TPSs) are the key enzymes responsible for the biosynthesis of terpenes. Although some species were employed for the genome-wide identification and characterization of the TPS family, limited information is available regarding the evolution, expansion, and retention mechanisms occurring in this gene family. We performed a genome-wide identification of the TPS family members in 50 sequenced genomes. Additionally, we also characterized the TPS family from aromatic spearmint and basil plants using RNA-Seq data. No TPSs were identified in algae genomes but the remaining plant species encoded various numbers of the family members ranging from 2 to 79 full-length TPSs. Some species showed lineage-specific expansion of certain subfamilies, which might have contributed toward species or ecotype divergence or environmental adaptation. A large-scale family expansion was observed mainly in dicot and monocot plants, which was accompanied by frequent domain loss. Both tandem and segmental duplication significantly contributed toward family expansion and expression divergence and played important roles in the survival of these expanded genes. Our data provide new insight into the TPS family expansion and evolution and suggest that TPSs might have originated from isoprenyl diphosphate synthase genes.Terpenes are organic compounds and play important roles in plant growth and development as well as in mediating interactions of plants with the environment. Terpene synthases ( C-methyl-d-erythritol 4-phosphate (MEP) pathway in plastids  motif and the C-terminal domain contains two highly conserved aspartate-rich motifs. One of them is the DDxxD motif, which is involved in the coordination of divalent ion(s), water molecules and the stabilization of the active site  of the arginine/tryptophan motif RRX8W is not conserved (TPS-b subfamily encodes monoTPSs and contains the conserved R(R)X8W motif, which functions in the initiation of the isomerization cyclization reaction X8W motif. These TPSs are required for biosynthesis of acyclic monoterpenes, which form floral VOCs X8W motif in its encoded proteins and its members may function in producing acyclic mono-, sesqui-, and diterpene products , 69 putatively functional TPSs have been identified by hidden Markov model (HMM) searches , 44 members were identified by TBLASTN searches  or the NCBI genome database . The sequences for the species Pic.abies were downloaded from the website http://congenie.org/; last accessed July 16, 2019 (Mentha spicata) and sweet basil (Ocimum basilicum), only assembled cDNA from RNA-Seq and their deduced amino acid sequences were used for this study. For another basil species Ocimumtenuiflorum, its genomic, cDNA, and protein sequences were downloaded from the TulsiDb .In this study, genomic, cDNA, and protein sequences from 50 species were used for genome-wide identification of 16, 2019 . For bothttp://www.clustal.org/; last accessed July 16, 2019). The aligned domain sequences were used to construct HMM profiles for either PF01397 or PF03936 with the HMMER 3.0 . We used these two profiles to carry out HMM searches against the above mentioned 50 protein databases with E-value cut-off of 1.0. Similarly, the HMM searches were also used to identify all putative TPSs in both mint and basil by searching against corresponding protein sequences deduced from assembled unigenes. These searches resulted in two sets of sequences containing either PF01397 or PF03936 domains. We then manually inspected these sequences by confirming the presence of these domains. Any artifacts were removed, which were lack either PF01397 or PF03936. The full-length TPSs with two domains were collected by combining these two sets of resulted data. On the other hand, to minimize the possible loss of any of putative TPSs, standalone BLASTP searches were also carried out by using the representative TPSs from the HMM searches with E-value cut at 0.01. After domain verification, these identified sequences were classified as the putative TPSs, which were used for all the remaining investigation in this study.All identified TPSs contain a conserved domain structure with the Pfam (pfam.xfam.org/) ID PF01397 or PF03936 and many of TPSs contain both of these domains. Representative domain sequences for either PF01397 or PF03936 were downloaded from the Pfam database and were used for sequence alignment using the program Clustal X 2.0 . The aligned sequences were used for phylogenetic tree construction by the MEGA7 program . The family classification was carried out according to the system developed by TPS-e and TPS-f were combined together into the subfamily TPS-e/f. We used either PF01397 or PF03936 for phylogenetic analysis followed by the family classification. The phylogenetic trees from these two domains showed the differences for some species. In this case, the trees deduced from the domain PF01397 were used for classification.A typical full-length  program . The tre program  and BootKa, Ks, and their ratios of these genes, their protein domain sequences were aligned, which were subsequently converted into the original cDNA sequences by using the PAL2NAL program  for constructing phylogenetic trees and 2) as a guideline for corresponding cDNA sequence alignment. Both phylogenetic trees and aligned cDNA sequences were then subjected to the “sitewise likelihood-ratio” (SLR) program  from multiple comparisons  for our analysis, which was downloaded from the website http://www.ebi.ac.uk/goldman-srv/SLR/; last accessed July 16, 2019.To determine purifying/positively selected amino acid sites in a  program  to detec program . The pro program  with the program . The posparisons . We usedhttp://www.ncbi.nlm.nih.gov/books/NBK52637/; last accessed July 16, 2019). Candidate sequences, which showed a minimum 70% of queried protein coding regions aligned with an E-value cutoff level at 0.01, were selected to further investigation. A HTG from a plant to a soil bacterium genome was identified when a candidate sequence showed the high-sequence similarity (>70% coverage and >80% identities in amino acid sequence) in multiple plant species but no significant homolog in any other bacteria.Horizontally transferred genes (HTGs) were identified between bacterium and plant genomes. Amino acid sequences from plant TPSs were used as queries to search against protein databases annotated from soil bacterium genome sequences using the standalone BLASTP program “ncbi-blast-2.4.0” , hobo/Ac/Tam3 (hAT), CACTA, and Helitron. The LTR_ FINDER program  isolation as described in http://trace.ddbj.nig.ac.jp/dra/index_e.html; last accessed July 16, 2019) with accession numbers DRA001856.Collected samples from roots, leaves, leaf-PGT, and PGT tissues were used for total RNA preparation using the Spectrum Plant total RNA kit from Sigma according to the manufacturer’s instructions. After checking the ratio of OD260 to OD280 and the integrity by measuring the RNA Integrity Number (RIN) using Agilent 2100 bioanalyser, eligible RNA samples were subjected to the RNA library construction using the TruSeq RNA Sample Preparation Kits v2, set A . The libraries were subjected to RNA-Seq by Hiseq-2000 (illumine Inc.). The unigene assembly and related bioinformatics analysis were carried out as described by TPSs. For the wheat TPS expression analysis, the RNA-Seq data sets including 57 sets of running were downloaded from the European Nucleotide Archive database  with accession number ERP004714. The data set was used to evaluate the expression patterns of the wheat TPSs and their expression divergence of tandemly or segmentally duplicated genes. For the Arabidopsis TPS expression analysis, the microarray data set containing 24 experimental samples were downloaded from the NCBI GEO data set  with accession number GSE5634. The data set was used to investigate the Arabidopsis TPS expression patterns and their expression divergence after duplication. For the mint and basil TPS expression, a total of eight and four RNA samples were submitted to RNA-Seq analysis, respectively. The original data sets have been deposited into the DDBJ database as mentioned earlier. For RNA-Seq data, transcript abundance was estimated by raw read counts and FPKM (Fragments Per Kilobase of transcript per Million mapped reads) values, which were calculated from the three replicates for wheat and one replicate was carried out for mint and basil. The resulted FPKM values were log2-transformed and were then used to generate heat maps. For microarray data set, normalized expression values were calculated from raw data using the Agilent GeneSpring GX 11.5 software, which were used to construct heat map. The heat map was prepared by the Java Treeview . A tissue-preferred gene or expression divergence among expanded/duplicated genes was determined according to their tissue specificity and/or expression abundance among different tissues or under different abiotic/biotic stresses. Genes with at least two times difference in their log2-transformed or normalized expression value between tissues/treatments were submitted for statistical analysis (Student’s t-test). These genes which showed at least two times higher in one tissue when compared with any other tissues with a statistical difference at P < 0.05 were regarded as a tissue-preferred gene. Similarly, expression divergence of two genes was statistically determined when a gene showed at least two times difference in their expression abundance in any tissues or under any treatments.Several expression data sets from either microarray or RNA-Seq experiments were achieved for profiling transcriptome of TPS family in the plant kingdom, the assembled genome sequences and their annotated protein sequences from all of the 50 species were downloaded for the HMM searches to figure out all members encoding either PF01397 or PF03936 domains . These species include algae, liverwort, moss, gymnosperm, and angiosperm , Cyanidioschyzon merolae , Bigelowiella natans . However, no TPS was detected from all these genomes.To obtain a general profile of the giosperm A. Our daorophyta B. Besideurpureum   mostly encoded small size of TPS families ranging from two to six full-length TPSs. The remaining species encoded at least 11 full-length TPSs. Only two TPSs Zosma26g01520 and Zosma52g00660 were identified in the aquatic plants (E. grandis and Aquilegia coerulea encoded the highest numbers (70) of full-length TPSs. In monocot plants, the highest numbers (79) of full-length TPSs were detected in the species Panicum virgatum  and full-length cDNAs, TPSs but these members were from several Picea species. In the Picea glauca genome, 83 unique TPSs were identified; however, they were unique gene models but not gene loci  followed by TPS-c (3) and TPS-e/f (2) based on the PF01397 domain sequences , liverwort (Marchantia polymorpha), and algae (no TPS), all other species encoded the TPS-e/f subfamilies , one moss , one lycophyte (S. moellendorffii), one gymnosperm (Pic.abies), three monocots , and three dicots . To determine the degrees of expansion among species during long evolutionary history, we broke down the phylogeny into ancestral units according to the method described by TPS (red star). No expansion occurred during the evolution to the MRCA of moss, gymnosperm, and angiosperm (blue triangle). After the origin of seed plants, one more TPS was found expanded in the MRCA of gymnosperm and angiosperm (filled pink circle). After this period, no expansion seems to have occurred in the MRCA of monocot plants (green square). However, three more TPSs expanded from the MRCA of dicot plants (black diamond). Thus, much larger size of the TPS families has evolved from the MRCA in dicots than in monocots. These data demonstrate that both monocot and dicot plants exhibit differences in TPS family expansion history. Further, many members from one species tend to cluster together, exhibiting lineage-specific expansion. A large scale of family expansion might occur during species divergence. In TPS-a and TPS-b. In E. grandis, the largest cluster consists of 38 TPS members and all of them belong to the subfamily TPS-a. Thus, subfamilies were mainly expanded through species-specific expansion.As no analysis . These sTPS subfamilies and found large expansion mainly in dicots and monocots , CACTA, and Helitron families toward this. Our data showed that few family members were expanded by these mobile elements indicating a limited contribution of these elements to family expansion. Compared with other species, less contribution of both tandem and segmental duplication to the maize TPS expansion was observed  were fully or partially located in a LTR-retrotransposon. One of the examples is shown in TPS gene GRMZM2G465812 is located between primer-binding site (PBS) and polypurine tract (PPT). Besides LTR-retrotransposons, we also surveyed the contributions of other mobile elements to the maize TPS family expansion. The data showed that except for one CACTA element, no other mobile elements were related to the family expansion.In addition to tandem and segmental duplications, other mechanisms can also contribute to family expansion. We examined the role of various mobile elements including long terminal repeat (LTR)-retrotransposons, retrogenes, mutator-like transposable element (MULE), observed A and B. http://www.ebi.ac.uk/interpro/entry/IPR000092/taxonomy; last accessed July 16, 2019). We used the PPD HMM profile to search against these bacterial IDS and TPS proteins. We detected 20,113 PPDs in 22,375 IDSs (89.9%) but none were found in TPSs.Both monoterpenes and diterpenes are synthesized from cis-prenyl diphosphates, which are substrates synthesized by cis-prenyl transferase genes. Report showed that prenyltransferase with Pfam ID PF01040 also exhibited TPS activity in animals . HoweverTo further analyze the sequence similarity between PPDs from IDSs and from TPSs, the 34 unique PPDs (33 amino acids in length) from IDSs were then submitted to BLAST searches against all 2,562 TPSs with e-value <0.01. Only 18 TPSs were obtained from these searches with PPD homolog. These PPDs from 18 TPSs and 34 IDSs were then used for alignment analysis. A total of five amino acid sites are very conserved (100% homolog) among these 52 analyzed sequences and they are highlighted by red, green, and blue colors B. BesideKa/Ks = 0. The most variable site was the fourth amino acid with Ka/Ks = 0.075. The average Ka/Ks is 0.017. The data reveal strong purifying selection of PPD sites even among different orders of species. IDSs are widely present in human/animals, plants, fungi, bacteria, and even in viruses while TPSs are mainly in plants, fungi, and bacteria. Some IDSs do exhibit TPS activities and we found that they have the common PPD motif. This suggests that TPS might have evolved from IDSs.As PPDs from both TPS and IDS fell into different groups, we studied the selection force on these 33 amino acids sites among different species by using the sitewise likelihood-ratio (SLR) program . Both alCitrus sinensis, up to 45 PF01397 and 51 PF03936 domain encoding TPSs genes were identified; however, only 30 out of them were full-length TPSs with two domain structures . Expression data for the remaining 66 TPSs is shown in TPSs including 2BL_135C46DE5.1 and 2DL_8E2AEFA74.2 (P < 0.01) that all duplicated genes showed expression divergence either in expression abundance in a specific tissue or in tissue specificity. For example, both 2DL_8B87AB74D.1 and 2DL_8E2AEFA74.2 were tandemly duplicated; the former showed root-preferred expression and the latter showed no expression in all tested tissues. Another example is the segmentally duplicated genes 1BS_8A9B3CE82.1 and 7BL_BFF509C87.2, they showed totally different expression patterns.We were interested to know how these genes survived after the large scale of expansion by duplication. Our data showed that the xpansion . RNA-Seqxpansion A. Among AEFA74.2 A. IntereA.thaliana, tandem duplication is the main force for the family expansion. In this species, a total of eight tissues were selected for expression analysis using microarray data as described in the methods. These tissues were sampled from eight different developmental stages (Stage 3 to Stage 10)  . Similar Stage 4 B. Both A tissues B. Tandem tissues B. Thus, O.tenuiflorum  tissues similar to mint. Based on the transcriptomic data set, we identified 25 full-length TPSs, 9 partial TPSs encoding PF01397 domain only and 8 partial TPSs with PF03936 domain only  and Ote100185690021 or Ote100079410021 (indicated by “#”) clustered into TPS-a, when the PF01397 domain sequences were used for phylogenetic analysis  PGT-preferred TPSs, 8 TPSs encoded both PF01397 and PF03936 domains. Four PGT-preferred TPSs encoded only one domain and three of them contained only the PF01397 domain including comp26858_c1, comp35437_c0, and comp43257_c0 and the remaining one comp34823_c3 encoded the PF03936 domain. However, this is only based on RNA-Seq assembling result and further experiments such as RACE  showed expression signal only in roots  showed PGT-preferred expression pattern. These data suggest the tissue-specific functions of some TPSs toward producing specialized metabolites in specific organs such as PGTs for plants ecological benefit.For the basil TPSs in plants, fungi, and bacteria shared a common evolutionary origin since they have similar reaction mechanism, conserved domain organization, intron, and exon structures , a total of 103 protein sequences has been deposited, which contain the PF03936 domain structure. We downloaded these protein sequences and then submitted to BLASTP search against all TPS proteins that were identified from the 50 species. We detected two bacterium proteins showed high-sequence similarity to plant TPSs. One of them is with protein ID A0A0C3RJ57 in the database (175aa), which showed 100% homolog (1-175aa) to a cotton protein with locus name Gorai.009G428400.1. Another one is A0A0C3RA45 (177aa), which showed 97.2% of identity (1-177aa) to the cotton protein sequence with locus name Gorai.009G428200.1. In the cotton genome, these two loci were tandem duplicated. Both A0A0C3RJ57 and A0A0C3RA45 are from the bacterium Nitrosospira sp NpAV. Its genome is fully sequenced and encodes 3,242 annotated genes . The genome-wide survey identified only two members of TPSs (A0A0C3RJ57 and A0A0C3RA45) in the bacterium. Three other genomes from Nitrosospira have also been sequenced and they are Nitrosospira multiformis, Nitrosospira briensis, and Nitrosospira lacus. All these three genomes do not encode any TPS based on our HMM/BLASTP searches against these protein data sets. In addition, no significant homologs of both A0A0C3RJ57 and A0A0C3RA45 (identities > 50%) could be found in any other bacteria in the Interpro database. On the contrary, many homologous TPSs could be detected among plant species when these two members were used as query for BLASTP searches against plant genomes. Thus, our analysis provided molecular evidence that these two members of bacterium TPSs might be horizontally transferred from the plant species Gossypium raimondii. However, no experimental evidence was obtained. It is possible that the observed results might be due to sample contamination; thus, further study should be carried out to confirm the HGT event.Evidence shows that ructures . These sa fungus . InteresTPSs among plants, fungi, and bacteria and at least one MRCA was detected among the 50 plant species. On the other hand, little is known as to why animals contain no TPS. Most of our knowledge on TPSs comes from plant studies. However, some animals have the ability to synthesize terpene-derived secondary metabolites. Evidence shows that these terpenes are synthesized by either prenyltransferase  different genome assemble and annotation version, 2) either PF01397 or PF03936 included, 3) different search methods, and 4) different databases. For example, TPSs in V.vinifera  and basil (O.basilicum) plants using our RNA-Seq data. No TPSs were identified in all six green algae genomes and the lack of algae TPSs was further confirmed by searching additional 12 algae genomes. The remaining 44 plant species encode various sizes of TPS family members ranging from 2 to 79 full-length TPSs. Phylogenetic analysis showed that these TPSs could be classified into seven different subfamilies including TPS-a, -b, -c, -d, -e/f, -g, and -h. No genome encodes all seven subfamilies of TPSs, suggesting the divergence of this family during long evolutionary history. Some species showed lineage-specific expansion of some subfamilies and a large-scale family expansion occurred mainly in dicot and monocot plants. Further investigation showed that both tandem and segmental duplication significantly contributed to the family expansion. Further analysis showed that expression divergence significantly contributed to gene survival after duplication or expansion. Interestingly, not only alga but also animals contain no TPS; however, they all encode IDSs. Our data provided the clue that TPSs might have originated from IDSs.In the present study, both N- and C-terminal domain sequences of seed TPSs were separately used to construct HMM profiling. They were then employed for HMM searches to genome-widely identify the Supplementary_Data_evz142Click here for additional data file.


Jsc) of the ternary OSC to 23.46 mA cm−2, with a 44% increment over those of binary devices. The significant current improvement originates from the broadened absorption range and the active layer morphology optimization through the introduction of IEICO‐4F component. Furthermore, the energy loss of the ternary cells (0.59 eV) is much decreased over that of the binary cells (0.80 eV) due to the reduction of both radiative recombination from the absorption below the band gap and nonradiative recombination upon the addition of IEICO‐4F. Therefore, the power conversion efficiency increases dramatically from 8.82% for the binary cells to 11.20% for the ternary cells. This work provides good examples for simultaneously achieving both significant current enhancement and energy loss mitigation in OSCs, which would lead to the further construction of highly efficient ternary OSCs.Herein, efficient organic solar cells (OSCs) are realized with the ternary blend of a medium band gap donor thiophen‐2‐yl)‐benzodithiophene))‐alt‐benzodithiophene‐4,8‐dione)] (PBDB‐T)) with a low band gap acceptor ‐bis‐4H‐cyclopentadithiophene‐6,2‐diyl))bis(methanylylidene))bis)dimalononitrile (HF‐PCIC)) and a near‐infrared acceptor ‐‐4,9‐dihydro‐s‐indacenodithiophene‐2,7‐diyl)bis(4‐((2‐ethylhexyl)oxy)thiophene‐5,2‐diyl))bis(methanylylidene))bis)dimalononitrile (IEICO‐4F)). It is shown that the introduction of IEICO‐4F third component into PBDB‐T:HF‐PCIC blend increases the short‐circuit current density ( Jsc) or fill factor (FF).Bulk‐heterojunction organic solar cells (OSCs) have received great progresses in recent years with the development of new photovoltaic materials and device engineering.Jsc is strongly expected. However, even the photocurrent response is enhanced in the part of the third component due to the broadened absorption, those in the parts of the original donor and acceptor are rarely seen improved, thus limiting the improvement of Jsc for TOSCs. Consequently, the increases in PCEs of TOSCs are also limited compared to those of binary OSCs. To address this issue, the introduced third component should not only own complementary absorption to those of original donor and acceptor, but also solve the drawbacks in morphology existing in the original binary blend.Although TOSCs are considered as an effective method to promote the performances of OSCs, many challenges remain unresolved for TOSCs. The top one of them is the disrupted morphology of the original binary blend, when the third component is added. As a result, the reduced FF is commonly observed.Voc) in TOSCs.Voc, there are three main different situations. The first one is that Voc will proportionally vary with the ratios of third component, namely, Voc will be lifted by adding a higher LUMO  acceptor or a deeper HOMO  donor, and vice versa.Voc is nearly decided by the smallest gap between the HOMO of donor and the LUMO of acceptor regardless of adding a higher LUMO acceptor or a deeper HOMO donor.Voc will almost keep the high value as that of binary OSCs when adding a lower LUMO acceptor.Voc is achieved by adding a third component with near‐infrared absorption and lower LUMO level, energy loss must be reduced to achieve this. Therefore, the last situation is preferred. However, the third situation is still rarely seen in TOSCs. In addition to these three situations, a recent paper reported a TOSC that demonstrated higher Voc values than both binary devices.Another challenge is how to reduce the energy losses for achieving a high open‐circuit voltage  the π–π stacking of acceptor–donor–acceptor (A–D–A) type nonfullerene acceptors is realized through the terminals of molecules, therefore, the same terminal structure of 2‐malononitrile (IC‐2F) may allow these two nonfullerene acceptors (HF‐PCIC and IEICO‐4F) to show good compatibility. The ternary PBDB‐T:HF‐PCIC:IEICO‐4F and the control binary PBDB‐T:HF‐PCIC solar cells are fabricated. The optimized TOSCs exhibit the best PCE of 11.20% with an excellent Jsc of 23.46 mA cm−2 and a Voc of 0.78 V. Compared with the binary solar cells , a dramatic efficiency improvement of 27% and a significant current enhancement of 7.20 mA cm−2 are observed in TOSCs. To the best of our knowledge, such a huge current enhancement is the highest value ever reported in TOSCs. Besides, nearly constant Voc is achieved regardless of the change of IEICO‐4F ratios. Further characterizations reveal that the energy loss of TOSCs is reduced to 0.59 eV, much smaller than that (0.80 eV) for the binary solar cells. Therefore, our work provides good guidelines for achieving a large current enhancement and a small energy loss in TOSCs, thus leading to the successful construction of highly efficient TOSCs.Here, we report highly efficient fullerene‐free TOSCs that have addressed the above‐mentioned two challenges in current enhancement and energy loss. The TOSCs are based on a polymer donor, polydithiophene))‐alt‐benzodithiophene‐4,8‐dione)] (PBDB‐T), and two nonfullerene acceptors, 2,2′‐‐bis‐4H‐cyclopentadithiophene‐6,2‐diyl))bis(methanylylidene))bis)dimalononitrile (HF‐PCIC) and 2,2′‐‐‐4,9‐dihydro‐s‐indacenodithiophene‐2,7‐diyl)bis(4‐((2‐ethylhexyl)oxy)thiophene‐5,2‐diyl))bis(methanylylidene))bis)dimalononitrile (IEICO‐4F) Figure1a. HF‐Figure 3/Ag propyl)‐2,7‐fluorene)‐alt‐2,7‐ and the thermal annealing at 110 °C for 10 min. More information about the optimization of the binary solar cells can be found in Table S1 (Supporting Information). Keeping the total D/A weight ratio as 1:1.2, different weight ratios of IEICO‐4F are added to the PBDB‐T:HF‐PCIC blends as the third component, and the TOSCs are fabricated with the same post‐treatment methods as those for binary solar cells.An inverted device structure of ITO/ZnO/PFN/Active Layer/MoOg Figure d is applJ–V curves of binary solar cells and TOSCs are displayed in FigureTableVoc of 0.80 V, a Jsc of 16.26 mA cm−2, and an FF of 68.44%. When 25% IEICO‐4F is introduced as the third component, the PCE of TOSCs is improved to 10.41% with a Voc of 0.79 V, a Jsc of 20.34 mA cm−2, and an FF of 63.01%. It is obvious that the addition of IEICO‐4F has little impact on the Voc and a negative effect on the FF. However, the Jsc has a huge enhancement of 4.08 mA cm−2, thus promoting the improvement of PCE. Upon the addition of 35% IEICO‐4F to the ternary blends, a champion PCE of 11.20% is achieved. For the champion device, though the FF is further reduced to 60.99%, the Jsc shows a recorded value of 23.46 mA cm−2, which is responsible for the substantial improvement of PCE. Notably, compared with the PBDB‐T:HF‐PCIC based binary solar cells, a significant current enhancement of 7.2 mA cm−2 is observed. If further increasing the weight ratio of IEICO‐4F to 45%, the PCE is reduced to 9.93% with the decrease in Jsc and FF. We also fabricate the binary solar cells based on PBDB‐T:IEICO‐4F blends under the same conditions as those for PBDB‐T:HF‐PCIC based devices. The PCE of PBDB‐T:IEICO‐4F based devices is relatively low with the value of 6.64% due to the disappointing FF of 44.60%. The above results reveal that IEICO‐4F is a satisfied material as the third component to enhance the Jsc for TOSCs. More results of ternary solar cells with different weight ratios of IEICO‐4F can be found in Table S2 (Supporting Information), and stable voltages as high as 0.76 V are still remained even if the weight ratios of IEICO‐4F vary from 55% to 85%.The Jsc enhancement in TOSCs. More importantly, it is observed that the photocurrent responses are also enhanced in the ranges of 400–500 and 550–800 nm. Since PBDB‐T and HF‐PCIC are responsible for the photocurrent responses in the ranges of 400–700 nm and 550–800 nm, respectively, the addition of IEICO‐4F in fact helps improve the photocurrent response of both PBDB‐T and HF‐PCIC. Besides, the device with 35% IEICO‐4F shows the highest EQEs in all of main absorption bands from the three components, implying that synergistic effect of three components induces the optimized morphology, which is in accordance with the results in J–V curves.External quantum efficiency (EQE) spectra are presented in Figure −2 and mostly in the range of 1–3 mA cm−2. The current enhancement of 7.2 mA cm−2 observed in our work is the highest value ever seen so far in TOSCs. Such a large current enhancement corresponds to a 44% improvement  at 975 nm. When IEICO‐4F is added to HF‐PCIC, the PL emission of HF‐PCIC is instantly diminished while the PL emission of IEICO‐4F is significantly enhanced with the intensity two times over that of the neat IEICO‐4F, suggesting that efficient energy transfer happens between HF‐PCIC and IEICO‐4F  spectra of acceptor mixtures with different weight ratios of IEICO‐4F Figure3a. ForWe further confirm the energy transfer via the transient absorption (TA) spectroscopy measurements, and the results are shown in Figure 1 represents the excitation process with the time scale of less than 1 ps. Here, in our cases, the values of τ1 are 0.14 and 0.18 ps for the neat HF‐PCIC and IEICO‐4F films, respectively. Then, τ2 reflects the first decay stage with the time scale of 10 ps, more or less. In our cases, the values of τ2 are 18.76 and 3.18 ps for the neat HF‐PCIC and IEICO‐4F films, respectively. When HF‐PCIC is mixed with IEICO‐4F, it can be seen from the kinetic curves that the excitation process is not influenced (τ1 = 0.15 ps), but the first decay stage becomes faster (τ2 = 1.95 ps). We suppose, the shortened lifetime constant of the first decay stage indicates the possible existence of extra process inducing the rapid decay besides spontaneous quenching. This extra process could be the energy transfer between HF‐PCIC and IEICO‐4F, and this process of energy transfer should also be fast. Apparently, energy transfer between HF‐PCIC and IEICO‐4F confirmed by PL and TA spectroscopy measurements plays an important role in the achievement of significant current enhancement, especially in the photocurrent response of IEICO‐4F.Figure 3/Ag, in which PEDOT:PSS is poly:poly(styrenesulfonate), while those of electron‐only devices are ITO/ZnO/PFN/Active Layer/PFN/Al. For the binary devices, the hole mobilities and electron mobilities are measured to be 1.63 × 10−4 cm2 V−1 s−1 and 0.47 × 10−4 cm2 V−1 s−1 for PBDB‐T:HF‐PCIC films, and 3.88 × 10−4 cm2 V−1 s−1 and 0.19 × 10−4 cm2 V−1 s−1 for PBDB‐T:IEICO‐4F films, respectively. After IEICO‐4F is introduced to PBDB‐T:HF‐PCIC films, all the ternary devices show improved hole mobilities but reduced electron mobilities when compared with those of PBDB‐T:HF‐PCIC films. The improved hole mobilities can help enhance the photocurrent response of PBDB‐T. Anyway, among the ternary devices, the film with 35% IEICO‐4F possesses the highest values and the most balanced ratio of hole and electron mobilities, thus allowing TOSCs with 35% IEICO‐4F show the best performances.The space charge limited current (SCLC) method is applied to check the charge transport properties of PBDB‐T:HF‐PCIC:IEICO‐4F films with various compositions , and relevant data are summarized in Table S4 (Supporting Information). The structures of hole‐only devices are ITO/PEDOT:PSS/Active Layer/MoOFigure−1 both in the out‐of‐plane and in‐plane directions, but the intensity of the peak in the out‐of‐plane direction is much stronger than that in the in‐plane direction. Besides, a weak broad (010) π–π stacking diffraction peak appears at 1.67 Å−1 in the out‐of‐plane direction, giving a stacking distance of 3.76 Å. For the neat HF‐PCIC film, a lamellar peak appears in the in‐plane direction at 0.490 Å−1 and a strong π–π stacking peak appears in the out‐of‐direction at 1.73 Å−1 (d = 3.63 Å), indicating that HF‐PCIC crystalline domains are dominantly face‐on oriented. Along the qz axis, there is another peak at 0.680 Å−1, indicating the existence of an additional structural ordering (d = 9.38 Å) normal to the substrate for the HF‐PCIC crystalline packing, though its origin is not clear. For the neat IEICO‐4F film, a π–π stacking peak at 1.81 Å−1 in the out‐of‐plane direction, giving a stacking distance of 3.47 Å, and a lamellar peak at 0.300 Å−1 in the in‐plane direction are observed, illustrating that IEICO‐4F also prefers the face‐on orientation. The binary PBDB‐T:HF‐PCIC blended film shows the in‐plane lamellar peak at 0.300 Å−1 and the out‐of‐plane lamellar peak at 0.330 Å−1, originated from the PBDB‐T crystalline domains. Compared with the corresponding peak intensity observed in the neat PBDB‐T film, the face‐on ordering is enhanced while the edge‐on ordering is weakened, which is a good trend for hole transport in photovoltaic devices. The scattering peaks of HF‐PCIC crystalline domains  can be clearly observed, indicating the maintaining of the HF‐PCIC crystalline packing in the binary film. When 25% IEICO‐4F is introduced to PBDB‐T:HF‐PCIC blended film, all the peaks remain at the same position, except for the π–π stacking peak, which appears at a relatively larger q (≈1.76 Å−1) in the out‐of‐plane. When the content of IEICO‐4F is increased to 35%, a similar GIWAXS pattern is observed. If further increasing the content of IEICO‐4F to 45%, the scattering intensity is significantly weakened, suggesting a decrease of the overall crystallinity of the film, which is not preferred. In a word, the enhancement of face‐on ordering and the tighter π–π stacking when not too much IEICO‐4F was added should be responsible for the photocurrent response enhancement of PBDB‐T and HF‐PCIC, compared with the PBDB‐T:HF‐PCIC based binary solar cells.Grazing‐incidence wide‐angle X‐ray scatteringTo investigate the impact of introducing IEICO‐4F on the thin film morphology, atomic force microscopy (AFM) and transmission electron microscopy (TEM) measurements are performed . Totally different morphological features are observed for two binary thin films in AFM images. A rough surface with obvious domains is present for the PBDB‐T:HF‐PCIC film, while the PBDB‐T:IEICO‐4F film shows a smooth and homogeneous surface. These should be related with the high crystalline property of HF‐PCIC and the relative low crystalline nature of IEICO‐4F. When IEICO‐4F is added to the PBDB‐T:HF‐PCIC films, the obtained ternary blends exhibit decreased surface roughness with reduced domain sizes. This change is reasonable since the low crystalline IEICO‐4F will influence the crystallization behavior of HF‐PCIC. But if too much IEICO‐4F is added, charge transport of the blends will be hindered, just as demonstrated in the SCLC measurement. Therefore, ternary blend with 35% IEICO‐4F shows the balanced domain sizes with superior charge transport properties remained. TEM images show the similar trend as revealed in AFM images. The optimized domain sizes, thereby a better morphology should be responsible for the photocurrent enhancement of HF‐PCIC.Jsc, employing nonfullerene acceptors in OSCs is an effective way to lower the energy loss, thus achieving a high Voc. Normally, energy loss can be defined as the following equation (see Note 1 in the Supporting Information)Eloss or ΔΕ is the energy loss, Egap is the band gap, VocSQ is the maximum voltage calculated by the Shockley–Queisser limit, Vocrad is the open‐circuit voltage when there is only radiative recombination, ΔVocrad,below gap is the voltage loss of radiative recombination from the absorption below the band gap, and ΔVocnon‐rad is the voltage loss of nonradiative recombination. Therefore, energy loss (ΔΕ) consists of three parts . In general, ΔΕ1 (Egap – qVocSQ) is unavoidable and the value could be 0.25–0.30 eV. As for ΔΕ2 , it varies greatly among different types of solar cells. It is negligible for inorganic or perovskite solar cells, but usually high for OSCs. In OSCs, a large contribution to ΔΕ2 is the existence of charge‐transfer (CT) states. The third part of ΔΕ3 (qΔVocnon‐rad) can be calculated through the following equationk is the Boltzmann constant (≈1.38 × 10−23J/K), T is the absolute temperature, and EQEEL is the radiative quantum efficiency of the solar cell when charge carriers are injected into the device in the dark.In addition to the advantage of obtaining high Voc and find out the exact values of three parts of energy loss, we measure the Fourier‐transform photocurrent spectroscopy external quantum efficiency (FTPS‐EQE) , and then the products of Egap's distribution and Egap itself are integrated to calculate the specific optical Egap for 0%, 35%, and 100% blend‐based devices, and the results are listed in TableEL values (see Note 3 in the Supporting Information) are measured to be 4.3 × 10−7, 2.7 × 10−5, and 1.6 × 10−5 for 0%, 35%, and 100% blends, respectively, ΔΕ3 values are calculated as 0.38, 0.28, and 0.28 eV for 0%, 35%, and 100% blends. Obviously, the nonradiative recombination is greatly reduced for TOSCs, relative to that of PBDB‐T:HF‐PCIC‐based binary solar cells. Besides, ΔΕ2 values are found to be 0.13, 0.04, and 0.04 eV for 0%, 35%, and 100% blends, respectively, which means the radiative recombination from the absorption below the band gap is also largely reduced for TOSCs, relative to that of PBDB‐T:HF‐PCIC‐based binary solar cells. Such a low ΔΕ2 value of 0.04 eV for TOSCs is comparable to that of inorganic solar cells. Without doubts, the decreases of ΔΕ2 and ΔΕ3 lead to the reduced energy loss of 0.59 eV for TOSCs. Interestingly, by adding IEICO‐4F to the binary blend, the energy loss of ternary blend is directly determined by the material with the lowest energy loss, which is preferred. So, the achievement of a small energy loss of 0.59 eV should be the reason for the nearly constant Voc in TOSCs.To confirm the origin of nearly constant ) Figureb of two Jsc from 16.26 to 23.46 mA cm−2, and reduced energy loss from 0.80 to 0.59 eV. As a result, PCE is increased from 8.82% of binary OSC to 11.20% of ternary OSC. It is proved that the third component IEICO‐4F can not only broaden the absorption range but also work as morphology modifier in our TOSC, and there also exists efficient energy transfer between HF‐PCIC and IEICO‐4F. These reasons should account for the greatly enhanced Jsc. Furthermore, the reducing in both voltage losses caused by radiative recombination from the absorption below the band gap and nonradiative recombination after introducing IEICO‐4F is the reason for the small energy loss of 0.59 eV and a high Voc of 0.78 eV for TOSCs. Our results indicate that combining two nonfullerene acceptors with complementary absorption and divergent crystallinity is effective to achieve a significant current improvement via the realization of energy transfer and optimized morphology. Besides, the component with the narrowest band gap in the ternary blend had better be a low energy loss material, so as to reduce the impact of extending absorption range on the Voc. Thus, our designing strategy can provide good guidelines for the future development of TOSCs.In summary, a type of TOSC with a significant current enhancement of 44% and a small energy loss of 0.59 eV is successfully demonstrated by introducing a near‐infrared nonfullerene acceptor (IEICO‐4F) as the third component to the binary blend of PBDB‐T:HF‐PCIC. Comparing with binary PBDB‐T:HF‐PCIC solar cells, ternary PBDB‐T:HF‐PCIC:IEICO‐4F solar cells exhibit enhanced The authors declare no conflict of interest.SupplementaryClick here for additional data file.


N-Methyl-D-aspartate receptor (NMDAR) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) activations induce fast and transient mitochondrial fragmentation under pathophysiological conditions. However, it is still unknown whether NMDAR or AMPAR activity contributes to mitochondrial dynamics under physiological conditions. In the present study, MK801 (a non-competitive NMDAR antagonist) did not affect mitochondrial length in hippocampal neurons as well as phosphorylation levels of dynamin-related protein 1 (DRP1)-serine (S) 616, extracellular-signal-regulated kinase 1/2 (ERK1/2), c-Jun N-terminal kinase (JNK), p38 mitogen-activated protein kinase (p38 MAPK) and AMPAR. In contrast, perampanel (a non-competitive AMPAR antagonist) elongated mitochondrial length in neurons concomitant with diminishing phosphorylations of DRP1-S616, ERK1/2, and JNK, but not p38 MAPK. Perampanel also reduced protein phosphatase (PP) 1, PP2A and PP2B phosphorylations, indicating activations of these PPs which were unaffected by MK801. U0126 (an ERK1/2 inhibitor) elongated mitochondrial length, accompanied by the reduced DRP1-S616 phosphorylation. SP600125 (a JNK inhibitor) did not influence mitochondrial length and DRP1 phosphorylations. Okadaic acid (a PP1/PP2A inhibitor) reduced mitochondrial length with the up-regulated DRP1-S616 phosphorylation, while CsA (a PP2B inhibitor) increased it with the elevated DRP1-S637 phosphorylation. Co-treatment of okadaic acid or CsA with perampanel attenuated the reductions in DRP1-S616 and -S637 phosphorylation without changing DRP1 expression level, respectively. GYKI 52466 (another non-competitive AMPAR antagonist) showed the similar effects of perampanel on phosphorylations of DRP1, ERK1/2, JNK, PPs, and GluR1 AMPAR subunits. Taken together, our findings suggest that a blockade of AMPAR may regulate the cooperation of ERK1/2- and PP1/PP2A for the modulation of DRP1 phosphorylations, which facilitate mitochondrial fusion. Mitochondria are dynamic organelles responsible for the generation of ATP via oxidative phosphorylation, which is essential for cell viability. To maintain mitochondrial homeostasis, mitochondria change their shapes by mitochondrial dynamics  and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) activations induce fast and transient mitochondrial fragmentation  drives mitochondrial division, while mitofusin 1/2 (MFN1/2) and optic atrophy 1 (OPA1) mediate mitochondrial elongation . Recentlentation . In contentation . Interesentation . Since Ntion  and non-competitive AMPAR antagonists (perampanel and GYKI 52466) on mitochondrial length in the rat hippocampal neurons to elucidate the receptor-mediated mechanisms underlying the mitochondrial dynamics ad libitum under controlled conditions . Animal protocols were approved by the Institutional Animal Care and Use Committee of Hallym University . The number of animals used, and their suffering were minimized in all cases. All reagents were obtained from Sigma-Aldrich , except as noted.Male Sprague-Dawley (SD) rats  were used in the present study. Animals were given a commercial diet and water n = 14), perampanel , GYKI 52466  or saline  was daily administered at a certain time of the day (PM 6:00) over a 1 week period. In pilot study, these dosages of MK801, perampanel, or GYKI 52466 treatment did not show behavioral and neurological defects in normal animals. After treatments (18 h after the last treatment), animals were used for western blot study and immunohistochemistry.MK801 , animals were infused with each chemical into the right lateral ventricle  using a brain infusion kit 1 and an Alzet 1007D osmotic pump . The osmotic pump contained (1) vehicle (n = 14), (2) U0126 , (3) SP600125 , (4) okadaic acid , (5) cyclosporin A , (6) U0126 + okadaic acid (n = 7), or (7) U0126 + CsA (n = 7). In pilot study and our previous studies, each compound treatment did not show behavioral and neurological defects in normal animals  were also given perampanel by the same protocol aforementioned. Seven days after infusion, animals were used for western blot and immunohistochemistry .Under Isoflurane anesthesia  were sacrificed via decapitation, the hippocampi were obtained. The hippocampal tissues were homogenized and protein concentration determined using a Micro BCA Protein Assay Kit . Western blot was performed by the standard protocol. The primary antibodies used in the present study were listed in After animals  were anesthetized with urethane  and then transcardially perfused with 4% paraformaldehyde (pH 7.4). The brains were removed and post-fixed overnight in the same solution, then sequentially placed in 30% sucrose at 4°C. Coronal sections were cut at a thickness of 30 μm on a cryostat. During sections, we confirmed the intracerebroventricular location of a brain infusion kit. Free-floating sections were first incubated with 10% normal goat serum  in PBS for 30 min at room temperature. Sections were then incubated in a mitochondrial marker  as the primary antibody (in PBS containing 0.3% Triton X-100) at room temperature overnight. After washing in PBS, sections were incubated for 1 h in a Cy3-conjugated secondary antiserum. For negative control, the hippocampal tissues were incubated with pre-immune serum instead of primary antibody. As the result of the negative control test, no immunoreactive structure was observed. Images were captured using an AxioImage M2 microscope or a confocal laser scanning microscope . Individual mitochondrion length in PV cells and CA1 neurons (n = 20/section) was measured by using ZEN lite software  following 3D-reconstruction: based on our previous study , SP600125 (a JNK inhibitor), okadaic acid (a PP1/PP2A inhibitor) and CsA (a PP2B inhibitor) on DRP1 phosphorylation and mitochondrial length to confirm the underlying mechanism of perampanel for mitochondrial dynamics. All chemicals did not affect DRP1 expression in the hippocampus . Howeverp < 0.05 vs. vehicle, n = 7, respectively; p < 0.05 vs. vehicle, n = 7, respectively; U0126 and SP600152 reduced ERK1/2 and JNK phosphorylations without altering their expression levels  PP1/PP2A and PP2B, we also applied co-treatment of okadaic acid, or CsA, with perampanel to investigate the role of PPs on DRP1 phosphorylation induced by perampanel. Co-treatment of okadaic acid and CsA with perampanel significantly attenuated the reductions in DRP1-S616 and -S637 phosphorylations without changing DRP1 expression level, respectively , on DRP phosphorylations and activities of kinases as well as PPs. Similarly to perampanel, GYKI 52466 reduced DRP1-S616 phosphorylation but not S637 phosphorylation level, without affecting DRP1 expression  831 site when NMDAR activation, while GluR1-S845 phosphorylation was decreased  of ERK1/2, PKC and JNK, but not p38 MAPK. Based on these results, it is likely that the blockade of AMPAR would inhibit mitochondrial fission by decreasing ERK1/2 and JNK activities. However, our other studies reveal that U0126 (an ERK1/2 inhibitor), but not SP600125 (a JNK inhibitor), abrogated DRP1-S616 phosphorylation and evoked mitochondrial elongation. Since AMPAR activation increases ERK1/2 phosphorylation , therefoProtein phosphatase activities also contribute to mitochondrial dynamics via dephosphorylating DRP1-S616 or -S637 site . DRP1-S6In the present study, co-treatment of okadaic acid, but not CsA, abrogated U0126-induced reduction in DRP1-S616 phosphorylation, although co-treatment of U0126 did not influence the effects of okadaic acid and CsA on PP phosphorylations. Furthermore, co-treatments of okadaic acid and CsA significantly alleviated the reductions in PP1/PP2A and PP2B phosphorylations induced by perampanel, respectively. Co-treatment of okadaic acid and CsA with perampanel also attenuated the reductions in DRP1-S616 and -S637 phosphorylations without changing DRP1 expression level, respectively. However, co-treatments of okadaic acid and CsA did not affect perampanel-mediated reductions in ERK1/2 and JNK phosphorylations. These findings indicate that both ERK1/2 and PP1/PP2A may coordinately regulate DRP1-S616 phosphorylation, and that each inhibitor may not show off-target effects in the present study. Thus, our findings suggest that blockade of AMPAR may regulate the cooperation of ERK1/2- and PP1/PP2A for the modulation of DRP1 phosphorylations.It is well-known that the phosphorylations of GluR1 subunit of AMPAR at S831 and S845 sites increase the conductance of AMPAR and potentiate rapid excitatory neurotransmission . InteresThe molecular machinery of mitochondrial dynamics is also regulated by MFN1/2 and OPA1, which elongate mitochondrial length . RecentlOn the other hand, the effects of AMPAR antagonist on GluR1 expression have been controversial. NBQX, a competitive AMPAR antagonist, increases GluR1 expression  or not . SimilarTo the best of our knowledge, the present data demonstrate the previously unreported AMPAR-mediated underlying mechanism for mitochondrial dynamics under physiological condition. Furthermore, our findings suggest that the regulation of AMPAR functionality may be one of the therapeutic targets for neurological diseases related to aberrant mitochondrial dynamics.Animal protocols were approved by the Institutional Animal Care and Use Committee of Hallym University .T-CK designed and supervised the project. J-EK, H-CC, H-KS, and T-CK performed the experiments described in the manuscript and analyzed the data. J-EK and T-CK 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.


Larix decidua (European larch) and Picea abies (Norway spruce) below, at, and above the current treeline into intact vegetation and into open microsites with artificially removed surface vegetation, as well as into plots protected from seed predators and herbivores. Seedling emergence and early establishment in treatment and in control plots were monitored over two years. Tree seedling emergence occurred at and several hundred metres above the current treeline when viable seeds and suitable microsites for germination were available. However, dense vegetation cover at lower elevations and winter mortality at higher elevations particularly limited early recruitment. Post-dispersal predation, species, and provenance also affected emergence and early establishment. This study demonstrates the importance of understanding multiple abiotic and biotic drivers of early seedling recruitment that should be incorporated into predictions of treeline dynamics under climate change.Treeline responses to climate change ultimately depend on successful seedling recruitment, which requires dispersal of viable seeds and establishment of individual propagules in novel environments. In this study, we evaluated the effects of several abiotic and biotic drivers of early tree seedling recruitment across an alpine treeline ecotone. In two consecutive years, we sowed seeds of low- and high-elevation provenances of  There is increasing evidence for climate-induced latitudinal range shifts via increased shrub abundance in circumarctic tundra ecosystems6 and elevational shifts of shrubs and trees in mountainous regions11. Treeline position, i.e. the range limit of forest ecosystems, is widely considered temperature sensitive and is thus expected to respond to climate warming15. However, global treeline dynamics are often modulated by regional-scale drivers such as historical land use changes16 and biotic interactions17. Hence, treeline responses to global warming vary among locations and are often asynchronous with the rate of climate change21.Plant species are responding to recent global temperature increases22. In treeline ecotones, viable seed availability commonly declines with elevation23 due to lower abundance of seed bearing trees and less frequent mast years, i.e. synchronous production of large seed crops26. Biotic interactions, such as pre-dispersal predation, may further constrain seed productivity at treeline27, impacting future treeline range expansion. Successful recruitment also depends on the availability of suitable microsites that provide the necessary conditions for emergence and establishment of seedlings29. Seed bed quality is determined by a complex interplay of abiotic and biotic factors such as microclimatic conditions, the presence of neighbouring vegetation, and herbivory30. Abiotic factors are considered key drivers of seedling recruitment in climatically harsh environments23. Early establishment is particularly limited by temperature and water availability33, but other abiotic factors, such as snow cover duration and desiccating winds, may also affect seedling recruitment36.Climate change-induced range expansion of treeline populations also depends on successful recruitment, which requires dispersal of viable seeds followed by successful establishment of individual propagules37. Microsite cover effects can be highly complex, with neighbouring vegetation positively or negatively affecting tree seedlings depending on vegetation type, species, demographic state, and prevailing weather conditions38. On the one hand, neighbouring vegetation can facilitate recruitment by sheltering seedlings from adverse climate effects, seed predators, and herbivores40. On the other hand, a dense vegetation cover can impede seedling emergence and establishment by competing for light, water and nutrients, exerting allelopathic effects, and preventing seeds from reaching a suitable seed bed45. The stress-gradient hypothesis predicts that these biotic interactions vary with abiotic conditions46. Therefore, it is expected that competition dominates at lower elevations with relatively low levels of environmental stress, whereas facilitative interactions prevail in more stressful environments at higher elevations40. Furthermore, seed predation and herbivory are other important biotic constraints on seedling recruitment at tree species’ upper range limits50. Dense vegetation may additionally promote post-dispersal predation by creating preferred microhabitats and foraging areas for seed predators and herbivores52. Thus, a large number of abiotic and biotic factors shape microsite conditions indicating the need for a better understanding of the interplay among these different drivers of seedling recruitment.Biotic interactions can be equally or even more important than abiotic factors in determining seed bed conditions13. In particular, tree species are adapted to different ranges of germination temperatures31. Recruitment at treeline is thus likely to vary among species. Furthermore, provenance tests have revealed high genetic diversity and site-specific adaptations in conifer species55. Physiological and growth adaptations of high-elevation provenances to cold climate conditions are known to exist for later-stage seedlings and adult trees56. Provenance may also be important in early life stages of seedlings but has rarely been evaluated (but see57).Seedling recruitment depends not only on environmental but also on genetic factors acting on seed availability, germination, growth, and survival. Individual tree species are adapted to different elevation ranges, reflecting different temperature sensitivities59, interactions among several abiotic and biotic factors have rarely been addressed60. In the European Alps, there exists, to the best of our knowledge, no experimental study testing the relative importance of multiple abiotic and biotic factors on early tree seedling recruitment along an elevation gradient across the treeline ecotone. Here, we investigated seedling emergence and early establishment of two conifer species, Larix decidua MILL. (European larch) and Picea abies (L.) KARST. (Norway spruce), below, at, and above treeline in the Swiss Alps. In two consecutive years, we sowed seeds of low- and high-elevation provenances of the two species into plots with intact vegetation and into plots where surface vegetation was removed to create open microsites to test the influence of seed availability, microsite cover, and provenance on early seedling recruitment. Moreover, herbivore exclosures allowed us to test the influence of seed predators and herbivores. We tested hypotheses addressing biotic and abiotic drivers of early seedling recruitment, specifically, predicting that: (i) emergence would be limited by both seed availability and harsh environmental conditions at high elevation, and thus would decline with increasing elevation and distance from the current treeline; (ii) recruitment would be greater at open microsites than in closed, intact vegetation at lower elevations, but the opposite effect would occur at high elevations where neighbouring vegetation shelters seedlings from adverse environmental conditions; (iii) there would be a negative effect of seed predation and herbivory on seedling recruitment, but this effect would be less pronounced at open microsites; and (iv) at and above treeline, recruitment would be greater for L. decidua than for P. abies and for high-elevation provenances of both species.Major bottlenecks to tree seedling recruitment clearly occur in early life stages, yet analysing abiotic and biotic key players in this process remains a scientific challenge. While the influence of individual abiotic or biotic factors on seedling recruitment in treeline ecotones has been tested experimentally in several studiesL. decidua seedlings and 7 P. abies seedlings were observed. Emergence in seeded plots was greater than in unseeded control plots . Germination of experimentally sown seeds was highest at the uppermost site , where 981 seedlings emerged . Total emergence was similar in both years of seeding, 4.2 ± 0.6% in 2013 and 5.1 ± 0.6% in 2014 (Pyear = 0.703). In 2013, emergence was more than three times as high at the treeline than at the alpine site (9.5 ± 1.4% vs. 3.0 ± 0.5%), whereas in 2014, emergence at the alpine site was more than six times as high than at the treeline site  and almost three times as high for low-elevation provenances than for high-elevation provenances . Emergence of L. decidua seedlings from low-elevation provenance (10.6 ± 1.3%) was three to five times as high than emergence of high-elevation provenance seedlings (2.1 ± 0.4%) and from both P. abies provenances  and the increase was more pronounced for low- than for high-elevation provenance seedlings (Pprovenance × exclosure = 0.005).Naturally emerged seedlings were found only at the lowest study site (referred to as forest site) and only during the baseline census in June 2013, when 15 Psite < 0.001; Table Pscarified < 0.001; Fig. Psite × year < 0.001; Fig. L. decidua than P. abies seedlings survived the first winter at the alpine site, whereas there was no difference in survival at treeline . First winter survival was higher for seedlings from low- than from high-elevation provenances seeded in 2014, whereas there were no provenance differences for seedlings seeded in 2013 (Pyear × provenance = 0.040). Slightly more seedlings from 2013 outside of herbivore exclosures than inside exclosures survived the first winter, whereas there was no difference for seedlings from 2014 (Pyear × exclosure = 0.030). However, herbivore exclosure alone did not influence first winter survival  than at the treeline site , whereas provenance did not influence survival .Similar to first winter survival, fewer seedlings survived the second winter at the alpine site 25.9 ± 10.3%) than at the treeline site  at the Stillberg climate station was 1.2 °C above average, but in 2014 it was 0.8 °C below the 30-year average (1981–2010) of 9.5 °C  logged at each site were consistently lowest at the forest site and highest at the alpine site  suggested that seeds were naturally available and able to emerge, as has been previously shown for other nearby subalpine forest standsL. decidua and P. abies seeds successfully germinated at the alpine site than at the treeline and forest sites , our results indicate predominantly negative effects on early seedling recruitment at the treeline site. This site is characterised by a dense dwarf shrub layer, a vegetation type that has been shown to impair tree seedling recruitment by competing for water, nutrients, and light67. Although we did not measure resource levels, and thus cannot determine the underlying mechanisms, seedlings in control plots tended to grow taller  and to predictions of the stress-gradient hypothesis40, may be due to the structure of the particular alpine plant community, the specific susceptibilities of the studied seedling species38, or the specific location of the study sites on a northeast-facing mountain slope, where heat stress and desiccation may be less important factors78.While removal of vegetation cover enhanced early seedling recruitment at treeline, there was no difference in emergence between scarified and vegetation-covered plots at the alpine site Table ; Fig. 1a29. Indeed, the reduced emergence at the alpine site in the warm and dry summer 2013 compared to in 2014  with tall and large-leafed herbaceous understorey vegetation . The mid-elevation site (treeline site) is located at 2,090 m a.s.l., at the current treeline, and is dominated by dense dwarf shrub vegetation  interspersed with low-tree islands of Pinus cembra and Pinus mugo. The soil was covered by a 10–15 cm thick moss layer at this site. The uppermost site  is located at 2,410 m a.s.l., approximately 300 m above treeline, in an alpine meadow with a vegetation height of approx. 5–15 cm (Caricetum curvulae).In summer 2013, three experimental sites were established along an elevational gradient across an alpine treeline ecotone located on a northeast-exposed slope in the Dischma valley, Davos, Switzerland Table . The low94. In a split-plot design, 20 whole plots (224 cm × 45 cm) were established at each site. They were completely randomly assigned to the 2 × 2 treatment combinations of the main factors seeding and scarification , resulting in five replications per main treatment combination. Distances between whole plots were at least 0.5 m, but usually between 1 m and 10 m. Each whole plot was divided into 16 split-plots , to which treatment combinations of the four additional two-level factors species, provenance, herbivore exclosure, and seeding year were randomly assigned. Overall, this resulted in 960 split-plots (3 sites × 20 main plots per site × 16 split-plots per main plot). Plot setup and seeding treatment applications were staggered in time at the three sites  to reflect the natural difference in growing season start at the three elevations. At the beginning of the experiment in summer 2013, natural recruitment and vegetation cover were assessed in each subplot. Thereafter, we applied the scarification treatment by removing vegetation, plant litter, mosses, and lichens from the plot surfaces with a hand-cultivator, but leaving roots and non-organic material in the soil. With this treatment we simulated soil disturbance and created open microsites, which is an established method to study biotic interactions with neighbouring vegetation95. While vegetation cover regrew within several weeks at the forest site, we did not observe significant regrowth of vegetation cover over the experiment duration in scarified plots at treeline and at the alpine site although the plots were scarified only once. Immediately after scarification, 200 seeds were spread evenly on each of the respective subplots. A second seeding treatment was applied to a different set of subplots at the beginning of the following growing season in spring 2014. In both years, immediately after seeding, herbivore exclosures made of durable and stable metal cages  were installed on half of the subplots for the duration of the growing season. Each cage covered two adjacent subplots. We expected that the cages would exclude small mammals and birds, whereas burrowing animals, such as voles, and invertebrates were not prevented from entering the plots . Fences were installed at each site to protect experimental plots from grazing and trampling by cattle and horses.The three experimental sites were set up following the standard protocol of the global G-TREE initiativeSeedling recruitment was assessed by counting the seedlings in each subplot at the beginning and end of the growing seasons in 2013, 2014, and 2015. All seedlings were individually marked to avoid double counts. Emergence was defined as the percentage of germinated seeds at the end of the first growing season (i.e. three to four months after sowing). First and second winter survival were defined as the percentage of surviving seedlings between the fall census and the spring census of the following year. Seedling height was measured with a hand ruler as the total length from the original emerging point to the apical meristem of approximately 15-month-old seedlings at the end of the growing seasons 2014 and 2015. In subplots with more than ten seedlings, only ten haphazardly chosen seedlings were measured. Seedling growth was defined as the average seedling height per subplot after two growing seasons. Maximum seedling height per subplot was also tested and showed similar results because of small height variation among seedlings (data not shown).96 approx. 50 m from the treeline site. At each site, two to five temperature loggers  recorded soil temperatures at a depth of 5 cm in vegetation-covered plots, as well as in plots where surface vegetation was removed. The beginning and end of the growing season were defined as the dates when soil temperature rose for the first time above (beginning) or fell below (end) 3.2 °C for two contiguous days97. Additionally, the dates of the first snow cover in autumn and snowmelt in spring were derived from soil temperature measurements and defined as the dates when daily temperature fluctuations stopped and soil temperature remained at 0 °C (snow cover), and when daily temperature fluctuations restarted (snowmelt).Daily values of mean air temperature, precipitation, and snow depth were measured at the Stillberg climate station at 2,090 m a.s.l. located at the Stillberg Long-Term Ecosystem Research sitet-test was applied to compare emergence in seeded versus non-seeded plots. Linear and generalised linear mixed-effect models (LMMs and GLMMs)98 were used to analyse the response of seedling recruitment  to the investigated abiotic and biotic factors and their interactions. Due to the almost complete lack of natural germination, non-seeded plots were omitted from these analyses. The forest site was excluded from survival and growth trait models because of very low seedling recruitment. GLMMs for seedling emergence and first winter survival contained site, scarification treatment, seeding year, species, provenance, and herbivore exclosure treatment as fixed effects. Because of the small data set for second winter survival, it was not possible to test the influence of seeding year and herbivore exclosure treatment, as well as their interactions. All three GLMMs used binomial distributions. Seedling height was modelled using a LMM with the fixed effects site and scarification treatment and their interaction. All models accounted for spatial correlation among plots and subplots by including plot and two subplot-structures as random effects. Significance of model factors was determined by likelihood ratio tests, and fixed effects that did not significantly improve the model fit were eliminated. All models were fitted using standard procedures for model diagnostics99 with the lme4-library (version 1.1–13)100 in R 3.3.3101.A two-sided 96 and 10.16904/envidat.42102. All other data generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.Climate data are archived in the EnviDat Digital Repository: 10.16904/envidat.43Supplementary Information


The dichloromethane extract of propolis showed potent inhibition of human MAO-A and MAO-B. Further fractionation identified the most active fractions as rich in flavonoids. Galangin and apigenin were identified as the principal MAO-inhibitory constituents. Inhibition of MAO-A by galangin was about 36 times more selective than MAO-B, while apigenin selectivity for MAO-A vs. MAO-B was about 1.7 fold. Apigenin inhibited MAO-B significantly more potently than galangin. Galangin and apigenin were further evaluated for kinetic characteristics and the mechanism for the enzymes’ inhibition. Binding of galangin and apigenin with MAO-A and -B was not time-dependent and was reversible, as suggested by enzyme-inhibitor binding and dissociation-dialysis assay. The inhibition kinetics studies suggested that galangin and apigenin inhibited MAO-A and -B by a competitive mechanism. Presence of prominent MAO inhibitory constituents in propolis products suggests their potential for eliciting pharmacological effects that might be useful in depression or other neurological disorders. The results may also have important implications in drug-dietary supplement interactions.Propolis is the resinous material that bees gather from leaf buds, flowers and vegetables. Propolis extracts contain constituents with a broad spectra of pharmacological properties and are important ingredients of popular dietary supplements. Propolis extracts were evaluated  The studies were further extended to identify the principal MAO inhibitory constituents in the propolis extracts.Propolis is the resinous material that bees gather from leaf buds, flowers and certain vegetables . The beel-deprenyl selectively inhibit MAO-A and B, respectively. Due to their central role in neurotransmitters metabolism, these enzymes represent attractive drug targets in the pharmacological therapy of neurodegenerative diseases and depression − .For HRESIMS, the mass detector was a time of flight (Model G1969A) equipped with an electrospray ionization interface and was controlled by Agilent software . The negative mode acquisition was performed with a capillary voltage of 3000 V, and nitrogen was used as nebulizer gas (30 psig) as well as drying gas at 10 L/min at drying gas temperature of 300 °C. The voltage of PMT, fragmentor and skimmer was set at 750 V, 125 V and 60 V respectively. Full scan mass spectra were acquired from 50 value at the point where 50% inhibition of the catalytic activity of the enzyme occurred. For MAO-A, the substrate concentration of 80 μM kynuramine was chosen because the apparent KM value for substrate binding reported previously was approximately 40 μM  were used to determine the Km and Vmax values in presence of the inhibitor. Controls without inhibitor were also run simultaneously. The results are presented as double reciprocal Lineweaver-Burk plots and the kinetic data namely Km, Vmax and Ki values were computed by SigmaPlot 12.3 using Enzyme-Kinetics module employing Michaelis-Menten equation. The results were also analyzed with SigmaPlot 12.3 using Enzyme-Kinetics module to determine the type of inhibition.For determination of the enzyme inhibition constants (Ki) for inhibition of MAO-A and MAO-B with apigenin and galangin the enzyme assays were carried out at different concentration of kynuramine substrate (1.90 μM to 500 μM) and at least two fixed concentrations  with the inhibitor at the concentration, which produces approximately >60% inhibition. The inhibitor concentrations used to test time-dependent inhibition were galangin (0.25 μM), apigenin (1.2 μM) and clorgyline (7.5 nM) with MAO-A (20 μg/mL) and; galangin (14.0 μM), apigenin (4.0 μM) and deprenyl (50 nM) with MAO-B (50 μg/mL). The controls without inhibitors were also run simultaneously. Activities of the enzymes were determined as described above and percentage of enzyme activity remaining was plotted against the preincubation time to determine time-dependent enzyme-inhibition.Most of the inhibitors produce inhibition of the target enzyme through formation of an enzyme-inhibitor complex. Formation of the enzyme-inhibitor complex may be accelerated in presence of high concentration of the inhibitor. The reversibility of binding of MAO inhibitory galangin and apigenin were determined by formation of the complex by incubating the enzyme with high concentration of the inhibitor followed by extensive dialysis of the enzyme-inhibitor complex and recovery of catalytic activity of the enzymes. MAO-A (0.05 mg/mL protein) enzyme was incubated with the test compounds; galangin (10.0 μM) and apigenin (20.0 μM) and MAO-B (0.05 mg/mL protein) enzyme was incubated with compound; galangin (50.0 μM) and apigenin (25.0 μM) in a total reaction mixture volume of 1 mL, containing 100 mM potassium phosphate buffer (pH 7.4). After 20 min incubation at 37 °C, the reaction was stopped by chilling the tubes on the ice bath. All the samples were dialyzed against potassium phosphate buffer  at 4 °C for 14 h (three buffer changes). Control enzyme (without inhibitor) was also run through the same procedure and activity of the enzyme was determined before and after the dialysis. Recovery of the catalytic activity enzyme after extensive dialysis of the enzyme-inhibitor mix provided the information about reversibility/irreversibility of binding of the inhibitor with the enzyme.Propolis, a natural wax-like resinous substance present in bee hives, has been extensively used in dietary supplements and also as folk medicine for treatment of several diseases, including neurological disorders. We have identified apigenin and galangin as prominent MAO-inhibitory constituents in propolis extracts. The presence of prominent monoamine oxidase inhibitory constituents in these products suggests their potential for eliciting pharmacological effects that might be useful in depression or other neurological disorders.


Hyperphosphorylation of the microtubule-associated protein tau and its resultant aggregation into neurofibrillary tangles (NFT) is a pathological characteristic of neurodegenerative disorders known as tauopathies. Tau is a neuronal protein involved in the stabilization of microtubule structures of the axon and the aberrant phosphorylation of tau is associated with several neurotoxic effects. The discovery of tau pathology and aggregates in the cortex of Temporal lobe epilepsy (TLE) patients has focused interest on hyperphosphorylation of tau as a potential mechanism contributing to increased states of hyperexcitability and cognitive decline. Previous studies using animal models of status epilepticus and tissue from patients with TLE have shown increased tau phosphorylation in the brain following acute seizures and during epilepsy, with tau phosphorylation correlating with cognitive deficits in patients. Suggesting a functional role of tau during epilepsy, studies in tau-deficient and tau-overexpressing mice have demonstrated a causal role of tau during seizure generation. Previous studies, analyzing the impact of seizures on tau hyperphosphorylation, have mainly used animal models of acute seizures. These models, however, do not replicate all aspects of chronic epilepsy. In this study, we investigated the effects of acute seizures (status epilepticus) and chronic epilepsy upon the expression and phosphorylation of tau using the intra-amygdala kainic acid (KA)-induced status epilepticus mouse model. Status epilepticus resulted in an immediate increase in total tau levels in the hippocampus, in particular, the dentate gyrus, and phosphorylation of the AT8 epitope , with phosphorylated tau mainly localizing to the mossy fibers of the dentate gyrus. During epilepsy, abnormal phosphorylation of tau was detected again at the AT8 epitope with lower total tau levels in the CA3 and CA1 subfields of the hippocampus. Chronic epilepsy in mice also resulted in a strong localization of AT8 phospho-tau to microglia, indicating a distinct pattern of tau hyperphosphorylation during chronic epilepsy compared to status epilepticus. Our results reaffirm previous observations of tau phosphorylation post-status epilepticus, but also elaborate on tau alterations in epileptic mice which more faithfully mimic TLE. Our results confirm seizures affect tau hyperphosphorylation, however, suggest epitope-specific phosphorylation of tau and differences in cell-specific localization according to disease progression. Tauopathies are a diverse group of neurodegenerative disorders characterized by misfolded, aggregated and aberrant forms of the microtubule-associated protein tau , Cyclin-dependent kinase 5 (CDK5) and Microtubule-affinity-regulating kinase  which produces inconsistent pathology and hippocampal epileptogenesis  and protein kinase A  into the amygdala, as described . Procedures were reviewed and approved by the Research Ethics Committee of the Royal College of Surgeons in Ireland (REC 1322) and the Irish Health Products Regulatory Authority (AE19127/P038). All efforts were maximized to reduce the number of animals used in this study. Mice used in our experiments were 8- to 12-week-old male C57BL/6 mice, obtained from the Biomedical Research Facility, Royal College of Surgeons in Ireland . Animals were housed in a controlled biomedical facility on a 12 h light/dark cycle at 22 ± 1°C and humidity of 40–60% with food and water provided To analyze the different hippocampal subfields separately, mouse brains were removed using sharp laboratory scissors and placed into a petri dish on top of a cold board. Following the separation of the cerebellum, the two brain hemispheres were separated. Then, using a dissecting microscope, the whole hippocampus was separated from the cortex. Following the identification of the boundaries between the dentate gyrus, cornus ammonis (CA)1 and CA3, the three hippocampal subfields were separated and immediately put on dry ice and stored at −80°C.The GSK-3 inhibitor NP031112  followed by a short incubation with DAPI. FluorSavet-test and one-way ANOVA with Fishers post hoc multiple comparisons analysis. Data are presented as mean ± standard error of the mean (SEM).Data were analyzed for statistical significance using StatView. Parametric analysis was carried out using Student’s in vivo, status epilepticus was induced in C57Bl/6 wild-type mice by an intra-amygdala injection of KA  on tau expression and phosphorylation in the hippocampus tau mRNA levels to be relatively unchanged compared to control at all time-points analyzed post-status epilepticus , p = 0.03; ANOVA post hoc Fisher’s test; p = 0.03; Ctrl vs. 8 h, 2.413 ± 0.2357 (mean ± SEM), p = 0.005; ANOVA post hoc Fisher’s test] with this increase tapering off at 24 h post-status epilepticus , p = 0.008; Ctrl vs. 8 h: 3.401 ± 0.4129 (mean ± SEM), p = 0.003; ANOVA post hoc Fisher’s test; p = 0.04; ANOVA with Fisher’s post hoc test; As a first approach, we analyzed whether status epilepticus has an effect on the expression of tau in the ipsilateral hippocampus. RT-qPCR revealed hippocampal lepticus . In contlepticus . IncreasThus, intra-amygdala KA-induced status epilepticus leads to an increase in total tau levels and in tau phosphorylation in the hippocampus.With AT8 showing the strongest increase in tau phosphorylation post-status epilepticus, we next sought to identify the localization of AT8 phospho-tau following status epilepticus using immunological staining of hippocampal tissue sections.DAB immunostaining for AT8 4 h post-status epilepticus revealed a loss of phosphorylated tau within the stratum pyramidal and lucidum region of CA3 and an apparent increase in the mossy fibers . Loss ofvia Western blotting. This revealed that total tau levels were increased at 8 h and 24 h in the dentate gyrus following status epilepticus , while CA1 showed no changes ,  changes .In summary, while tau phosphorylation remained elevated during epilepsy at the AT8 epitope, total tau expression was reduced in the CA3 and CA1 subfield of the hippocampus.via DAB staining, was not detected in the mossy fibers  following status epilepticus. We have previously shown status epilepticus-induced inhibition of the UPS mainly to occur in the dentate gyrus, while proteasome activity has been shown to be slightly increased in the CA3 subfield of the hippocampus post-status epilepticus  compared to serine 396/404 (PHF-1) with only AT8 phospho-tau increased in epileptic mice at 14 days. AT8 phosphorylation is the standard immunostaining utilized for the assessment of neurofibrillary tangle (NFT) formation and tau aggregation for Braak stage scoring and Alzheimer’s Disease progressions, with a very strong correlation with cognitive decline in preclinical Alzheimer’s Disease (Braak et al., in vitro and in vivo using transgenic models of tauopathy (Luo et al., In contrast to status epilepticus, during epilepsy tau expression was not increased in the dentate gyrus, but reduced in the hippocampal subfields CA3 and CA1. Again, it is tempting to speculate that this is likely a protective response to potentially toxic levels of phosphorylated tau in the cells occurring during seizures. Another novel observation during the study was the presence of phosphorylated tau in microglia during chronic epilepsy. Tau is not natively expressed in microglia and its presence is most likely due to active microglia internalizing extracellular tau as has been previously described The aberrant tau hyperphosphorylation occurring in epileptic mice presents a convergence of numerous mechanisms that could have significant implications with epilepsies as well as Alzheimer’s Disease. These findings point to experimental epilepsy models examined over a longer period of time to replicate the potential mechanisms of tau hyperphosphorylation and aggregation which have been observed in TLE patients. The intra-amygdala KA mouse model of status epilepticus represents, therefore, a valid model that could be utilized to further elucidate developing treatments against the propagation of hyperphosphorylated tau occurring in TLE patients.All datasets generated for this study are included in the article/The animal study was reviewed and approved by Research Ethics Committee of the Royal College of Surgeons in Ireland.MA carried out Western blotting, PCRs, immunostainings and analyzed the data. AK analyzed the data and wrote parts of the manuscript. GL performed immunostainings. EB carried out experiments with GSK-3 inhibitors. TE 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.


Isotopic signatures (−60.2‰ to −7.6‰ for δ13Cch4 and −324.3‰ to +161.1‰ for Dch4), support a biogenic signature within waters emerging from the subglacial environment. Temperate glacial methane production and release may thus be a significant and hitherto unresolved contributor of a potent greenhouse gas to the atmosphere.The base of glaciers and ice sheets provide environments suitable for the production of methane. High pressure conditions beneath the impermeable ‘cap’ of overlying ice promote entrapment of methane reserves that can be released to the atmosphere during ice thinning and meltwater evacuation. However, contemporary glaciers and ice sheets are rarely accounted for as methane contributors through field measurements. Here, we present direct field-based evidence of methane production and release from beneath the Icelandic glacier Sólheimajökull, where geothermal activity creates sub-oxic conditions suited to methane production and preservation along the meltwater flow path. Methane production at the glacier bed (48 tonnes per day, or 39 mM CH The source of carbon essential for fuelling microbiologically-mediated reactions can be generated either in-situ at the bed of the glacier through chemolithoautotrophic production4, through utilising organic containing fossil soils7, or sourced from the surface environment8. Geogenic subglacial methane comprises abiogenic sources from subglacial volcanism, geothermal activity, and thermogenic sources through the thermal degradation of organic matter and subsequent migration of methane from hydrocarbon reserves to a stable sub-ice storage location e.g.9. Methane present at the bed of glaciers and ice sheets can then be retained in situ by high overburden pressures and low temperatures, which promote the entrapment of gases, or the storage of methane in hydrate reserves. Vast methane reservoirs potentially containing hundreds of petagrams of carbon could therefore accumulate and, if released as the ice melts, contribute positive feedback to rising atmospheric greenhouse gas concentration and global temperature3.The subglacial environment provides conditions suitable for the production and storage of methane. The presence of liquid water beneath temperate and polythermal ice masses, sub-oxic conditions due to poor hydrological connectivity, and carbon within basal sediments allow the survival of microbiological communities with the potential to produce biogenic methane eg.10 and favourable pressure–temperature relationships3 for methane production and storage in the subglacial realm, methane in glacial meltwaters has only been directly detected as aqueous methane in one study 11, or else inferred indirectly using δ13C of dissolved organic carbon12. For methane to be detected in meltwater outflow, sub-oxic conditions must occur not only at the glacier bed, but also throughout the subglacial drainage path. These conditions typically arise at the onset of subglacial discharge, during winter baseflow or as brief reversals in redox status of subglacial waters18. The inherently transient nature of these conditions thereby provides limited opportunity for direct field-based characterisation of methane production. Here, we examine an Icelandic glacier, Sólheimajökull, an outlet glacier of the Mýrdalsjökull icecap  and laboratory incubation of associated subglacial sediments demonstrate a strong potential for methanogenesis  this equates to a subglacial production capacity of 39 mM CH4 m−2 day−1. Using an upstream – downstream mass balance along the 4 km length (20 m width) of proglacial meltwater channel . This mass balance approach to calculating an evasive methane flux along the stream assumes minimal dilution, and no in-stream methanotrophy. Both are valid assumptions given the minimal input of additional meltwater between upstream and downstream sampling points, the minimal production/consumption of methane in the proglacial sediments . Evasion to the atmosphere was calculated as 54% along the 4 km stream reach, equating to 0.25 M CH4 m−2 day−1. Methane evasion from the Sólheimajökull sub-aerial stream network greatly exceeds mean flux values between river to atmosphere reported in the literature (4.23+\−8.41 mM CH4 m−2 day−1)22 indicating the potential significance of the subglacial methane source, if similar processes are also occurring at other glaciers.The appearance of elevated aqueous methane concentrations that are commensurate with the location and onset of subglacial drainage, suggests the environment of methane production must be beneath the glacier. Fluctuating discharge and changing subglacial methane concentrations on a seasonal basis preclude straightforward calculation of an annual methane flux from beneath the glacier. However, a typical summer season discharge of 50 mts Table , and the13Cch4 and Dch4. Isotopic fractionation during biogenic methanogenesis typically leads to δ13C values between −50 to −110‰, and δD values between −170 to −531‰23. Geogenic methane produced at high geothermal temperatures undergoes exchange with the surrounding water and mantle carbon, producing deuterium and carbon contents enriched in 2H and 13C respectively24. Signatures of mixed geogenic/microbial origin should therefore lie on an end member mixing trajectory as depicted in Fig. 13C and deuterium. As the most enriched values exceed the geogenic range, the observed isotopic signatures cannot be explained by a mixture of biogenic and geogenic methane ) and composition of residual methane (CH4(t)) is quantified following25 as α = 1.019 for 13C/12C, and for fractionation of D/H as α = 1.197. These incubation determined values of C and H enrichment during methanotrophy are encompassed within the published range of experimental values23, and result in relative changes to isotopic signatures during reaction progress that lie on a similar gradient to field data from this study . Under these conditions of distributed drainage (the ‘closed’ system), connectivity to the atmosphere is poor and dissolved gases can be depleted to produce meltwaters of low redox status. During the summer season, a discrete well-connected subglacial drainage system, characterised by well-defined conduits, expands up-glacier dependent upon the flux of surface run-off to the glacier bed, and typically follows the supraglacial snowline. Within this ‘open’ configuration, oxygen saturated meltwaters can drain rapidly from the surface of the glacier and through the subglacial system28. At polar glaciers of a polythermal nature, the drainage system displays similar characteristics, albeit with the winter slow flow component of the drainage system remaining sealed beneath the glacier until basal water pressures force a pressurised outflow, either shortly after the onset of the summer season29, or intermittently throughout the winter to produce characteristic proglacial icings e.g.30. However, at Sólheimajökull, the presence of the Katla geothermal area beneath the head of the glacier imparts profoundly different characteristics to meltwater discharge , together with methane produced during the summer season. During the winter season  of meltwater discharge. Greater headward expansion of drainage systems towards geothermal areas currently isolated beneath ice mass overburden would also ensure transport of meltwater and associated methane content to a position of sub-aerial degassing into the atmosphere. Pressure driven sub-oxia would likely become more prevalent with ice thinning until overwhelmed by the flux of oxygenated surface melt reaching the glacier bed or until ice disappearance. In this manner, this poorly quantified flux of sub-ice cap methane is likely an indirect, albeit self-reinforcing consequence of climatic change.The geothermally-influenced nature of the Sólheimajökull system is unusual in its ability to present a low redox status window which inhibits methane oxidation and preserves aqueous methane until the point of release from beneath the glacier. The dominance of biogenic methane production beneath an Icelandic temperate ice mass nonetheless raises the distinct possibility that methane generation could be proceeding undetected in other subglacial environments where the cocktail of temperate ice, low oxygen concentration, organic carbon and methanogenic communities coincide to promote methanogenesis. Increasing evidence for zones of strong geothermal activity beneath the West Antarctic Ice Sheet suggests that subglacial microbial communities with methanogenic potential may be more significant and extensive than previously anticipatedField samples were collected over restricted periods within the melt seasons of 2013 to 2017. Precise collection intervals are depicted in Table Samples for the determination of aqueous methane concentration were collected as a known volume of unfiltered water and stored within an airtight chamber with headspace at atmospheric pressure. Samples were left for 24 hours to undergo headspace equilibration and gases were then extracted through a sampling port and injected into evacuated exetainers  for later analysis of methane concentration and isotopic determination. Exetainers were over-pressurised to prevent ingress of atmospheric air and stored at ambient temperature to prevent vessel contraction and leakage. Headspace gas extraction at time t = 0 was used to determine background concentration prior to sample equilibration.4 m−2 day−1 following36.Proglacial sediments were monitored for the production and consumption of methane (methanogenesis and methanotrophy respectively) using static chambers (15 cm diameter × 10 cm height). Chambers were inserted into the sediments in triplicate at each site, and covered in aluminium foil to minimise temperature changes during the sampling period. Headspace gases were removed at set time intervals over a 45 minute incubation period to monitor the rate of methane production/consumption. Headspace gases were injected into evacuated exetainers which were over-pressurised to prevent the ingress of atmospheric air and stored at ambient temperature prior to further analysis for methane concentration. Flux values were calculated as µM CH37 were deemed the closest analogue to typical subglacial sedimentary deposits from the Sólheimajökull catchment. Sediments were incubated to determine the potential for methane production (methanogenesis) and consumption (methanotrophy) using standard procedures38. For each incubation type 10 grams of fresh weight sediment was added to a 100 ml sterilised Wheaton bottle and slurried with 20 ml deionised water. For anaerobic methane production incubations, the headspace was flushed with nitrogen gas to eliminate oxygen. For aerobic incubations the headspace was flushed with synthetic air, following which the methane concentration was adjusted to 150 ppm methane to assay for methanotrophy. Each set of incubations operated alongside control chambers supporting identical headspace conditions, but without the inclusion of sediment. All incubations were undertaken at a set temperature of 15 °C, reflecting optimal conditions for methane production and consumption, as established through preliminary testing. For methane production and oxidation potentials, triplicate samples were incubated for 49 and 7 days, respectively with regular sampling intervals during the periods of incubation . Fractionation between starting methane isotopic composition (CH4(i)) and composition of residual methane (CH4(t)) in the closed headspace is calculated following25:f is the fraction of methane remaining and δX is the isotopic composition of methane.Sediments extruded onto the glacier surface via thrust planes or melt out of fracture fill deposits c.f.4)  were analysed in every analytical sequence to encompass the expected sample concentrations. Standards were repeated at regular intervals39 to check for drift and ensure accuracy to within 95% of the true value. Sample triplicates had a precision (1S.D) representing <0.2% of the average value. The concentration of methane in water (Caq) is related to the concentration of gas measured in the headspace (Cg) via the dimensionless Henry’s Law solubility Constant (HCC) at a temperature of 273 K (0 °C)40.Methane concentrations were analysed using a PerkinElmer Autosystem XL Gas Chromatograph (GC)  fitted with a Flame Ionisation Detector (FID) operating at 300 °C. The GC was fitted with a stainless steel Porapak Q 50–80 mesh column  maintained at 60 °C. Three calibration gas standards  at the NERC Life Sciences Mass Spectrometer Facility, CEH Lancaster, UK. Manual injection volumes were dependent upon methane concentration and did not exceed 10 ml. Samples were initially passed through a Magnesium perchlorate/Carbosorb scrubber trap at 20 ml/min to eliminate water and CO2. Methane is oxidised in a combustion furnace using a braided platinum/copper/nichrome furnace wire inside a ceramic furnace tube of 200 mm × 0.4 mm i.d. heated in a furnace at 960 °C41. A preparation flow rate of 10 psi was required to give a flow rate of 20 ml/min through the furnace at full operating temperature. For δDch4, gas samples were purged from vials using a dual core needle and Helium carrier gas into a ThermoScientific precon concentration unit interfaced to a ThermoScientific Delta V plus isotope ratio mass spectrometer at UC Davies, University of California, USA. Cryogenic trapping and GC separation followed by pyrolysis at 1450 °C yielded H2 for determination of D/H ratios of methane gas42. δ13C values were corrected to VPDB using working CH4 standards cross calibrated with a CO2 reference gas, calibrated to NIST REF-Heavy Palaeomarine Origin (CO2) (RM 8562) and NIST REF-Biogenic Modern Biomass Origin (CO2) (RM 8564). The reproducibility of δ13Cch4 was better than ±0.2‰. δD was corrected to VSMOW using reference gasses calibrated to international standards NIST 8559, 8560, and 8561. Within-run standard replication of both samples and standards (1SD) was better than 2.6‰ for Hydrogen.Supplementary information