While dif/Xer systems have been characterized or predicted in the vast majority of proteobacteria, no homologs to dif or xer have been identified in the order Legionellales. Here, we report the discovery of a distinct single-recombinase dif/Xer system in the intracellular pathogen Legionella pneumophila. The dif site was uncovered by our analysis of Legionella mobile element-1 (LME-1), which harbors a dif site mimic and integrates into the L. pneumophila genome via site-specific recombination. We demonstrate that lpg1867 (here named xerL) encodes a tyrosine recombinase that is necessary and sufficient for catalyzing recombination at the dif site and that deletion of dif or xerL causes filamentation along with extracellular and intracellular growth defects. We show that the dif/XerL system is present throughout Legionellales and that Coxiella burnetii XerL and its cognate dif site can functionally substitute for the native system in L. pneumophila. Finally, we describe an unexpected link between C. burnetiidif/Xer and the maintenance of its virulence plasmids.In bacteria, the mechanisms used to repair DNA lesions during genome replication include homologous recombination between sister chromosomes. This can lead to the formation of chromosome dimers if an odd number of crossover events occurs. The dimers must be resolved before cell separation to ensure genomic stability and cell viability. Dimer resolution is achieved by the broadly conserved  IMEXachinery , 28.xerC and xerD have been predicted to be present in the vast majority of proteobacterial species  (–att) in LME-1 that is identical to a sequence on the L. pneumophila genome  –33. We p10.1128/mbio.02171-22.2TABLE S1att site is close to the cumulative GC skew maximum in all sequenced L. pneumophila strains and Legionella species. The nucleotide positions of the att site and cumulative GC skew maximum (cGC skew max) are shown for each L. pneumophila strain and Legionella species with a completed genome sequence available in Genbank. The cGC skew maximum corresponds to the site of replication termination  intergenic location  silocation . However-bp arms . Further-bp arms .att site (here referred to as the Legionella dif site) and established dif sites suggest that it likely contains two binding sites for one or more tyrosine-type recombinases that catalyze site-specific recombination  is transformed into L. pneumophila strain Lp02. If site-specific recombination occurs between the att site on the plasmid and the chromosomal dif site, the entire plasmid will be integrated into the genome and confer gentamicin resistance (Gmr) to the cell. We compared the number of transformants resulting from the att-containing plasmid to one with a control 22-bp sequence derived from the L. pneumophila genome near the dif site. To evaluate the efficiency of recombination supported by the dif site, we also included a plasmid containing 2,200 bp of unrelated intergenic sequence from L. pneumophila, which can integrate into the genome via a single-crossover homologous recombination event. Considering that chromosomal dif site-specific recombination is known to be RecA independent . These data indicate that, similar to other dif sites, site-specific recombination at the L. pneumophiladif site is efficient and RecA independent.The similarities between the chromosomal LME-1 bination . To asseon assay . In thisependent , 16, 35,n strain . To conte strain . In bothLegionella dif site. No orthologs of XerC, XerD, XerS, or XerH have been identified in Legionella using sequence homology  show structural similarity to tyrosine-type recombinases (probability of >99%). Importantly, dif and xer deletion mutants in other species exhibit slight growth defects and filamentation but are viable  and a pan-deletion strain with all six deleted. In our intermolecular recombination assay, integration of the att-containing plasmid was similar to wild-type levels in the 5-deletion strain and nonexistent in the pan-deletion strain  cassette at the normal dif locus of the Lp02 pan-deletion strain, such that recombination between the two flanking dif sites would result in loss of kanamycin resistance. To quantify excision of the reporter, we determined the proportion of kanamycin-resistant cells in the population after transforming the cells with wild-type or mutant Lpg1867. Overexpression of wild-type Lpg1867 in this strain resulted in a high level of cassette excision, while overexpression of the catalytic mutant resulted in an excision level similar to background level  Consistent with reported findings for dif or xer deletions in other species , catalyzes recombination between two dif sites to resolve chromosome dimers in Legionella.Deletion of id media . Again, ckground , consistckground , mirrorickground  and B. Irophages , indicatL. pneumophila chromosome at what we now know to be the dif site  resulted in markedly reduced excision compared to the reporter flanked by two wild-type dif sites, while one or two substitutions resulted in an intermediate level of excision  reside not on the circular chromosome, but on a large ubiquitous plasmid that is critical for virulence  search using the 29-nucleotide (nt) conserved sequence containing the L. pneumophiladif site. We identified a short sequence of 30 nt on the virulence plasmid immediately adjacent to XerLCb . As we observed for difLp, the Coxiella burnetii chromosomal site is always located opposite the predicted origin of replication and close to the cumulative GC skew maximum  was almost identical to that of wild-type L. pneumophila , in concert with XerLCb, is also able to complement the small colony phenotype  are not strong candidates for drug targets due to their redundancy. In contrast, we show that disruption of one protein in this pathway (XerL) is sufficient to dramatically restrict the growth of the pathogen.The discovery of the ellaceae , which idif or Xer homologs in Legionella, the CDR system was instead unearthed through our investigation of LME-1 and its attachment site. In turn, the discovery of the Legionella dif site and XerL has allowed us to explore new LME-1 biology. Our findings are consistent with LME-1 belonging to the IMEX class of integrative mobile elements, which exploit the host CDR machinery for integration and in some cases excision  of Neisseria gonorrhoeae, generates a similarly modified dif site (difGGI) at one end of its integrated form, while the wild-type dif (difNg) remains intact at the other . Our future investigative priorities include determining the involvement of FtsK in L. pneumophila CDR and its contribution to the stability of LME-1. It is possible that even if Legionella CDR is FtsK dependent, LME-1 might circumvent FtsK for integration and excision, as is the case for several other IMEX elements  with no interruptions, whereas other dif sites show only partial dyad symmetry between the two arms, even for single-recombinase systems. Additionally, in L. pneumophila, dif and xerL are separated by >400 kb in the genome, whereas in the other bacterial single-recombinase systems , the dif site is always near the xer gene, indicating they may have been acquired as a single module -2-aminoethanesulfonic acid (ACES) buffered yeast extract supplemented with 100 μg/mL thymidine (AYET) and on charcoal AYET (CYET) agar plates.The a, Spain . All L. mazF-Kanr cassette flanked by ~1.5-kb chromosomal homology arms is introduced into the parental strain via natural transformation. The mazF-Kanr cassette provides both positive (Kanr) and negative  selection markers. Cells in which the mazF-Kanr cassette has been integrated via homologous recombination are selected by plating on medium containing kanamycin. The resulting colonies are screened on kanamycin- and IPTG-containing plates to identify cells that have mazF-Kanr incorporated . In the second stage, these integrant strains are transformed with linear DNA containing only the homology arms with the desired mutation. Homologous recombination leads to excision of the cassette, and cells in which the cassette was lost are selected on plates containing IPTG. Colonies are again screened on kanamycin- and IPTG-containing plates to identify those in which the cassette was removed . All mutations made in this study were verified by PCR screening and Sanger sequencing.Deletion and mutant strains were made using a scar-free suicide cassette method described recently  with somdif-Kanr-dif cassette  into the Lp02 Δlpg1867 strain or pan-deletion strain. Strains containing the cassette were selected on plates containing kanamycin, and the correct integration of the cassettes was verified by Sanger sequencing. Similarly, for the yeast-based excision assay, linear DNA containing the dif-KanMX-dif cassette (flanked by homology arms around the HO locus) was transformed into S. cerevisiae strain BY4741 using the high-efficiency polyethylene glycol (PEG)-LiAc method (The reporter strains used for the intramolecular recombination (reporter excision) assays were generated by introducing linear DNA containing the c method . Integraatt site sequence, a control 22-bp sequence, or 2,200 bp of intergenic Lp02 sequence into pJB4648 digested with XhoI and ApaI. The gentamicin-resistant plasmid pJB1806-GmR was generated by first amplifying the gentamicin resistance (Gmr) gene and promoter from pJB4648 and cloning it in place of the chloramphenicol resistance gene in plasmid pJB1806. Protein expression plasmids used for the recombination and colony size assays were made by cloning the lpg1867 gene (wild type or modified to encode the Y387F mutation) into the multiple-cloning site of pNT562 (lacIq gene and tac promoter in pJB1806-GmR with the tetR gene and tetracycline-responsive promoter from pLJR965 (The pJB4648-based plasmids used for the intermolecular recombination assays were constructed by cloning the 22-bp f pNT562 . The tet pLJR965  and then pLJR965 .Legionella genome (see C. burnetii genome (https://genskew.csb.univie.ac.at) with default settings. The whole-genome GC skew profiles and dif site locations for seven L. pneumophila isolates, seven Legionella species, and seven C. burnetii strains, selected to show a range of cGC skew maximum locations relative to the origin, were plotted using Circos (L. pneumophila isolates and Legionella species (with GenBank accession numbers in parentheses) are L. pneumophila Philadelphia_2 (CP015929.1), Philadelphia_1 (AE017354.1), E7_O (CP015954.1), Paris (CR628336.1), NY23 D-7705 (CP021261.1), NCTC11985 (LT906452.1), and L. pneumophila subsp. fraseri strain D-4058 (CP021277) and Legionella species L. israelensis L18-01051 (CP041668.1), L. micdadei (LN614830.1), L. spiritensis NCTC11990 (LT906457.1), L. sainthelensi NCTC12450 (LR134178.1), L. longbeachae NSW150 (FN650140.1), L. oakridgensis NCTC11531 (LR134286.1), and L. fallonii LLAP-10 (LN614827.1). The selected C. burnetii isolates are 3262 (CP013667.1), Heizburg (CP014561.1), Dugway FJ108-111 (CP000733.1), RSA 493 (AE016828.3), CbuG_Q212 (CP001019.1), Schperling (CP014563.1), and CbuK_Q154 (CP001020.1).The cumulative GC skew maximum value for each i genome  was deteg Circos . The GC att, dif, or control sequences as indicated. The strains were also transformed with the replicative plasmid pJB1806-GmR to control for strain-to-strain differences in general transformation efficiency. Plasmid concentrations were determined using a Quant-iT PicoGreen double-stranded DNA (dsDNA) kit (Invitrogen), and 200 ng of each plasmid was electroporated into 2 optical density units (ODU) of L. pneumophila cells as described previously (For the intermolecular recombination (plasmid integration) assays, each strain was transformed with a pJB4648-based plasmid containing the indicated eviously . After aLegionella, strains containing the kanamycin resistance cassette were transformed with tet-on-pJB1806-GmR containing wild-type Lpg1867, Lpg1867-Y387F, XerLCb, XerLCb-Y389F, or empty vector by electroporation as described above. Transformants were selected on CYET plates containing both gentamicin and kanamycin. The transformant colonies were then collected in AYE and spread onto nonselective plates and plates containing kanamycin to quantify the proportion of the population that had lost kanamycin resistance. For the intramolecular recombination (excision) assay in yeast, S. cerevisiae strain BY4741 containing the dif-KanMX-dif cassette was transformed with yeast vector pAG413GPD (For the intramolecular recombination (excision) assay in AG413GPD  expressidif, Lp02 Δlpg1867, and Lp02 Δlpg1867 ΔrecA strains were grown from a 2-day-old patch in AYET medium. Bacteria were collected at postexponential phase (OD at 600 nm [OD600] of 4.0 to 4.5). Approximately ~1 × 109 cells (1 ODU) from each strain were washed once with 1 mL of 1× phosphate-buffered saline (PBS) before a final resuspension in 500 μL of 1× PBS. The bacteria were stained with 15 μg/mL of DAPI  (Roche) for 30 min at room temperature and imaged using a 63× oil immersion lens on a Zeiss Axio Imager.M2 microscope. The frequency of filamentation was quantified using the MicrobeJ plugin for ImageJ . Colony diameter was determined using ColTapp automated image analysis software  and used to inoculate the U937 cells at a multiplicity of infection (MOI) of 0.05. After 2 h, cells were washed three times with medium to remove extracellular bacteria before incubating in fresh medium at 37°C with 5% CO2 for a further 2 days. At 2 h and 48 h postinfection, cells were lysed with 0.02% saponin and then plated on CYET to determine the number of bacterial CFU.Tetradecanoyl phorbol acetate (TPA)-differentiated U937 cells were seeded in a 24-well plate at 4 × 10L. pneumophila was used to uncover putative orthologs of XerL. XerL was queried against the NCBI Legionellales database (taxid 118969) using both blastp and tblastn with the default settings (Legionella species that were deposited in the NCBI Sequence Read Archive (SRA)  , 62. The10.1128/mbio.02171-22.4TABLE S3Table S3, XLSX file, 0.03 MB.Xer recombinases used in the phylogenetic analyses. The accession numbers and amino acid sequences for the Xer recombinase proteins used for phylogenetic analyses are shown. Download Copyright © 2022 Nicholson et al.2022Nicholson et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the An unrooted phylogeny of Xer proteins was generated using the amino acid sequences from representative XerL orthologs, in addition to reference Xer sequences . The amiEscherichia coli as the root.A rooted phylogeny of all putative XerL orthologs was generated as described above, using XerD from dif sites are listed in figures and All strains and plasmids are available upon request. Sequences and locations of


Highly Pathogenic Avian Influenza Viruses (HPAIVs) arise from low pathogenic precursors following spillover from wild waterfowl into poultry populations. The main virulence determinant of HPAIVs is the presence of a multi-basic cleavage site (MBCS) in the hemagglutinin (HA) glycoprotein. The MBCS allows for HA cleavage and, consequently, activation by ubiquitous proteases, which results in systemic dissemination in terrestrial poultry. Since 1959, 51 independent MBCS acquisition events have been documented, virtually all in HA from the H5 and H7 subtypes. In the present article, data from natural LPAIV to HPAIV conversions and experimental in vitro and in vivo studies were reviewed in order to compile recent advances in understanding HA cleavage efficiency, protease usage, and MBCS acquisition mechanisms. Finally, recent hypotheses that might explain the unique predisposition of the H5 and H7 HA sequences to obtain an MBCS in nature are discussed. Anseriformes  and Charadriiformes  [Avian influenza A viruses (AIVs) circulate in wild waterfowl, predominantly in the orders of the , gulls) . AIVs ar, gulls) . In wild, gulls) ,4. The r, gulls) ,6,7. TheIncursions of AIVs from wild waterfowl into terrestrial poultry species, e.g., chickens and turkeys, occur frequently via (in)direct contact ,9. In thThere have been 51 independent documented events of MBCS acquisition in natural settings since 1959. In this review, all historical emergences of AIVs with an MBCS since 1959 are listed, and the current understanding of MBCS amino acid composition and acquisition is discussed. Furthermore, we shine light on the remaining questions regarding HPAIV genesis, primarily on the molecular mechanisms of nucleotide insertions leading to MBCS acquisition and why those are restricted to LPAIVs of the H5 and H7 subtypes.The first recorded AIV outbreak occurred in 1878, when a chicken flock in Italy contracted a contagious disease with high mortality rates . Over thGenerally, HPAIV outbreaks occurred in terrestrial poultry holdings, e.g., chicken, turkey, and ostrich farms, and were short-term epizootics with limited regional spread. Most outbreaks were halted by stringent culling measures and/or vaccination. However, despite intervention attempts, multiple HPAIVs have circulated for longer periods of time following their initial emergence. HPAIVs from the H5 lineage whose HA originates from the H5N1 HPAIV A/goose/Guangdong/1/96 (Gs/Gd) strain are currently enzootic in poultry and wild birds in various parts of the world. Gs/Gd-H5 HPAIVs caused outbreaks in poultry in Hong Kong in 1997, alongside human infections . The outThe emergence of HPAIVs is thought to occur in terrestrial poultry following the transmission of H5 or H7 LPAIVs from the wild bird reservoir. The link between HPAIV genesis and terrestrial poultry is evident when an LPAIV progenitor is detected in the same or neighboring poultry farm prior to HPAIV detection. These sparse occasions 12 in total) have been indicated in  in totalThe HA glycoprotein mediates two essential events during viral entry, i.e., binding to sialic acid moieties on target cells and fusion between the viral and endosomal membranes. HA is produced as precursor HA0, anchored in the membrane of the endoplasmic reticulum . HA0 monThe cleavage of HA0 is performed by host proteases as AIV genomes do not encode proteases. The cleavage site of LPAIVs contains one basic amino acid, an arginine (R) or in some cases a lysine (K). This monobasic cleavage site is recognized by trypsin-like serine proteases that are expressed in a tissue-specific manner. In chickens, trypsin-like proteases are expressed in the RT and GIT, limiting the tropism of LPAIVs to these organ systems. In contrast, the MBCS, here referred to as cleavage site motifs that contain a minimum of four basic amino acids or at least one inserted basic amino acid, from HPAIVs is cleaved by proteases from the subtilisin-like proprotein convertase family, including furin ,113. In The virulence of HPAIVs is a polygenic trait that is, apart from the presence of an MBCS, mediated by other properties of HA as well as other viral proteins. This is exemplified by the fact that the virulence in chickens of an LPAIV H5 with artificially inserted MBCS does not necessarily equal that of a Gs/Gd-H5 HPAIV . Many amThe cleavage of HA0 can occur at multiple stages during the viral replication cycle. HA0 can be cleaved upon translation in infected cells by proteases in the secretory pathway, in the extracellular space by soluble proteases, or on the plasma membrane of target cells following budding or prior to endocytosis . The natFurin was the first protease to be appointed as the activator of HPAIV HA0. Furin belongs to the proprotein convertase (PC) family, consisting of nine proteases that activate protein precursors during post-translational processing. PCs are membrane-attached or soluble and each have specific subcellular residencies (reviewed in ). Furin nbXnbR, where Xnb is any non-basic amino acid. Such a motif can still be cleaved by furin, as was demonstrated for a laboratory H7N3 AIV with a large insertion, resulting in the MBCS motif SLSPLYPGRTTVLHVRTAR [The MBCS amino acid composition, surrounding sequence, three-dimensional loop structure, and accessibility of the cleavage site strongly influence HPAIV H0 cleavage by host proteases. The cleavage site motifs of documented newly emerged HPAIV strains vary extensively in length and in amino acid composition . MoreoveVLHVRTAR . H7 MBCSVLHVRTAR .The presence of an MBCS in AIVs does not automatically confer trypsin-independency or high virulence in vivo . As indiAll naturally evolved AIVs with an MBCS, defined as a tetrabasic motif or with inserted basic amino acids, are of the H5 and H7 subtypes, except for the previously mentioned trypsin-dependent H4N2 isolate with cleavage site motif PEKRRTR (IVPI: 0) ,177. HowFirstly, it was hypothesized that the putative glycosylation site p22, which can reduce HA cleavage efficiency by furin-like proteases, might be less present in H5 and H7 AIVs . HoweverThirdly, it has been hypothesized that the subtype restriction of MBCS acquisition might be the result of incompatibility at the protein level of an MBCS in HAs from subtypes other than H5 and H7. Nevertheless, reverse genetics studies have shown that HAs from non-H5/H7 subtypes can accommodate an artificial MBCS, which can be cleaved by ubiquitous proteases ,190,191.Although the exact mechanisms by which H5 and H7 LPAIVs acquire an MBCS have not been elucidated, multiple non-exclusive hypotheses have been proposed ,194,195.−5 substitutions per nucleotide per replication cycle [The influenza A virus RNA-dependent RNA polymerase (RdRp) is inherently error-prone. Single nucleotide substitutions occur at an approximate rate of 2.5 × 10on cycle . The conon cycle . Both coon cycle ,199.MBCS insertions are often duplications of neighboring sequences, as can be appreciated by comparing HPAIV and LPAIV cleavage site sequences A,C. SuchTemplates with adenine/uracil stretches have been shown to be more prone to influenza virus RdRp slippage than those with cytosine and guanine stretches, probably due to weak interactions between the base pairs . InteresThese hypotheses are corroborated by results from experiments on the genetic stability of different sequences at the HA cleavage site. The serial passaging of LPAIVs with mono-, di-, or tribasic cleavage sites in cell culture without trypsin, embryonated eggs, or chickens to generate and/or select for HPAIVs has been attempted  164,165,215,216.The results from the abovementioned passaging experiments and in vitro reporter systems ,203,212 RNA folding in the region coding for the HA cleavage site has been suggested to influence RdRp backtracking/stuttering ,200,203.The insertion of exogenous RNA into the cleavage site sequence following NHR has been shown in seven out of 33 natural H7 HPAIV emergences and is probable in four additional H7 emergences based on codon usage and sequence alignment, as the stretch of inserted nucleotides did not consist of duplications of the surrounding sequence  195,222222. NHR There have been a total of 51 independent emergences of MBCS-containing AIVs in the past 60 years, and their frequency has increased over the past decades. The importance of an MBCS as a virulence determinant was already established decades ago. More recently, knowledge has been acquired about factors beyond the MBCS that determine the pathogenicity of AIVs in avian hosts. Interesting discoveries were made recently regarding HA-activating proteases, such as the systemic dissemination of LPAIVs due to alternative HA cleavage mechanisms, and work is underway to characterize proteases in avian species. The biggest remaining questions concern the emergence of HPAIVs at the molecular level and the restriction of the HPAIV phenotype to the H5 and H7 subtypes in nature. Here, we shed light on the different aspects that might explain the subtype restriction of HPAIV emergence. Viruses with HAs of the H5 and H7 subtypes do not stand out from those of other subtypes with regards to circulation in terrestrial poultry, the glycosylation of p22, the presence of RNA structures at the cleavage site region, or the intrinsic ability to accommodate an MBCS at the protein level. The presence of yet-undetermined factors within H5 and H7 HA might influence the genesis of HPAIVs. Our recent analysis confirmed the previously published notion that H5 LPAIVs harbor exceptionally high numbers of adenine and purine residues at the cleavage site, which might promote errors by the RdRp. Furthermore, we showed that the minimum number of substitutions necessary for an LPAIV to obtain an insertion-prone cleavage site sequence is significantly lower in H5 and H7 subtypes. We postulated that the chance of H5 and H7 HAs acquiring an MBCS in this multi-step process is therefore higher. Recent advances have been made by using reporter assays and deep sequencing methods to elucidate the mechanisms of MBCS acquisition, highlighting that the RNA template sequence seems to be crucial for RdRp stuttering and backtracking. The role of local RNA structures remains to be investigated. Future studies utilizing in vitro replication systems and ultra-sensitive deep sequencing methods will provide the reproducibility, flexibility, throughput, and sensitivity that are necessary to elucidate the specific details of stuttering, backtracking, and recombination by the influenza RdRp.


Dracaena angustifolia Roxb has been used as an anti-inflammatory agent by the Li people in Hainan, China. In preliminary phytochemical studies conducted in our lab, its fractions were found to inhibit α-glucosidase in vitro, indicating a potential for alleviating glucose dysregulation.As a traditional herbal medicine, Through in vitro enzymatic assays, the abilities of the separated components to affect α-glucosidase and α-amylase were evaluated. By establishing concentration gradients and generating Lineweaver–Burk plots, the corresponding inhibition modes together with kinetic parameters were assessed. Following the evaluation of the outcomes of their combination with acarbose, computational docking and molecular dynamic simulations were carried out to analyse the interaction mechanisms and perform virtual screening against human enzymes.Compared with acarbose, 7 compounds, including flavonoid derivatives, amides and aromatic derivatives, with higher α-glucosidase inhibitory efficiencies were confirmed. It was found that those competitive/mixed candidates and acarbose interacted synergistically or additively on α-glucosidase. Moreover, 3 of them were able to inhibit α-amylase in mixed mode, and additive effects were observed in combination with acarbose. Through in silico docking, it was found that the active site residues as well as adjacent residues were involved in α-glucosidase and α-amylase binding, which were mainly achieved through hydrogen bonding. Among those dual-function flavonoids, Compound 9 was predicted to be a considerable inhibitor of human enzymes, as the formation of ligand–enzyme complexes was mediated by the residues responsible for substrate recognition and catalysis, the stabilities of which were reiterated by molecular dynamics simulations.Dracaena angustifolia Roxb in diabetes treatment.Despite their mild effects on α-amylase, considerable α-glucosidase inhibitory efficiencies and potential synergy with acarbose were exhibited by these natural candidates. Furthermore, a stable ligand, human α-glucosidase, was predicted by the performed simulations, which provided useful information for the application of The online version contains supplementary material available at 10.1186/s12906-022-03649-3. Type II diabetes mellitus T2DM) is a chronic disease that causes long-term body damage and mental issues. T2DM is diagnosed by persistent hyperglycaemia, which is caused by the insufficient secretion of insulin or insulin resistance . AlthougDM is a cRehmannia glutinosa, an essential constituent of Xiao Ke Wan  [Dracaena plants [Isolated compounds from pharmaceutical plants are considered to be alternatives. As indicated in clinical trials and laboratory studies, equivalent efficiency and improved safety could be ensured by monotherapy with those antidiabetic compounds or in combination with reduced acarbose , 11. Furiabetes) . Activita plants , 15.Dracaena genus, Dracaena angustifolia Roxb is an evergreen shrub widely distributed in tropical areas, and it is utilized by the Li people in China’s Hainan province as an herbal remedy [D. angustifolia Roxb [D. angustifolia Roxb in antidiabetic drug development, the IC50 values of each separated substance against α-glucosidase were initially evaluated. Compared to the reference acarbose, a total of seven compounds  with better inhibition efficiencies, ranging from 1.99 μM to 0.65 mM, were confirmed. Then, the corresponding standard curve and Lineweaver–Burke plots were constructed to investigate the corresponding inhibition models, and it was found that Compound 18 with the lowest IC50 and Compound 5 were an uncompetitive inhibitor and a noncompetitive inhibitor, respectively. Competitive or mixed-type inhibition was observed for Compounds 6, 8, 9, 22, and 24, all of which were able to exhibit synergistic effects with acarbose in the subsequent combination assay. Moreover, those five compounds were subjected to α-amylase activities assays, and only the flavonoids  showed weak inhibitory actives, with IC50 values two orders of magnitude higher than that of acarbose (10 μM). As revealed by kinetic and synergism analyses, the three compounds acting as mixed inhibitors were able to enhance the inhibition of acarbose against α-amylase. The docking technique was employed to assess the possible molecular mechanism. In addition to the active site residues and the adjacent residues, HIS112, GLU411, and ASP442 were thought to contribute to the interactions between those small ligands and α-glucosidase. For porcine α-amylase, GLN63 was important for the inhibitory activities of Compounds 6 and 9. Then, docking was repeated to assess the compounds that displayed inhibitory effects on α-glucosidase and α-amylase, in which homologous enzymes of humans were chosen. Compound 9 generated the best configuration, by which four sites for substrate binding  in human α-glucosidase, part of the catalytic sites and one residue for calcium binding  in human α-amylase were affected. With the information created by the molecular dynamics simulation, the stabilization of the human α-glucosidase–Compound 9 complex was confirmed. This study provides useful information for further in vivo research and antidiabetic drug discovery regarding D. angustifolia Roxb.As a no-resin-producing species of the l remedy . Accordilia Roxb , 18. Ourlia Roxb , and beiD. angustifolia Roxb were prepared as reported by Zhao et al. [Saccharomyces cerevisiae), and α-amylase (porcine pancreas) were purchased from Sigma–Aldrich. 4-Nitrophenol (pNP), 4-nitrophenol-α-D-glucopyranoside (pNPG), soluble starch from potato and other reagents were purchased from common commercial suppliers and used as received.Bioactive compounds from the stems of o et al. . 2S)-4′S-4′D. anD. angustifolia Roxb, which were diluted to 4 mM. After being kept at 37 °C for 10 min, 25 μL of α-glucosidase (0.5 U/mL) was added. Following another 10 min incubation at 37 °C, the reaction was stopped with 125 μL of 0.2 M Na2CO3, and the absorbance at 410 nm of each sample (converted pNP) was measured via a microplate reader . A standard curve was generated using serially diluted pNP, acarbose and assay buffer as positive and blank controls. The percent inhibition was calculated by the following formula: % inhibition = (1 - ASample / AControl) × 100%. For the compound with a greater inhibition rate (vs. the same amount of acarbose), IC50 values were determined by plotting the concentration gradient against the corresponding inhibition percentage.α-Glucosidase inhibitor screening was conducted according to a previously reported procedure with slight modifications . A measu2: 2% KI), and the optical density at 580 nm was directly proportional to its concentration. Their influences on α-amylase were calculated as percent inhibition according to the equation % inhibition = (APositive - ASample)/(APositive - ABlank) × 100%, where APositive and ABlank are the absorbance values of PBS buffer containing acarbose or without compounds from D. angustifolia Roxb. A starch calibration curve ranging from 0.0625 to 4 mg/mL and a plot of inhibition rate versus compound concentration were prepared to derive corresponding IC50 values.Changes in α-amylase activities were quantitatively analysed via a method based on starch-iodine colorimetric detection . Soluble50 value) was quantified to create Lineweaver–Burk plots. The equations were rearranged into double reciprocal forms:To acquire the inhibition type and related parameters of those inhibitors, kinetic assays were carried out, and the conditions of enzymatic reactions are detailed in the above section, in which the amount of enzymes was fixed. With an increasing amount of substrate, the amount of hydrolysed pNPG or starch in the presence of compounds  of acarbose and chosen compounds were combined using freely available software  [D)1 and (D)2 are the doses of sample and acarbose that inhibit a certain level of enzyme in the combination system, respectively, and (Dx)1 and (Dx)2 are the doses of a single inhibitor that produce the same level of inhibition. When the CI values were above 1.1, between 0.9 and 1.1, and below 0.9, the effects were defined as antagonistic, additive, and synergistic.Three concentrations  . A combiHomo sapiens (PDB IDs: 5NN8 and 2QV4) are available in the protein databank (www.rcsb.org/pdb). 3D structures with minimized energy of Compounds 6, 8, 9, 22, and 24 were sketched using Chem3D . Prior to docking, water molecule removal, Gasteiger charge addition, and the addition of hydrogen were carried out. Compounds were incorporated as ligands, whose bond rotations were set as default. The docking region was placed in the sites covering the active residues. For the α-glucosidase from Saccharomyces cerevisiae, a grid box, with a spacing of 30 Å, was centred at the coordinates of 20.159, − 6.004, and 22.986. For porcine pancreatic α-amylase, the X, Y, and Z centres were 36.436, 37.487, and − 2.166, respectively, with a spacing of 30 Å. For enzymes in human saliva and the pancreas, docking boxes with a spacing of 30 Å were generated, whose centres were defined as − 14.312, − 38.186, and 95.627 and 12.805, 46.042, and 25.979, respectively. Subsequently, the Broyden-Fletcher-Goldfarb-Shanno algorithm was chosen, and 50 independent calculations were conducted. Enzyme-compound complexes with the lowest binding energies were extracted, and the superimposed diagrams were analysed using PyMOL 2.6 [The mechanisms of action and possible interactions were predicted by AutoDock Vina . CrystalThe human enzyme–Compound 9 complexes were subjected to molecular dynamics simulations. After being separated, human α-glucosidase and α-amylase were prepared using Gromacs , in whicEach experiment was performed in triplicate, and the data were interpreted as the mean ± standard deviation (SD). Statistical analysis was carried out by one-way analysis of variance (ANOVA) using Origin 9.0 software.D. angustifolia Roxb were rendered for the preliminary assay, in which compounds with poor aqueous solubilities were excluded, and only 7 of them were found to have higher potency than acarbose (4.07 ± 0.516 mM). As shown in Fig. 50 values at low micromolar levels for Compounds 18 (1.99 ± 0.2 μM) and 22 (40 ± 4.0 μM), which are phenoic derivatives that have been briefly mentioned in the phytochemical screenings of Crataegus pinnatifida Bge and Polygonum aubertii Henry [50 values of 0.24 ± 0.03 mM, 0.37 ± 0.02 mM, 0.52 ± 0.01 mM, 0.65 ± 0.01 mM, and 0.78 ± 0.03 mM, respectively.Despite the lack of scientific evidence confirming the genetic susceptibility to T2DM in the Asian population, a robust association between inappropriate dietary habits and the disease incidence is undoubtable . Especiaii Henry , 30, werSince the mechanism underlying the postprandial blood glucose control of acarbose and other approved α-glucosidase inhibitors is the targeting of the enzyme in a competitive manner, the corresponding reversibility should be emphasized. Modes of their inhibition were distinguished based on kinetic analyses, and it was demonstrated that the type for Compound 18 showing the most effective inhibitory activity was uncompetitive Fig. A. As a r50 value.In addition to the verification of the competitive behaviour of Compound 8, others were found to be mixed inhibitors. For a further comparison, their kinetic constants were calculated. As listed in Table D. angustifolia Roxb on α-glucosidase activity were determined. As shown in Fig. To identify candidates that could be potential substitutes for acarbose or complementary, the impacts of the combination of acarbose with competitive or partly competitive inhibitors from 50 value of acarbose against α-amylase was found to be 10.25 ± 0.01 μM, while mild α-amylase inhibition was recorded; only flavonoid compounds from D. angustifolia Roxb  had IC50 values at the millimolar level   method usually used for the detection of converted maltose was found to be not acceptable . The int50, was supposed to be more probable  of α-glucosidase and all of the active site residues (ASP197 and GLU233) of α-amylase  and − 242,119.5 Kcal/mol (α-amylase–Compound 9). The details of the corresponding energy graphs, having minimal variations, are displayed in Fig. D. angustifolia Roxb have been verified, in which the functions of bioactive components are strongly related to their chemical structures. The previous phytochemical assay and the preliminary assessment of enzyme inhibition recalled the existence of substances that might interrupt carbohydrate digestion. In subsequent research, more efficient α-glucosidase inhibitors  were identified (with acarbose as a reference) and were proven to exhibit uncompetitive, competitive, noncompetitive, or mixed manners. While their abilities to inhibit α-amylase activities were unremarkable, only three of them  were considered to be bifunctional. As revealed in the computational docking, the mechanism of α-glucosidase inhibition was attributed to binding to residues HIS112, ARG213, GLU277, GLN279, ASP352, GLU411, and ARG442. Relatively weak hydrogen bonds with residues GLN63, ASP197, HIS299, and ASP300 were essential for α-amylase inhibition. Among compounds with dual inhibitory activities, Compound 9 was characterized by good redocking performance. Despite detecting a higher variation in RMSD values of human α-amylase–Compound 9, the possible human α-glucosidase inhibition of this compound isolated from D. angustifolia Roxb is worth being investigated in future research.As a representative of Li folk medicine, the bacteriostatic, antitumor, and anti-inflammatory features of Additional file 1.


Bacillus spp. with different levels of antifungal activities as model antagonists and quantify their inhibitory potencies against classic plant pathogens.Large screens of bacterial strain collections to identify potential biocontrol agents often are time-consuming and costly and fail to provide quantitative results. In this study, we present two quantitative and high-throughput methods to assess the inhibitory capacity of bacterial biocontrol candidates against fungal phytopathogens. One method measures the inhibitory effect of bacterial culture supernatant components on the fungal growth, while the other accounts for direct interaction between growing bacteria and the fungus by cocultivating the two organisms. The antagonistic supernatant method quantifies the culture components’ antifungal activity by calculating the cumulative impact of supernatant addition relative to the growth of a nontreated fungal control, while the antagonistic cocultivation method identifies the minimal bacterial cell concentration required to inhibit fungal growth by coinoculating fungal spores with bacterial culture dilution series. Thereby, both methods provide quantitative measures of biocontrol efficiency and allow prominent fungal inhibitors to be distinguished from less effective strains. The combination of the two methods sheds light on the types of inhibition mechanisms and provides the basis for further mode-of-action studies. We demonstrate the efficacy of the methods using IMPORTANCE Fungal phytopathogens are responsible for tremendous agricultural losses on an annual basis. While microbial biocontrol agents represent a promising solution to the problem, there is a growing need for high-throughput methods to evaluate and quantify inhibitory properties of new potential biocontrol agents for agricultural application. In this study, we present two high-throughput and quantitative fungal inhibition methods that are suitable for commercial biocontrol screening. Pseudomonas, Burkholderia, Streptomyces, and Bacillus genera are well known for their antifungal capacity and for the production of a large variety of bioactive metabolites  culture supernatants. We demonstrate the efficacy of the methods using bacterial strains with different antifungal performance. Using the two novel methods, the antifungal properties of the bacteria were compared, and prominent fungal inhibitors were distinguished from less effective bacterial strains. Both methods were developed utilizing 600) and 5-fold serial dilutions were prepared . The OD600 of each strain used in the study was correlated with viable cell counts (CFU). A fungal spore suspension was prepared and mixed thoroughly to ensure a homogeneous spore distribution. Then, samples from the bacterial dilution series were coinoculated with a fixed quantity of fungal spores to determine the minimal inhibitory cell concentration (MICC) that abolished fungal growth  pigmentation, even in the absence of visible hyphae. The coinoculation of bacterial culture dilutions and fungal spores was used to distinguish the limits of the bacterial inhibition capacity.Fungal growth inhibition was scored as no growth (1), weak growth (2), and (positive) growth (3) . Fungal B. amyloliquefaciens BCF007 and B. velezensis BCF015 showed the most potent inhibition properties, and even at the highest dilution step , the two strains were able to inhibit F. culmorum’s growth. Determining the MICC more accurately would require smaller dilution steps to be included in the assay. Nevertheless, the experimental setup is optimized for HTS of large strain collections. B. subtilis BCF001 also displayed potent fungal inhibition properties, abolishing fungal growth up to an OD600 of 3.2 × 10−5, corresponding to 1,900 CFU inoculated. B. paralicheniformis BCF009, however, did not affect fungal growth even at the lowest dilution step, corresponding to an OD600 of 2 × 10−2, or 3.89 × 104 CFU inoculated.Comparison of bacterial MICCs allowed ranking of the strains in accordance with their fungal inhibition properties .To generate visual and directly comparable plots of the inhibition results, we calculated a numerical inhibition score that reflects the inhibitory capacity of each strain. In brief, the lowest cell concentration that caused fungal growth inhibition was identified for each strain, and a numerical inhibition score was calculated based on the natural logarithm to the MICC by applying the empirical formula presented in B. subtilis BCF001, B. amyloliquefaciens BCF007, B. paralicheniformis BCF009, and B. velezensis BCF015 were also quantified against other phytopathogenic filamentous fungi, specifically F. graminearum and B. cinerea strains. Images acquired to record the experimental results and the calculated MICCs and inhibition scores can be found in Fig. S1 and Table S1. Interestingly, our inhibition assay proved applicable to these additional species of plant-pathogenic fungi. The initial spore concentration was the only parameter that required adjustment when testing growth inhibition against the new fungal strains.Using the newly developed method, the antifungal activities of B. amyloliquefaciens BCF007 and B. velezensis BCF015 displayed the most efficient growth inhibition of F. culmorum, the differences between them and B. subtilis BCF001 were minimal when assayed against F. graminearum DSM4528, and the MICCs were not significantly different (Table S2). Furthermore, B. subtilis BCF001 proved more efficient than B. amyloliquefaciens BCF007 and B. velezensis BCF015 against B. cinerea Kern B2. The inhibition scoring results obtained for B. paralicheniformis BCF009 were in accordance with the poor inhibitory properties of this strain, regardless of the fungal pathogen tested. For comparison between strains with similar inhibition potencies, the range of the dilution series can readily be adjusted to allow determination of a more accurate MICC.The above-described scoring system was applied to the results obtained for the three fungal species . While B600 measurements in liquid cultures, and therefore, reduced fungal growth in the presence of bacterial metabolites reflects greater inhibition potency of a given strain. For this method, bacterial cultures were grown overnight and normalized to the same OD600 value prior to collection of the culture supernatants by centrifugation , suggesting an effect of supplemented nutrients (not consumed by the bacteria) that outweighed the effect of the antifungal bioactive metabolites.The inhibition assay demonstrated a reverse correlation between the added volume of bacterial cell-inactive supernatant and the growth of  cinerea  to C. FoA numerical inhibition score was assigned to each strain by quantifying the fungal growth in response to supernatant addition (5 different volumes). The inhibition scores were calculated by subtracting the accumulated relative fungal growth from the total potential fungal growth under the 5 conditions tested , possibly due to variations in the initial spore count or spore viability. These variations could be minimized either by prolonging the incubation time until readout or by preparing assays from a unique spore stock. For this reason, biological replicates were prepared with the same fungal spore solution. Nevertheless, the overall conclusions remained unchanged despite variations in the final fungal growth.F. culmorum, F. graminearum, and B. cinerea was somewhat affected by the addition of the respective antibiotics . The results obtained with filtered supernatants with and without antibiotics revealed that the relative inhibition results remained unaltered, although the addition of antibiotics slightly but significantly reduced the fungal growth . Both filtration and antibiotic addition had generally no effect on the fungal inhibitory potency, suggesting that bioactive metabolites remained active after both procedures .Typically, bacterial-cell-inactive supernatants are generated by filtration of the cell cultures –45. In c–Bacillus strains  an antagonistic cocultivation method based on the inoculation of a constant number of fungal spores together with bacterial dilution series on solid medium to generate a quantitative measurement of the minimal inhibitory  cell concentration (MICC) of fungal growth and (ii) an antagonistic cell-inactive-supernatant method based on the inoculation of a constant number of fungal spores together with different volumes of bacterial culture supernatants in liquid medium to provide a quantitative measurement of fungal growth inhibition by secreted metabolites.Although classic antagonistic methods that assess the adjacent growth of two species on agar plates allow the assessment of fungal inhibition potential 3234, 53–5553–in planta assays include the tripartite interaction of the biocontrol candidate, phytopathogen, and plant host . Fifteen microliters of each bacterial dilution was inoculated in consecutive wells by spotting the solution in the center of each well. One strain was assigned per column. Next, a fungal spore solution was prepared with peptone saline and vortexed vigorously to disperse clumps of spores. Fifteen microliters of fungal spore solution was coinoculated with the bacterial dilutions in each well. The approximate final fungal spore concentrations of F. culmorum, F. graminearum, and B. cinerea were 5.5 × 106 spores/mL, 6.25 × 104 spores/mL, and 2 × 107 spores/mL, respectively. Coinoculated plates were sealed with 3M tape  to reduce growth differences between inner and peripheral wells and incubated at room temperature under natural light conditions. After 5 days, the fungal inhibition was evaluated by visual inspection and the plates were imaged by scanning (Epson Perfection V800 Photo). The minimal inhibitory cell concentration (MICC) was identified for each strain and averaged between technical duplicates and then between biological triplicates. The MICC (CFU) against each fungal species was converted to an inhibition score using t test.The fungal inhibition assay was prepared in 48-well microtiter plates with 0.5 mL PDA in each well. F. culmorum, F. graminearum, or B. cinerea were added to a final concentration of 1.1 × 106 spores/mL, 1.25 × 104 spores/mL, or 2 × 106 spores/mL, respectively. The spore suspensions were mixed thoroughly by vortexing to ensure a homogeneous distribution. Bacillus species cultures were adjusted to an OD600 of 2 and centrifuged to pellet the cells. The supernatants were collected, and the cell pellets discarded. Increasing volumes of bacterial supernatants (ranging from 10 to 80 μl) were inoculated into the fungal spore suspensions. Two approaches were implemented for sterilization of the supernatant to omit bacterial growth. Either the bacteriostatic antibiotics chloramphenicol and tetracycline were added to the fungal spore suspension to a final concentration of 50 μg/mL and 10 μg/mL, respectively, or the supernatants were sterilized by filtration  prior to coinoculation with the fungal spores. The plates were sealed with 3M tape and incubated at 25°C without shaking in the dark. The fungal growth was quantified by spectrophotometric measurements (OD600) after 48 h for F. graminearum and B. cinerea inhibition assays and after 67 to 72 h for F. culmorum inhibition assays. For more accurate fungal growth estimation, the OD600 was measured using a 5-by-5 area-scanning matrix, resulting in 25 measurements per well, which were subsequently averaged. Following the evaluation of fungal growth, the supernatants were collected and plated on LB with fungicides (50 mg/L nystatin) to check for unwanted bacterial growth. Statistical analyses were done to compare the effects of (i) bacterial culture supernatants on fungal growth, (ii) filtration and antibiotics on the bacterial supernatants’ potency, and (iii) prokaryotic antibiotics on fungal growth. Statistical significance was calculated by Student’s t test (two tailed). A numerical inhibition score was assigned to each strain by quantifying the fungal growth in response to the addition of supernatant (5 volumes). The inhibition scores were calculated by subtracting the accumulated relative fungal growth from the total potential fungal growth (5 conditions tested) as shown in The fungal inhibition assay was prepared in 48-well microtiter plates with 0.5 mL PDB medium. Spores of


Since basophils are implicated in asthma severity, our aims were to address whether SERCA2 is implicated in human basophil responses, especially following IgE-mediated activation. Human basophils were obtained from buffy coats, following research ethics approval, and further purified by immunomagnetic cell sorting. Expressions of SERCA2, and other isoforms, were determined by Western blotting in parallel to measuring IgE-dependent histamine releases from the same donors. The effects of a SERCA-activator and inhibitor were also assessed on their abilities to modulate basophil histamine release. We observed an inverse correlation between basophil responsiveness to IgE-dependent stimulation and SERCA2 expression. Thapsigargin, a highly-specific SERCA inhibitor, stimulated basophil histamine release and potentiated IgE-dependent secretion of the amine. Conversely, disulfiram, a SERCA activator, inhibited IgE-dependent basophil activation. The results obtained from this exploratory study indicate that SERCA2 may be an additional regulator of basophil reactivity alongside early excitatory or inhibitory signal transduction pathways.Basophils crucially contribute to allergies and other Th2-driven diseases by rapidly releasing inflammatory and immunomodulatory mediators following high-affinity IgE-receptor crosslinking. Although these basophil-mediated responses depend on sensitization with antigen-specific IgE, this does not necessarily predict clinical symptom severity. It is thought that the balance of early stimulatory (e.g. SYK) and inhibitory (e.g. SHIP-1) intracellular signals are associated with basophil responsiveness, which is also critically dependent on calcium mobilization. Previous studies suggest that the sarcoplasmic reticulum Ca They also play a pivotal role in initiating and sustaining Th2-type pro-allergic immune responses by releasing IL-4 and IL-13, alongside various inflammatory cytokines such as TNFα. Despite their relative scarcity, especially to mast cells with which they share the ability to release pro-inflammatory mediators by IgE-dependent mechanisms, animal models of allergy and immunity to parasites have demonstrated that basophils play a non-redundant role in initiating Th2 responses and in chronic allergic inflammation  by allergens crucially determines basophil activation in humans, whereas in mice IgG-mediated anaphylaxis due to basophil activation may also occur , underliper se . This anper se , 20, Allper se , FcγRIIbper se  and siglper se . Basophi3). IP3 is crucially responsible for the increase in intracellular free calcium that drives the opening of calcium-sensitive calcium channels, allowing for the influx of extracellular calcium ions into basophils, without which no mediator release occurs. Calcium mobilization in basophils is therefore an essential step in determining basophil responses. IP3-mediated leakage of calcium ions from intracellular stores, such as the sarcoplasmic reticulum, is potentially offset by the sarcoplasmic reticulum Ca2+-ATPase (SERCA2). Interestingly, SERCA2 expressions in airway smooth muscle cells have been reported to be inversely associated with airway inflammation  Research Ethics Committee (reference number 07/Q1206/3), purchased from the NHS Blood and Transfusion service. Basophils were first isolated by Ficoll-density centrifugation  and purified further by immunomagnetic cell selection (negative selection) using commercial isolation kits  as previously reported , 34. Bas2.25 cells) were pelleted by centrifugation, and then lysed by vigorous mixing with lysis buffer containing 50 mM Tris-HCl pH 7.5, 5 mM EDTA, 10mM EGTA, 5 mM DTT, 1% Nonidet P-40, 1mM PMSF, 100 ug/ml aprotonin, 20 ug/ml leupeptin and 10 mM benzamidine. An equal volume of 2x-concentrated Laemmli sample buffer was then added to the lysed basophils which were then heated to 99°C, with agitation, for 2 min before storage at -80°C. Proteins were separated by 12% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and then blotted onto nitro-cellulose membranes. Prestained molecular weight rainbow markers  were also included for each SDS-PAGE run. Membranes were blocked for 4 h in 5% skimmed milk dissolved in TBST buffer  with gentle agitation. After 3 x 5 min washes in TBST, membranes were incubated overnight (at 4°C) with primary antibodies, directed against human SERCA2  purchased from Abcam, Cambridge, UK). Membranes were then successively washed  followed by incubation with anti-mouse horse radish peroxidase-conjugated secondary antibodies for 2 h with gentle agitation. After washing, unbound secondary antibody proteins were visualized by autoradiography according to the manufacturer’s instructions . After detection, membranes were stripped for 10-20 min using Re-blot plus reagent , washed in TBST (4 x 5 min) and reprobed. Beta-actin expressions were measured in order to validate equal protein loading using mouse monoclonal HRP-conjugated antibodies (ab20272). Densitometric analysis was performed using ImageJ and the relative band densities of SERCA were normalized to respective band densities of β-actin and adjusted to control samples.Aliquots of purified basophils , were warmed for 15 min at 37°C before stimulation with 1 µg/ml goat anti-human IgE  for 30 min, alongside unstimulated controls. Reactions were then terminated by adding ice-cold calcium-free buffer and centrifuging vials for 2 min at 1000 x g. Histamine content in the supernatants and cell pellets, which were diluted as required and lysed with perchloric acid (4%), was assessed using a spectrofluorometric autoanalyzer, based on the method reported by Shore et al.  on basophil histamine release were investigated by preincubating isolated basophils with various concentrations of disulfiram (together with buffer controls) for 15 min at 37°C before stimulation with anti-IgE and assessment of histamine releases as described above. Part of the remaining cell pellets were also subjected to MTS viability assays. Briefly, cells were incubated with 3--5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) and absorbance was measured at 490 nm using a plate reader, according to the manufacturer’s instructions .2.4Experiments were repeated using different basophil donors and results were first tested for normal distribution using the Shapiro-Wilk test. For normally-distributed data, a one-way ANOVA followed by Holm-Bonferroni correction was employed to assess statistically significant differences when multiple comparisons were made and a paired Student’s t-test when comparing two events. The potential association between IgE-dependent basophil reactivity and SERCA2 expression was analyzed using linear regression analysis as well as Spearman’s rank correlation- and Pearson correlation coefficients. Statistical probabilities (p) were expressed as *, where p < 0.05, **p < 0.01 and ***p < 0.001, unless shown otherwise.3In agreement with previous reports , 28, 32,2 = 0.1; p>0.2). Because IgE-dependent basophil activation between different donors  is highly variable, we grouped the donors into low, medium and high responders to anti-IgE stimulation. We observed that the expression of SERCA2 was diminished most noticeably in the high responder group  channels, resulting in a substantial influx of extracellular calcium ions into basophils. Without the influx of extracellular calcium, intermediary signalling is considerably abrogated and mediator secretion from basophils does not occur  was reported to probably arise from the same internal source of the ion  which enhance IgE-dependent mediator release. Importantly, basophil releasability to other stimuli, such as the bacterial peptide fMLP, does not correlate with IgE-mediated histamine release, although the initial Ca the ion . This su the ion  and, acc the ion  as well To the best of our knowledge, this is the first study to implicate a role for SERCA in regulating the function of allergic effector cells. A possible role for diminished SERCA expressions in the context of allergic inflammation is currently not well understood, where studies to date have focussed only on its role in airway smooth muscle cells regarding asthma. Here, Mahn et al.  reportedSERCA proteins are expressed in at least seven different isoforms , of which only SERCA2b and SERCA3 isoforms are expressed in non-muscle cells  Research Ethics Committee (reference number 07/Q1206/3). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirementsBG conceived the study, conducted most of the experiments, analysed and interpreted the data, and wrote the first draft of the manuscript. AH contributed to the experiments shown in


The flow speed of the Greenland Ice Sheet changes dramatically in inland regions when surface meltwater drains to the bed. But ice-sheet discharge to the ocean is dominated by fast-flowing outlet glaciers, where the effect of increasing surface melt on annual discharge is unknown. Observations of a supraglacial lake drainage at Helheim Glacier, and a consequent velocity pulse propagating down-glacier, provide a natural experiment for assessing the impact of changes in injected meltwater, and allow us to interrogate the subglacial hydrological system. We find a highly efficient subglacial drainage system, such that summertime lake drainage has little net effect on ice discharge. Our results question the validity of common remote-sensing approaches for inferring subglacial conditions, knowledge of which is needed for improved projections of sea-level rise. The effect of increasing surface melt on annual discharge is unknown for the Greenland Ice Sheet. Here, the authors find that Greenland’s largest single-glacier contributor to sea-level rise accommodates basal floods following supraglacial lake-drainage events with limited impact on ice flow. Glacier basal resistance depends on water pressure and distribution within the subglacial drainage system9 and is controlled by where, when, and how much surface melt reaches the bed11. The flow of the inland Greenland Ice Sheet is sensitive to the variability of surface-melt inputs on hourly to seasonal timescales13. Sea-level-rise contributions from the ice sheet, however, are dominated by the calving of fast-flowing tidewater glaciers at the marine margin4 —a region where the effects of surface-melt forcing on ice flow are poorly understood15.Fast-flowing 29. The flow response to lake drainage along the length of a high-discharge, fast-flowing tidewater glacier has never been measured. Here, we present observations from a lake drainage at Helheim Glacier showing that the hydrological system is dominated by an efficient drainage network that is capable of rapidly exporting the additional meltwater input from the lake, with an increase, and subsequent decrease, in drainage-system water pressure. The water-pressure changes are small and short-lived, such that the lake drainage has minimal impact on the glacier’s longer-term average flow speed.Supraglacial lake drainages7, Helheim Glacier hosts multiple supraglacial lakes and water-filled crevasses30  over a four-month melt season34, the basal drainage system receives high meltwater volumes from abundant surface crevasses30. This setting facilitates a well-developed drainage system that allows rapid response to and recovery from a sudden lake-drainage event. The relative insensitivity of net glacier advection to lake drainage observed at Helheim, however, is unlikely to extend to tidewater glaciers that experience lower seasonal meltwater forcing. For example, remote-sensing observations show that sporadic austral summer-melt events (<0.005 m d−1 w.e. for 1-week duration) at multiple Antarctic Peninsula tidewater glaciers coincide with ice-flow accelerations of up to 100% above annual speeds20. These flow accelerations are not followed by sustained periods of reduced velocities and result in net positive glacier advection, likely because water pressure spikes into an inefficient drainage system20, consistent with our model results for simulated winter-season lake drainage at Helheim Glacier. Thus, while these Antarctic Peninsula20 and other, currently colder, High Arctic tidewater glaciers51 may initially undergo a net speed-up as the amount of surface meltwater reaching the bed increases, their flow response to individual melt events may eventually decrease as higher seasonal melt magnitudes are attained as the climate continues to warm52.At Helheim, when lakes drain during the melt season16 to expected changes in surface-melt production on timescales longer than individual melt or lake-drainage events. In particular, we have argued that the Helheim Glacier flow response to lake drainage provides strong evidence that the lake drains into an efficient drainage system. Helheim Glacier’s near-terminus seasonal velocity pattern has, by contrast, been invoked to infer that an inefficient drainage system persists throughout the melt season18. Our observations suggest that near-terminus seasonal velocity patterns at glaciers of this type may not be well correlated with drainage-system efficiency, or the corresponding capacity to accommodate meltwater input with minimal impact on glacier discharge. At fast-flowing tidewater glaciers, where a marine margin and high surface melt rates keep subglacial water pressure high24, observations of seasonal velocity patterns19 may be misinterpreted to indicate inefficient drainage, where, in fact, an efficient system exists and is capable of exporting large volumes of meltwater rapidly. The widely used binary framework for interpreting subglacial drainage system efficiency from seasonal velocity patterns20, though observationally justified for inland ice-sheet regions13, does not explain the full range of behaviors observed at lightly grounded2, fast-flowing tidewater glaciers with high meltwater throughput.Observational and theoretical advances are needed along the surface-melt continuum to test this response-evolution hypothesis and improve projections of global tidewater-glacier response53 to yield position estimates every 15 s23. Here, we eliminate position estimates with unfixed biases, and rotate the timeseries to obtain position estimates in the local along-flow and vertical directions at each station. We use a stochastic filter to estimate a horizontal along-flow velocity 24. Step changes in along-flow velocity are allowed at times of glacial earthquakes, which represent large calving events24  se; and,  \documense; and,  \documenWe calculate the speed of the down-glacier propagation of the velocity pulse by differencing  station .55. Finally, we observe no change in other supraglacial water bodies or the structure of the proglacial ice mélange between sequential satellite images spanning the event  show no anomalously high values in the days leading up to the drainage, suggesting that the velocity pulse is not related to a period of above-average surface melt  . The off-ice AWS recorded hourly temperature and relative humidity and a record of precipitation every 6 h.We use AWS data recorded on˚W) Fig. , and recAn internally logging HOBO water-pressure transducer was deployed within the L1 lake basin  from late June to late August 2009, and recorded measurements of water depth at an hourly sampling rate   is greater than the volume of water in the simulated lake drainage (0.009 km3), which results in lake-drainage inputs being mostly accommodated within the englacial void space. In these cases, a response in Model parameter values are chosen from previous work applying this model to the western margin of the Greenland Ice Sheetmentclass2pt{minimN is the time when We assess parameter-space fitness using two criteria. First, we compare the observed pulse duration for the GPS network to modeled values of eak Fig. . We calceak Fig. .−2 Pa−1 s−1 and −3, changes in Second, we compare the amount of observed vertical uplift at stations IS27–29 following 229 simulations has a pulse-duration misfit of –0.7 h (42 min), with −1 s−1 and −6 (Supplementary Fig. 229 scenario and an Mwinter scenario with equivalent parameter values are shown in Fig. Overall, both pulse duration and uplift are more strongly controlled by sheet permeability than by englacial void fraction. The pulse-duration criterion provides a finer model-space calibration than the uplift criterion. One of the three best-fitting MSupplementary InformationPeer Review File


Antibodies play a critical role in linking the adaptive immune response to the innate immune system. In humans, antibodies are categorized into five classes, IgG, IgM, IgA, IgE, and IgD, based on constant region sequence, structure, and tropism. In serum, IgG is the most abundant antibody, comprising 75% of antibodies in circulation, followed by IgA at 15%, IgM at 10%, and IgD and IgE are the least abundant. All human antibody classes are post-translationally modified by sugars. The resulting glycans take on many divergent structures and can be attached in an N-linked or O-linked manner, and are distinct by antibody class, and by position on each antibody. Many of these glycan structures on antibodies are capped by sialic acid. It is well established that the composition of the N-linked glycans on IgG exert a profound influence on its effector functions. However, recent studies have described the influence of glycans, particularly sialic acid for other antibody classes. Here, we discuss the role of glycosylation, with a focus on terminal sialylation, in the biology and function across all antibody classes. Sialylation has been shown to influence not only IgG, but IgE, IgM, and IgA biology, making it an important and unappreciated regulator of antibody function. Antibodies are critical mediators of to host defense and homeostasis. Further, the therapeutic potential of antibodies has been fundamental in advancing basic immunology and biotechnology. Antibodies have two unique functions that are responsible for their biological function. They can recognize specific structures with high affinity and specificity, and simultaneously engage with cells of the innate immune system. Antibodies can be passively transferred across individuals or species, which gives them therapeutic utility. Indeed, polyclonal IgG from tens of thousands of healthy individuals, intravenous immunoglobulin (IVIG), is administered as IgG replacement therapy to immunocompromised individuals, and as an anti-inflammatory agent to some patients suffering from inflammatory and autoimmune diseases –3. HybriThe monomeric structures of antibodies are composed of two identical heavy chains and two identical light chains connected by disulfide bonds , 6. In hTherapeutic antibodies currently used in the clinic belong only to the IgG class because of their functional characteristics such as long half-life, strong antigen binding, and effector functions such as antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). There is interest in developing therapeutic IgM, IgE, and IgA antibodies to explore novel targets and harness the effector functions of different immune cells. In contrast to IgG antibodies, IgM antibodies do not bind to Fc gamma receptors (FcγRs), but do bind the Fc mu receptor (FcμR) and can trigger potent CDC activity by binding to C1q . CurrentStudies over the last several years have revealed that glycosylation, both N-linked and O-linked, can play profound roles in modifying the effector functions for each antibody class. This ranges from maintaining the structure, tuning effector functions, engaging co-receptors and co-factors, improving their stability, and modifying antigenicity , 15. In Glycosylation of antibodies is initiated in the endoplasmic reticulum (ER) of antibody-producing cells and further trimming and remodeling steps are processed by glycosidases and glycosyltransferases in the Golgi apparatus . N-linkeBased on their composition, glycans are classified into three types: oligomannose, hybrid, and complex –18. Oligcis-Golgi. Next, the addition of galactose is catalyzed by β1,3-galactosyltransferase , an enzyme which also requires the molecular chaperone COSMC for stability and function. O-linked glycans are further extended by the addition of sialic acid to the GalNAc and/or galactose residues by α2,6-sialyltransferase or α2,3-sialyltransferase , respectively  is involved in the recognition of antigens and the fragment crystallizable region (Fc) interacts with FcγRs and other effector proteins, including complement component C1q to mediate effector functions. The Fab region is composed of one variable and one constant domain (CH1) of both the heavy and light chains, while the Fc domain is a homodimer consisting of the heavy chain constant domains (CH2 and CH3). A flexible hinge region connects the Fab and Fc domains.The four subclasses of IgG antibodies are numbered based on their prevalence in the serum: IgG1, IgG2, IgG3, and IgG4 –32. ThesIn a healthy individuals, approximately 10-15% of serum IgG are sialylated, with the majority of those possessing monosialylated glycoforms . Indeed,via mutants D221N/N297A/N563A and D221N/N563A increases sialyation 75% and 44% respectively, resulting in increased binding to Siglec-1 , and these mutants also inhibited demyelination by anti-MOG antibodies in an ex vivo model when multimerized  and Dendritic Cell-Specific ICAM-3 Grabbing Non-Integrin (DC-SIGN) in mice and humans, respectively, were also required , 39, 54.imerized . Anotherimerized .IgG sialylation is emerging as a therapeutic option to treat autoimmune diseases. A phase 1/2 clinical trial (NCT03866577) reported sialylated IVIG offered protection to patients with ITP . ConfirmStreptococcus pneumonia and SARS-CoV-2, and administration of sialylated IgG immune complexes led to an enhanced breadth of IgG responses in a FcϵRII (CD23)-dependent manner , mono-galactosylated (G1F), or di-galactosylated (G2F), and the effector functions of each glycoform can vary significantly. In the serum of a healthy individual, G0F, G1F, and G2F each account for approximately 35%, 35%, and 15% of IgG glycoforms, respectively , 95. A dIn healthy individuals, only a small fraction (10-15%) of antibodies contain bisecting GlcNAc (biGlcNAc) . In the In comparison with other antibodies, IgE is the least abundant antibody in serum with a concentration of 50–100 ng/ml, and a half-life of only two to three days; binding to the high affinity receptor FcϵRI expressed on mast cells extends tissue half-life to three weeks . IgE is IgE is composed of two identical heavy chains and two light chains. Each heavy chain consists of a single variable domain and four constant domains, and the light chain is composed of one variable and one constant domain. IgE is a heavily glycosylated monomeric antibody, with seven N-linked glycosylation sites spread across the four constant domains of the heavy chain. N394 is a conserved glycosylation site with an oligomannose glycan, N383 is unoccupied, and the other five sites  are occupied by complex type biantennary glycans –111. The11 M−1 , equivalent to human N383Q, abolished binding to FcϵRI in ear mast cells and cell-based assays, and similar results were also observed with the enzymatic treatment of mIgE using PNGaseF to remove all N-glycans , and a light chain . In contApart from multimerization, glycosylation sites add further complexity to the IgM structure. IgM is heavily glycosylated in comparison with IgG; it has five N-linked glycosylation sites in the heavy chain (N171 (CH1), N332 (CH2), N395, N402 (both in CH3)), one in the tailpiece (N563), and one on the J chain , 141. ThColucci et al. shows that IgM’s inhibitory effects depend on antibody glycosylation  and kidney failure . AnalysiRecent studies have shown IgA subclasses isolated from serum display different effector functions Figure 2Monoclonal antibody (mAb) based therapeutics are the fastest-growing group of therapeutics for several clinical indications including oncology, autoimmune diseases, inflammatory disease, and bacterial and viral infections. This field is dominated by IgG-based therapeutics. However, IgE has been developed as an immunotherpeautic agent for cancer, and IgA-based therapeutics have been proposed for treatment of bacterial and viral infections, and as anti-inflammatory and anti-tumor agents , 157. Moin vitro glycoengineering are widely used to produce homogeneously glycosylated antibodies  selection produced 60% afucosylated antibodies with a resulting 100-fold increase in ADCC  targeting FUT8 reduced mRNA expression levels to 20%. Coupling this method with  in ADCC .Afucosylated antibodies can also be generated by manipulation of GDP-fucose biosynthetic pathways . GDP-manin vitro glycoengineering, where trimming or extending of antibody glycans is performed using substrates, glycosyltransferases, and glycosidases  and β-1,4 galactosyltransferase-1  to generate the G2F glycoform, which is further modified by treating the product with cytidine 5′ mono-phospho-N-acetyl neuraminic acid (CMP-NANA) and α 2,6 sialyltransferase  to produce the G2S2F glycoform . This mein vivo and in vitro studies have shown that only afucosylated glycoforms increased FcγRIIIA binding and elevated ADCC compared to the G2F and G2S2F glycoforms  mutants D233A and EndoS D233Q, which allowed the addition of N-linked glycans to GlcNAc or core-fucosylated GlcNAc . This isycoforms . Enzymatycoforms . The Endycoforms .Currently, antibody glycoengineering efforts are exclusively focused on the Fc-core due to its role in mediating effector functions , 77, 82,in vitro glycoengineering methods require more time and effort in the purification steps. Another emerging strategy is glycoengineering circulating IgG antibodies in vivo using glycosidases and glycosyltransferases , thereby targeting neuraminidase to IgE-bearing cells . AdminisEndogenous antibody glycosylation is heterogeneous and varies with age and pathophysiological conditions. Harnessing antibody glycosylation is in its infancy, but applications that are engaged in this endeavor include the development of biologic therapeutics and using certain glycosylation patterns as biomarkers. Therapeutic antibodies are a rapidly growing class for the treatment of cancer, autoimmune diseases, infectious diseases, and other conditions. Glycosylation of therapeutic antibodies is very sensitive to cell culture and other production conditions and variations in glycosylation impacts the quality of the product. Therapeutic antibody glycosylation is a critical quality attribute because of its impact on effector functions and half-life. In depth understanding of IgG glycosylation has revealed the role of each glycan in modulating IgG function and resulted in the development of therapeutic afucosylated and sialylated antibodies.In vitro sialylation of IgG markedly enriches sialylated glycoform for desire effector functions. This method has been successfully applied to generate sialylated antibodies to mediate anti-inflammatory activity. Indeed, glycoengineering has applicability across antibody classes is a major advantage. More understanding of the role and regulation of antibody sialylation and glycosylation will likely uncover additional applications for glycoengineering.Glycosylation across antibody classes regulates the structure and function of antibodies. Several studies have shown that sialic acid has divergent functions in antibody classes. For instance, sialylated IgG1 mediates anti-inflammatory activity, sialylated IgE is associated with allergic pathogenicity, sialylated IgA shows anti-viral activity, and sialylated IgM shows inhibitory effects on T-cell proliferation. For most antibody classes, sialylation exerts profound influence over the effector functions. There are multiple, non-mutually exclusive reasons for this, including influencing receptor binding and introducing addition receptors and co-factors. Further studies are required to characterize specific mechanisms of antibody activity and the involvement of additional receptors. Also, the role of sialylation across all antibody subclasses is in need of more examination. RV, SS, and RA wrote the article. All authors contributed to the article and approved the submitted version.This work was supported by NIH grants  to RA.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Winter surface air temperature (Tas) over the Barents–Kara Seas (BKS) and other Arctic regions has experienced rapid warming since the late 1990s that has been linked to the concurring cooling over Eurasia, and these multidecadal trends are attributed partly to internal variability. However, how such variability is generated is unclear. Through analyses of observations and model simulations, we show that sea ice–air two-way interactions amplify multidecadal variability in sea-ice cover, sea surface temperatures (SST) and Tas from the North Atlantic to BKS, and the Atlantic Meridional Overturning Circulation (AMOC) mainly through variations in surface fluxes. When sea ice is fixed in flux calculations, multidecadal variations are reduced substantially (by 20–50%) not only in Arctic Tas, but also in North Atlantic SST and AMOC. The results suggest that sea ice–air interactions are crucial for multidecadal climate variability in both the Arctic and North Atlantic, similar to air-sea interactions for tropical climate. Sea ice–air interactions greatly amplify multidecadal variability in Arctic air temperatures and sea ice cover, North Atlantic sea surface temperatures, and Atlantic meridional overturning circulation through changes in surface fluxes. Model simulations5 show that internal variability can generate similar low-frequency variations in Arctic Tas; and multidecadal variations in poleward energy transport associated with the Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning Circulation (AMOC)6 have been identified as a leading cause of the Arctic Tas multidecadal variations8. It is suggested8 that above-normal oceanic heat transport from the North Atlantic into the Barents–Kara Seas (BKS) and other Arctic regions reduces sea-ice cover (SIC) there, which allows the Arctic Ocean to absorb more energy during the summer but release more heat to the air to cause warmer Tas during the winter. On the other hand, Arctic sea-ice loss10 is found to weaken the AMOC in coupled model simulations12, and sea ice in the subpolar Atlantic and Nordic Seas might play a role in Atlantic multidecadal variability (AMV)14. These findings raise an important question: Can the multidecadal variations in AMV (or AMO) and AMOC, a major source of multidecadal climate variability around the Atlantic and beyond6, and thus the oceanic heat transport itself be influenced by sea-ice changes and variations? Furthermore, it is unclear whether poleward energy transport alone can directly cause large multidecadal variations in Arctic Tas without the participation of sea ice. Answers to these questions have major implications for the formation mechanisms of the AMOC and AMV14 and for our upcoming climate, as models project large sea-ice loss over the BKS and other Arctic regions in the coming decades to centuries17.Superimposed on a rapid warming trend, Arctic surface air temperature (Tas) since the early 20th century also exhibits large multidecadal variations19. Furthermore, the projected sea-ice loss will also weaken and eventually eliminate sea ice–air interactions in the subpolar North Atlantic, which may contribute to the weakening of the AMOC and AMV and their variability that have major impacts on European and global climate20.Here we analyze observations and various model simulations, which exhibit realistic patterns for SIC and Tas multidecadal variability  and both are related to AMV, the multidecadal variations in North Atlantic SST (NASST) , and Labrador Sea-Davis Strait (LSDS) Fig.. These vST) Fig. , with eiST) Fig. . HoweverST) Fig. .2 increase run (1%CO2), with large multidecadal variations for both SIC and Tas over the Arctic regions and for NASST  , which only allow the atmosphere and oceans to affect sea ice but not the other way under a fixed sea-ice cover  for flux calculations only (see Methods), such multidecadal variations in Tas   or 1% per year COMV) Fig. . HoweverTas Fig.  and SIC Tas Fig.  over theuns Fig. . For exauns Fig. . Similaruns Fig. , and suc21. However, the relative roles of internal variability and external forcing in causing the recent Arctic warming trends still require further investigations.The large multidecadal temperature variations induced by the sea ice–air interactions can cause apparent warming or cooling trends over decadal-multidecadal periods over many Arctic regions, such as BKS, where a large decadal warming trend was observed from 1997 to 2009  variations also weaken substantially when fixed SIC is used in calculating surface fluxes over the Arctic and subpolar North Atlantic .These results suggest that the sea ice–air two-way interactions act to amplify not only the multidecadal Tas anomalies  over the Arctic regions, but also Arctic SIC variations and AMV. While we expect the Tas anomalies to weaken in CTL_FixedIce and 1%CO2 run, the sea ice–air interactions would weaken or even disappear completely over these regions. As a result, multidecadal SIC . This result suggests that the locations and magnitudes of multidecadal variations in Arctic SIC and Tas and NASST greatly depend on the locations of ice margins where the sea ice–air coupling is strongest. In other words, if subpolar and Arctic sea ice continues to retreat or melt away, its ability to cause such large multidecadal variations will diminish.As sea ice melts away over the BKS, GNS and LSDS after year ~150 in the 1%COConsistent with the CESM1 results, other climate models also simulate large multidecadal SIC and Tas variability over the GNS, BKS, and LSDS along the ice margins and NASST variability during the historical period (1920–2019), and these multidecadal variations would weaken greatly or almost disappear in the 23rd century when winter SIC is mostly gone over the subpolar North Atlantic, BKS and other Arctic regions  and turbulent heat fluxes   or even reverses   and both SIC and Tas over the LSDS  and LHF  leading the AMOC index by 4–5 years  relative to CTL, respectively, leading to considerably weakened variations in upper-ocean salinity and density  can also provide a positive feedback on SIC through AMOC-induced poleward heat transport. For example, a stronger (weaker) AMOC would transport more (less) heat into the LSDS and other subpolar North Atlantic, thereby further reducing (increasing) SIC there. This may have occurred in CTL_FixedIce for its mean SIC and AMOC strength. The CTL_FixedIce run shows increased mean SIC , not the AMOC-induced heat transport itself, that are largely responsible for the large Tas and SIC multidecadal variations in these regions. Without the sea ice–air interactions, not only the Tas variations would largely disappear, but also the multidecadal variations in SIC and SSTs from the northern North Atlantic to BKS (and thus the poleward oceanic heat transport itself), as well as the AMV and AMOC, would weaken substantially. This is consistent with the important role of sea ice–air interactions for Arctic multidecadal climate variations suggested (but not clearly demonstrated) previously31. Because the AMV-induced SST variations are relatively small compared with the SST and Tas variations over the LSDS, GNS and BKS in observations and the fully coupled CTL run, and a weakened AMOC and AMV cannot really affect winter surface fluxes over these regions due to fixed SIC in the CTL_FixedIce run, the weakened variability in CTL_FixedIce has to come mainly from the lack of the local sea ice–air coupling rather than the weakened AMOC.Our results, summarized in Fig. 30. This suggests that winter sea ice–air interactions in the subpolar North Atlantic are a major mechanism for generating or amplifying multidecadal variability in AMOC and AMV, which is consistent with the significant roles of sea ice for AMOC and AMV suggested previously14. This differs from and complements previous notion that the AMOC’s multidecadal variability is generated by stochastic atmospheric variability32, oceanic planetary wave instability33, thermohaline instability34, and other processes35. Our new findings highlight the need to examine more closely the major impacts of the diminishing sea ice–air interactions in the LSDS, GNS, BKS, and other Arctic regions on Arctic and North Atlantic climate variability and on the AMV and AMOC under GHG-induced global warming, besides the weakening impact on AMOC’s mean strength by Arctic sea-ice loss under increasing GHGs that results from upper ocean warming and freshening in the subpolar North Atlantic27. The long-term weakening of the AMOC under increasing GHGs, which concurs with declining sea ice, is due to the warming and freshening-induced upper ocean stratification, not due to the sea ice–air interactions discussed here, although the sea-ice loss can enhance the upper ocean stratification  and thus contribute to AMOC’s weakening12.The reduced AMOC multidecadal variability under weakened sea ice–air interactions is consistent with the projected future weakening of the AMOC multidecadal variability shown here and previouslyIn contrast to AMOC’s weakening under GHG-induced warming with declining sea ice, for the internally generated decadal-multidecadal variations, reduced sea ice around the Labrador Sea and Davis Strait  increases LHF and thus SSS and ocean density, which enhances the deep water formation and AMOC and thus amplifies the AMV. Apparently, this process plays a smaller role for AMOC’s long-term response to GHG-induced warming than the warming and freshening-induced ocean stratification in climate change simulations with increasing GHGs, leading to an overall weakening of the AMOC under increasing GHGs and declining sea ice, in contrast to a stronger AMOC under lower SIC for internally generated multidecadal variations discussed above.6 could be related to biases in model-simulated mean sea-ice extent over the Labrador Sea and Nordic Seas, as excessive or too little ice cover in these regions could lead to unrealistic sea ice–air interactions, leading to unrealistic SSTs and SSS and thus deep water formation. Further work is needed to examine how the current AMOC strength and its future change are linked to current sea ice biases and future sea-ice loss in the Atlantic sector. Correlations of the decadal-multidecadal variations between AMOC and LSDS SIC reveal considerable differences among different models for both piControl runs , sea surface temperature (SST) and sea ice data from 1950 to 2020 were obtained from the newly released European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5)41 or CMIP642 models  and RCP8.5  simulations from twelve CMIP543 from the National Center for Atmospheric Research with version 4 of the Community Atmosphere Model (CAM4) for its atmospheric component. The CESM1 has been widely used to study the global and Arctic climate and it simulates the global, Arctic and midlatitude mean climate fairly realistically, including the spatial and seasonal patterns of the sea-ice and surface fluxes and their interannual variability45. We ran the CESM1 with grid spacing of 2.5° longitude × ~2.0° latitude for the atmospheric model, and ~1.0° longitude × ~0.5° latitude for the sea-ice and ocean models. Most of the simulations used here (including the fixed-ice setup) have already been described in detail and used by refs. 22, and 45.We used the Community Earth System Model version 1.2.1 (CESM1)2 fixed at 284.7 ppmv and one 235-year simulation with increasing CO2 by 1% per year (1%CO2). The FixedIce 1%CO2 simulation (1%CO2_FixedIce) is described in detail and used by refs. 22, and 45. The FixedIce runs, which include a new 500-year piControl run with fixed SIC (referred to as CTL_FixedIce), use fixed SIC derived from the monthly climatology from the standard piControl run (CTL) only in the coupler for determining the ice and water surface fractions that are used as the weights in calculating the grid-box mean fluxes. The fluxes over the ice or water fraction, as well as the sea-ice cover within the sea-ice model, are not altered by us. Only their weights may be affected by our prescribed SIC . Thus, the use of a fixed SIC in the coupler, albeit unnatural, does not alter any physical laws .We made two types of long-term CESM1 simulations: one type with fully coupled dynamic sea ice  and the other type (FixedIce) with fixed sea ice concentration (SIC) only in the coupler of the model for estimating the water and ice fractions used in calculating grid-box mean values of the exchange fluxes of energy, mass and momentum between the atmosphere and underlying ocean and ice surfaces. For each type, we made one 500-year pre-industrial control (piControl) run with atmospheric COBy fixing the SIC to its climatological value in our fixed-ice runs, instead of using its internal value as in the standard CESM1, we essentially cut off the impact of a variable SIC on the climate. This is similar to using climatological SST instead of time-varying SST from observations in AMIP-type simulations, except in our case we have a fully coupled ocean and ice model to feel the impact from the fixed SIC used in the coupler. One can also think of our fixed-ice setup as a change of ocean surface type (between water and ice) for certain grid boxes and at certain times , similar to changing a land surface type  for studying the effect of the land cover change . While both changes are unnatural and artificial, such modeler-specified surface type changes  are already included in the standard CESM1; thus, we view our prescribed SIC as another modeler-induced perturbation of the climate system for studying its impact on the climate.48; rather, we specifically cut off the impact of sea ice variations on the exchange fluxes between the atmosphere and the ocean/ice surface while allowing the atmosphere and ocean to influence sea ice freely. Thus, we can attribute any differences between the CTL and CTL_FixedIce runs or between the standard 1%CO2 and the FixedIce 1%CO2 runs to a specific physical process, namely the impact of varying sea ice through changes in surface fluxes. That is, all the internal processes (including the impact of AMOC’s advection on North Atlantic surface conditions) are allowed to work in both simulations, except for the sea ice–air two-way interactions that are missing in the FixedIce run. In other words, these differences are triggered by the lack of the two-way ice–air interactions in the FixedIce run. We will refer the sea ice–air (and sea ice-ocean) interactions in the standard CTL and 1%CO2 runs as two-way interactions, while they are referred to as one-way interaction  in the CTL_FixedIce and 1%CO2_FixedIce runs.In our FixedIce runs, we did not attempt to fix sea ice in the ice model, in contrast to previous similar simulations2 forcing48 over the Arctic and North Atlantic regions in individual realizations, which resemble the real world.Here, we focus on the decadal-multidecadal variations, rather than long-term mean changes in response to CO50. Here we defined the forced signal as the time series of the global-mean (60°S–75°N) surface air temperature (GMT) averaged over twelve all-forcing historical and RCP8.5 runs from twelve CMIP5/CMIP6 models used in this study. For reanalysis over 1950–2020 and CMIP5/CMIP6 historical and RCP8.5 runs over 1900–2299, we used linear regression between the CMIP model-averaged GMT (as the x variable) and a given variable (as the y variable) at each grid box to obtain the forced component in variable y, and then subtracted this forced component from the original time series of variable y. The regression coefficient varies spatially and largely accounts for different regional responses to the same forcing49. Similar procedure was also applied to the CESM1 1%CO2 and 1%CO2_FixedIce runs from years 1–235 but using their own GMT time series as the x variable in a 3rd-order polynomial fit in the detrending procedure (instead of the linear fit) to eliminate any nonlinear long-term trend, as Arctic sea-ice concentrations decrease nonlinearly with monotonically increasing CO2. After removing the externally forced signal , the internally generated decadal-multidecadal anomalies were obtained by applying a 10–90-year Lanczos band-pass filter with 21 weights, to filter out any interannual or centennial-multicentennial variability in order to focus on the decadal-multidecadal variability. Note that results are similar using more filter weights  but with larger multidecadal magnitudes and, more importantly, a greater data loss .As our focus is on internally generated decadal-multidecadal variability, we first removed the externally forced signal in all analyzed fields from reanalysis and model simulations based on the method used previouslyWe calculated the standard deviation (SD) of the detrended and filtered DJF-mean anomalies to quantify the decadal-multidecadal variability. Note that the SD may not be sufficient for quantifying the probability density function, which is not our purpose here, as the distribution may not be exactly Gaussian. For the CMIP5/CMIP6 simulations, the SD pattern of the detrended and filtered DJF-mean anomalies was first obtained from each simulation and then averaged over the models (one simulation for each model) with equal weighting to create the multi-model mean pattern.The AMV index was defined as the detrended and filtered DJF-mean SST anomalies averaged over the northern North Atlantic , and the AMOC index was defined as the detrended and filtered DJF-mean anomalies of the Atlantic zonal-mean meridional stream function averaged over the depths of 1000–2000 m and 40°–55°N throughout the study, as these two regions see larger multidecadal variability in SST . Student’s t-tests were applied to test whether the composite differences are statistically significant based on a 5% significance level. The significance of a correlation between two strongly autocorrelated time series (X and Y of length N) was tested on the basis of a resampling method51: we randomly selected a number i between 1 and N to reconstruct a new X that starts from year i to year N and followed by the original X from year 1 to year i–1 immediately, and a similar reshuffling process was applied to Y but with a different random number i. We calculated the correlation between the randomly reshuffled X and Y, and then repeated this resampling procedure for 10,000 times to create a correlation distribution that could occur by chance. For a 5% significance level based on a one-tailed test, the 5th and 95th percentile values of this correlation distribution were chosen as the lower and higher confidence bounds, respectively.We used Supplementary InformationPeer Review File