of either the sulfonamide or thiazole group, which guaranteed facilitation of the ortho-C–H activation processes in the transition state TS1 or TS1′. Both aryl C–H deprotonation to the mono-coordinated OAc– ligand and Rh–C bond formation processes were observed in the concerted-metalation–deprotonation (CMD)TS1 or TS1′. Subsequently, the Rh(iii)-bound neutral HOAc molecule would be easily replaced by the diazo compound 2a, and metal–carbene formation through clear nitrogen extrusion processes was observed in both TS2 and TS2′. The active metal–carbene would attack an adjacent aryl carbon center to generate C–C bond formation transition state TS3 or TS3′. Finally, transient product PC or PC′ was obtained through site-selective carbenoid functionalization at the ortho-position of either the sulfonamide or thiazole moiety. Alternatively, the active catalyst RhCp*(OAc)2 might directly react with diazo compound 2a to form a metal–carbene complex via a similar nitrogen extrusion process in carbeneTS.In order to delve into our conjecture about the mechanism on selectivity, density functional theory (DFT) calculations were performed. The RhCp*(OAc)carbeneTS  were higher than the barriers depicted in iii) catalysts would preferentially react with aryl substrates (details in the ESIortho-positions of the sulfonamide and thiazole groups at a lower reaction concentration (0.005 M) in toluene, which was supported by the energy barrier of the ortho-sulfonamide C–H activation in toluene . Furthermore, the competitive C–H activation results shown in TS1 and TS1′  in DCE. The concentration factor was considered in ε = 25.0) wherein a narrower free energy gap between TS1 and TS1′ was observed . More importantly, a stable thiazole-directed intermediate IM′-OAc was generated, which was responsible for more deuteration at the thiazole side in The profiles of the potential energy surface proposed above are shown in ortho-sulfonamide C–H carbenoid functionalization product 3 was the major product in toluene  and TS1′ , and of metal–carbene formation transition states TS2  and TS2′  in DCE were observed (black pathway). The calculated competitive reaction pathways in DCE were in good agreement with experimental findings that both ortho-sulfonamide product 3 and ortho-thiazole product 3′ were obtained in DCE at a lower AgOAc concentration -catalyzed arene C–H carbenoid functionalization with good yields and excellent site-selectivity switching for aryl sulfonamides containing strongly coordinating N-heterocycles. The polarity of the reaction environment was an important factor influencing the site-selectivity. Notably, the combination of a less-polar solvent, such as toluene, and a lower additive concentration favored C–H functionalization at the ortho-position relative to the sulfonamide group with excellent site-selectivity. Furthermore, strongly coordinating N-heterocycles, including pyridine, pyrrole, thiazole, pyrimidine, and pyrazine, were tolerated. This switchable site-selectivity carbenoid functionalization methodology is suitable for the late-stage modification of N-heterocycle-derived sulfonamide drugs.In summary, we have developed a Rh(There are no conflicts to declare.Supplementary informationClick here for additional data file.Crystal structure dataClick here for additional data file.


In vitro, the multiply phosphorylated form of MTHFR is more sensitive to allosteric inhibition by SAM. Here we sought to investigate the kinases responsible for MTHFR multisite phosphorylation and the physiological function of MTHFR phosphorylation in cells. We identified DYRK1A/2 and GSK3A/B among the kinases that phosphorylate MTHFR. In addition, we found that MTHFR phosphorylation is maintained by adequate cellular SAM levels, which are sensed through the C-terminal SAM binding domain of MTHFR. To understand the function of MTHFR phosphorylation in cells, we generated MTHFR CRISPR knockin mutant lines that effectively abolished MTHFR phosphorylation and compared them with the parental cell lines. Whereas the parental cell lines showed increased 5-methyl-THF production in response to homocysteine treatment, the knockin cell lines had high basal levels of 5-methyl-THF and did not respond to homocysteine treatment. Overall, our results suggest that MTHFR multisite phosphorylation coordinates with SAM binding to inhibit MTHFR activity in cells.Methylenetetrahydrofolate reductase (MTHFR) catalyzes the irreversible conversion of 5,10-methylene-tetrahydrofolate (THF) to 5-methyl-THF, thereby committing one-carbon units to the methionine cycle. While MTHFR has long been known to be allosterically inhibited by S-adenosylmethionine (SAM), only relatively recently has N-terminal multisite phosphorylation been shown to provide an additional layer of regulation.  The one-carbon unit is carried by the cofactor THF, and can exist in three different oxidation states, including the most oxidized formyl state, the intermediate methylene state, and the most reduced methyl state  in a competitive manner. Second, when expressed in insect cells or human cells, human MTHFR is found to be phosphorylated at up to 11 serine or threonine sites in a serine-rich region8. This multisite phosphorylation increases the sensitivity of MTHFR to SAM inhibition in vitro8.Two types of regulation of MTHFR have been documented. First, MTHFR is allosterically inhibited by the pathway end product SAM Fig. 5,6. This8. Specifically, when both the N-terminal phosphorylation and SAM binding are present, MTHFR is maximally shifted to an inactive conformation.Human MTHFR consists of an N-terminal, catalytic domain and a C-terminal, regulatory domain. The N-terminal domain contains the serine-rich phosphorylation region and the catalytic active site. The C-terminal domain binds SAM to exert allosteric inhibition of MTHFR. The recently solved crystal structure of human MTHFR does not contain the N-terminal serine-rich phosphorylation region (aa 1–37). Nevertheless, the crystal structure suggests that the N-terminal phosphorylation region is positioned near the C-terminal SAM-binding site, raising the possibility that the negative regulations of MTHFR by N-terminal phosphorylation and by SAM could be concertedMany questions related to MTHFR phosphorylation remain open. Which kinases phosphorylate these sites in the N-terminal serine-rich region? How is the phosphorylation regulated? What’s the physiological function of the phosphorylation? This study was initiated to address these questions. In particular, regarding the first question, we formulated hypotheses based on our knowledge of protein kinase substrate specificity, and then used a combination of pharmacology and genetics to test these hypotheses.9 P motif antibody P motif antibody Fig. . Thus, GGSK3B CRISPR knockout cells. Whereas knocking down GSK3A in the parental background had no effect, in the GSK3B-knockout cells this led to marked reduction in MTHFR phosphorylation, as indicated by the prominence of the lower MTHFR band P motif band and by the band shift on the phos-tag gel  nes Fig. , and comnes Fig. . For botion Fig. . By contion Fig. . For MDAion Fig. , homocyslls Fig. . Thus, w16, thus explaining why the majority of MTHFR is phosphorylated under basal conditions. However, these kinases could be inhibited under certain conditions, thereby altering the degree of MTHFR phosphorylation. For example, GSK3 is known to be inhibited by PI3K-Akt signaling17, so the level of MTHFR phosphorylation might be reduced under conditions of PI3K hyperactivation, which occurs often in cancers. By contrast, the regulation of DYRK1A/2 is poorly understood15. DYRK1A is overexpressed in Down Syndrome, and DYRK1A overexpression in mice led to perturbations of the methionine cycle, specifically a decrease in plasma homocysteine level18. Such an effect of DYRK1A overexpression is not predicted by our model, where DYRK1A-primed MTHFR phosphorylation would lead to a decrease in MTHFR activity, hence an increase in homocysteine.In this study, we identified DYRK1A/2 and GSK3A/B among the kinases that phosphorylate the N-terminal serine-rich region of MTHFR Fig. . Both of13. Furthermore, we provided evidence that this regulation requires the C-terminal SAM binding domain. Such interaction between MTHFR N-terminal phosphorylation region and the C-terminal SAM-binding domain is well-supported by the recently solved crystal structure of human MTHFR, which suggests proximity of these two regions8. Presumably, when SAM is bound, the N-terminal phosphorylation region interacts with the C-terminal domain, such that the multiple phosphorylation sites are buried and therefore shielded from phosphatases . SpTP motif, DYRK1A, GSK3A/B, GSK3A, P-glycogen synthase antibodies was purchased from Cell Signaling Technology .DYRK inhibitor harmine was purchased from Sigma-Aldrich (Cat# 286044). GSK3 inhibitor CHIR-99021 was purchased from Selleckchem (Cat# S2924).Reagents used for the peptide library experiments include: Kinase substrate library (Anaspec). Streptavidin conjugated membranes (Promega). Recombinant kinases were obtained from the following sources: DYRK2 , GSK3A , GSK3B , CK1G , CK1E , CK1A (ThermoFisher Scientific), CK2A1 (NEB), and DYRK1A (gift from the Matthias Geyer Laboratory).in vitro kinase assays were performed with recombinant kinases on the kinase substrate library in the presence of ATP[γ-32P]. There reactions were carried out in Kinase Buffer I  at 30 °C for 90 minutes. The peptides, which contain C-terminal biotinyl groups, were blotted onto streptavidin-conjugated membranes and imaged with a Typhoon FLA 7000. Detailed information of the experimental protocol is provided elsewhere20.To determine the phosphorylation motifs for the kinases, 21.The spot densitometry values were used to generate sequence logos. The densitometry matrix was normalized by each row, in order to create a probability matrix, was converted to a probability sequence logo. All the sequence logos were generated in R 3.5.1 using the ‘ggseqlogo’ package22. Cell lines with transfected with guide using Lipofectamine 3000 or Lipofectamine LTX (Invitrogen). 24 hr post transfection, puromycin  was added to enrich positively transfected cells. The puromycin selection typically lasts for 2 days, until mock-transfected, control cells were completely eliminated by puromycin. Single cell cloning was performed by serial dilution in 96-well plates. After 1.5–3 weeks, 15–20 clones were picked for knockout verification.Single guide RNA sequence was cloned into PX459_V2.0 (Addgene) according to a published protocolIf antibodies were available, knockout clones were first screened by western blotting. The genotypes of selected clones were determined by PCR amplification of a genomic region encompassing the editing site, TOPO cloning of the individual alleles into PCR4-TOPO vector (Invitrogen), and Sanger sequencing. At least 20 bacterial colonies were picked for sequencing to ensure approximately equal representation of both alleles. We were unable to find a specific DYRK2 antibody, so DYRK2 knockout status was determined by TOPO cloning followed by Sanger sequencing.MTHFR CRISPR Knockin cells was generated using nucleofection of sgRNAs together with ssODN repair templates. The PAM sequence was mutated and a restriction site was introduced into the ssODN repair templates. Correct clones were initially screened using restriction digest, and further verified using Sanger sequencing of the genomic DNA PCR amplicon.Pooled siGENOME siRNA (30 nM) against DYRK1A and DYRK2 were purchased from Dharmacon and transfected using Lipofectamine RNAiMAX reagent.http://splashrna.mskcc.org/) and cloned into the inducible lentiviral vector according to a previously published protocol23. Lentivirus-infected, GFP-positive cells were sorted prior to analysis.DOX-inducible GSK3A knockdown target sequence was predicted using the Splash algorithm  which contains a N-terminal Flag tag, and lentiviral pLEX_306 (addgene #41391) which contains a C-terminal V5 tag.The cDNA for Human/Arabidopsis MTHFR chimera was synthesized by IDT. The coding region contains the first 357 amino acids of human MTHFR, followed by KNEE, followed by the last 266 amino acids of Arabidopsis MTHFR. The cDNA was then subcloned into pLEX_306 using gateway technology.For lentivirus generation, 293T cells were co-transfected with the viral plasmid of interest together with pVSVG and delta8.9 using Lipofectamine 3000. For retrovirus generation, Phoenix-Ampho cell were transfected with the viral plasmid using Lipofectamine 3000. Lentivirus or retrovirus-containing supernatant was collected at 48 hr after transfection. Target cells were infected with 0.45 μm PVDF membrane-filtered viral supernatant in the presence of 8 μg/ml polybrene for 24 hr and then replaced in fresh media. At about 48–72 hr post-infection, puromycin  was added to select positively transduced cells for at least 3 days.Flag- or V5-tagged proteins were immunoprecipitated using anti-Flag M2 agarose  or anti-V5 agarose , according to manufacturer’s instructions.2 was included in each sample, and EDTA washes were performed before proceeding to the transfer step. SDS-PAGE was followed by standard immunoblotting steps. Immunoblot signals were detected by enhanced chemiluminescence.Cells were quickly washed twice with ice-cold PBS, and lysed in NP-40 lysis buffer  freshly supplemented with protease inhibitors (Roche or Thermo). Lysates were cleared by centrifugation at 13,000 g at 4 °C for 10 min. Protein concentration was determined by BCA assay. Proteins were denatured in NuPAGE LDS 4X sample buffer (Invitrogen) supplemented with β-mercaptoethanol. Typically, 20–50 μg of total protein was loaded per lane on an 8% Bis-Tris Bolt gel (Invitrogen), and the apparatus was kept on ice, for a 2–3 hour run at 120 volts. 7.5% SuperSep Phos-tag gels were run according manufacturer’s protocols (Wako Cat# 198–17981); in particular, 10 mM MnClE.coli BL21(DE3) (Invitrogen) was transformed with DYRK1A-pNIC28 vector . The bacteria were grown at 37 °C in 2xYT medium containing 100 μg/ml Carbenicillin until A600nm reached ~0.6, cooled down to room temperature, followed by 0.5 mM IPTG induction of protein expression at room temperature for 16 hours. The DYRK1A protein was purified using the standard protocol for Ni-NTA purification under native conditions as described in “The QIAexpressionist Handbook”.For DYRK1A protein expression, One-shot in vitro kinase assay, immunoprecipitated human or chimeric, wild-type or T34A, MTHFR was incubated with 3 μg of DYRK1A in a kinase assay buffer  at 30 °C for 90 min. The reaction was stopped by adding Invitrogen LDS 4X sample buffer.For DYRK1A Pre-cooled 80% methanol with 0.1% formic acid (1 mL) was added to each 6-cm dish of 70% confluent cells. The lysate was scraped into an Eppendorf tube and then centrifuged at 4 °C for 10 minutes at 14,000 rpm. The supernatant was evaporated using a Speed-Vac. Targeted LC/MS analyses were performed on a Q Exactive Orbitrap mass spectrometer (Thermo Scientific) coupled to a Vanquish UPLC system (Thermo Scientific). The Q Exactive operated in positive mode. An XBridge amide column  was used for separation of metabolites. The flow rate was set at 150 μL/min. Mobile phases consisted of 0.1% formic acid in acetonitrile for line A, and 0.1% formic acid in water for line B. Gradient ran from 70% to 0% A in 13 min followed by a wash with 0% A and re-equilibration at 70% A. Metabolites were identified on the basis of exact mass within 5 ppm and retention time. Relative metabolite quantitation was performed based on peak area for each metabolite. Data analysis was done using in-house written scripts. SAM and SAH metabolites were also manually checked using Thermo X-Caliber. Normalization was based on protein content.24. Briefly, cells were cultured in 50 nM 3H-5-formyl-tetrahydrofolate for 48 hr. Then cellular folates were liberated from proteins and protected from air oxidation by boiling in 50 mM Tris-HCl pH7.4 buffer with 3% (w/v) ascorbate and 200 μM β-mercaptoethanol. The polyglutamate tails of folates were then cleaved by recombinant γ-glutamyl hydrolase (GGH), and the resulting folate monoglutamates were resolved by reversed phase ion-pair HPLC with radioactivity detection.HPLC analysis of intracellular folates was performed as previously reportedSupplementary info