Many freshwater environments experience dramatic seasonal changes with some systems remaining ice-covered for most of the winter. Freshwater systems are also highly sensitive to environmental change. However, little is known about changes in microbial abundance and community composition during lake ice formation and times of persistent ice cover. The goal of this study is to characterize temporal dynamics of microbial communities during ice formation and persistent ice cover. Samples were collected in triplicate, five days per week from surface water in the Keweenaw Waterway between November and April. Environmental conditions along with microbial abundance and microbial community composition was determined. Distinct community composition was found between ice-free and ice-covered time periods with significantly different community composition between months. The microbial community underwent dramatic shifts in microbial abundance and diversity during the transitions into and out of ice cover. The richness of the microbial community increased during times of ice cover. Relatives of microbes involved in nitrogen cycling bloomed during times of ice cover as sequences related to known nitrifying taxa were significantly enriched during ice cover. These results help to elucidate how microbial abundance and diversity change over drastic seasonal transitions and how ice cover may affect microbial abundance and diversity. These strong perturbations have the potential to dramatically alter the microbial community composition during times of ice cover. Recent advances in sequencing technologies have provided unprecedented insights into microbial community diversity and dynamics. However, much still remains to be known about the dynamics of microbial communities during times of ice formation and persistence of lake ice.Microbes in aquatic environments are drivers of many biogeochemical cycles. Many temperate freshwater ecosystems experience dramatic seasonal variation with some environments remaining ice-covered for most of the winter2. Despite the dramatic change in environmental conditions from ice-free to ice-covered times, there is limited information regarding the impact of ice cover on microbial community composition in freshwater environments. Changes in microbial activity during ice-covered periods have implications on the ecosystem function and biogeochemical processes in these settings4.While lakes and other freshwater systems represent a small portion of the total water on earth, they are integral to ecosystem function and biogeochemical cycling. Microbial community composition, activity, and function have been shown to change seasonally in freshwater settings1. Temperature is known to affect rates of biological reactions5. As temperatures are lower during times of ice cover compared to ice-free periods, it is expected that microbial activity would be lower. However, many microbes including psychrophilic and psychrotolerant microbes have adapted for growth under cold conditions and maintain high enzymatic activities and growth rates6.Factors such as temperature, salinity, and dissolved oxygen may all act as limiting constraints on microbial activity and thus impact microbial diversity. During times of ice cover there are decreased temperatures, limited nutrient inputs, and low light levels7. Additionally, as ice and snow accumulate at the surface of the lake, the extent of penetration of photosynthetically active radiation (PAR) into the underlying water is decreased8. This decrease in PAR can impact the activity of phototrophs during times of ice cover, and alter the primary productivity during ice cover. Despite lower light levels during ice cover, many systems experience routine under ice algal blooms, which have been shown to dramatically alter the microbial community composition following the algal bloom10. Additional work has shown that the extent of ice cover can strongly affect the phytoplankton and bacterial communities11.As nutrients are often the limiting factor for microbial growth in these systems, the altered nutrient regime that occurs during times of ice cover may select for distinct populations capable of growth under nutrient limited conditions15, lakes16, rivers and streams18. These reports indicate that there was a distinct microbial community composition in different seasons. In many cases, this seasonal variation exhibits reproducible and predictable patterns in both the oceans and lakes19. Higher resolution variability on a day-to-day basis has been more finely investigated in marine settings20 with a few time series studies in freshwater systems21. These studies in the oceans have shown that there were dramatic and rapid shifts in the marine microbial community composition following seasonal change and in the days following phytoplankton blooms20. Time series of microbial community composition in freshwater lakes has shown that there is surprising variation in the microbial community between years21. These studies have also demonstrated that extrinsic factors such as environmental conditions play a role in determining the microbial community composition and providing some synchrony to the system22. In many freshwater and coastal systems, seasonal differences have been linked to differences in organic matter and nutrient inputs17. Biological interactions were also shown to be important in controlling the bacterial community composition of several temperate lakes during a time series study22. Despite our growing knowledge of temporal variation in freshwater microbial communities, very little is known about the stability of freshwater microbial communities on daily timescales, especially during the formation and persistence of lake ice.Microbial communities are also known to be highly dynamic, with community changes on the timescales of days to months to seasons. Seasonal changes in microbial community composition have been studied in the oceans23. The Keweenaw Waterway experiences ice cover for approximately 3 months out of the year. Water samples were collected on a daily basis enabling a detailed look at the extent of change that a microbial community undergoes during this dramatic seasonal change. We expected there would be limited change in the microbial community during times of ice cover due to the stability of environmental conditions. We additionally, expected that microbial abundance and diversity would decrease during winter months. This study advances our understanding of the microbial community dynamics and diversity in freshwater systems that experience seasonal ice cover and opens the way for more targeted studies investigating the biogeochemical implications of these changes under lake ice.The goal of this study was to understand the temporal dynamics of microbial community diversity before, during, and after ice-cover using high-resolution time series sample collection in a freshwater lake. The fresh water system chosen was the Keweenaw Waterway located in the Upper Peninsula of Michigan adjacent to Michigan Technological University. The Keweenaw Waterway is primarily fed by Portage Lake with some inputs from Lake SuperiorWater temperature along with other physical and chemical measurements , dissolved oxygen, pH, and ORP) were measured from surface water at the time of sampling during this time series . The temperature consistently dropped until ice formation, at which point, the surface water temperature remained constant throughout the winter at approximately 0 °C Fig. . A sligh6 copies per ml of lake water, and the average abundance of bacterial 16S rRNA gene copies across the time series were found to be 8.52 × 107 copies per ml. The average abundance of archaea during ice-free times was 6.35 × 106 copies ml−1 whereas in ice-covered samples it was 8.62 × 106 copies ml−1. The average bacterial abundance in ice-free conditions was 1.26 × 108 copies ml−1 and during ice cover was 3.3 × 107 copies ml−1. A Kruskal-Wallis test was performed on log transformed abundance data to determine if there was a significant difference in the bacterial and archaeal abundance in ice-free compared to ice-covered samples  . Furthermore, there are temporal changes in the microbial community that occurred throughout the year with a significant difference in the microbial community composition between months of the year . To better understand the role of environmental conditions in explaining the microbial diversity, we fit the measured environmental variables to the NMDS of weighted unifrac distances . The environmental conditions  explained about 17% of the variance (adjusted R2 = 0.174).Multivariate analysis was performed in order to understand changes in the microbial community that occur during times of ice cover. Non-metric multidimensional scaling (NMDS) of weighted unifrac distances indicated that a distinct community of microbes existed in the water during times of ice cover relative to ice-free samples Fig. . PERMANOces Fig. . Temperaces Fig. . AnalysiThe clustering of the samples on the NMDS plot indicated that during ice-free periods there was a high amount of variability on a day-to-day basis in community composition Fig. . This fi25. This test is designed to normalize the sequencing data and determine taxa that are differentially abundant between different conditions. Eighteen orders were significantly enriched in samples collected from ice-free conditions, whereas thirty-eight orders were enriched in ice-covered conditions relative to ice-free conditions  and ammonia oxidizing archaea (AOA – Thaumarchaeota) were enriched during ice cover. Additionally, relatives of nitrite oxidizing bacteria of the order Nitrospirilales were enriched more than 6-fold during times of ice cover . Ice cover was present from early January to mid-March during the time of sampling in this study. During ice cover the temperature of the surface water stabilized at approximately 0 °C and the dissolved oxygen of the surface water stabilized at approximately 12.5 mg/L. This indicated that despite the limited gas exchange during times of ice cover, the surface water remained oxygenated, allowing for dominance of aerobic physiologies during the ice-covered time period.Here we sought to investigate the dynamics of the microbial community of surface water across dramatic seasonal changes in the Keweenaw Waterway. The Keweenaw Waterway is a highly dynamic system where movement of water can be influenced by wind driven currents26. Others have reported bacterial biomass is typically lower during ice cover1. The decrease in bacterial abundance observed in this study was slight (less than one log), suggesting that microbes in this lake are well adapted for cold conditions. This could be due to the consistent long periods of ice cover and the limited warming that occurs in this lake during the summer.Our results suggest that microbial biomass in the surface water showed some limited change between ice-free and ice-covered conditions. Previous studies have shown that bacteria cell numbers remain fairly constant throughout the year with blooms associated with thermal mixing1. This active growth suggests the possibility for rapid change to brief or more gradual changes in environmental conditions or inputs of nutrients. This can be observed in the gradual changes that occur throughout the ice-covered times. Our results would suggest that the microbial community present during times of ice cover was more stable on a day-to-day basis compared to the ice-free periods. However, the microbial community present under ice exhibited gradual changes, which is in line with the previous studies that demonstrate an actively growing microbial community during times of ice cover and changes in the bacterial community composition during ice cover26. Part of this actively growing community appears to be algae. We observed a substantial increase in chloroplast sequences during the middle of ice cover and increasing until ice melt. This under ice algal bloom matches with other previously described blooms of under ice algae9. This bloom was quite slow in forming as the build-up lasted for almost 2 months – starting in mid-January not long after ice formation and continued to increase until ice melt in mid-March.Despite the conditions found under ice, previous studies would suggest that these microbes are actively growing27. The decreased grazing would relieve some of the top down controls on the microbial community composition and allow for a more diverse community to proliferate without the control of grazing that occurs during warmer months. The increase in phylogenetic diversity could also be explained by alternation in the nutrient inputs into the system. It is possible that during warmer months the increased temperatures or nutrients allow for particular taxa to dominate the system. The seasonal changes that occurs during ice cover could select against these warm-adapted microbes and may allow for more access to the available nutrients, thus enabling the proliferation of a more diverse community. Alternatively, this increased diversity could be explained by the persistence of a large number of dormant microbes in this system. Our work was done on the level of DNA, which often does not represent the actively metabolizing microbes in the system28. Additionally, there are studies that have suggested that microbial dormancy can be a mechanism by which microbial diversity is maintained in low nutrient environments29. In Jones and Lennon (2010), a dormant taxon is considered to be one which is detectable on the DNA level, but is not detectable at the RNA level. It is therefore possible that the increased diversity reflects an expanding number of detectable, but dormant taxa that are now observable due the decrease in the dominant taxa found in warmer months. Previous work has demonstrated that the percent of dormant organisms in a lake was in part affected by the nutrient loads29. This previous work demonstrated that, in some nutrient-poor systems, up to 40% of the taxon richness is derived from dormant cells. However, we did not measure the active community in these samples and thus cannot confirm that this observed increase in diversity is indeed due to dormancy. Furthermore, the dynamic nature of the Keweenaw Waterway leads to mixing of water from Lake Superior and Portage Lake. While it is possible that this mixing could contribute to some of the increased diversity, the stability of this elevated diversity over many months suggests that this is not a local or ephemeral phenomenon impacted by transient changes in mixing and water movement. Additionally, Churchill, et al. (2004) observed little mixing during times of ice cover, which supports the concept that the microbial community compositional changes are stable and not impacted by wind driven mixing23. Therefore, it is possible that this increased diversity could be due to a number of factors including decreased grazing, competition, or dormancy, which should be further investigated in future studies.Interestingly, we observed an increase in the phylogenetic diversity of the microbes during the ice-covered conditions. Our initial hypothesis, that the diversity would decrease, was based on the previous observations that microbial biomass decreases during times of ice cover coupled with the fact that the conditions found under ice cover are much more selective for growth . Therefore, it was surprising to observe an increase in the both richness and evenness during times of ice cover. This increase in diversity could be explained through a couple different ways. The increased diversity could be due to limited grazing that occurs during times of ice cover30. This increased nitrate was proposed to be associated with nitrification, which could decreased oxygen levels in deeper waters under ice31. In our study, we observed an increase in sequences related to nitrifying bacteria in the surface water below the ice. However, we did not measure nitrification as part of this study. While other studies have shown increased nitrification under ice, more work is needed to confirm the role of these organisms related to nitrifiers in nitrogen cycling under ice in the Keweenaw Waterway. Our work only examined the microbial community in the surface water using 16S rRNA gene sequencing. We did not observe decreased oxygen levels, which may be more prevalent in deeper waters. It would be important to follow up this work to link these putative nitrifiers with increase rates of nitrification under ice observed in other under ice lake systems.To parse out the differences observed on the overall community, differentially abundant operational taxonomic units (OTUs) were identified. A number of taxa were shown to be differentially abundant between ice-free and ice-covered periods. Many of taxa that showed the highest fold change during times of ice cover were related to microbes known to be involved in then nitrogen cycle. In particular, sequences related to microbes involved in the process of nitrification were enriched during times of ice cover. Members of the Nitrospirales, Nitrosomonadales, and Thaumarchaeota were all significantly enriched in the ice-covered conditions. A recent study suggested that ice duration drives accumulation of nitrate in north temperate lakesThis study aimed to understand how microbial abundance and diversity changes over drastic seasonal transitions, and how ice cover affects microbial abundance and diversity. Molecular techniques and next generation sequencing provided a detailed survey of the microbial community in the Keweenaw waterway through a period of ice cover. Our results suggest that ice formation may cause shifts in the microbial community composition. The increase in diversity during times of ice cover suggests that the conditions during ice formation may be a strong constraint on the growth of some species and in return remove the constraint for growth of other species. Additionally, an increase in sequences related to taxa involved in nitrification during times of ice-cover suggests that ice cover may impact biogeochemical cycling and potentially have impacts on the nitrogen cycle. A better understanding of the impact of ice cover on biogeochemical cycling will be important for characterizing the impact of changes in the extent and duration of lake ice cover on biogeochemical fluxes. In the long-term there is need to characterize the temporal changes in microbial community composition and biogeochemical cycling in order to better understand how seasonal variations and ice cover impact ecosystem function.in situ environmental variables were measured with a YSI proDSS sonde which measured temperature, dissolved oxygen (DO), conductivity, Total Dissolved Solids (TDS), ORP, and pH  along with 300 µl of Miller Phosphate buffer, 300 µl of Miller SDS lysis buffer, and 600 µl of Phenol:Chloroform:Isoamly alcohol (25:24:1). A process blank was also setup and subjected to all following steps of extraction without a filter. The tubes were homogenized in a FastPrep-24 bead-beater  for 45 seconds at a speed of 5.5 m/s. To remove cell debris and filter material, the tubes were centrifuged at 10,000 × g for 5 minutes. 600 µl of aqueous supernatant was transferred to a new 2 ml tube along extracted with one volume of chloroform. Tubes were centrifuged at 10,000 × g for 5 minutes, then the aqueous phase was kept. Purification and concentration of recovered DNA was performed by adding two volumes of MoBio solution C4 to the aqueous phase. This was passed over a MoBio spin filter. The spin filters were then washed with 400 µl of MoBio C5 solution. Residual C5 was removed by centrifuging the empty tubes at 10000 × g for two minutes. DNA was eluted by two 30 µl additions of MoBio C6 solution. Final eluted environmental DNA was stored in −80 °C freezer. DNA concentrations were determined using NanoDrop spectrophotometer.DNA was extracted from half of each filter using a modified Miller protocol−4 pM to 20 pM. The equation for the standard curve to convert CT to pM of 16S rRNA genes was y = 16736(e(−0.515x)). The R2 of our standard curves was 0.97. Environmental DNA was diluted 1:10 to limit the impact of inhibitors from environmental DNA. To each reaction 1 µl of the diluted environmental DNA was used in 20 µl qPCR reactions. The copy numbers of bacterial 16S rRNA, archaeal 16S rRNA in environmental DNA were determined in duplicate for each sample. For bacterial 16S rRNA gene quantification, Bact341 and Uni519R primers were used according to the protocol described in Jorgenson et al.33. Archaeal 16S rRNA abundance was determined using Uni519R and Arch908R as described in Jorgenson et al.33. Standards and PCR reaction set up was similar to that described in Techtmann et al.34. Normality of the qPCR data was tested with the Shapiro-Wilk test for normality as implemented in R35. Since the data was not normally distributed, the Kruskal-Wallis one way analysis of variance was used to determine if there was a significant difference in the microbial abundances between ice-free and ice-covered periods.The abundance of bacterial and archaeal 16S rRNA was determined using qPCR. qPCR was performed on an StepOne Plus instrument . Six-point standard curves were performed in triplicate with concentrations ranging from 2 × 1036. These primers were able to amplify Bacterial and Archaeal 16S rRNA gene as well as many Eukaryotic 18S rRNA genes. The 16S rRNA gene was amplified by 25 cycles. The amplicon was purified using AxyPrep PCR Clean up magnetic beads (Axigen). Index sequences and sequencing adapters were added to each sample by an additional 8 cycle PCR as described in the Illumina 16S rRNA Metagenomic Library Preparation protocol. Sequencing was performed on the Illumina MiSeq according to the Illumina protocol for amplicon sequencing. The resulting DNA sequences were analyzed using the QIIME version 1.9.0-dev pipeline37. Paired-end raw reads were assembled using fastq-join38. The assembled sequences were demultiplexed and quality filtered in QIIME to remove reads with phred scores below 20 (-q 19). Chimera detection was then performed on assembled reads using VSEARCH39. The taxonomy for each read was assigned using RDP classifier40 retrained with SILVA release 123. Data was rarified to the lowest number of sequences in a sample (3052). Alpha diversity was calculated using the alpha_diversity.py command in QIIME. Faith’s phylogenetic diversity, Observed Species, and Shannon diversity were calculated from the rarified OTU table. Weighted and unweighted Unifrac distances as well as Bray Curtis dissimilarity were calculated from the rarified OTU table using the beta_diversity.py command in QIIME. Raw sequencing reads have been deposited in the SRA as accession number SRP159623.The V4 and V5 hypervariable region of the 16S rRNA gene was amplified using Phusion DNA polymerase  with universal primers 515F-Y and 926R−16, which indicates that the data is not normally distributed. Since the Faith’s Phylogenetic Diversity data was not normally distributed, we chose to use a Kruskal-Wallis test to test the hypothesis that there were significant differences in the alpha diversity between ice-free and ice-covered samples. To determine if there was a significant difference in the alpha diversity between months, a Kruskal-Wallis test was performed comparing differences in the Faith’s Phylogenetic diversity between months. A Dunn test was used as a post-hoc test to determine between which months there was a statistically significant difference. The Dunn test was performed using the dunn.test package in R41. P-values for the Dunn test were adjusted for multiple comparisons using the Bonferroni method.Normality of the alpha diversity data was tested with the Shapiro-Wilk test. The Shapiro-Wilk test for normality of the Faith’s Phylogenetic alpha diversity returned a p-value of less than 2.2 × 1042. The lowest stress configuration of 50 iterations was chosen. NMDS analysis with unweighted unifrac distances was also performed and is included in Supplementary Fig. 42. To further understand the impact of environmental variables on explaining the data, a CCA was performed on the weighted unifrac distances. Co-linear environmental factors were removed. The role of Temperature, conductivity, TDS, and Dissolved oxygen was tested using the CCA. The CCA plot is shown in Supplementary Fig. 2 was then adjusted using the RsquareAdj function in vegan.To visualize differences in the community structure between ice states and between months, nonmetric multidimensional scaling (NMDS) was performed on the weighted unifrac distance matrix using the metaMDS command implemented in the vegan packageTo determine rates of change in community composition a time-decay analysis was performed to identify how ice cover impacted rates of community change. This approach was used to further determine the rates of community composition change during times of ice cover compared to ice-free conditions. Weighted unifrac distances were determined for each sample in a pair-wise manner. The log of these pair-wise dissimilarities were then plotted based on the time between each comparison and regression line generated for each case. Rates of change can be determined through analyzing the slope of these regression lines. ANCOVA analysis was performed to determine if the differences in rates of change were significant between ice-free and ice-covered conditions.25, as implemented in QIIME, was used to identify which OTUs that were differentially abundant between ice-states. This analysis was done on the non-rarified OTU table. OTUs that were significantly different  in one state were considered to be differentially abundant.A finer scale analysis on the level of OTUs was undertaken to examine how particular OTUs are affected by ice state. The MetagenomeSeq packageSupplementary MaterialsDataset 1


A receptors (GABAAR) are the major players in fast inhibitory neurotransmission in the central nervous system (CNS). Regulation of GABAAR trafficking and the control of their surface expression play important roles in the modulation of the strength of synaptic inhibition. Different pieces of evidence show that alterations in the surface distribution of GABAAR and dysregulation of their turnover impair the activity of inhibitory synapses. A diminished efficacy of inhibitory neurotransmission affects the excitatory/inhibitory balance and is a common feature of various disorders of the CNS characterized by an increased excitability of neuronal networks. The synaptic pool of GABAAR is mainly controlled through regulation of internalization, recycling and lateral diffusion of the receptors. Under physiological condition these mechanisms are finely coordinated to define the strength of GABAergic synapses. In this review article, we focus on the alteration in GABAAR trafficking with an impact on the function of inhibitory synapses in various disorders of the CNS. In particular we discuss how similar molecular mechanisms affecting the synaptic distribution of GABAAR and consequently the excitatory/inhibitory balance may be associated with a wide diversity of pathologies of the CNS, from psychiatric disorders to acute alterations leading to neuronal death. A better understanding of the cellular and molecular mechanisms that contribute to the impairment of GABAergic neurotransmission in these disorders, in particular the alterations in GABAAR trafficking and surface distribution, may lead to the identification of new pharmacological targets and to the development of novel therapeutic strategies.GABA The appropriate equilibrium between excitatory and inhibitory neurotransmission, which is mainly mediated by glutamate and γ-aminobutyric acid (GABA), respectively, is necessary for the correct function of neuronal circuits in the central nervous system , which are heteropentameric chloride channels, composed in most cases of 2α-, 2β-, and 1γ2-subunits  may regulate the response to the activation of GABAAR  and NKCC1  and are then transported to the Golgi. In the ER, unassembled receptor subunits are subjected to poly-ubiquitination that targets them for proteasomal degradation /N-ethylmaleimide-sensitive factor (NSF) complexes, facilitating their transport to the plasma membrane  zinc finger protein (GODZ), a Golgi resident palmitoyltransferase responsible for the palmitoylation of γ subunits. GODZ interacts with the GABAAR γ2 subunit recognizing a 14-amino acid cysteine-rich domain conserved in the intracellular domain of γ1–3 subunits, NH2-terminal to the GABARAP binding site  analysis  clathrin adaptor protein complex , as an important motif for AP2/clathrin/dynamin-mediated GABAAR internalization  was identified within the β3 subunit that is responsible for the interaction of GABAAR with AP2 and in the stabilization of the receptors at dendritic endocytic zones where they are internalized  was identified in the GABAAR γ2 subunit, which is also conserved in the γ1 and γ3 subunits  determines whether endocytosed GABAAR are recycled  amplitude in cultured hippocampal neurons  of the receptors have been associated with genetically determined epilepsies, as well as, with idiopathic generalized epilepsies . Moreover, a recent study identified a de novo heterozygous missense mutation in GPHN, which encodes for gephyrin, in a patient with Dravet-like syndrome -tagged α2 subunits. The observed decrease in the surface expression of GABAAR was mediated by activation of NMDARs for glutamate and was sensitive to inhibition of the phosphatase calcineurin , and recurrent epileptiform discharges, is the time-dependent pharmacoresistance; about 30% of the patients become resistant to the treatment , SE reduces PKC-dependent phosphorylation of GABAAR β3 subunit on the serine residues 408/9  family protein radixin acts a scaffold to anchor α5βγ2 GABA+-Cl− cotransporter KCC2. The resulting increase in the intracellular Cl− concentration may account for the positive shift of the GABAAR reversal potential, and the consequent depolarizing effects of GABA, observed in hippocampal slices exposed to conditions mimicking status epilepticus . In this set of experiments the activation of phosphatidylinositol 3-kinase/Akt-dependent signaling pathway, through PTEN downregulation, was shown to protect neurons from the toxic effects of OGD by preventing the reduction in the surface expression of GABAAR  within this binding motif that are essential for the interaction with μ2–AP2; mutation of these residues impairs receptor recruitment to clathrin-coated pits, significantly reducing receptor endocytosis  and in vitro (OGD). In particular, it was found that brain ischemia induces the dephosphorylation of GABAAR β3-subunit (Ser408/Ser409) in vitro and in vivo , which does not undergo internalization, reduced significantly the OGD-induced apoptotic neuronal death -induced rat model of ASD. The reduced phosphorylation levels of GABAAR-β3 subunit suggests alterations in the trafficking of the receptor, namely an increase in receptor internalization. The changes in GABAergic neurotransmission induced by prenatal exposure to VPA were also associated to impaired spatial memory, limited exploration, increased anxiety, and reduced sociability . Moreover, whole-cell patch–clamp experiments detected a reduction in the amplitude of mIPSCs with no significant differences in their frequency, suggesting that the postsynaptic responsiveness to inhibitory input is impaired without alteration in the presynaptic release of the neurotransmitter. Interestingly, stimulation with a GABAAR agonist improved some autistic-like phenotypes of PX-RICS−/− mice  of excitatory synapses have been associated with neuropsychiatric disorders , Parkinson’s disease (PD) and Huntington’s disease  in these brain regions suggests that this peptide plays an essential role in AD pathogenesis , in different brain regions, namely in the hippocampus  due to progressive neurodegeneration of dopaminergic neurons . This study showed a marked reduction in the levels GABAAR in the CNS, particularly in the lower motor neurons, and, interestingly, Trak1 was found to interact with GABAAR , with an expanded polyglutamine (polyQ) repeat  showed a reduction in the abundance of benzodiazepine receptors in the striatum (but not in the cortex) of HD patients , which mediates the insertion of GABAAR into the plasma membrane, and HAP1, the adaptor that links the motor protein to the receptors. Accordingly, HAP1-KIF5 dependent GABAAR trafficking was reported as a fundamental mechanism controlling the strength of synaptic inhibition in the brain  with GABAAR β3 subunits and dephosphorylates the amino acid residue of the β3 subunit responsible for the regulation of the phospho-dependent interactions with the endocytic machinery , which might play a role in the observed synaptic excitatory/inhibitory unbalance (Frankola et al., AR trafficking have been reported as a key mechanism that contributes to the unbalance between excitation an inhibition, which ultimately will lead to neuronal hyperexcitability. Interestingly, similar alterations in the mechanism coupled to an increased internalization of GABAAR result in distinct outcomes/symptoms associated to different pathologies of the CNS. Depending on the circuits, the brain region and the developmental stage in which the postsynaptic alteration of GABAergic system is initiated, different structural and molecular modifications of the involved neurons may occur, triggering distinct pathologic responses. However, the disruption of the GABAergic neurotransmission characteristic of various illnesses may partly account for some common symptoms. For example, patients with cerebral ischemia, as well as certain cases of ASD or HD (Gambardella et al., AR are key players in the modulation of neuronal excitability. However, considering the recent findings showing that the nanoscale redistribution of the scaffold protein gephyrin is a key event in the potentiation of inhibitory synapses, additional studies are required to evaluate the alterations in GABAAR and gephyrin nanoscale redistribution induced by hyperexcitability in pathological conditions. The outcome of this type of studies may contribute to the identification of novel therapeutic targets for various brain disorders characterized by an impaired regulation of the excitation/inhibition balance.Aberrant excitability is a common feature of numerous disorders of the CNS. Dysfunction of GABAergic synapses and in particular alterations of postsynaptic GABAMM, RC and CD wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Escherichia coli and Pseudomonas aeruginosa were investigated using potassium loss, flow cytometry, and scanning electron microscopy (SEM). Supra-bactericidal colistin concentrations induced just 4–12% intracellular potassium loss from bacteria after 24 h. Flow cytometry data suggested colistin might alter cell arrangement, and SEM confirmed the antibiotic causes bacterial aggregation. Filamentation was not detected in either species at any concentration or time-point up to 24 h. These results argue against the hypotheses that colistin kills bacteria by puncturing the cytoplasmic membrane or disrupting DNA synthesis. The colistin-induced bacterial aggregation detected has implications for the interpretation of MBC, time-kill, and other test results obtained with this antibiotic.Whilst colistin (polymyxin E) represents the last mainstream treatment option for multidrug-resistant Gram-negative pathogens, details of its mechanism of action remain to be fully resolved. In this study, the effects of sub-inhibitory, inhibitory-bactericidal, and supra-bactericidal levels of colistin on the membrane integrity and morphology of The online version of this article (10.1007/s00203-018-1485-3) contains supplementary material, which is available to authorized users. Pseudomonas aeruginosa and Escherichia coli. Systemic use of colistin largely ceased in the 1970s due to concerns about nephrotoxicity and neurotoxicity, but growing resistance to other antibiotic classes prompted a reassessment of its safety at the turn of the century (Tängdén and Giske Colistin (polymyxin E) is an antibiotic with a spectrum of activity that includes problematic carbapenem-resistant and extensively drug-resistant Gram-negative bacteria such as Because colistin is rapidly bactericidal against Gram-negative but not Gram-positive species, and has a strong binding affinity for lipopolysaccharide (LPS), it is widely accepted that this antibiotic targets the bacterial outer membrane. However, precise details of how colistin exerts its antibacterial effect remain unclear  that normally stabilize the LPS monolayer , model membranes, and other techniques. Consensus exists that initial electrostatic and hydrophobic interactions occur between colistin molecules, which are positively charged, and the negatively charged LPS layer of the outer membrane. This first step, sometimes referred to as ‘self-promoted uptake’, leads to displacement of the divalent cations  and minimum bactericidal concentration (MBC) values determined for assay-specific inoculum densities.The purpose of the present study was to gain further insight into the interaction between colistin and bacterial cells including its underlying mechanism of action. Cytoplasmic membrane damage was assessed by measuring potassium loss from colistin-treated cells, as leakage of this intracellular solute is an early sign that membrane integrity has been compromised . These bacteria were stored, sub-cultured, harvested, and washed as described previously , while flow cytometry Sheath fluid, Flow Check™ fluorospheres and all plastic disposable equipment were from Beckman Coulter .Colistin sulfate, phosphate buffered saline (PBS) tablets, isopropanol (99+%), and sodium phosphate were purchased from Sigma-Aldrich Company . Potassium dihydrogen orthophosphate SLR and glutaraldehyde were from Fisons Scientific , and sodium carbonate was from BDH . Sodium chloride , acetone , and formaldehyde were purchased from Fisher Scientific , and nutrient broth and agar were from Oxoid . The Bac5 cfu mL−1 and CLSI-recommended incubation time of 16–20 h, MICs were determined for assay-specific inoculum densities  and assay-specific incubation time of 24 h. Microtitre plates  were sealed with an optically clear, gas-permeable seal (Fisher Scientific) and incubated at 37 °C .MICs were determined according to the CLSI broth microdilution method CLSI , but witMBC values were established by a replica plating procedure, with 1–2 µL from each well transferred to the surface of a 13.5-cm-diameter nutrient agar plate using a 96-pin multi-point replicator . The presence or absence of growth was recorded after 24 h aerobic incubation at 37 °C. All assays were conducted in triplicate on six separate occasions.6 cfu mL−1E. coli and P. aeruginosa were incubated with inhibitory-bactericidal (1 × MIC and 1 × MBC) and supra-bactericidal (10 × MBC) levels of colistin  for various time periods , and examined for potassium loss using a flame atomic absorption spectrophotometer  as described previously , inhibitory-bactericidal (1 × MIC and 1 × MBC) and supra-bactericidal (10 × MBC) levels of colistin  prior to analysis by flow cytometry using BacLight™ Live/Dead Bacterial Viability reagents (Invitrogen). In accordance with the manufacturer’s instructions, bacterial populations incubated in aqueous 0.9% (w/v) NaCl and 70% (v/v) isopropyl alcohol were employed as viable and non-viable controls. All bacterial populations, both control and colistin-treated, were prepared for flow cytometric analysis as follows. Firstly, 10 µL of each bacterial suspension was pipetted into a series of sterile 1.5-mL microcentrifuge tubes containing 987 µL of 0.9% (w/v) NaCl with 1.5 µL of Syto9 and 1.5 µL propidium iodide (PI) fluorescent dye solutions. Tubes were then incubated in the dark for 15 min at room temperature prior to analysis using an Epics®XL MCL flow cytometer (Beckman Coulter). Prior to using the flow cytometer, the discriminator was set at 0.2 µm and the laser alignment was checked and adjusted using Flow Check™ fluorospheres. The test samples were processed once the half-peak co-efficient variation was ≤ 2% on channels FL1, FL2, FL3 and FL4. Channels FL1 and FL3 were set to detect Syto9 and PI, respectively. When being analysed, each sample either had 10,000 events recorded requiring approximately 5 s for controls, or was left for up to 5 min permitting the maximum number of events to be gathered. All assays were conducted in triplicate on three separate occasions.Populations of 1 × 107 cfu mL−1E. coli and P. aeruginosa were incubated with sub-inhibitory (1/20 × MIC), inhibitory-bactericidal (1 × MIC and 1 × MBC), and supra-bactericidal (10 × MBC) levels of colistin  for various time periods , then prepared for and analysed by SEM  using a protocol described previously  and antibiotic-induced morphological changes are known to occur much earlier than 24 h  in this study  and supra-bactericidal  levels of colistin, respectively, lost 5.7 and 5.9% of their total potassium content within 1 h of exposure . Suspensions of P. aeruginosa treated with inhibitory-bactericidal  and supra-bactericidal  levels of colistin, respectively, lost 3.8 and 4.0% of their total potassium pool within 1 h, these values remaining unchanged or almost unchanged  when cells were examined at 24 h.A similar response was seen with osa Fig. b. Low le6 cfu mL−1 bacteria exposed to the antibiotic for 24 h. For populations of E. coli treated with sub-inhibitory (1/20 × MIC) levels of colistin  and supra-bactericidal (10 × MBC) levels of colistin, by contrast, very few events were detected in the gated population  colistin revealed a decrease in number of the smaller-sized cells and a slight increase in number of the larger-sized cells  and supra-bactericidal (10 × MBC) levels of colistin, very few events were detected in the gated population , inhibitory-bactericidal , and supra-bactericidal  levels of colistin triggered an immediate response. Within 60 min, profound cell aggregation was observed, these aggregates being spherical in shape and measuring 5–15 µm in diameter depending on the antibiotic concentration , inhibitory-bactericidal , and supra-bactericidal  levels of colistin, the morphological changes observed were both concentration- and time-dependent. After 60 min, a decrease in the length of individual cells was detected in populations treated with sub-inhibitory (1/20 × MIC) and inhibitory-bactericidal (1 × MIC and 1 × MBC) levels of colistin  levels of colistin, E. coli populations lost less than 12% of their total potassium pool and P. aeruginosa populations lost less than 5%. Genuinely cytoplasmic membrane-active agents such as protegrin and cathelicidin have, by comparison, been shown to induce 90–100% potassium loss in similar studies with E. coli in less than 1 h  or supra-bactericidal (10 × MBC) levels of colistin resulted in a near-complete loss of signal from the gated population  or supra-bactericidal (10 × MBC) levels of colistin resulted in a near-complete loss of signal  and inhibitory-bactericidal (1 × MIC and 1 × MBC) levels of the antibiotic both caused a decrease in bacterial cell length  inducing phospholipid exchange between the outer and cytoplasmic membranes, (2) inhibiting respiratory enzymes, and/or (iii) inducing reactive oxygen species formation. Colistin-induced aggregation of bacterial cells hindered our attempt to study this antibiotic’s effects by flow cytometry, but represents an interesting observation in itself, one with implications for the interpretation of MBC, time-kill, and other microbiology assay results.In conclusion, our study has shown that colistin induces minimal potassium loss and no filamentation in populations of Below is the link to the electronic supplementary material.Supplementary material 1 (DOCX 946 KB)Supplementary material 2 (DOCX 1063 KB)


Sea ice loads on marine structures are caused by the failure process of ice against the structure. The failure process is affected by both the structure and the ice, thus is called ice–structure interaction. Many ice failure processes, including ice failure against inclined or vertical offshore structures, are composed of large numbers of discrete failure events which lead to the formation of piles of ice blocks. Such failure processes have been successfully studied by using the discrete element method (DEM). In addition, ice appears in nature often as discrete floes; either as single floes, ice floe fields or as parts of ridges. DEM has also been successfully applied to study the formation and deformation of these ice features, and the interactions of ships and structures with them. This paper gives a review of the use of DEM in studying ice–structure interaction, with emphasis on the lessons learned about the behaviour of sea ice as a discontinuous medium.This article is part of the theme issue ‘Modelling of sea-ice phenomena’. During contact with a structure, sea ice fails into a myriad of small and large pieces that may accumulate into a pile and further affect the ice failure process, and finally, leave the active failure zone. Such an ice failure process has a feedback loop: earlier failure events affect both the initial and the boundary conditions of later ice failure events . As an eice–structure interaction is often used.Several different ice failure modes have been observed –6. When a priori assumptions of the ice failure mode. As an example, if we knew that an ice sheet of thickness h would fail through bending against a structure with an inclination angle α and form a rubble pile with height H in front of the structure, and how the rubble would affect the bending failure, we could form equations to estimate the ice load. But we do not know the failure process that well, and maybe we will never know: there is evidence that the failure process is extremely sensitive to initial conditions and we cannot make many a priori assumptions of the ice failure mode . I. Ia) [28strength .Figure Another type of material test used with ice rubble is the punch-through test  where a The use of DEM to study the interaction between ridges and offshore structures has included modelling ridges as thick areas between thinner level ice , load tr(c)(i)The early studies were limited by computer resources and could only analyse the initial part of the process. After the simulations of longer rubbling processes became practical, DEM was used to estimate the ratio of rubbling work to increase in potential energy of the ice blocks, and to discuss the differences between 2D simulations and physical experiments with narrow ice strips . In the The failure of an ice sheet against an inclined structure has also been studied with a combined 2D FEM-DEM, where the ice sheet and its fracture are modelled with FEM, while the contact forces between the colliding ice blocks are calculated with DEM . Simulat(ii)The 2D simulations of ice failure against wide inclined structures, discussed above, have provided many interesting results. However, the failure of ice against a conical offshore structure is a 3D process and needs to be simulated as one. The process starts by ice edge crushing and formation of radial cracks until the vertical force is high enough to create circumferential cracks and discrete ice blocks, which pile up against, and clear around, the structure . For shiBoth ship–ice and cone–ice  interactBonded-particle models , where a(iii)Ice failure against a vertical structure, crushing, is a complicated process including contact between ice and the structure, fragmentation of the ice into discrete particles, motion of the particles against and around the structure, and the dynamic response of the structure . The abiA 2D DEM model, where tensile stresses lead to brittle fragmentation and compressive stresses to viscoplastic flow, has been developed to study the failure of ice against a flexible vertical structure as a plane strain problem . The modAnother class of problems is the impact of an ice floe against a vertical structure. This has been simulated as a plane stress problem, 2D in the horizontal plane. DEM simulations of this case have shown both ice failure in the vicinity of the structure  and spli4.An ice–structure interaction is a complicated process to model. The ice model must account for large deformations and displacements, fracture and fragmentation, and the motion of the ice fragments formed. For the structure, the model should take into account the static or dynamic response under ice loading, but the structural response may have an effect on how the ice fails; thus this process is called ice–structure interaction. These modelling demands can be dealt with by several different techniques. DEM is one of the suitable methods, especially in applications where the discrete ice blocks have a central role.The DEM models developed for sea ice applications can be divided into two groups: those where the discrete elements have a physical meaning (an ice floe or an ice block) and those where the discrete elements are used for describing material behaviour and failure in the same way as elements in FEM or lattice models. An example of the former type are models used for ridging, where the formation and interactions of discrete blocks is the key phenomenon, the number of ice blocks is small and the process needs to be modelled as discrete . ExampleIn other fields such as soil mechanics, continuum models of  material behaviour have been derived based on DEM simulations of particle-level  phenomena. In ice mechanics, this approach has been successfully used to estimate the yield curve of an ice floe field . HoweverReal-time simulation of ship navigation can be useful in crew training and in planning of marine operations. For such simulations, models relying on physics engines and general-purpose computing on graphical processing units have been developed ,118,119.With increasing computing power and effective numerical techniques, in the future ice failure processes can be modelled in more detail and over longer time periods than today. As ice loads are the result of ice failure processes, simulations of long processes are important. Also, detailed 3D DEM simulations and studies on ice-induced vibrations can be expected to expand in the future. There have been a few DEM simulations on flexible structures and ice-induced vibrations ,105,109,DEM has been used for studies on ice–structure interaction since the mid-1980s and major development has taken place since then. However, rather than placing the emphasis on ice mechanics research, many studies have focused on the development of numerical techniques, especially in the case of engineering applications. As the examples in this review demonstrate, careful analysis of DEM-simulated sea ice failure processes has led to several important observations related to the behaviour of sea ice and the physical phenomena behind ice loads. Hopefully, in the future, the use of DEM as an ice mechanics research tool will further expand.5.(i) ice floe fields need to be modelled in 3D, unless it can be ensured that floe concentration stays low everywhere in the simulation domain;(ii) the possible angularity of ice blocks needs to be modelled. Circular and angular blocks behave in different ways;(iii) DEM simulations have shown that the energy dissipation during ridging is higher than was previously assumed;(iv) ice arch formations, or force chains, can be important force-transmitting mechanisms in ice floe fields and in ice rubble, and need to be considered in ice load models;(v) no unique shear plane can be observed in ice rubble punch-through experiments; and(vi) DEM simulations can be used to produce ice load data for studying the statistics of ice loading processes.During the last few decades the DEM has become one of the key numerical methods used to study ice–structure interaction. The review given in this paper has concentrated on DEM as formulated by Cundall & Strack . The empIt can be expected that the use of DEM in research on ice–structure interaction will continue, and important insights will be obtained into the mechanics of local and global ice loads. One active line of research, where computational speed is important, supports the development of ship simulators for ice navigation and the planning of marine operations. The other future challenges include modelling of 3D fragmentation of ice sheets, and the incorporation of hydrodynamics in DEM models.


Eggs of thick-billed murres (Uria lomvia) and northern fulmars  were collected in the Canadian Arctic during four years of highly contrasting ice conditions, and analysed for HBIs, isotopic (carbon and nitrogen) and energetic composition. Murres heavily relied on ice-associated prey, and sea-ice was beneficial for this species which produced larger and more energy-dense eggs during icier years. In contrast, fulmars did not exhibit any clear association with sympagic communities and were not impacted by changes in sea ice. Murres, like other species more constrained in their response to sea-ice variations, therefore appear more sensitive to changes and may become the losers of future climate shifts in the Arctic, unlike more resilient species such as fulmars.In the Arctic, sea-ice plays a central role in the functioning of marine food webs and its rapid shrinking has large effects on the biota. It is thus crucial to assess the importance of sea-ice and ice-derived resources to Arctic marine species. Here, we used a multi-biomarker approach combining Highly Branched Isoprenoids (HBIs) with δ In the Arctic, primary production includes two consecutive pulses of marine autotrophs: sea-ice algae and phytoplankton3. In early spring, increasing irradiance and rising temperatures enable ice algae to grow. Later in the season when snow and sea ice melt, a phytoplankton bloom develops and follows the ice retreat5. Sea ice algae alone contribute 3–25% of the total primary production6, while in the central Arctic Ocean, this contribution could reach 57–83%8. In the last decades, the Arctic has changed rapidly as a result of anthropogenic climate change, facing particularly drastic changes in sea ice conditions9. One of the most visible changes in Arctic sea ice is a significant decrease in coverage11, with a mean rate of decline in summer extent of 12.8% per decade relative to the 1981–2010 average , and similar trends are observed for the winter ice extent. Besides changes in coverage, Arctic sea ice has undergone a significant decrease in thickness12 with a shift from largely perennial to seasonal first-year ice cover13. Concurrently, earlier ice break-up15 and a prolonged melting season16 have produced changes in the open-water season. With these ongoing trends, climate models predict an ice-free Arctic Ocean in summer by 2050 or by the end of 21st century at the latest17. The productive period will thus start earlier and extend until later18, which will have strong implications on the phenology of primary producers19, ultimately impacting the total primary productivity of the Arctic20. For example, the primary production in the Arctic Ocean increased by 30% between 1998 and 201221. Clearly, these changes will deeply modify the structure and the functioning of Arctic marine ecosystems22, in particular large community shifts and changes in range, abundance and growth of several species24. In such a context, it appears crucial to assess the dependency of key Arctic species on sea ice and its resources and to understand the risks associated with its current decline.Sea ice plays a central role in polar marine ecosystems; it drives the phenology of primary producers that constitute the base of marine food webs. Primary producers provide the energy which is transferred to successive trophic levels, including zooplankton, fish, seabirds and marine mammals15N) and carbon (δ13C) provide information on the relative trophic level of consumers (i.e. diet) and the feeding habitat (i.e. benthic versus pelagic food chains), respectively25. In polar regions, the distinct δ13C signatures of ice algae (i.e. more enriched in 13C) and pelagic phytoplankton allow for reconstructing foraging on sympagic prey and can hence be considered as an ice proxy in the Arctic27. Additionally, HBI biomarkers provide complementary information on the relative contributions of the two primary production pools along with the food web29, namely sea ice algae and phytoplankton pools. HBIs are lipid biomarkers synthesized by diatom species almost exclusively belonging to genera Haslea, Navicula, Rhizosolenia and Pleurosigma28. In the Arctic, a restricted number of ice-associated diatom species produce IP25, a mono-unsaturated HBI isomer, which is often associated with a di-unsaturated isomer (diene)31. When observed in biological matrices, IP25 and diene provide direct evidence for the contribution of sympagic algae to the diet of the studied organisms. In contrast, a tri-unsaturated HBI (triene) is mostly synthesized by open-water diatom species, representing an indicator of the phytoplankton contribution. Both HBIs and stable isotopes, therefore, constitute powerful analytical tools for assessing environmental effects on marine biota and combining them would enable to better understand how much sea ice and its derived resources are important among Arctic marine ecosystems, from zooplankton consumers up to top predators, such as seabirds.Biomarker approaches enable us to infer the dependency of Arctic consumers on both sympagic (i.e. sea ice-associated) and pelagic resources, by using conservative bioindicators produced by primary producers , then transferred along the food chain. Trophic biomarkers, such as stable isotopes and Highly Branched Isoprenoids (HBI), thus allow for tracking the trophic fingerprint of both primary producers. Stable isotopes of nitrogen  and northern fulmars  represent ideal candidates to investigate the importance of current and future Arctic sea ice conditions for seabirds. Both exhibit a near circumpolar distribution; they are amongst the most abundant seabird species in the Arctic during the breeding season and show contrasting feeding ecologies and flight constraints. Both are primarily “income breeders” relying on resources acquired just prior to breeding to form eggs45. While thick-billed murres are pursuit-divers feeding mainly on fish and macrozooplankton and present high flight costs46 restricting their large-scale movements, northern fulmars are opportunistic surface-feeders with limited flight constraints42. Given these contrasting characteristics, thick-billed murres and northern fulmars might be affected differently by changes in sea ice in areas surrounding their breeding grounds. Widely distributed in ice-free waters, northern fulmars are not tied to sea ice, whereas thick-billed murres largely breed in waters where sea ice occurs. We, therefore, hypothesize that sea ice would be more important to the breeding ecology of thick-billed murres. Previous studies highlighted negative impacts of a heavy ice cover on thick-billed murre breeding success48, resulting in delayed laying and smaller eggs49. Hence, the observed decline in Arctic sea ice extent and modifications in phenology could have strong implications on the fate of seabird populations. Surely, sea ice represents a physical barrier for seabirds excluding certain areas for foraging, and thus potentially increasing their energy expenditure to access prey in open water. However, an extensive ice cover does not impede them to access sympagic resources if several leads are present between ice floes that allow them to dive and feed. More importantly, sea ice could provide high-quality sympagic resources for breeding birds, and investigations on the profitability of sea ice are thus required.Thick-billed murres  and northern fulmars (hereafter ‘fulmars’) to variations in sea-ice conditions in the vicinity of their breeding grounds. More specifically we used a multi-biomarker approach combining HBIs and stable isotopes to: (i) determine if changes in sea ice conditions influence bird association with ice-derived resources; and (ii) investigate how this association influences bird feeding ecology and egg parameters (proxies of bird investment in the reproduction) of each species.Between 2010 and 2013, both northern fulmars and thick-billed murres encountered contrasting ice conditions around PLI during the entire breeding season . In mid-June, which corresponds to the egg formation period, sea ice concentrations ranged from 29% to 99% during the study period Table . In 2010Thus, we distinguished two major ice regimes Fig. : (1) 201F3,40 = 12.1, p < 0.001, ANOVA), with 2010 (1.0 ± 1.1 SD) and 2012 (0.7 ± 1.0) differing from 2011 (−1.1 ± 1.1) and 2013 (−0.7 ± 0.7), and increased linearly with increasing ice concentrations , with 2013 (−1.1 ± 1.1) differing from 2010 (0.6 ± 1.0), 2011 (0.6 ± 1.2) and 2012 (−0.0 ± 1.0), and did not vary linearly with ice concentrations (p > 0.05).In murres, the ice use index differed significantly across years  were present in all samples, but their concentrations were highly variable between individuals  compared to those observed in murre eggs   and H-Print differed significantly across years . In 2012, ice association differed between two groups : one group with higher amounts of ice biomarkers  and a second group with higher amounts of pelagic biomarker . Finally, in 2013 eggs exhibited an intermediate H-Print (63.4 ± 18.1%).For murres, HBI concentrations varied among years, ranging overall from 0 to 38.2  in murres, in contrast to fulmars for which no relationship was found (p > 0.05).There was a significant positive linear relationship between H-Print and ice concentrations around the colony  than fulmars (13.2 ± 0.33‰) . For murres, δ13C values were significantly different between years , with 2010 and 2012 differing from 2011 and 2013. δ15N were also different between years , with 2012 differing from 2011. In icy years, murre eggs were enriched in both 15N  and 13C  compared to years characterized by open-water presence . For this species, δ15N values reached a maximum when the ice use index was intermediate , with 2013 differing from all other years . δ15N values also differed across years , with 2012 (13.4 ± 0.3‰) different from 2010 (13.0 ± 0.3‰) and 2011 (13.0 ± 0.30‰). For this species, however, δ15N did not linearly respond to varying ice use index (p = 0.9).For fulmars, δ3; F3,56 = 2.5, p = 0.07, ANOVA; Fig. 3 in 2010 and 198.4 ± 18.7 cm3 in 2012) than in years of open-water (186.4 ± 16.1 cm3 in 2011 and 183.2 ± 17.6 cm3 in 2013) . Egg volume of murres increased linearly with increasing ice use index . For fulmars, egg volume remained stable across years  and egg energy contents (only for murres) were both compared to the ice use index. First, the egg volume did not differ significantly across years for murres , with higher energetic content in icier years  than in open-water years  . The energetic content linearly increased as the ice use index increased  and snow petrels (Pagodroma nivea)52. Our results, therefore, provide additional insights into HBI transfer to the highest trophic levels across the marine food web in the Arctic, even if the metabolism, the assimilation and the elimination processes still remain poorly understood. The presence of IP25 and diene in egg samples reflects the contribution of ice-derived organic matter in the diet of females while the contribution of the organic matter produced in open waters is represented by the triene. With ice- and plankton-derived isomers observed in all samples  patterns suggesting high ice use, in contrast to biomarker patterns from low ice years. The positive linear relationships observed between ice concentrations and ice use index suggest that murres strongly respond to changes in sea ice and would thus be more sensitive to potential impacts of climate change.42). Also abundant in 2010, sea ice was however fragmented in relatively large and mobile floes separated by numerous leads. This configuration provided easy access to water and its resources for murres in the vicinity of the colony (e.g. murres could forage for sympagic prey on the undersides of sea ice). As such, while ice use indices and to some extent HBI distributions are correlated to sea ice concentration around PLI, it seems that HBI abundances reflect the accessibility of prey to murres which, at least in this study, are associated to ice “type” and configuration. In 2012, the distribution of HBIs in murre eggs highlighted two distinct groups: one made by birds more associated with sea ice and one where eggs contained more of the phytoplankton-derived triene. Like earlier in 200242, 2012 can be considered as an extreme year regarding ice conditions, with no access to open water except at the ice edge located more than 250 km away to the east. The only other access to open water was a small polynya located approximately 130 km southwest from PLI  feeding behaviour was allowing them to maintain their fitness levels and attenuate effects of climate change.Amongst the four years studied, 2012 was the iciest year. The entire region around Prince Leopold Island (PLI) was covered by a dense, thick and unfragmented fast ice that remained until very late in the season. With the highest ice use indices during 2012 on average, birds were relying the most on sea ice for feeding Fig. . In fact25 and diene are relatively unavailable to higher trophic levels. Indeed, high abundances of HBIs were reported in copepods collected in spring in Beaufort Sea55, but a three week lag between the sympagic bloom and HBI accumulation in zooplankton was observed. Further, even in the middle of winter (January), HBIs were observed in most compartments of the Ripfjorden ecosystem except those from above 75 m deep56. Since the highly mobile and opportunistic fulmars are restricted to surface waters, it is likely that only a small amount of HBIs are available during their pre-laying period. As such, the large differences in HBI abundances in murre and fulmar eggs most likely originate from their distinct and contrasting trophic ecologies. Fulmars are capable of travelling over large distances57 (>250 km) to reach their feeding grounds, and in our study region they can fly >500 km one way to feed58. Furthermore, during the pre-laying period, fulmars undertake their pre-laying exodus, during which they leave the colony and probably travel out of Lancaster Sound to the eastern Baffin Bay or potentially the North Water Polynya58, where open-water is more predictable across years and algal blooms may occur earlier. Thus, fulmars are easily able to reach open waters even during extreme years, and this could explain the lack of interannual differences in this species. In this case, studying GPS-equipped birds would help refining their actual feeding grounds and adjusted analyses of ice conditions in this particular area would help clarify the influence of sea ice for northern fulmars.While HBIs were quite abundant in murre eggs, the analysis of those laid by fulmars revealed much lower HBI abundances with, on average, concentrations approximately five times lower than those observed in murres , and macrozooplankton47. Their feeding range is much shorter than the fulmar’s and typically restricted to approximately 150 km from their colony60. Murres are often observed near ice edges61 where they can easily dive under sea ice to forage on sympagic prey. Northern fulmars are opportunistic surface-feeders relying on fish such as arctic cod, but also on copepods, mysids, and gelatinous prey66. Given such differences in their feeding ecology, it is not surprising to see that H-Print and the ice use index differ between the two species. For thick-billed murres, both indices were closely linked to local ice concentrations and varied linearly with mid-June ice concentrations within a 100 km radius circle from the colony. For northern fulmars, neither H-Print nor ice use index were influenced by ice conditions. However, these interspecific differences might be explained by the fact that ice concentrations are defined in mid-May and mid-June for fulmars and murres, respectively. Ice concentrations exhibited much higher interannual variability during mid-June (29–99%) than during mid-May (80–99%). Hence, in our study fulmars did not experience years with reduced ice cover during egg formation. It is thus reasonable to expect smaller variations in HBI concentrations and distributions and, therefore, a weaker correlation to sea ice conditions for fulmars. Besides, fulmars have a longer breeding period, and Mallory and Forbes67 suggested that the high Arctic is near the environmental limit at which fulmars can complete their breeding. In contrast, thick-billed murres naturally lay eggs at a time closer to seasonal ice retreat and are hence already exposed to larger variations in ice conditions. Thus, the much lower interannual variations in sea ice cover might be below the threshold for northern fulmars to be influenced by sea ice variations (as they are constrained to breed early and fly far to complete chick-rearing before migration), and maybe that only extremely early open-water conditions (e.g. as early as in mid-May) would lead to observable impacts.Thick-billed murres are pursuit-divers, diving down to 200 m depth to feed mainly on fish, especially the ice-associated Arctic cod . The average increase of 0.7‰ in δ15N observed between 2011 and 2010 , however, is too low to reflect a change in trophic level but rather suggests a higher percentage of prey of higher trophic level in their diet. Higher δ15N values are correlated to low H-Print. The presence of ice in the vicinity of the colony favors murre access to prey belonging to higher trophic levels and exhibiting a stronger relationship to sea-ice derived resources. Inversely, in years with reduced ice coverage, murres prey on organisms from lower trophic levels such as hyperiid amphipods (Parathemisto spp.), mysids or copepods68 that are more associated with pelagic resources. Our data confirm that murres take advantage of sea ice for feeding and thus any variation in ice cover has an influence on its accessibility to prey. Interestingly, δ15N values obtained from 2012 egg samples are lower than those of 2010, even if 2012 was the iciest year of the study. Again, as with HBI abundances, nitrogen isotopic values suggest that in 2012, ice conditions were too harsh to provide birds with easy access to their preferred fish resources. This suggests that an intermediate ice cover during egg formation represents the optimal breeding (foraging) scenario for murres at this colony. Indeed, arctic cod hide under the ice to avoid predators69, and during years like 2010 where ice was abundant but highly fragmented, birds could easily access their fish prey. In extreme years like 2012, ice precludes access to much of the sympagic prey for murres, and birds would forage more in the open water, spending much energy while focusing on fish, and had also to rely on zooplankton.Variations in sea ice conditions clearly influenced the feeding ecology of both species. However, as for the usage of ice-derived resources, there appear to be large interspecific differences  and invariable δ15N values also indicate that fulmars preyed upon lower trophic levels (likely zooplankton), without any influence of ice conditions. This absence of variation in isotopic composition has also been observed recently53 and suggests that every year, birds reach the same “predictable” feeding areas. These are probably located along the western Greenland coast in Baffin Bay, as suggested by tracking of foraging fulmars from a colony farther north on Devon Island58.In contrast, high and relatively invariable δ70. Indeed, top-predators such as birds closely synchronize their breeding schedule with their food supply in order to meet the energetic needs of their reproduction72. In the Arctic, food supply is closely linked to sea ice since both phytoplankton and sea ice algal blooms are controlled by its presence or absence73. In our study, we used egg size (i.e. egg volume) as a proxy for breeding investment. Indeed, a number of studies showed that although energetically costly to produce, larger eggs produce bigger chicks which then have a greater survival potential76. For murres and fulmars, Gaston and collaborators42 performed an exhaustive study and monitored colonies of both species at PLI between 2000 and 2003. They showed that in 2001 and 2002 (years relatively similar to 2012) laying was delayed and thick-billed murres produced smaller eggs. This was also reported by Hipfner and colleagues49 who showed that thick-billed murres laid smaller eggs later in the season during years of extensive sea ice in the High Arctic (PLI and Coburg Island). Both studies therefore showed that heavy ice conditions were leading to reduced breeding success, delayed laying date and decreased body condition/growth of chicks. In our study spanning very contrasting ice conditions, we observed an opposite effect of sea ice on murre breeding investment, with eggs on average larger in icy years than in years of open water. In previous studies, sea ice was only considered as a physical barrier that forces birds to commute over larger distances and involves higher energetic costs for breeding adults42. Hence, ice conditions were defined only according to the distance between colony and ice margin and did not consider the type of ice and how it was distributed (e.g. fast ice versus pack ice) as in the present study. Here, ice concentration around PLI, the position of the margins and the breakout period in 2010 and 2012 were relatively similar. However, as described above, the situation is extremely different when it comes to accessibility to food resources. In 2010, the very fragmented ice pattern provided murres with easy access to open water. In contrast, in 2012, birds had to travel over very long distances to reach open water. This situation prevented them from fully relying on ice-associated resources. The correlation between egg size and ice use index illustrate these differences in resource accessibility and use. Larger eggs were more associated with ice-derived resources (i.e. lower H-Print and higher ice use index) and therefore sea-ice conditions impacted the size of thick-billed murres eggs by modulating the availability of sympagic prey. Goutte et al.77 reported similar findings from their study on Adélie penguins (Pygoscelis adelia). They also highlighted a positive impact of a higher contribution of ice-derived resources on the breeding success of this species during years of extensive ice cover. Like murres, the Adelie penguin is an ice-associated diver that feeds mainly on Antarctic krill (Euphausia superba) and fish such as Pleurogramma antarcticum78, in waters covered by 20 to 80% ice as well as in the open sea, under pack ice or under coastal fast ice79. Guen et al.80 showed that intermediate ice coverage (20% ice), provided optimal breeding for Adelie penguins since krill juveniles rely exclusively on sympagic flora and the presence of sea ice promotes higher abundances of krill81. However, Emmerson and Southwell82 also showed that, as for murres, sea ice and, in particular, the presence of fast ice close to the shore could negatively impact reproduction performance of Adelie penguins by reducing their access to prey items. Thus, prey availability  clearly influences the breeding performance of various seabird species.In the current context of sea ice decline in the Arctic, studies focusing on the relationships between bird reproductive performances and ice are neededMallotus villosus) in southern Arctic waters at the expense of Arctic cod41. A switch from Arctic cod to demersal sculpins, resulting from shifts from arctic to subarctic regimes, was also observed in black guillemots (Cepphus grille mondtii) in the Beaufort Sea and associated with a decrease in chick condition83. For seabird species laying a single egg, quality and quantity of food delivered by parents to the chick has a strong effect on the reproductive success84. In pigeon guillemots (Cepphus columba), chick growth and survival decreased as the proportion of the lipid-rich Pacific sand lance (Ammodytes hexapterus) decreased and as the proportion of low-lipid demersal fish increased85. Here, we provide evidence that ice-derived resources influence murre egg size (proxy for breeding investment) and further investigations including other breeding parameters  would help to confirm the observed trends and understand murre vulnerability to sea ice declines in the Arctic.In subarctic areas, like in Hudson Bay, a decrease in the breeding success of murre colonies resulted from an increase in relative abundances of capelin , with yolk-area positively related to nestling survival, and nestling body size positively impacted by egg volume. Larger eggs with larger yolk contain more lipids and more energy for the chick’s development, producing ultimately a larger chick with higher chances of survival86. Therefore, sea ice represents a real and valuable asset for ice-associated seabirds, like murres, that might be more sensitive to future changes in Arctic sea ice.The energy content of murre eggs was greater with higher use of ice resources and when the birds fed at a higher trophic level, suggesting higher investment in eggs during icier years. Furthermore, larger eggs contained more energy for the chick’s development, ultimately providing nestlings with higher chances of survival. Barrionuevo and Frere42. Unlike murres, fulmars thus appear less sensitive to sea ice variations which do not seem to impact their investment in reproduction. As such, northern fulmars are more likely to be dramatically affected by a « tipping point » in Arctic sea ice conditions at the time of egg development in females; a point at which previously small changes become significant enough to impact their feeding ecology and reproductive investment. Further investigations on fulmars during years of highly variable ice conditions are thus required to fully understand the influence of sea ice for this species.For northern fulmars, egg size remained stable Fig. , withoutvia the resources it provides to marine predators. Our multi-biomarker approach, combining highly branched isoprenoids and stable isotopes, showed how important sea ice is for seabirds and how its use conditions different aspects of their biology, including their egg characteristics. For the fulmar, which has exceptional ability to fly long distances but must breed early to complete its long breeding period, variation in sea ice had limited effects, presumably because birds have adapted to fly long distances to open water remote from the colony but predictably open early in the season. However, the influence of sea ice is especially important for species such as diving thick-billed murres, perhaps more constrained in their response to sea ice variations, that rely heavily on local environmental conditions. At least for this colony, murres appear to have “optimal” ice conditions when ice cover is heavier but still broken up providing feeding locations; ice-associated biomarkers and proxies of reproductive effort are reduced at higher or lower ice conditions. Overall, we provide new and essential knowledge to comprehend the consequences of current and future climate changes on the fate of Arctic seabird populations. We also emphasise the importance of combining different biomarkers to better understand the importance of sympagic resources for top predators within changing Arctic marine ecosystems.Our study examined the importance of sea ice and ice-derived resources for breeding Arctic seabirds in a context where the Arctic might become ice-free in summer within the next decades. Instead of considering the sea ice cover as a physical barrier preventing seabirds to access their prey, we highlight the importance of sea ice 47  from nests on the eastern and southern cliffs at the multi-species colony on Prince Leopold Island in Lancaster Sound . For consistency, murre and fulmar eggs were sampled at the same period every year (late June – early July). One egg per nest was randomly sampled shortly after laying for murres and at mid-incubation for fulmars . Eggs were either taken by hand or by using an extension pole holding a small cup. In the field, eggs were kept cool and shipped to the National Wildlife Research Center (Ottawa) for processing. All eggs were taken under appropriate annual research and collection permits . Egg length (mm), width (mm) and weight (g) were measured, and a volume index (cm³) was calculated according to previously published methodology0–2013 frEgg contents were homogenized and stored frozen at −40 °C in acid-rinsed polyethylene vials. One- or two-gram aliquots (15 eggs per species per year) were sent to Laval University (Quebec City) where HBI and caloric content analyses were performed.59), we described environmental conditions by characterizing the presence/absence of sea ice, its type  and concentration in a 100 km radius circle around Prince Leopold Island. To determine the presence and the type of sea ice around the colony, regional ice maps  were downloaded from Canadian Ice Service Archives for the 2010–2013 period. Ice maps for the 2000–2003 period were also downloaded in order to compare our data with a previous study42. As these maps gather weekly data at a regional scale, we used satellite images from NASA Worldview dataset  to determine sea ice distribution and concentration at a finer temporal and spatial scale. The proportion of sea ice around the colony was calculated using MODIS 500 m resolution raster images and only images with clear sky were considered. Pixels were first extracted in a circle of 100 km radius around the colony. Land pixels were then masked out using Open Street Map mask (http://openstreetmapdata.com/data/water-polygons). The remaining pixels were classified into two categories (open water or sea ice) using a K-means clustering procedure. The clustering has been performed using the RGB values of the pixels. A maximum of 100 iterations was allowed for convergence. The proportion between pixels classified as open water and sea ice was then calculated and used as a proxy for the proportion of sea ice around the colony.As murres have a local feeding range  were added as internal standards to dried aliquots (~0.1 g to 0.3 g dry weight). Total lipids were extracted four consecutive times with dichloromethane-methanol mixture . Delipidized samples were dried overnight at 45 °C (12 h) and stored frozen (−20 °C) for isotopic analyses. Total lipid extracts were then dried under a gentle stream of N2 and subjected to saponification . Non-Saponifiable Lipids (NSL) were extracted from saponification mixture by liquid-liquid extraction , evaporated (nitrogen stream <35 °C) and purified using open column chromatography  to yield an apolar lipid fraction containing HBIs. These apolar fractions were then analysed via GC-MS following the procedure described in Belt et al.87. Briefly, the abundance of IP25, diene and triene were determined to integrate 350.3, 348.3 and 346.3 responses, respectively. The ratio of these responses against those of internal standards (m/z 266) was normalized to the mass of the sample and multiplied by the mass of standard added to the sample. For IP25, response factors were determined by injection of authenticated standards and results are expressed in ng.g−1. For other HBI isomers, in the absence of pure standards results are expressed in ng of standard equivalent.g−1.HBIs were analysed following the procedure initially described in Belt et al.31:Once individual HBIs were identified and quantified, the H-Print index was calculated for each sample using Eq.  from Bro13C or 15N, and R is the corresponding ratio 13C/¹²C or 15N/14N. Standard values were obtained from Vienna Pee Dee Belemnite (VPDB) and atmospheric N2 (air) for C and N respectively. Stable isotopes analyses were performed at the Littoral, Environment and Societies institute . Replicate measurements of laboratory standards (USGS-61 and USGS-62) indicated that the measurement accuracy was <0.2% for both δ15N and δ13C values . δ15N and δ13C isotopic values provide information on the relative trophic level of birds (i.e. diet) and their feeding habitat (i.e. carbon source) respectively89. Based on distinct δ13C signatures of ice algae and phytoplankton , δ13C is also considered as an ice proxy in the Arctic27.Stable isotope analyses were performed on aliquots of the delipidized fractions resulting from HBI analyses and loaded into tin cups (0.2 to 0.8 mg dry weight). An elemental analyser  coupled in continuous flow mode to an isotope ratio mass spectrometer  was used to determine stable isotope abundances. Results were expressed in δ notation as the deviation from standards in parts per thousand (‰), according to Eq. :3\documen = 32) were compressed to form pellets and analysed in a Parr 6300 Automatic Isoperibol-Oxygen Bomb Calorimeter. A Benzoic Acid standard was added to each sample (0.3–0.7 g) due to low sample weight (<0.2 g). Instrument precision was determined by running Benzoic Acid standards  prior to the samples. Results were expressed in both cal.g−1 dry and wet sample. The energy available per egg  was calculated by multiplying cal.g−1(wet) with the total egg weight. Unfortunately, the weight of the shell of each egg was not determined prior to homogenization and we, therefore, make the assumption that the variation amongst individuals is negligible.Aliquots of dried homogenized samples (13C) in order create a single variable representing bird-ice association (hereafter named Ice Use Index). The first principal component (PC1) explained 78.4% and 79.3% of the total variance in murres and fulmars, respectively, representing a range of sea-ice use, on which individual coordinates were projected. To investigate the influence of ice association on bird feeding ecology and reproductive parameters, we tested linear or quadratic regressions of δ15N, egg volume and energetic content with the Ice Use index. Normality of residuals and homoscedasticity were tested prior to interpretation using the Shapiro-Wilk normality test and a Breusch-Pagan test, respectively, and data were log-transformed when assumptions were not respected.A principal component analysis (PCA) was performed using the two sea-ice tracers  of birds between years. One-way ANOVA then enabled to test significant differences of each variable between years, and posthoc Tukey HSD tests were performed to locate these differences. Residuals normality and variance homogeneity were tested prior analysis with tests described above, and data were log-transformed when these assumptions were not respected.For each species, a Multivariate Analysis of Variance (MANOVA) was performed to test whether there were significant differences in the isotopic niche (δt-test to distinguish groups of murres in 2012 (H-Print and egg volume), for interspecific differences (δ15N) and for inter-annual differences in egg volume and energetic content between reduced-ice (i.e. 2011 and 2013) and extensive-ice years (i.e. 2010 and 2012). All statistical analyses and figures were computed in R90 (Version 3.5.0).Due to small sample sizes, we used Welch-modified All applicable institutional and national guidelines for the care and use of animals were followed and methods were carried out in accordance with relevant guidelines and regulations, including appropriate scientific and land use permits. All eggs were taken under appropriate annual research and collection permits . The local indigenous community was consulted and had representatives participate in the work in most years.Supplementary Information