FCER1A, a locus encoding an allergen-biding FcԑRI subunit, are related to acquired AS severity. Indeed, the major allele of rs2251746 polymorphism, known to associate with higher IgE levels, turned out to correlate with larger AVA, a marker of less severe AS. Our findings surprisingly suggest a protective role of IgE pathways against AS progression. IgE-mediated protective mechanisms in AS require further investigations.Allergic mechanisms are likely involved in atherosclerosis and its clinical presentations, such as coronary artery disease (CAD). It has been previously reported that CAD severity associates with serum levels of immunoglobulin E (IgE), the molecule that, along with its high-affinity receptor (FcԑRI), plays a central role in allergic reactions. Considering multiple pathophysiological similarities between atherosclerosis and acquired aortic  stenosis (AS), we speculated that allergic pathways could also contribute to the AS mechanisms and grading. To validate this hypothesis, we first checked whether total serum IgE levels associate with echocardiographic markers of AS severity. Having found a positive correlation between serum IgE and aortic valve area (AVA), we further speculated that also total IgE-determining genetic polymorphisms in  The immune system plays an essential role in the development and progression of atherosclerosis and related diseases, including coronary artery disease (CAD), peripheral artery disease, and stroke. Moreover, there is a growing body of evidence for the contribution of allergic mechanisms, such as those related to the immunoglobulin E (IgE) network, to the pathogenesis of atherosclerosis ,2,3. TheFCER1A) representing the two tagging bins constituting the primary total serum IgE susceptibility loci  and were analyzed with Mann–Whitney test or Kruskal–Wallis test . Adjustments for potential categorical and continuous confounders were performed using analysis of covariance (ANCOVA), with variables having distribution different from normal subjected to square-root transformation before entering the model. Associations between two continuous variables were calculated using Spearman’s coefficient of rank correlation. Adjustments for potential categorical and continuous confounders were conducted using least squares multiple regression, with variables having distribution different from normal subjected to square-root transformation before entering the model. Conformity with HWE was tested with the chi-squared goodness-of-fit test. Statistical calculations were performed using MedCalc Version 18.10  and Dell Statistica 13  programs.R = 0.27, P = 0.01; P <0.05).First, we sought to investigate whether the echocardiographic parameters correlate with total serum IgE concentrations in AS patients. Although a mean or maximum gradient and left ventricular ejection fraction were not associated with total serum IgE, we documented a positive correlation between IgE and aortic valve area . However, the rs2251746 polymorphism demonstrated a significant association with AVA , which remained significant after adjustment for age, sex, BMI, and CRP levels (P = 0.02). Moreover, contrasting minor or major homozygotes with the reminder as well as opposite homozygotes with each other also yielded significant results , with the highest values in TT and the lowest in CC homozygotes  expression [An increase in FcεRI expression might lead to higher concentrations of IgE in serum, for instance, through the stabilizing effect of mast cell or basophil receptor on IgE upon binding ,22. Thispression ,24, withpression . Howeverpression ,28,29,30pression . These cpression ,33. It ipression . Thus, mFCER1A and not directly related to the IgE network. For example, a strong correlation was observed between a FCER1A polymorphism belonging to the same tagging bin as rs2251746 and the expression of OR10J5, a gene located about 250 kb upstream [Another possible explanation of the observed relationship might be a linkage disequilibrium between rs2251746 polymorphism and genetic variants in another gene localized distantly from upstream . One canOur study has several limitations. Most importantly, total serum IgE was not measured in all analyzed subjects. The reason behind this was the design of the study, with the original group  being a FCER1A rs2251746 polymorphism. This intriguing observation is, however, preliminary and requires further investigation. Moreover, the mechanisms underlying our current results need to be elucidated.We found for the first time the relationships between the elements of the IgE network and acquired AS severity. Specifically, higher AVA corresponding to the less advanced AS was associated with elevated total serum IgE levels or the major allele of


Streptomyces ghanaensis ATCC14672 c-di-GMP was shown to be involved in the regulatory cascade of the peptidoglycan glycosytransferases inhibitor moenomycin A (MmA) biosynthesis. Here, we report the role of four c-di-GMP-metabolizing enzymes on MmA biosynthesis as well as morphological progression in S. ghanaensis. Functional characterization revealed that RmdAgh and CdgAgh are two active PDEs, while CdgEgh is a DGC. In vivo, overexpression of ghrmdA and ghcdgA led to precocious sporulation, whereas overexpression of ghcdgE and ghcdgD (encoding a predicted DGC) caused an arrest of morphological development. Furthermore, we demonstrated that individual deletion of ghrmdA, gh,cdgA and ghcdgD enhances MmA accumulation, whereas deletion of ghcdgE has no impact on antibiotic production. Conversely, an individual deletion of each studied gene does not affect morphogenesis. Altogether, our results show that manipulation of c-di-GMP-metabolizing enzymes represent a useful approach to improving MmA production titers in S. ghanaensis.Diguanylate cyclases (DGCs) and phosphodiesterases (PDEs) are essential enzymes deputed to maintain the intracellular homeostasis of the second messenger cyclic dimeric (3′→5′) GMP (c-di-GMP). Recently, c-di-GMP has emerged as a crucial molecule for the streptomycetes life cycle, governing both morphogenesis and secondary metabolite production. Indeed, in  Actinobacteria to combat multidrug-resistant (MDR) pathogens.Streptomycetes are filamentous soil bacteria with a complex, strictly-regulated morphological development. Their life cycle begins with the germination of spores to vegetative mycelium. In response to stress signals, aerial hyphae are formed, which ultimately differentiate into spore chains ,2. Due tStreptomyces strains including Streptomyces ghanaensis ATCC14672  were individually incubated with 200 µM GTP. To test a PDE activity, 5 µM purified His6-RmdAgh, His6-CdgAgh, and Trx-His6-CdgAghAAL were individually added to a reaction mixture containing 200 µM c-di-GMP, 50 mM Tris-HCl [pH 8.0], 50 mM NaCl, and 10 mM MgCl2. Following 2 h incubation at 37 °C, reactions were stopped first by adding 10 mM CaCl2 and then by heating at 70 °C for 10 min. Reaction products were analyzed by LC–MS. Standards were prepared by using purchased c-di-GMP  and GTP .Enzymatic in vitro assays were performed and analyzed as described previously ,30. To tghcdgE, cdgDgh, rmdAgh and cdgAgh) was amplified by PCR, using primers 02707_exp_for/02707_exp_rev, 02343_exp_for/02343_exp_rev, rmdA_exp_for/rmdA_exp_rev, and cdgA_exp_for/cdgA_exp_rev, respectively. The PCR products corresponding to ghcdgE, cdgDgh, and cdgAgh were digested with NdeI and XhoI and cloned under the control of the constitutive promoter ermEp into the NdeI-XhoI digested integrative pIJ10257 vector. Instead, the fragment containing the coding sequence of rmdAgh was digested with NdeI and HindIII and ligated into the pIJ10257 vector, linearized by NdeI and HindIII. The resulting plasmids pIJcdgE, pIJcdgD, pIJcdgA, and pIJrmdA were individually transferred into S. ghanaensis by conjugation, leading to the formation of four different strains .In order to perform gene-overexpression experiments, the coding sequence of each target gene  was performed as following. The DNA fragment containing cdgAghAAL was digested from pETcdgAAAL plasmid using NdeI and XhoI and subcloned into the NdeI-XhoI linearized pIJ10257 vector, yielding pIJcdgAAAL.Next, overexpression of rmdAgh (named rmdAghAAL), PCR mutagenesis was used to amplify a 7.4 kb DNA fragment from pETrmdA using primers designed to bring the point substitution E485A (rmdA_AAL_for and rmdA_AAL_rev). The obtained amplicon was treated with T4 Polynucleotide kinase and then self-ligated, yielding pETrmdAAAL. The latter was digested with NdeI and HindIII and the resulting rmdAghAAL fragment was subcloned into the NdeI-HindIII linearized pIJ10257 vector, yielding pIJrmdAAAL. Finally, pIJcdgAAAL and pIJrmdAAAL were transferred into the S. ghanaensis strain by intergeneric conjugation.To generate a mutated version of S. ghanaensis ΔghcdgE, S. ghanaensis ΔcdgDgh, S. ghanaensis ΔghrmdA, and S. ghanaensis ΔghcdgA were generated through homologous recombination, as described previously , flanked by loxP sites. The resulting fragments cdgE::aac(3)IV, cdgD::aac(3)IV, rmdA::aac(3)IV, and cdgA::aac(3)IV were amplified by PCR and individually cloned into the suicide pKGLP2 vector, linearized with EcoRV. The obtained pKGcdgE::aac(3)IV, pKGcdgD::aac(3)IV, pKGrmdA::aac(3)IV and pKGcdgA::aac(3)IV were individually transferred into S. ghanaensis by conjugation, and double-crossover mutants were selected for hygromycin sensitivity and apramycin resistance. Finally, marker-free mutants were generated by introducing the Cre-expressing helper plasmid pUWLCre into mutants by conjugation −) was indeed observed in RmdAghGGDEF  in its EAL motif, generating CdgAghAAL protein. Upon mutagenesis, CdgAghAAL resulted poorly soluble. Hence, to improve its solubility, the protein was fused N-terminally with a Trx-His6tag. The resulting Trx-His6-tagged CdgAghAAL was purified and used for an in vitro assay. As a result, the hydrolytic activity was reduced of 1.8-fold in comparison to the wild-type protein, indicating that mutations in the EAL domain of CgdAgh strongly affect its catalytic activity. Moreover, we found that the mutation did not trigger the activity of the GGDEF domain, since no c-di-GMP accumulation was observed upon incubation of CdgAghAAL with GTP  carrying both G271A and G272A substitutions in its GGDEF domain was purified. Upon reaction, no c-di-GMP was synthesized  were used to construct the plasmids pIJrmdAAAL and pIJcdgAAAL. As depicted in ghrmdA and ghcdgA observed phenotypes.In contrast to gene deletion experiments, gene overexpression led to remarkable consequences on morphological development. First, we used the φBT1-based integrative vector pIJ10257 to generate four plasmids , where the corresponding gene was placed under control of the strong constitutive promoter ed white . To provghcdgE, ghcdgD, ghrmdA, and ghcdgA severely alters morphological development in S. ghanaensis. Particularly, we demonstrated that CdgEgh and CdgDgh act as DGCs in vivo, leading to the arrest of morphological progression. On the contrary, RmdAgh and CdgAgh function as PDEs and their overexpression strongly induces sporogenesis.Altogether, these results showed that overexpression of gh and the two DGCs CdgBgh and CdgCgh are strongly involved in the regulation of MmA production in S. ghanaensis [ghcdgE, ghcdgD, ghrmdA, and ghcdgA may also have a role in antibiotic biosynthesis, we analyzed MmA accumulation in both null-mutants and gene-overexpressed strains.Recently, we showed that the PDE RmdBanaensis ,30. In oS. ghanaensis ΔghrmdA, S. ghanaensis ΔghcdgA and S. ghanaensis ΔghcdgD mutants produced on average 140%, 170%, and 136% of MmA, respectively , ectively A. Conver ΔcdgEgh A. In ordoduction .ghcdgA (plasmid pIJcdgA) led to a 40% less antibiotic production with respect to the control strain, carrying an empty copy of pIJ10257 plasmid. Additionally, the introduction of pIJcdgAAAL  had no effect on MmA accumulation  of antibiotic production  led to a slight increase in MmA levels, while S. ghanaensis + pIJrmdAAAL (carrying a mutated copy of ghrmdA) displayed around a twofold increase of MmA biosynthesis  was also shown to be a DGC and to undergo a substrate inhibition [S. coelicolor exclusively as a PDE enzyme [S. venezuelae it was revealed to have double activity [gh is able to synthesize c-di-GMP in vitro, although this molecule is immediately converted into pGpG at the presence of full-length protein. Such dominance of a PDE activity over the DGC one was also shown in the YciR protein from E. coli [gh from S. venezuelae [gh is most likely mediated by the binding of specific signals to its PAS-PAC domain, determining thus the dominance of a function over the other. Surprisingly, we found that CdgAgh is able to hydrolyse c-di-GMP through its EAL domain and has no cyclase activity. Indeed, the mutation in the highly-conservative glutamate strongly reduces its catalytic activity but does not trigger the GGDEF domain. Upon in vivo experiments, the ortholog of CdgAgh in S. coelicolor was identified as a DGC [in silico analysis, these proteins share 72% identity and both possess key residues in GGDEF and EAL domains. Nevertheless, they seem to have solely a single, opposite function in two organisms. It would be of high interest to study why these orthologs evolved different activities and how their catalysis is regulated. Both sequences possess an N-terminal PAS domain (46% identity), known to adapt to numerous ligands [S. ghanaensis and S. coelicolor CdgA activity might be controlled by two diverse environmental stimuli, which in turn differently trigger the catalytic domain and keep the other one inactive. Many examples of inactive EAL and GGDEF domains have been described previously [gh might also be required to enhance the PDE activity of the cognate EAL domain or simply to stabilize the protein conformation. Finally, it cannot be excluded that the inactivity detected in our in vitro assay might be due to the lack of specific signal(s) under the tested conditions.In line with our enzymatic in vitro assays, we showed that CdgEhibition . RmdA waE enzyme , whereasactivity . Similar E. coli  and in tnezuelae . In agreas a DGC , but its ligands . Due to eviously . These deviously ,48 or beeviously . SimilarS. ghanaensis null-mutant strains. This phenomenon was also observed by Liu et al. in S. coelicolor [S. venezuelae revealed that the majority of these genes are simultaneously expressed during the entire life cycle [rmdA and rmdB remarkably affected S. coelicolor phenotype in comparison to individual mutants, highlighting the overlapping functions of these two PDEs in regulating morphological development [S. ghanaensis. The arrest of development observed in both ghcdgE and ghcdgD overexpressed strains resembles the phenotypes obtained in S. coelicolor upon cdgA, cdgB and cdgD overexpression  [ghcdgB and ghcdgC overexpressed S. ghanaensis strains [Morphologically, no obvious differences were detected among the four generated elicolor  and suggfe cycle . In addielopment . Conversrmation) ,25,26 an strains ,30.WhiG factor were shown to be two c-di-GMP sensing effectors in streptomycetes [WhiG factor blocks the transcription of sporulation-associated genes when bound to its anti-σ [WhiG -anti-σ binding are mediated by c-di-GMP. Consequently, high concentrations of the second messenger—caused by the overproduction of DGC enzymes—induces the dimer formation as well as the σWhiG-anti-σ interaction, resulting in the arrest of morphological progression.Until now, BldD and the sporulation-specific σomycetes ,18. BldDomycetes ,16,17, wS. ghanaensis overexpression of ghrmdB (encoding a PDE) resulted in an accelerated spore formation [ghrmdA and ghcdgA remarkably led to precocious sporulation and mutations in their catalytic EAL domain could revert the obtained phenotype.On the contrary, increased hydrolysis of c-di-GMP due to an enhanced PDE activity triggers morphogenesis. For example, in ormation . SimilarwblA but positively regulates the expression of adpA [moe cluster [ghrmdA and ghcdgA led to an increase in MmA biosynthesis, as also shown previously in the ΔghrmdB mutant [ghrmdA and ΔghcdgA mutants, promoting BldD dimer formation and thus its binding to the target promoters. An opposite effect was instead observed in ghcdgA-overexpressed S. ghanaensis.Next, we aimed to study the influence of these enzymes on secondary metabolite production. Given its high potency and broad spectrum of activity, MmA is a promising lead to combat MDR pathogens. Recently, we expanded the knowledge regarding MmA regulation, showing that variations in intracellular c-di-GMP levels strongly affect antibiotic accumulation ,30. Inde of adpA . WblA an of adpA , whereas cluster . In thish mutant . In agreghrmdA resulted in a slight increase of antibiotic titers. As discussed above, RmdAgh is capable of both DGC and PDE activities and its overproduction might lead to a change in dominance between the two functions. Indeed, inactivation of the EAL domain by point mutation caused a more remarkable increment of MmA accumulation in comparison to ΔghrmdA mutant. This phenotype resembled that observed in S. ghanaensis strains overproducing the DGCs CdgBgh and CdgCgh, respectively [gh EAL domain.Strikingly, overexpression of ectively ,30, suggin silico analysis, CdgDgh is predicted to be a DGC, albeit we could not prove its enzymatic activity in vitro. Nevertheless, Liu et al. demonstrated that CdgD (an ortholog of CdgDgh) indeed functions as a cyclase and its overexpression negatively affects actinorhodin production in S. coelicolor [ghcdgD greatly reduced MmA levels, whereas S. ghanaensis ΔghcdgD accumulated more antibiotic. These results are somewhat puzzling considering that in S. ghanaensis deletion of other two active DGCs  was previously shown to have an opposite effect [S. ghanaensis, a decrease of c-di-GMP levels caused a reduction in antibiotic biosynthesis. The majority of DGC and PDE enzymes contain N-terminal transmembrane and/or sensor domains associated with the catalytic ones. Exceptionally, CdgDgh has only a stand-alone GGDEF domain, which lacks the RxxD inhibition site, suggesting that this enzyme might undergo an uncommon mechanism of regulation. In addition, ghcdgD is in operon with other three genes of yet-unknown functions. We speculate that ghcdgD might be a part of a local c-di-GMP-dependent micro-compartment, whose perturbation can lead to a signaling cascade involving yet-undiscovered regulators associated with antibiotic production. Numerous examples of local c-di-GMP signaling pathways were already described previously in other bacteria [In line with our elicolor . Similare effect ,30. In fbacteria ,50,51,52S. ghanaensis null-mutants, ΔghcdgE did not show any changes in MmA accumulation, but overexpression of ghcdgE slightly reduced antibiotic titers. We propose that this enzyme is not directly involved in secondary metabolism pathway and that the results obtained upon overexpression are rather due to a spillover of an excess of c-di-GMP from its local pool. Indeed, indirect effects of guanylate cyclase overexpression were previously reported [gh might be associated to a parallel and compartmentalized signaling cascade mostly implicated in morphogenesis and/or primary metabolism. In addition, CdgEgh possesses an N-terminal GAF sensor domain, therefore elucidating the nature of its ligand(s) might provide further hints regarding the mechanism of action and the regulation of CdgEgh.Finally, among all generated reported ,53. As mS. ghanaensis BldD binds to the promoter regions of ghcdgB and ghcdgC, repressing their transcriptions [cdgA, cdgB, cdgC (homolog of ghcdgC), and cdgE (homolog of ghcdgE) are under control of BldD in S. venezuelae ,54. Interestingly, multiple sequence alignment  led to an arrest of morphological progression, whereas overproduction of PDEs RmdAgh and CdgAgh triggered sporogenesis. Finally, we investigated the influence of these enzymes on antibiotic production. The strongest impact was observed upon deletion of ghrmdA, ghcdgA, and ghcdgD, which led to an increase in MmA accumulation. Conversely, deletion of ghcdgE caused no changes in antibiotic titers, suggesting that this enzyme may be rather involved in some local, secondary metabolism-independent signaling pathway. Altogether, these results provide a useful approach to improving MmA levels in S. ghanaensis and expanding the knowledge about the function of c-di-GMP-metabolizing enzymes in governing the Streptomyces life cycle.In this work, we showed that manipulation of c-di-GMP-metabolizing enzymes strongly affects both morphological development and MmA production in activity . Next, w


Ursus maritimus), declining Arctic sea ice reduces access to prey and lengthens seasonal fasting periods. We used a novel combination of physical capture, biopsy darting, and visual aerial observation data to project reproductive performance for polar bears by linking sea ice loss to changes in habitat use, body condition , and cub production. Satellite telemetry data from 43 (1991–1997) and 38 (2009–2015) adult female polar bears in the Baffin Bay subpopulation showed that bears now spend an additional 30 d on land  in the 2000s compared to the 1990s, a change closely correlated with changes in spring sea ice breakup and fall sea ice formation. Body condition declined for all sex, age, and reproductive classes and was positively correlated with sea ice availability in the current and previous year. Furthermore, cub litter size was positively correlated with maternal condition and spring breakup date , and negatively correlated with the duration of the ice‐free period . Based on these relationships, we projected reproductive performance three polar bear generations into the future (approximately 35 yr). Results indicate that two‐cub litters, previously the norm, could largely disappear from Baffin Bay as sea ice loss continues. Our findings demonstrate how concurrent analysis of multiple data types collected over long periods from polar bears can provide a mechanistic understanding of the ecological implications of climate change. This information is needed for long‐term conservation planning, which includes quantitative harvest risk assessments that incorporate estimated or assumed trends in future environmental carrying capacity.Climate change has broad ecological implications for species that rely on sensitive habitats. For some top predators, loss of habitat is expected to lead to cascading behavioral, nutritional, and reproductive changes that ultimately accelerate population declines. In the case of the polar bear ( Progressive changes in the abiotic environment are expected to result in profound ecological disruptions for Arctic fauna, particularly sea‐ice‐dependent species  and bearded seals  negatively affects body condition and reproduction prior to adult survival Fowler . As suchThe annual life cycle of polar bears is characterized by large seasonal changes in body condition  covering portions of Baffin Island and all of Bylot Island (66.2° N to 73.8° N) in Nunavut, Canada, as well as parts of West and Northwest Greenland . Location qualities were assigned by ARGOS to each position, with qualities of 0–3 estimated to have errors of 1.5 km or less, whereas positions categorized as “A,” “B,” or “Z” did not have a predicted accuracy Argos . UnrealiDue to varying study objectives in the two time periods, different duty cycles were used to extend battery life or gather information from specific time periods. The 1990s collars were programmed to transmit on intervals ranging from 1 to 6 d, while the 2000s collars all transmitted on 4‐d intervals. We sub‐sampled the 1990s data and created a strict 4‐, 5‐ or 6‐ d interval time series for each individual to best match the 2000s data. This ensured that the impact of serial autocorrelation was largely consistent between study periods.Polar bears collared in this study ranged over the entire Baffin Bay region  for the entire tracking period as their use of glacial ice and land throughout the summer could not be differentiated. We quantified the date individual AF polar bears arrived on Baffin Island in summer, the duration of time spent on land, and the date they returned to the sea ice in fall. In some cases, individual bears contributed more than one arrival date because they were tracked over multiple years; these were considered to be independent because land use by polar bears is primarily a function of sea ice availability  and the subsequent position was on land. In these cases, there were data gaps (12–30 d) in locations due to the inability of satellite collars to transmit data when polar bears were swimming  digital elevation model  score from 1 to 5, where 1 and 5 represent the leanest and fattest bears, respectively . Repeat observations of individual i in the same year were excluded. Observations of individual i in different years were retained, following the example of Stirling et al.  would be positively correlated with BCS . Analyses for COY and YRL litters were performed separately, following the same three‐step modeling approach employed for body condition. The general model for COY was lsit = β0 + β1 springtrant + β2 ts.springtranit + β3 durfreet−1 + β4 p2000t + β5 BCSit, where BCSit is a three‐level factor for body condition of a cub's mother at the time of sampling. The general model for YRL was lsit = β0 + β1 ts.springtranit + β2 durfreet−1 + β3 durfreet−2 + β4 p2000t + β5 BCSit, where durfreet−2 is the duration of the ice‐free period in year t − 2, which we hypothesized was related to maternal body condition and thus reproductive success in the year that the litter was produced  per adult female in each year and evaluated changes between the 1990s and 2000s. These metrics have been used as indices of productivity for other polar bear subpopulations  exhibited this behavior and all moved to Baffin Island for the ice‐free season. Bears that remained in West Greenland in the 2000s spent the entire on‐ice season on the fast ice near glacier fronts, and during the summer used glacial ice, land, or the glacier itself until the sea ice reformed.Of the 38 AFs collared in BB in the 2000s, 7 bears (18.4%) remained on glaciers or on fast ice at glacier fronts in Melville Bay through summer, and in some cases for over 2 yr, and did not move to Baffin Island. No bears in the 1990s  was significantly earlier (by 20 d) than in the 1990s . The mean date of departure from land in the 2000s  was not statistically different than the mean date of departure in the 1990s . The mean arrival latitude in the 2000s  was not statistically different than in the 1990s . Similarly, the mean departure latitude in the 2000s  was not statistically different than in the 1990s .The mean date of arrival on land in the 2000s  from 1992–1996 and 2009–2014, while the date of spring sea ice retreat had a long‐term trend of −6.4 d/decade  over the period 1979–2017. Polar bear departure date exhibited a trend of +4.7 d/decade  from 1992–1996 and 2009–2014, while the date of fall sea ice advance had a long‐term trend of +4.6 d/decade  over the period 1979–2017.The decadal changes in the dates of AF arrival on land and departure from land are consistent with the long‐term changes in the sea ice metrics Fig. . Polar bP < 0.001). If only bears on Baffin Island were compared, the mean duration of time on land in the 2000s  was still significantly longer (by 20 d) than in the 1990s .Duration of time spent on land was determined for 14 and 26 individuals in the 1990s and 2000s, respectively, for which both arrival and departure dates were available. The mean duration of time on land in the 2000s  was significantly longer (by 33 d) than in the 1990s , 89% (n = 36), and 100% (n = 309) of AMs, AFs without dependent young, and AFs with dependent young, respectively . The low‐AIC model included 22 parameters indicating that BCS in year t varied as a function of sex, age, and reproductive class, spring sea ice transition date in year t, duration of the ice‐free period in the year t − 1, interactions between sea ice conditions and class, and an additive difference between the 1990s and 2000s , whereas AFs with dependent young, subadults, and AMs were 86%, 85%, and 50% less likely, respectively, to have BCS = 3. Similarly, AFs without dependent young had the lowest probability of BCS = 1 (approximately 0.11), whereas AFs with dependent young, subadults, and AMs were 2%, 91%, and 62% more likely, respectively, to have BCS = 1 . This suggests that key ecological relationships were not driven by potential sampling differences between the 1990s and 2000s.We performed a separate analysis of BCS for the 1990s data only, to determine whether the same relationships between BCS and sea ice were present during this 4‐yr time series, when data were collected by a single observer. Using the same procedures as the main analysis, the sea ice covariates springtranDuring the 1990s, 88 AFs accompanied by 1–3 COY  and 45 AFs accompanied by 1–3 YRL  were sampled . The low‐AIC model included five parameters indicating that COY litter size in year t varied as a function of spring sea ice transition date in year t, duration of the ice‐free period in the year t − 1, and maternal body condition at the time of sampling , whereas AFs with BCS = 1 were 53% less likely to have two cubs. AFs with BCS = 3 also were less likely to have two‐cub litters compared to adult females with BCS = 2 . The low‐AIC model included two parameters, indicating that YRL litter size differed between the 1990s and 2000s . The candidate model set included 23 models with ΔAIC < 4, reflecting a high degree of model‐selection uncertainty. Importance score was the highest (0.69) for the parameter p2000t, indicating moderate support for a change in YRL litter size across decades. There was relatively low support for the effects of sea ice conditions or maternal body condition on YRL litter size. Based on the low‐AIC model, the probability that an adult female had a two‐cub litter in the 1990s (approximately 0.64) was 29% higher than in the 2000s.The general model for YRL litter size provided an adequate fit to the data . The number of YRL per AF in the 1990s  was not statistically different from the 2000s  at a significance level of 0.05 (P = 0.18). For the four instances that annual sampling occurred in two successive years, mean COY per AF in year t was positively associated with mean YRL per AF in year t + 1 , which was likely a function of cohort effects with higher COY production subsequently resulting in higher YRL recruitment.The mean number of COY and YRL per AF varied across years Table . The numt] = −0.83 d/yr, SE = 0.13, P < 0.001; slope[durfreet−1] = 1.85 d/yr, SE = 0.36, P < 0.001), and (2) data for the period 2000–2013, during which sea ice was largely stable . Projections demonstrate that the reproductive success of BB polar bears is sensitive to sea ice conditions and can be expected to decline in coming decades if ice loss continues and the estimated relationships between sea ice, body condition, and litter size do not change.Analyses of sea ice metrics, body condition, and reproduction were linked together to project COY litter size three polar bear generations into the future Fig. . For theWe analyzed multiple types of data on habitat use, body condition , and cub production during a period of rapid habitat loss for the BB polar bear subpopulation. Our analyses indicate that reduced sea ice availability has been associated with longer times spent on land, reduced body condition, and reduced reproductive success. To our knowledge, this is the first large‐scale analysis for polar bears using data from both visual observation and physical capture to evaluate long‐term patterns of ecological change. Consistency between our findings and smaller‐scale physical capture studies  and from summer to winter sea ice conditions (date of advance), and not necessarily to predict the behavior of polar bears . The area was established as a sanctuary (Melville Bay Nature Reserve) in 1980, which protects nearshore areas from hunting , and duration of the ice‐free season in the previous year (except for AFs with dependent young) suggesting a multiyear lag in the effects of environmental variation Table . Body coThe BCS used in our study is a qualitative, categorical index that is a coarser and potentially less precise measure of condition than the metrics derived from physical capture data by Rode et al. . Thus, oMeasures of body condition have been identified as a key metric of polar bear health , which could not be directly estimated in the current study; and reductions in COY survival, as evidenced by declining COY litter size.In this study, the number of COY per AF was significantly lower in the 2000s than the 1990s. This suggests that COY production has declined over time, likely due to a combination of reduction in breeding probability .We demonstrated how relationships between environmental conditions, body condition, and litter size might be used to project future reproductive performance. To our knowledge, such projections have not been made based on empirical data for polar bears outside of multistate capture–recapture modeling (e.g., Regehr et al. The impact of climate change on the world's biota has manifested broadly, resulting in latitudinal range shifts, advancing dates of arrival of migrants and onset of breeding, and altered ecosystems (Post et al. Our analyses indicate that reduced sea ice availability has been associated with longer times spent on land, reduced body condition, and reduced reproductive success in Baffin Bay polar bears. This subpopulation inhabits a seasonal ice ecoregion (Amstrup et al.  Click here for additional data file.


The ice arches that usually develop at the northern and southern ends of Nares Strait play an important role in modulating the export of Arctic Ocean multi-year sea ice. The Arctic Ocean is evolving towards an ice pack that is younger, thinner, and more mobile and the fate of its multi-year ice is becoming of increasing interest. Here, we use sea ice motion retrievals from Sentinel-1 imagery to report on the recent behavior of these ice arches and the associated ice fluxes. We show that the duration of arch formation has decreased over the past 20 years, while the ice area and volume fluxes along Nares Strait have both increased. These results suggest that a transition is underway towards a state where the formation of these arches will become atypical with a concomitant increase in the export of multi-year ice accelerating the transition towards a younger and thinner Arctic ice pack. Ice arches that form along Nares Strait, which separates Greenland and Ellesmere Island, act to reduce the export of thick multi-year ice out of the Arctic. Here, we show that there has been a recent trend towards shorter duration arch formation that has resulted in enhanced transport of ice along the strait. The formation of either of these arches results in the cessation of ice transport from the Lincoln Sea southwards towards Baffin Bay and the subpolar North Atlantic3. The oldest and thickest sea ice in the Arctic is found to the north of Nares Strait6 and as a result, the formation of these arches, as well as ones that form along channels through the nearby Canadian Arctic Archipelago7 (CAA), contribute to the cessation of the transport of this important ice-class out of the Arctic8. For the period 1997–2009, the southern arch formed most winters while the northern arch formed during ~50% of the winters9. During the winter of 2007, neither arch formed resulting in annual ice area and volume fluxes that were twice as large as the corresponding climatological means over 1997–20092.Along Nares Strait, the channel that separates north Greenland from Ellesmere Island, please refer to Fig. 11. In addition, climate models suggest that the area to the north of the Lincoln Sea will be the last to lose its perennial ice cover13 thus providing an important refuge, referred to as the Last Ice Area, for ice-dependent species15. The stability of these arches is a function of the thickness of the ice16 and there is a concern that the thinning of the Arctic ice pack may negatively impact their stability resulting in an acceleration in the loss of multi-year ice from the Arctic as well as impacting the ecosystems of the North Water Polynya and the Last Ice Area14.The cessation of ice transport down Nares Strait contributes to the formation of the Arctic’s largest and most productive polynya, the North Water, at its southern end in the vicinity of Smith Sound17, this arch failed to develop during the winters of 2018 and 2019. In contrast, we report that the southern ice arch was only present for a short period of time during the winter of 2018. The winter of 2019, like the previously documented winter of 20072, was one in which no ice arches formed along Nares Strait. We furthermore show that there has been a recent increase in both the ice area and ice volume flux along Nares Strait as compared to the period from 1997 to 20092. Over the period for which we have observations, 1997–2019, there has been a statistically significant trend towards shorter duration of ice arch formation each winter.We show that in addition to the previously identified early collapse of the northern ice arch in May 201717. Fig. 18. On May 8 .Finally, we assess the time evolution of the stability of the Nares Strait ice arches by combining their duration as previously reported31, on the east side of north Greenland, with typical annual ice area fluxes on the order of 900,000 km2. Although there has been a similar recent increase in ice area flux through Fram Strait, again indicative of a more mobile ice pack, there has been no corresponding increase in ice volume flux31. Given that the ice volume flux is the product of the ice area flux and the ice thickness, this implies that for the Nares Strait region the increase in ice area flux exceeds the reduction in thickness with the two compensating more or less for the Fram Strait region.The largest loss of Arctic sea ice occurs through Fram Strait14. In addition, a number of theoretical32 and observational17 studies have proposed that the stability of the Nares Strait ice arches decreases with thinning ice cover. These results are consistent with those presented herein all of which provide additional evidence of the changing nature of the Arctic as we transition to a thinner more mobile ice pack. Results of this study also highlight that with continued Arctic warming, ice arch stability in Nares Strait as well as throughout the adjacent CAA will decrease resulting in more frequent transport of Arctic Ocean multi-year to southerly latitudes7, that will have negative implications for the maritime industry34 as well as impacting food security and other traditional activities for indigenous communities in the Arctic35.Recent work indicates that ice motion in the Last Ice Area, that includes the Lincoln Sea, is increasing at twice the rate as the entire Arctic Ocean36 to restrict the southward flux of thick multi-year ice along Nares Strait. This allows the strong winds and ocean currents that occur in the vicinity of Smith Sound37 to advect thin ice away allowing the polynya to form. It follows that a weakening of the Nares Strait ice arches may impact the North Water Polynya leading to regional changes in primary and secondary production that will be felt throughout the entire food chainThe current configuration of the North Water Polynya, as a latent heat polynya, depends on the presence of the Nares Strait ice arches38. First, sea ice motion from each sequential pair of Sentinel-1 imagery (~0.5 to 1-day time separation) was determined using the Komarov and Barber tracking algorithm39. Sea ice motion was then interpolated to a 30 km buffer region surrounding the gate and sampled at 5 km intervals across. Considering that ice rapidly deforms as it is being funneled through Nares Strait we placed our gate farther north of Nares Strait than has been done previously2 to facilitate improved motion detection. The ice area flux (F) was calculated using: i is the ice concentration obtained from the closest Canadian Ice Service ice chart40 to the Sentinel-1 image date, ui is the ice speed normal to the flux gate at the ith location and Δx is the spacing along the gate (5 km). If we assume that the errors of the sea ice motion samples are additive, unbiased, uncorrelated, and normally distributed, then the uncertainty in ice area flux across the gate (σf) can be determined using the following equation: e is the error in ice motion of 0.43 km/day determined previously39, L is the width of the gate and Ns is the number of samples across the gate. For L=139 km and Ns=27 the uncertainty in ice area flux at our gate is ~±12 km2/day. On monthly or annual timescales, the uncertainty is close to zero.Annual (September to August) ice area flux through Nares Strait for 2016–2019 was determined using an established technique42. To account for this characteristic, which if unaccounted for may result in an overestimation of the significance42, we use is a non-parametric Monte Carlo technique where a large number, in this instance 100,000, of synthetic time series that share the same power spectrum as the original time series are generated. The distribution of the trends of these synthetic time series are used to estimate the significance of the trend in the underlying time series. By sharing the same spectral characteristics, one has greater confidence that they share the same background variability and one is not introducing a bias into the assessment of the statistical significance of the trend. To generate the synthetic time series, the Fast Fourier Transform (FFT) of the underlying time series is calculated. For each individual synthetic time series, the phase of the Fourier components are randomized and then the Inverse FFT is calculated41.Many geophysical time series are characterized by red-noise arising from temporal autocorrelation that results in power spectra that have elevated power at low frequencies


Neuronal circuits within the spinal dorsal horn play a crucial role in how we ultimately perceive sensory inputs, and disruption to these circuits can lead to altered sensation and chronic pain states. To understand how these circuits process sensory information in health and disease, it is necessary to identify the individual neuronal components, determine how they are connected, and define the functional significance of these pathways. Here, we provide an overview of current strategies used to better define interneuron populations and the circuits they form within the dorsal horn.1 and play critical roles in modulating modality-specific circuits to ultimately affect our perception of afferent input.22 These cells represent a potential target for pharmacological intervention to manage various forms of chronic pain, but to achieve this we must first define their contributions to distinct spinal circuits under normal conditions and determine how these change in pathological states. Given that dorsal horn interneurons are diverse in terms of their morphological, neurochemical, and functional properties, identifying a series of distinguishing features to characterise discrete populations can be challenging. In this PAIN Pictured article, we outline key features that can be used to define distinct interneuron groups and provide an example where this approach has helped identify a population of spinal interneurons that are implicated in the development of tactile allodynia.Interneurons account for 99% of all neurons in the spinal dorsal horn19 Both interneuron classes can be further subdivided into distinct subpopulations based on their morphological, electrophysiological, neurochemical, and genetic characteristics.24 For example, in lamina II of the rodent spinal cord, 4 morphologically distinct populations of neurons  have been described, although other cells that do not conform to these classes (unclassified neurons) are also relatively common.24 Islet cells are considered to comprise a subpopulation of inhibitory interneurons, whereas the remaining morphologies are common among excitatory interneurons.24Spinal interneurons can be subdivided into 2 principal classes based on their neurotransmitter content: excitatory interneurons release glutamate, whereas inhibitory interneurons use GABA and/or glycine. In both the rat and mouse, inhibitory interneurons account for approximately 25% of all neurons in laminae I and II and 40% of those in lamina III.16 Axoaxonic synapses are the anatomical basis of presynaptic inhibition and exert strict control on the passage of sensory information relayed at the first central synapse. Axon terminals from inhibitory interneurons often form synaptic triads by establishing axoaxonic synapses onto the central terminals of sensory fibres and also axodendritic synapses onto dendrites that are themselves postsynaptic to the same primary afferent terminal, providing a powerful mechanism to regulate afferent input in the dorsal horn.16 Anatomical features can therefore provide valuable insight into the role of individual cells in spinal circuits, but identifying the neuronal population that give rise to the various types of synapses in the dorsal horn remains challenging.Like neuronal morphology, synapses formed by excitatory and inhibitory interneurons show distinct ultrastructural features. Axon terminals from glutamatergic interneurons typically contain rounded agranular synaptic vesicles and form asymmetrical synapses onto cell bodies (axosomatic synapses), dendrites (axodendritic synapses), or dendritic spines (axospinous synapses). Axon terminals from inhibitory interneurons contain flattened (pleomorphic) synaptic vesicles and form symmetrical synapses onto cell bodies and dendrites primarily but can also form axoaxonic synapses onto the central terminals of most classes of sensory afferents (with the exception of peptidergic C fibres).17 These discharge patterns often correlate with cell morphology, where islet cells typically exhibit tonic firing or initial bursting, and vertical cells show delayed-firing patterns.24 As with morphology, however, action potential discharge classification requires caution as some responses fall outside the patterns commonly described.17 These response patterns can also vary depending on membrane potential,23 the laminae in which responses have been recorded,2 and whether recordings were performed in vitro or in vivo.6Electrophysiological properties are also used to distinguish dorsal horn neurons. For example, 5 distinct action potential discharge patterns in response to current injection are routinely described in lamina II neurons .24 whereas other approaches use neurochemical expression patterns to help define cells within this region. For example, various neuropeptides, calcium-binding proteins, enzymes, and amino acid transporters have helped define both excitatory and inhibitory interneuron subpopulations in the dorsal horn based on the neurochemical content.20 More recently, molecular and genetic profiling has broadened the spectrum of molecular markers that can be used to define distinct neuronal populations.18 When coupled with the increasing availability of different transgenic mouse lines, viruses, and experimental approaches to label, manipulate, and control these cells, researchers are now well placed to define spinal circuits responsible for acute and chronic pain.Attempts to identify distinct populations of dorsal horn interneurons have assessed correlations between morphological and electrophysiological properties,12 In this circuit, inhibitory interneurons act directly on the central terminals of both large- and small-diameter primary afferents, through axoaxonic inputs, to modulate input directly. Given that axoaxonic synapses have been established on most classes of afferent fibres,20 surprisingly little progress has been made in identifying the cells that give rise to these connections. We have recently combined the above approaches to identify parvalbumin-expressing inhibitory interneurons (iPVINs) as a source of axoaxonic input onto myelinated low-threshold mechanoreceptor afferents (ALTMRs). These iPVINs mediate both presynaptic inhibition of ALTMR terminals and postsynaptic inhibition of several populations of cells targeted by ALTMRs, including vertical cells.10 Vertical cells comprise a population of excitatory interneurons that relay information to spinoparabrachial projection neurons in lamina I5 but have also been proposed as a route through which ALTMR input can activate pain circuits under pathological conditions.25 Targeted manipulation of PVINs using chemogenetic, optogenetic, and cell-ablation approaches has established the functional significance of these cells13 and shows that a reduction in the inhibition they mediate results in the development of mechanical hypersensitivity. The precise mechanism underlying spinal disinhibition after peripheral nerve injury remains the subject of debate,25 but recent evidence implicates changes in the intrinsic excitability of iPVINs rather than a loss of their synaptic connections.4 Nonetheless, a reduction in spinal inhibition can unmask otherwise dormant circuits, and these can lead to aberrant activation of pain circuits.25 Together, these multidisciplinary studies identify iPVINs as critical components in microcircuits that gate ALTMR input under normal conditions13 and serve to present these cells as potential therapeutic targets to alleviate tactile allodynia.Current models of how interneuron populations modulate spinal sensory processing have their origins in Melzack and Wall's gate control theory of pain, where a spinal circuit that influences the relaying of pain signals to higher brain centres is described.The authors declare no conflict of interest but acknowledge funding provided by the NHMRC, Australia , the Hunter Medical Research Institute (B.A.G.), and the BBSRC (grants BB/J000620/1 and BB/P007996/1 to D.I.H.).


Non-invasive imaging techniques demonstrate that SSc-related digital ulcers can be hypoxic as well as poorly perfused.Dear editor, Systemic sclerosis (SSc)-related finger or toe  ulcers (DU) affect up to 50% of patients with SSc  underwent imaging of one finger ulcer. Images were taken to include the site of ulceration, adjacent skin) and a site away from the ulcer .Measurements of oxygenation were extracted from images taken by a bespoke multispectral imager. Broadband (white) light was shone onto skin and several images were taken over multiple wavelengths. The amount of light absorbed by de-oxyhaemoglobin and oxyhaemoglobin within the skin differs across wavelengths. Thus, de-oxyhaemoglobin and oxyhaemoglobin each have their own unique absorption spectrum, allowing the oxygenation levels to be calculated (as described previously ).Perfusion was measured using three imaging techniques: laser speckle contrast imaging , which images the upper levels of the cutaneous microcirculation, laser Doppler imaging , which images more deeply (both upper and lower microvascular levels) and thermography , which measures skin temperature; providing a proxy for superficial (microvascular) and deeper (macrovascular) tissue perfusion. The lesion area size was measured from laser Doppler images on accompanying grey-scale images. A Spearman’s rho test was used to assess correlations. This study complied with the Declaration of Helsinki and was approved by the NW Research Ethics Committee 6. All participants gave written consent.vs distant sites; U/D vs A/D, P = 0.046. Perfusion as measured by laser speckle contrast imaging was decreased in the ulcer vs distant site for 11% (1/9) and all adjacent sites vs distant sites were increased (9/9); U/D vs A/D, P <0.0001. Perfusion measured by laser Doppler imaging was lower in 44% (4/9) of ulcer sites vs distant sites and perfusion was higher in 78% (7/9) of adjacent sites vs distant sites; U/D vs A/D, P =0.021. Thermal imaging identified 44% (4/9) of ulcer sites as lower in perfusion than the distant sites and 67% of adjacent sites had increased perfusion as compared with the distant site; U/D vs A/D, P =0.026.Eight fingertip and one extensor DU were imaged. A region of interest was defined at the site of the ulcer, in an adjacent area of skin and at a distant area, away from the ulcer. The distant site was assumed to be unaffected by microvascular changes associated with the lesion. The ratios of ulcer/distant (U/D) and adjacent/distant (A/D) express the differences at the ulcer and adjacent sites compared with an ‘unaffected’ site. Data are shown in 2. Oxygenation was associated with perfusion as assessed by laser Doppler imaging  but not as assessed with laser speckle contrast imaging  or with thermography . Neither oxygenation , nor perfusion  were associated with the size of the lesion.The median lesion area was 3.4 [3.25–4.95] cmvs A/D), suggesting ulcers affect both superficial and deeper tissue perfusion. Oxygenation showed a strong relationship to perfusion as measured by laser Doppler imaging, suggesting that hypoxic ulcers are poorly perfused. As well as providing insights into pathogenesis, measuring ulcer oxygenation and perfusion may provide a biomarker of ulcer healing for novel therapies.In conclusion, oxygenation was reduced for some but not all ulcers, offering support to our first hypothesis, although we acknowledge that the number of ulcers studied was small. Oxygenation was increased in the adjacent areas of all ulcers indicative of possible inflammation. All perfusion imaging techniques were sensitive to differences in perfusion between the ulcer site and adjacent and distant areas when considering the distant site (U/D


Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales.Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 °C (interquartile range: 0.39−0.46 °C) at a CO The disintegration of cryosphere elements such as the Arctic summer sea ice, mountain glaciers, Greenland and West Antarctica is associated with temperature and radiative feedbacks. In this work, the authors quantify these feedbacks and find an additional global warming of 0.43°C. If this trend continues, the Arctic could become ice-free in summer for the first time within the 21st century. Projections with CMIP-56 (Coupled Model Intercomparison Project Phase 5) models show that this could be the case as early as 2030 to 2050 for higher emission scenarios such as RCP8.5 (Representative Concentration Pathway)7. Some GCMs  show an ice-free Arctic for the first time within this century also for the moderate emission scenarios at a warming of 1.7 °C above pre-industrial9. Furthermore, observations reveal that the Arctic summer sea ice declines faster than expected in experiments from GCMs1.From the late 1970s to the mid-2000s, the Arctic summer sea ice area has declined by more than 10% per decade, as satellite measurements reveal10. This translates, in the same time span, into a loss of 21% of the glaciated volume of mountain glaciers worldwide, excluding (Sub-)Antarctic peripheral glaciers, as found in model simulations11. During this time, it is estimated that approximately 600 glaciers have disappeared and many more are likely to follow in the future . 36  ±  8% of today’s glacier mass is already committed to be lost in response to past greenhouse gas emissions12 and it has been found that many mountain glaciers are currently in disequilibrium and will be subject to further ice loss13.At the same time, mountain-glaciers world-wide have retreated, with an average weight equivalent ice loss of approximately 250 ± 30 Gt per year between 1901 and 20095. With progressing global warming, ice loss from the polar ice sheets and subsequent sea-level rise is expected to further increase15. Beyond a critical temperature threshold, large parts of the Greenland Ice Sheet might melt, accelerated by positive feedbacks such as the ice-albedo and melt-elevation feedbacks17. From model simulations, this threshold temperature is suggested to range between 0.8 and 3.2 °C above pre-industrial levels18.Moreover, both the West Antarctic and the Greenland Ice Sheet have lost mass at an accelerating pace in the past decades19. Similar dynamics might be induced in other parts of the Antarctic Ice Sheet and could eventually lead to its complete disintegration under unmitigated climate change20.Parts of the West Antarctic Ice Sheet might already have crossed a point of instability: the grounding lines of several glaciers in the Amundsen basin are rapidly retreating and have likely become unstable, causing sustained ice discharge from the entire basin which could lead to more than 1 m of global sea-level rise21, with observable impacts on the cryosphere elements mentioned above6. It has also been suggested that these regions are likely to change dramatically with ongoing climate warming and some of these changes are suspected to possess some degree of irreversibility23.Anthropogenic climate change has already caused a rise in global mean temperature (GMT) by 0.9 °C comparing 1850–1900 to 2006–201523. The disintegration of these elements is associated with feedbacks that impact back on GMT, for instance via a change in albedo, clouds or lapse rate, among others, which has not been quantified comprehensively so far. Therefore, we assess the additional global warming caused by disintegration of the Greenland Ice Sheet, the West Antarctic Ice Sheet, the mountain glaciers and the Arctic summer sea ice. Although the Arctic summer sea ice is implemented in more complex Earth system models and its loss part of their simulation results (e.g. in CMIP-5), it is one of the fastest changing cryosphere elements whose additional contribution to global warming is important to be considered. Therefore, we compute and separate its contribution to GMT increase. On the other side, the temperature feedbacks of ice sheets like Greenland, West Antarctica and mountain glaciers are not yet fully integrated in assessments such as CMIP-5.Following these recent developments of the cryosphere components, it seems possible that they might be lost at lower temperatures than commonly thought, potentially as low as 1.5 °C above pre-industrial levels25 because it is computationally efficient and allows a systematic analysis of the decay of the cryosphere components. CLIMBER-2 includes atmosphere, ocean, sea ice, vegetation and land-ice model components and has been applied extensively to understand past and future climate changes27.We base our simulations on the Earth system model of intermediate complexity, CLIMBER-228 (see “Methods”), we compare the long-term GMT change in idealised scenarios, where the cryosphere elements are removed, to scenarios where they remain intact. The uncertainty in the additional warming in our simulations is constrained by the uncertainty of the feedback strength in the GCM simulations which we used to mimic the more complex behaviour of GCMs28  is lowered to average values for open ocean waters instantaneously similar to Blackport and Kushner31. Here, we focus on the purely radiative effects and neglect freshwater contributions to feedbacks and warming. Thus, our estimates are long-term equilibrium responses when the large ice masses are disintegrated. However, transient warming responses would be reduced due to freshwater input from the West Antarctic and Greenland Ice Sheet on centennial time-scales35.In this study, we find that global warming is amplified by the decay of the Earth’s cryosphere as expected from theory and quantify the contribution of each of the four cryosphere components. We further separate the GMT response into contributions from albedo, lapse rate, water vapour and clouds in terms of perturbation of the net radiation at the top of the atmosphere2 concentrations ranging from the pre-industrial 280 ppm up to 700 ppm and run the model forward until it reaches equilibrium. If not stated otherwise, our findings are shown for a reference simulation at a fixed CO2 concentration of 400 ppm in equilibrium after 10,000 years. 400 ppm corresponds to an equilibrium GMT increase of 1.5 °C above pre-industrial in CLIMBER-2 simulations. Upon this, we evaluate the additional regional and global warming caused by the large-scale loss of the Arctic sea ice during summer, mountain glaciers, and the polar ice sheets. While this ad-hoc loss of the ice masses poses a hypothetical scenario, it allows us to separate the additional warming through the ice-climate feedbacks from other effects. In our experiments, we report the median value of the ensemble and the brackets represent the interquartile range unless stated otherwise.We consider several different climate scenarios, with atmospheric COIn our simulations, we find that global warming is increased by the decay of the Earth’s cryosphere. The disintegration of the Arctic summer sea ice and the retreat of mountain glaciers, the Greenland and the West Antarctic Ice Sheets together cause an additional GMT increase of 0.43 °C (0.39–0.46 °C) for a baseline-scenario of 1.5 °C warming above pre-industrial levels, which translates into an additional warming of 29% (26–31%).37. Local warming around the cryosphere components is up to 5 °C stronger, particularly around Greenland and West Antarctica . The actual minimal sea ice cover observed by NERSC  as an average area from 1979 to 2006 is on the order of 5.5–6.5 × 106 km2 which would correspond to a warming of approximately 0.15 °C in our simulations 45. We find a slightly higher value of 0.49 W/m2 for albedo plus clouds value when the Arctic summer sea ice is removed , but we can only make this statement for the combined feedbacks of lapse rate and water vapour since we do not separate them in our analysis.In Supplementary Fig. Our results concern short and long term effects on GMT due to the disintegration of cryosphere elements which experienced significant changes within the last decades and are likely to also change strongly in the future due to global warming.2 emission scenarios up to 700 pm and corresponds to 29% extra warming relative to a 1.5 °C scenario.On shorter time scales, the decay of the Arctic summer sea ice would exert an additional warming of 0.19 °C (0.16–0.21 °C) at a uniform background warming of 1.5 °C (=400 ppm) above pre-industrial. On longer time scales, which can typically not be considered in CMIP projections, the loss of Greenland and West Antarctica, mountain glaciers and the Arctic summer sea ice together can cause additional GMT warming of 0.43 °C (0.39–0.46 °C). This effect is robust for a whole range of CO49. Furthermore, it has been shown for WAIS and GIS that transgressing their critical thresholds is likely not reversible due to hysteresis effects51.In fact, some feedbacks will also be at play before the complete disintegration of the large ice sheets, for instance due to increased ice-drainage from the Amundsen region in West AntarcticaThe additional commitment to global warming that we study here represents a long-term, mean-field effect which is separated from possible direct interactions between the elements such as the freshwater input into the thermohaline circulation from the large ice sheets. In other words, the disintegration of the ice sheets has a direct increasing temperature impact on the GMT via the feedbacks quantified here.25 on a coarse spatial resolution of 10 × 52° (lat × lon) resolution. CLIMBER-2 includes a 2.5-D dynamical-statistical atmosphere and a multi-basin, zonally averaged ocean model including sea ice as well as a dynamic model of the terrestrial biosphere. CLIMBER-2 also includes a model for ice sheets, a global carbon cycle model and an atmosphere surface interaction coupler, which are not used in this study since ice sheets and atmospheric CO2 are prescribed in our experiments. In CLIMBER-2, changes in the cloud fraction are possible. Apart from that, cloud top height can change following changes in the height of the tropopause. The cloud optical thickness parameterisation includes a dependence on the cumulus cloud fraction in addition to a prescribed increase of optical thickness with latitude. With this representation of clouds, CLIMBER-2 is able to reproduce the planetary albedo as observed from CERES  CLIMBER-254. We also included a mountain glacier mask with data from the Randolph glacier inventory55. Since we are interested in the climatological behaviour of the disintegration of one or more of the cryosphere elements, we artificially change the setup of CLIMBER-2 depending on which element we remove: In case of WAIS and GIS, the topography of the ice sheet itself is removed together with the ice sheet as the height of the ice sheet is several thousand metres thick and thus might play an important role on the feedbacks. The albedo is replaced by the albedo of bare land or ocean (where appropriate) at first, but can then change freely into any kind of vegetation or snow cover during the simulation run. For our simulations, isostatic rebound is neglected.In preparation of the model runs, we set up the ice sheets inbuilt in CLIMBER-2. For distinguishing the West and East Antarctic Ice Sheet, we created a mask based on the Antarctic drainage basins30, who also reduce albedo values of the sea ice instantaneously. They do this for the whole year and all sea ice compared to our setup, where the albedo is changed only in the northern hemisphere in the summer months.For the Arctic summer sea ice and the mountain glaciers, the topography is not taken into account as either the height of the ice or the spacial extent of high thickness regions is very low. To remove the Arctic summer sea ice during the summer months , the surface covered by sea ice is darkened and the albedo in this region is replaced by the ocean albedo. With this procedure the energy conservation law is not violated since the ice is not just removed and still retains its function as boundary layer between ocean and atmosphere. Thus we are able to compute the effect of summer sea ice in an energetically self-consistent manner. Note that CLIMBER-2 is mass conserving. Our procedure is similar to the experimental setup of Blackport and Kushner28 using an ensemble of GCMs. Equally, this could have been done with the feedbacks stated in the IPCC assessment report 5 (AR5), but changes in the reported feedback strengths are small except for the cloud feedback which is less well constrained in AR5 . Thus, our ensemble and our results can be expected to stay the same. The fast climate feedbacks include the water vapour, the lapse rate, the cloud and the albedo feedback. Each of our 39 ensemble members, that we end up with, is constructed from a pair of simulations: one control run at 280 ppm and one perturbed run at a CO2 doubling of 560 ppm. We then compute the magnitude of the fast climate feedbacks between these pairs of runs  are determined by diagnostically rerunning of the model radiation code.To emulate the behaviour of more complex general circulation models (GCMs) we created a model ensemble by perturbing several parameters with the target to cover the range of strength of the fast climate feedbacks found by Soden and Held2/K. These two feedbacks are evaluated together as they are correlated negatively57. The cloud feedback is supposed to range between 0.3 and 1.1 W/m2/K and the albedo feedback between 0.2 and 0.45 W/m2/K. Furthermore, we put a constraint on the minimal summer sea ice cover in the northern hemisphere to 1.5–6.5 km2  to possess an equilibrium climate sensitivity above 1.5 and below 4.5 °C, where the equilibrium climate sensitivity is the global warming per doubling of atmospheric CO57  influencing lapse rate together with the water vapour, cloud and albedo feedbacks similarly to Deimling et al.We used these 39 calibrated runs, which also represent the uncertainty of our results, as initialisation for our large-scale ensemble simulations. For each of the cryosphere elements, i.e., WAIS, GIS, Arctic summer sea ice and mountain glaciers, as well as all together, we performed the following experiments: (i) Control runs: the respective cryosphere element(s) is/are kept and (ii) experiment runs: removed cryosphere element(s).2 concentrations as external forcing. We chose the CO2 concentration parameter since it is the one which is most probably increasing in future climate change scenarios. Each of the experiments is performed as a long term equilibrium run for 10,000 simulation years with today’s boundary conditions, i.e., astrophysical parameters like eccentricity and obliquity, and fixed CO2 concentration. The results are taken as the mean over the last 4000 simulated years since this cancels out minor fluctuations in the equilibrium state. In the end we subtract the experimental run (ii) from the control run (i) to retrieve the temperature difference. Since we are reporting these differences between perturbed  and control run throughout the main manuscript, the uncertainties given as interquartile ranges are small, also compared to the calibration  and (ii) for different atmospheric COSupplementary InformationPeer Review File


Agricultural soils are a likely sink for nanosilver due to its presence in agrochemicals and land-applied biosolids, but a complete assessment of nanosilver’s effects on this environment is lacking because the impact on the natural soil microbiome is not known. In a study assessing the use of nanosilver for phytopathogen control with maize, we analyzed the metatranscriptome of the maize rhizosphere and observed multiple unintended effects of exposure to 100 mg kgWe found several unintended effects of nanosilver which could interfere with agricultural systems in the long term. Firstly, the archaea community was negatively impacted with a more than 30% decrease in relative abundance, and as such, their involvement in nitrogen cycling and specifically, nitrification, was compromised. Secondly, certain potentially phytopathogenic fungal groups showed significantly increased abundances, possibly due to the negative effects of nanosilver on bacteria exerting natural biocontrol against these fungi as indicated by negative interactions in a network analysis. Up to 5-fold increases in relative abundance have been observed for certain possibly phytopathogenic fungal genera. Lastly, nanosilver exposure also caused a direct physiological impact on maize as illustrated by increased transcript abundance of aquaporin and phytohormone genes, overall resulting in a stress level with the potential to yield hormetically stimulated plant root growth.This study indicates the occurrence of significant unintended effects of nanosilver use on corn, which could turn out to be negative to crop productivity and ecosystem health in the long term. We therefore highlight the need to include the microbiome when assessing the risk associated with nano-enabled agriculture.Video Abstract The development and application of nanotechnology has impacted numerous disciplines across a broad array of sectors, including communications, medicine, energy, and agriculture. In order to ensure the sustainable and optimal application of these products and materials, it is important to thoroughly understand both the risks and benefits associated with their use. However, the diverse and highly complex interplay of biotic and abiotic factors in environments such as soil serve as a major confounding factor to efforts designed to understand the potential negative or positive impacts associated with nanomaterials and nano-enabled products. Studies in artificial in vitro conditions or with a single species cannot be easily extrapolated to natural multispecies conditions. The rhizosphere or soil root-zone is a prime example of such a complex environment. Both prokaryotic and eukaryotic microorganisms reside in root-affected soil, and these groups of microbes can interact directly or indirectly with each other or with the plant in ways that may be beneficial, antagonistic, or neutral –3. HowevSilver nanoparticles are among the most widely used nanomaterials, largely due to their known antimicrobial properties which make them highly valuable in textiles, food packaging, cosmetics, medicinal products, and many other applications , 6. ThisIn this study, we grew maize to maturity in nanosilver-containing soil and analyzed a range of endpoints, including plant biomass, tissue element content, and the rhizosphere metatranscriptome. The primary benefit of a metatranscriptomic analysis is that it offers an opportunity to investigate all active organisms in the corn rhizosphere as a function of nanosilver exposure. Specifically, the microbial community structure and the expressed genes of both prokaryotic and eukaryotic microorganisms can be studied, as well as the expressed genes from maize roots themselves. This allows to provide new information on nanosilver’s direct and indirect effects on biota at the individual and community level, as well as on important processes in the complex soil ecosystem. Hence, this creates a study framework where multiple interactors of a natural system are studied, getting a step closer to the holistic view of nanosilver toxicology in a natural setting which is alluded to above. Because of the importance and ubiquity of maize growth, the data provided on this model crop has relevance to both nanotoxicology and to nano-enabled agriculture. Also, similar mechanisms of response can be expected in the rhizosphere of other crops, extending the results of this study beyond this single species.p = 0.1). Nonetheless, taxonomic analysis of the bacterial communities clearly indicates already at the phylum level that different bacterial groups responded differently to nanosilver exposure  in the active rhizosphere microbiome, Bacteroidetes, Alphaproteobacteria, Gammaproteobacteria, and Acidobacteria were all increased in response to nanosilver exposure. Other groups, such as Actinobacteria and Deltaproteobacteria, showed a trend of decrease, although the effect was not statistically significant. Figure Acidimicrobiales, Solirubrobacterales, and Pseudonocardiales, that show significant decreases due to nanosilver exposure. This lower taxonomic level also indicated that important bacteria orders such as Fimbriimonadales, Chthonomonadales, Verrucomicrobiales, Myxococcales, Synthrophobacterales, and Rhodobacterales showed significant decreases.Nanosilver’s antimicrobial properties are expected to affect the microbiome, and the bacterial community composition in the maize rhizosphere does clearly reflect this. Indeed, alpha diversity analysis indicates a significant decrease in richness Fig. b. Howeveure Fig. . While Cp < 0.05) different abundance in rhizosphere soil. Gene transcripts of P-type ATPases, Cu+-exporting ATPases, and Cu(I)/Ag(I) efflux system proteins showed increases in abundance. Some of these are related to bacterial groups that increased in abundance due to nanosilver, such as Proteobacteria, Bacteroidetes, and Acidobacteria, as well as to bacterial groups that decreased due to nanosilver, such as Actinobacteria and Planctomycetes. Hence, regardless of their final decrease or increase in abundance in response to nanosilver exposure, diverse bacterial groups initiate defense responses. However, the groups that thrive under nanosilver exposure display increased abundances of additional important genes such as cation efflux system CzcA, copper-resistance protein CopA, and Copper-resistance protein K. These additionally expressed genes could explain the advantage that these bacterial groups have over others which do not express these genes and decrease in overall abundance. Such copper and other metal resistance genes seem to be similar and evolutionarily linked to silver resistance systems such as the sil silver-resistance system [sil system often is associated with the incompatibility group H1 (IncH1) plasmid pMG101, which is transferred horizontally and confers resistance to Gram-negative but not to Gram-positive bacteria [Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes in nanosilver-exposed soil. Groups that cannot rely on the defensive action of this silver resistance system will be at a disadvantage, and if these organisms are plant-beneficial microbes, then plants could also be negatively affected.The impact of nanosilver on the bacterial community is also illustrated by the functional characterization of the metatranscriptome. Table e system . The silbacteria , 14. Thip = 0.1). Community composition at the phylum level showed a significant increase in abundance of Ascomycota, which appear to benefit from the presence of nanosilver in soil . These negative interactions involved a large number of orders which displayed an increased abundance in the nanosilver-exposed rhizosphere microbiome. Hence, according to this network, the increased abundance of certain groups upon nanosilver exposure was not a direct consequence of nanosilver. Rather, these groups benefited from the negative effect of nanosilver on certain other groups which are involved in negative interactions with them. A wide range of microbial phyla were included in this positively affected group. Among these, most notable are the fungal orders which harbor well-known fungal pathogens, as described previously: Diaporthales, Eurotiales, and Botryosphaeriales. This negative interaction of certain microorganisms with phytopathogens suggests the presence of natural biocontrol. When evaluating the role of the rhizosphere microbiome in plant health, biocontrol of phytopathogens is always of high importance [Actinobacteria are often increasingly abundant in the rhizosphere of maturing plants [Actinobacteria have focused on Streptomyces, illustrated by the fact that this group is responsible for over 80% of all known antibiotics of actinobacterial origin [Streptomycetales are the only Actinobacteria with increased abundance in the rhizosphere under nanosilver exposure. As such, only non-streptomycete Actinobacteria could be involved in the phytopathogen proliferation. Next to Streptomycetales, other Actinobacteria are also recognized as a valuable topic for biocontrol-research, as has been highlighted for Actinomycetales [Actinobacteria orders could be involved here. This includes orders within the class Actinobacteria, e.g., Corynebacteriales and Bifidobacteriales, and orders in other classes, such as Rubrobacterales and Solirubrobacterales. Another interesting group of bacteria involved in the negative interaction with phytopathogens are Myxococcales. These bacteria are also known for their production of a wide range of antibiotics and lytic enzymes, and are often considered to be important to biocontrol [Rhodobacterales are another well-studied group of biocontrol agents. All of these bacterial groups could play an important role in limiting maize phytopathogen activity, and importantly, are all reduced by nanosilver exposure. These groups may potentially be joined by other bacteria that can negatively impact phytopathogen activity but whose role is unknown due to a lack of culturability. Biocontrol agents are of high value in both natural ecosystems and in agricultural crop production, and nanosilver-induced disturbance of this native protection system could have significant ecologic and economic consequences.Network analysis based on co-occurrence and co-exclusion interactions enabled differentiation between groups which play an important role in the rhizosphere microbiome by influencing other groups from those that act more individually. As shown in Fig. ibiotics  and hencportance , 17. Cerportance . Our datportance  that is portance . A possig plants  and are g plants . The majl origin . In the ycetales , and ourocontrol , 25. Rho+-exporting ATPase  and 0.42 mg kg−1, respectively, while values for the non-exposed plants were nearly non-detectable  in roots under nanosilver exposure from 1683 to 1115 mg kg−1, root P concentration significantly increased (p = 0.002) from 692 to 1053 mg kg−1 and root K concentration showed no effect with values stable around 7800 mg kg−1. A different pattern emerged in the shoots; although the increased P concentration was still evident (p = 0.003) with values of 1612 versus 494 mg kg−1, the statistical significance of the Fe decrease was lost, although a decrease from 435 to 283 mg kg−1 was evident. In addition, the K concentration exhibited a statistically non-significant trend of increase (p = 0.12) from 1290 to 1725 mg kg−1. These changes in nutrient content could be attributed to a variety of causes, including a direct molecular effect of nanosilver on these enzymes or indirectly as a plant response to physiological changes from the exposure.Nanosilver exposure seems to also stress maize indirectly by increasing the abundance of potentially phytopathogenic fungi. A possible defense response of maize to phytopathogen infection can be seen in the induced transcription of genes involved in the production of beta-glucosidases and phenylpropanoids. Although not definitive, these findings could indicate a significant additional burden on maize grown in nanosilver-containing soil. Nonetheless, the findings certainly demonstrate that maize responds at the molecular and biochemical level to nanosilver exposure. The diversity of these physiological responses is also illustrated by changes in plant gene expression related to phytohormones and nutrient balance Table . Plant hp = 0.046) than the control plants, increasing from 9.8 g to 12.3 g. The shoot biomass was approximately 23 g and remained unaffected by exposure; the shoot/root-mass ratio decreased from 2.3 to 1.9, although the effect was not statistically significant. Although most studies on nanosilver exposure highlight a neutral to negative effect on plant growth, our results are not the first indication of a nanosilver-induced plant biomass increase [Overall, it is clear that there are a number of diverse ways through which nanosilver directly or indirectly affects maize, and ultimately this seems to induce an increase in root biomass Fig. . Maize pincrease . We did increase . It has increase . Hence, increase . In addiincrease . Hence, Using the extensive information, the rhizosphere metatranscriptome has to offer, we show that soil borne nanosilver has various unintended effects on maize and its rhizosphere microbiome. On the prokaryote side, nanosilver can interfere with the nitrogen cycle due to a decrease in abundance of archaea taking place in the process and can potentially compromise natural biocontrol systems because of a decrease in abundance of bacterial groups with a biocontrol function. This latter effect can yield an increase in phytopathogen activity, instead of the intended decrease. Nanosilver also induces direct stress on the maize plants, likely through oxidative stress and aquaporin interference. Together, these indirect and direct effects on maize suggest that the observed increase in root biomass, which could be considered a positive outcome, is the result of hormetic growth stimulation that is unlikely to be sustainable in the long term. Hence, the overall balance suggests that the application of nanosilver in agriculture comes with significant unintended effects which could turn out to be negative for crop productivity and ecosystem health in the longer term. Therefore, it seems essential that these microbiome-related processes are included when assessing the risk associated with nanosilver use in agriculture.−1 and an effective cation-exchange capacity (CEC) of 20.7 meq/100 g. After collection, the soil was sieved to 6 mm and homogenized. Zea mays variety LG 30.223 seeds were acquired from LimaGrain Belgium. Soil nutrient content was augmented by fertilization until conditions favorable for maize cultivation were reached: 106 mg N g−1 soil, 34 mg P g−1 soil, 31 mg K g−1 soil, and 15 mg Mg g−1 soil. Maize plants were grown individually in 10 L-pots, each pot containing 10 kg of soil. Three replicate pots contained nanosilver at 100 mg kg−1, which was added by mechanical mixing for 5 min. This nanosilver concentration was established in earlier research, because it provides a baseline response in the system and takes into account the possibility of nanosilver accumulation in agricultural soils due to the application of biosolids and nano-enabled agrichemicals [Uncoated silver nanoparticles  were obtained in solid form from US Research Nanomaterials, Inc., Houston, TX, USA. Particle zeta potential and hydrodynamic size were characterized in 500 mg/L solutions by dynamic light scattering (DLS) on a zetasizer . The average size for AgNP is 259.7 nm ± 10.05), and the zeta potential is − 30.3 mV (± 2.71). The particles were also characterized by transmission electron microscopy (TEM) (Hitachi HT7800). TEM indicated a wide variety of sizes due to clustering of the original particles of ca. 20 nm . Samples with Ag content below the ICP-OES limit of quantification were subsequently analyzed by Inductively Coupled Plasma-Mass Spectrometry .At harvest, the wet and oven-dry biomass of root and shoot tissues were determined. For plant element content analysis, oven-dried samples of roots and shoots (approximately 0.5 g) were digested in 50 ml polypropylene digestion tubes with 5 ml of concentrated nitric acid at 115 °C for 45 min using a hot block . A small volume of HTM RNA assays ; these data were used as an indicator for the need to repeat failed extractions.Total RNA was extracted from the rhizosphere soil samples using the PowerSoil® RNA Isolation Kit , according to the manufacturer instructions. Starting material for every extraction was 6 g of soil. Extracted RNA was additionally purified using the NucleoSpin® RNA kit , including DNase-treatment according to the manufacturer’s instructions. RNA integrity, purity, and concentration were confirmed by ExperionSequencing was performed by Macrogen . Libraries were constructed using the Illumina TruSeq Stranded Total RNA kit  without rRNA depletion or mRNA enrichment. Illumina HiSeq4000 paired-end sequencing 2 × 100 bp) resulted in at least 35 million high-quality reads per library (Table  × 100 bp−1 silver nanoparticles after 117 days of growth and exposure.Basic composition of the metatranscriptomes obtained from maize rhizosphere soil with or without 100 mg kghttp://www.bioinformatics.babraham.ac.uk/projects/fastqc). Based on the FastQC quality report, the Kraken pipeline [E value cut-off of 10−3. The resulting alignments were annotated to the InterPro2GO [Raw sequencing reads were controlled for quality using FastQC version 0.10.1  based on Bray-Curtis dissimilarities were performed and plotted for the archaea, bacteria, and fungi communities individually, and the separation between the control and the nanosilver-exposed treatment was statistically evaluated by the use of analysis of similarity (ANOSIM). The relative abundance of individual taxa was analyzed for statistically significant differences between the two treatments (control vs. nanosilver-exposed) using the Bioconductor packages phyloseq [p values < 0.05 (using the Benjamini and Hochberg procedure). Functional annotations extracted from MEGAN6 were statistically analyzed using DESeq2 version 1.14.1, also by means of the Wald test and adjusted p value < 0.05 (Benjamini and Hochberg) considered as statistically significant.The taxonomic community compositions were exported from One Codex for further analysis. Richness and Shannon diversity of archaea, bacteria, and fungi separately were calculated for the control and nanosilver-exposed conditions. Differences between the two treatments for these parameters were analyzed using phyloseq  version phyloseq  version p values were used as a cut-off value at 0.01. The resulting network was visualized in Cytoscape.Network analysis of the taxonomic microbial community compositions was performed with the Cytoscape  version Additional file 1. Transmission electron microscope image of the silver nanoparticles used in the study. Nanoparticles were obtained in solid form from US Research Nanomaterials, Inc. , and were applied to soil in this form.