The attachment of the spike protein in SARS-CoV-2 to host cells and the initiation of viral invasion are two critical processes in the viral infection and transmission in which the presence of unique furin (S1/S2) and TMPRSS2 (S2′) cleavage sites play a pivotal role. We provide a detailed analysis of the impact of the BA.1 Omicron mutations vicinal to these cleavage sites using a novel computational method based on the amino acid–amino acid bond pair unit (AABPU), a specific protein structural unit as a proxy for quantifying the atomic interaction. Our study is focused mainly on the spike region between subdomain 2 (SD2) and the central helix (CH), which contains both S1/S2 and S2’ cleavage sites. Based on ab initio quantum calculations, we have identified several key features related to the electronic structure and bonding of the Omicron mutations that significantly increase the size of the relevant AABPUs and the positive charge. These findings enable us to conjecture on the biological role of Omicron mutations and their specific effects on cleavage sites and identify the principles that can be of some value in analyzing new variants. These Vachinery . The furge site) . Mutatioge site) ,11. Nearge site) . Moreovege site) . TherefoThe S-protein of SARS-CoV-2 is the main target of most therapies ,14,15,16divide and conquer strategy [In this work, we focus on the impact of the Omicron mutations close to the cleavage sites S1/S2 and S2′ between SD2 to FP (SD2-FP) and HR1 to CH (HR1-CH), which contains 10 mutations  see . Most imstrategy ,20. The strategy  to quantdivide and conquer strategy [For large-scale ab initio quantum chemical calculations of a complex biomolecular system, the first step is to design the starting atomistic model. Based on the strategy ,20,21, Sstrategy , which ostrategy . We chosstrategy , respectstrategy ,25, whicstrategy  implemenstrategy . SimilarWe would like to point out two limitations or challenges that could not be avoided during our research. The first is that extremely large-scale ab initio all-atom calculations of the entire S-protein are clearly impossible currently. Therefore, our study is limited to small, manageable size models, such as SD2-FP and HR1-CH, which include Omicron mutations at the S1/S2 and S2′ cleavage sites. Second, any significant conformational changes that could be associated with these ten OV mutations are difficult to assess using these small models and our ab initio approach. It is necessary to include all atoms of the S protein trimer, which is currently impossible to perform in a single QM calculation. Other approaches, such as molecular dynamics (MD) simulation, will be useful to investigate any conformational changes for the entire S-protein, which are beyond the scope of our current study.In this study, we used two well-established density functional theory (DFT)-based packages: the Vienna ab initio Simulations package (VASP)  and the −4 eV; (3) force convergence for ionic steps at −10−2 eV/Å; (4) single k-point sampling at the center of the supercell. The final relaxed structure of the models has been achieved with a total energy difference of less than −0.330 eV or −0.000108 eV per atom and will be used as the input for OLCAO calculations. The initial structures derived from the protein data bank (PDB) are further modelled as discussed in αβρ between any pair atoms α and β in the large supercell of the biomolecule. They are obtained from the ab initio wave functions with atomic basis expansion, calculated quantum mechanically for the large biomolecule. The two OLCAO structural parameters are defined as:A different DFT method, the OLCAO method, developed in-house , is usedIn the above equations, AA) as well as any desired unit. In this study, we have also analyzed partial charge for amino acid amino–acid bond pair unit (AABPU) denoted by PC*. PC* is discussed below in From Equation (3), the PC value for every atom in the model can be calculated. This PC can be further unified for every AA (PC−) and usually scales with the bond length (BL) or the distance of separation between atoms α and β, also depending on the configuration of the vicinal atoms. It should be pointed out that the calculated PC and BO in Equations (1) and (2) are basis-dependent since they are based on the Mulliken scheme [The BO quantifies the strength of the bond between two atoms in the unit of electrons  [In complex biomolecules, one can extend the concept of the bond order (BO), defined for a pair of atoms, and apply it to the interaction between a pair of amino acids (AAs). We refer to this generalized quantifier of molecular interactions as the r (AABP) , definedIn Equation (4), the summations are over all atoms In the Methods section, we have described the previously introduced AABP  as an exThe results for the structure and some pertinent properties of the 10 mutations in the two models containing the cleavage sites are summarized in (1)NN–AA is the dominant interaction, as evidenced by the primary sequence of the S-protein.The largest total AABP is from site 796, close to cleavage site S2′, with only two NL–AAs. D796Y mutation reduces AABP slightly, but it increases size, surface exposure, and positive charge. The largest NN–AABP is from the same site 796 with only two NL–AAs. This confirms that (2)The smallest total AABP comes from site 981, which is relatively far from the S′ cleavage site but near the prefusion-stabilizing two-proline (2P) mutations (K986P and V987P) utilized in Pfizer-BioNTech and Moderna vaccines ,14. Site(3)The 954 site has the largest NL–AABP contribution among all 10 mutations. It is part of the HR1 domain, as are the other two sites, 969 and 981, which have low NL–AABPs. These three Omicron mutations have slightly different interatomic interactions than their WT counterparts, while their size, shape, and PC*s are all changed. We speculate that these mutations may play a role in the binding of HR1 and HR2 domains to enhance the formation of six-helix-bundle (6-HB), which brings the viral lipid and the host lipid membranes close together, resulting in membrane fusion and the initiation of infection . Here, i(4)The smallest NL–AABP is from site 614 in group A ahead of the S1/S2 cleavage site. D614G mutation reduces the number of NL–AAs from 5 to 3 but results in a shift in charge distribution toward a more positively charged state, which could enhance the susceptibility of protease cleavage at the S1/S2 junction and/or promote the up conformation of the S-protein, as previously reported ,42,43.(5)The largest contribution from HB to total AABP is from site 954, while the smallest HB contribution is from sites 614 and 655. This attests to the importance of the contribution of HB to the overall bonding network.(6)The role of the PC* distributions is obvious from five mutations, D614G, N679K, P681H, D796Y, and N969K. They exhibit a significantly changed, more positive, PC*. Importantly, the mutation at the 681 site, which is adjacent to the furin cleavage site, has been reported to play a significant function in the cleavage process ,11,20,44These observations clearly indicate that the changes in the total AABP values and their non-local components depend on the nature of the substitution, interatomic interactions, location with respect to the cleavage sites, and the HB contribution. In To better illustrate the size and shape due to mutation, we replot the cases of the N856K and Q954H mutations in more detail in The total and partial density of states (TDOS and PDOS) for SD2-FP and HR1-CH in both cases have been shown in We would like to focus on the HBs with BL above 1.56 Å and the data are shown as star symbols. The strongest HB has a BO of 0.12 e- at 1.56 Å. Mutation can either enhance or weaken the HB strengths. Even though HBs are relatively weak, they are ubiquitous and constitute a significant component of interatomic bonding in biomolecules see b. FigureIn AA of the key AA at each site. To easily distinguish them, we used two PC symbols: PC* for the whole unit of AABPU and PCAA for only one unique AA site. Interestingly, the D614G, N679K, N764K, D796Y, N856K, and N969K OV mutations significantly shift their PCAAs to positive, whereas H655Y, Q954H, and L981F have minor or negligible changes. P681H exhibits a distinct behavior when comparing The trend toward positive charges of OV mutations is emphasized further in Protein–protein interactions (PPIs) are essential for many biological processes, so they have to be accurately identified not only at the molecular level but also at the AA and atomic levels. In fact, the AA–AA pairing governs these PPIs as well as protein folding and assembly. In this paper, we strongly advocate the concept of AABPU, based on the AABP interaction proxy, as a special structural unit to describe and quantify atomistic level resolution of biomolecular structures and interactions. AABPU includes many key parameters, such as interatomic interaction, PC, size, and shape. AABPU may be useful for studying biological networks ranging from AA–AA pairing to 3D protein structure and protein–protein networks. It provides new insights into the geometry alterations and interatomic interactions of different S-protein domains. This concept could also be extended to investigate the mutational effects on other S-protein domains and S-protein protomers not covered in this study. The cleavage efficiency of S-protein at the furin-cleavage S1/S2 site increases the chances that the newly generated virus will be able to fuse rapidly with the host membrane. In this regard, mutations in the Alpha and Delta variants′ S1/S2 junction region have been shown to improve the cleavage efficiency at this site ,11. SpecThe cell–cell fusion also requires the S′ site. Protease activity can occur either by TMPRSS2 at the plasma membrane or by cathepsins in the endosomes . TMPRSS2Together, the roles of the cleavage sites of Omicron are still unclear and requires further investigation. The main goal of this work is to speculate on the connection between Omicron mutations at proximal cleavage sites and the cleavability and fusogenicity based on AABPU. It is clear from our study that the Omicron mutations induce more positive partial charges in the charge distribution of S-protein. This change may play a function in controlling proteolytic cleavage, render S-protein more sensitive to low-pH induced conformational changes, promote an adaptation that utilizes the low-pH endosomal entry pathway, and/or boost virus entrance in the lower pH environment of the upper airway . Unlike the Delta variant, the high transmissibility of OV may not be due to its efficient cleavability, but rather to the immune evasion and the strong binding affinity between RBD and ACE2 ,46,47,48Another future direction that has not been addressed above is how to use the calculated data on AABPU in Machine Learning (ML) applications, which is described in ab-initio can complement molecular dynamics (MD). Even though there is a size limitation in ab-initio calculation, its pseudopotential can provide a valuable alternative to analyze complicated biological systems in comparison to a priori force fields of MD simulation. In our past calculation, PC obtained from ab-initio calculation for the RBD–ACE2 interface complex were fed into the MD force field for prediction of electrostatic interaction [Finally, we would like to point out that eraction .In summary, we analyzed both WT and OV models for SD2-FP and HR1-CH regions, including the cleavage sites S1/S2 and S2′ of S-protein. We developed a quantitative scheme and methods for rapid assessment of the effect of 10 mutations in OV using the novel concept of AABPU. Based on AABPU, we have further analyzed its interatomic bonding, volume, surface area, and PC*. We have conjectured a possible reason for the fast infection rate in the Omicron variant based on this detailed analysis. This ab initio study provides a road map for computational research on new variants of concern in the SARS-CoV-2 virus.


Neither the level of RAE nor ESS seems to affect the perceived competence of the players, regardless of gender. The results of this study highlight the presence of RAE and ESS in Canadian minor ice hockey, especially at the elite level, but indicate that they do not affect the self-perception of ice hockey players. Additional research on these concepts is needed to obtain a complete picture of their potential impact on sports development.The relative age effect (RAE) and early sport specialization (ESS) have been of growing interest in the sports world, especially in ice hockey, because of their potential adverse effects. However, little is known about their distribution within each level of play in Canadian minor ice hockey, or whether they influence young people’s perceived competence, a variable of interest in long-term sports development. A sample of elite adolescent players (N = 204) and a sample of recreational and competitive players (N = 404) were used to measure these constructs, and chi-square tabulations were conducted to compare their distribution. Our results reveal that RAE (χ The benefits of sustained physical activity on the health of individuals, regardless of age, have long been known and promoted . In CanaYouth sport has greatly changed over the past 20 years to become a hyper-organized and competitive environment primarily driven by adults . An incrAnother organizational factor observed in multiple sports for decades is the relative age effect (RAE), which can be defined as the age difference between individuals in the same group . To brinAs important as RAE or ESS may be in terms of their direct impacts on the development of young athletes, they may also affect another important construct in sports practice: perceived competence. Perceived competence refers to an individual’s perception of their capacities in a certain performance area . DevelopThis study has two objectives. The first is to measure the prevalence of RAE and ESS within a selection of elite adolescent teams compared with its prevalence in non-elite teams. The second is to establish the effects of RAE and ESS on players’ perceived competence within an elite environment. These objectives are the basis for five hypotheses.Hypothesis 1 (H1).RAE will be present in higher proportions in the elite selection compared with the non-elite teams.Hypothesis 2 (H2).ESS will be present in the same proportions in the elite selection and the non-elite teams.Hypothesis 3 (H3).ESS and RAE will be present in the same proportions in both genders.Hypothesis 4 (H4).Positive perceived competence will not be present in the same proportion based on level of ESS.Hypothesis 5 (H5).Positive perceived competence will not be present in the same proportion based on birth quartiles.For this study, 1 primary sample was used to measure the perceived competence, ESS, and RAE of elite ice hockey players, and 2 secondary samples were used to compare these with non-elite ice hockey players. Data for the main sample were collected at a Team Québec selection camp for men (U15) and women (U17) in summer 2021. During this camp, players came to the arena, participated in physical tests and were then evaluated on the ice 2 times a day for 4 days for a chance to make the provincial team. They were asked to complete a questionnaire measuring their perceived competence and ESS during a free period of about 1 h on the second day to ensure they were in a good mental condition. During this collection, 89 males and 115 females were surveyed in compliance with the ethics committee of the researchers’ institution. Players came from all corners of Quebec, all spoke French, and a binary definition of gender was used, as it currently is in the federation. This was the last step in a year-long selection process during which the number of candidates fell from about 204 in the provisional teams to about 45–50 players per gender at the end of this camp. Thus, these players were the best of their cohort, at least according to those involved in the selection process. The second sample had already been used in a research project by the authors of this article. Data for the sample used as a comparison for the prevalence of ESS and RAE in lower-level ice hockey  were collected in a previous project, and the details surrounding the collection are discussed in this article [The same measurement method for ESS was employed for both data collections . To calcWe measured the prevalence of RAE using the same method as in a previous article . Each bi2(154) = 204.160, p = 0.004, RMSEA = 0.021, CFI = 0.997, TLI = 0.993) [I win my “one-on-one” battles”), ice hockey IQ , offensive skills , skating abilities , resilience , and leadership . A composite score of all dimensions was then calculated in addition to an overall competence score.We measured perceptual competence in ice hockey specifically using a recently validated questionnaire that showed robust psychometrics values (χ= 0.993) . The quep < 0.05) indicated a different distribution between the different variables studied, and the interpretation of Cramer’s V was as follows: >0 = very weak, >0.05 = weak, >0.10 = moderate, >0.15 = strong and >0.20 = very strong [Chi-square cross tabulations were complketed, and Cramer’s V was calculated to assess effect size and interpreted using Volker’s recommendations  and in ay strong . We alsop < 0.05) and playing level (p < 0.001), with a moderate size effect (V > 0.10) in both cases. These results confirm Hypothesis 1 and partially confirm Hypothesis 3. We also note that the elite players show different distributions regarding RAE; more players are born in Q1 and fewer in Q4 at this playing level compared with other playing levels and the Canadian population of this age.p > 0.05). However, a substantial difference in magnitude (p < 0.001) exists in ESS levels based on the playing level of the ice hockey players. Specifically, there are fewer competitive players in the high ESS group and more in the low ESS group than at the other two playing levels. Elites also have a significantly larger proportion of highly specialized athletes and a lower proportion of athletes with low ESS. These results refute Hypothesis 2, but partially confirm Hypothesis 3.p < 0.001).This study, which was conducted using two samples of adolescent ice hockey players, aimed to describe the prevalence of ESS and RAE at several levels of play and relate them to perceived ice hockey skill, a variable that impacts sports development. We can now review the five hypotheses put forward earlier. First, Hypothesis 1 was confirmed because the distribution of the RAE differed between elite male and female players. It also differed between those playing at other playing levels and in the Canadian population of the same age. The presence of RAE is hardly surprising, as the concept has been part of Canadian ice hockey for over 40 years . Our datNext, we disproved Hypothesis 2, which predicted that the proportion of specialized players would be the same, regardless of playing level. However, the opposite was observed: each playing level had a different ESS distribution than the others. Compared with competitive and recreational players, elite players seem to have a significantly smaller proportion of low or no specialized players and a larger proportion of highly specialized players. Competitive players have many more non-specialized or less specialized players and fewer highly specialized players than other playing levels. At the recreational level, patterns of specialization fall between those observed at the elite and competitive levels. As Quebec ice hockey already demonstrated , competiRegarding SSE, this study’s results partly confirm Hypothesis 3 as well, because no significant difference was found between male and female players. Previous work suggests that girls are more prone to experience SSE, but this may be largely because most studies deal with early developing individual sports such as synchronized swimming or gymnastics . The perThe last two hypotheses addressed perceived competence in ice hockey and its relationship with the two constructs under study, RAE and ESS. Contrary to what one might have expected from the literature, the proportion of field hockey players with a positive perception of their skills did not change according to ESS or RAE levels. Indeed, previous work established a link, albeit a relatively weak one, between perception of endurance and ESS , while aA strength of this work is the number of concerns it addresses relative to ESS and RAE research. Although these issues have attracted increasing attention in the last 20 years, there is still an absence of data regarding their representation in a particular team sport such as ice hockey at all youth playing levels ,15. FurtRAE has been present for at least a hundred years in practically all sports, and it affects both men and women at an equivalent level of competition . This isIn conclusion, this study explores the distribution of the relative age effect as well as early sports specialization within Canadian minor ice hockey in function of the different playing levels and the two genders. It confirms that these two issues are present in Canadian elite ice hockey, especially at the elite level, but do not affect players’ perception of competence. Although this research adds to the present ESS and RAE literature, it is purely descriptive and somewhat limited by its cross-sectional design. Further research is needed to investigate the additional impacts they may have on the athletic development and long-term physical activity of these young athletes. Awareness of the harmful effects of ESS and RAE must continue in youth sport, especially at the elite level.


P for interactions > 0.05). Our study indicates that an elevated plasma cystatin C concentration is associated with an increased risk of all-cause, cardiovascular and cancer mortality both men and women among the middle-aged and elderly individuals.We investigated the associations of plasma cystatin C with all-cause and cause-specific mortality risk and identified potential modifying factors affecting these associations in middle-aged and elderly people (≥ 50 years). This community-based prospective cohort study included 13,913 individuals aged ≥ 50 years from the Health and Retirement Study. Cox proportional hazard models were used to estimate the associations between cystatin C concentrations and the risk of all-cause and cardiovascular and cancer mortality after adjustment for sociodemographic characteristics, lifestyle factors, self-reported medical history, and other potential confounding factors. During a total of 71,988 person-years of follow-up , 1893 all-cause deaths were documented, including 714 cardiovascular-related and 406 cancer-related deaths. The comparisons of the groups with the highest (quartile 4) and lowest (quartile 1) cystatin C concentrations revealed that the adjusted hazard ratios and 95% confidence intervals were 1.92 (1.62–2.28) for all-cause mortality, 1.98 (1.48–2.65) for cardiovascular mortality, and 1.62 (1.13–2.32) for cancer mortality. The associations of cystatin C concentrations with all-cause, cardiovascular and cancer mortality did not differ substantially when participants were stratified by sex, age, BMI, current smoking status, current alcohol consumption, and regular exercise (all  Renal function is usually determined by the estimated glomerular filtration rate (eGFR), serum creatinine, blood urine nitrogen, or calculated creatinine clearance. The GFR is considered the best global index of renal function, but direct measurement of the GFR is complex. Creatinine has been applied to estimate the GFR. However, the eGFR is insensitive for the detection of moderate renal dysfunction and is greatly influenced by factors6, such as age, sex, and muscle mass. Therefore, the early detection of renal-related biomarkers for mild-to-moderate renal injury with an appropriate intervention is likely to promote health and increase life expectancy.Chronic kidney disease (CKD)7, is considered to be superior to creatinine as a measure of renal function9. Numerous studies have investigated the association of cystatin C levels with the risk of all-cause and cardiovascular mortality12. For instance, elevated cystatin C concentrations were suggested to be associated with a higher risk of all-cause mortality in many10 but not all studies13. CKD has also been shown to contribute to cancer morbidity and mortality16. Nonetheless, evidence regarding the relationship between cystatin C concentration and cancer mortality is very limited18. In addition, whether the associations of cystatin C concentrations with mortality vary by potential modifying factors, such as gender and age group, remain controversial20, which may have important implications for the application of cystatin C.Cystatin C, which is a cysteine protease inhibitor produced by nucleated cellsIn the current study, using nationally representative community-based cohort data from the Health and Retirement Study (HRS), we aimed to examine the associations of cystatin C concentrations with all-cause and cause-specific mortality and to identify potential modifying factors affecting these associations among middle-aged and older individuals (≥ 50 years).22. Briefly, the participants were surveyed biennially beginning in 1992; five additional waves of participants were added in phases between 1994 and 2014. Starting in 2006, an enhanced face-to-face survey that included biomarker assessments was implemented in the HRS (http://hrsonline.isr.umich.edu). For this study, we included participants aged ≥ 50 years between 2006 and 2014. Participants with missing cystatin C concentration data or cancer at baseline were excluded. In total, 13,913 participants (5841 men and 8073 women) were eligible. A flowchart of participant enrollment is shown in Figure These study data were obtained from the HRS, which is a nationally representative community-based prospective cohort study of middle-aged and elderly Americans. Details regarding the study design and participants have been previously reported3. The measurement of cystatin C concentrations was performed with a standard ELISA procedure at the University of Vermont in 2008 and University of Washington in 2012 was assayed from dried blood spots3. To account for dried blood spots assay and laboratory variability in cystatin C values, HRS data are released with National Health and Nutrition Examination Survey equivalent assay values23, which we used for our analyses. Cystatin C concentrations were classified as belonging to quartile 1 , quartile 2 , quartile 3 , or quartile 4 .Blood samples were obtained by pricking a participant’s finger with a sterile lancet after cleansing the finger with an alcohol swab22. Causes of death were categorized according to the International Classification of Diseases 10 (ICD 10). ICD codes I00-I99 and C00-C97 were categorized as cardiovascular mortality and cancer mortality, respectively24. We calculated the follow-up time from the baseline survey until the date of death or December 31, 2014, whichever occurred first.Deaths were measured in each cohort through data from the National Death Index (NDI) and by exit interviews with family members. Previous HRS analyses indicated a rate of death validation of ~ 99%25. The following covariates were included: sociodemographic factors ; lifestyle factors ; laboratory measures , and hemoglobin A1c [HbA1c] levels); the 8-question Center for Epidemiologic Studies Depression Scale (CES-D 8) score; self-reported prevalent health conditions; and limitations in any of the following 5 activities of daily living (ADLs): getting in and out of bed, bathing, walking across a room, dressing, and eating. We classified current alcohol consumption as drinking (one or more drinks per day) or not drinking. BMI was calculated by weight in kilograms (kg) divided by the square of height in meters (m2). All covariate data were obtained from the structured questionnaire and biochemical tests conducted at baseline (available at the HRS website: http://hrsonline.isr.umich.edu).Potential confounding factors included in this study were selected based on previous studies26. Baseline tables were generated using descriptive statistics (the mean and standard deviation [SD] or the number and percentage [%]) stratified by cystatin C quartiles. Kaplan–Meier curves were generated for the cystatin C quartiles, and log-rank tests were conducted to compare different groups. Cox proportional hazards models were performed to estimate hazard ratios (HRs) with 95% confidence intervals (95% CIs) for mortality according to the cystatin C quartiles (with the lowest quartile [Q1] as the reference group). We also evaluated the HRs of mortality per 1 mg/L increase in the cystatin C concentration. The Cox proportional hazards assumptions were assessed with Schoenfeld residual plots27, and no violation of the assumptions was observed. The baseline model (Model 1) tested the association between cystatin C concentrations and mortality and was adjusted for age and sex, while the multivariable-adjusted model (Model 2) further controlled for the following: ethnicity ; household income ; education level ; BMI (continuous variable); regular exercise (yes or no); smoking status (current smoker or nonsmoker); alcohol consumption (current drinker or nondrinker); HDL-C level (continuous variable); TC level (continuous variable); hsCRP level (continuous variable); HbA1c level (continuous variable); prevalent health conditions ; CES-D 8 score (continuous variable); and limitations in ADLs (yes or no).To correct for missing values and reduce the potential for inferential bias, we imputed missing data for the covariates using multiple imputation methods2] or nonobese [≤ 30 kg/m2]) and regular exercise (yes or no) were measured by computing likelihood ratios. To determine the robustness of the results, we performed sensitivity analyses, including (1) excluding participants who died during the first 2 years of follow-up, (2) stratification by tertiles and quintiles of cystatin C concentration (3) additionally adjusted for measurement of cystatin C concentrations laboratory (the University of Vermont and University of Washington). All analyses were conducted with R software version 4.0.5 , and a two-tailed P value < 0.05 was considered statistically significant.Effect modifications of the associations between each 1 mg/L increase in cystatin C concentration and mortality by sex (men or women), age (< 65 or ≥ 65 years), current smoking status (smoker or nonsmoker), current alcohol consumption (drinker or nondrinker), BMI , 1893 deaths were documented, including 714 from cardiovascular diseases and 406 from cancer. Rates of all-cause, cardiovascular and cancer mortality increased in association with increases in cystatin C concentrations assessed as quartiles Fig. . Additio2)  regarding the associations of cystatin C concentrations with all-cause, cardiovascular and cancer mortality .28. Some possible explanations for the positive association of cystatin C with all-cause and cardiovascular mortality have been proposed. First, cystatin C has been suggested to be a promising measure of kidney function, while kidney dysfunction is an acknowledged risk factor for all-cause and cardiovascular mortality. Second, cystatin C has also been shown to be a marker of inflammation29. Furthermore, a higher cystatin C concentration was also associated with incident prediabetes30, hypertension31, coronary heart disease33, myocardial infarction8, and stroke34, all of which could contribute to increased mortality. With regard to cancer mortality, there is very limited evidence examining the association of cystatin C with cancer mortality18. Our study indicated that a higher cystatin C concentration is associated with an increased risk of cancer mortality. The result is consistent with previous studies showing a potential association between markers of CKD and a higher risk of incidence and death from overall and site-specific cancer38. Cystatin C is rarely used to measure renal function in actual practice, which may be due to other unknown or unmeasured factors contributing to this effect, and this issue should be addressed in future studies. Overall, monitoring cystatin C concentration may help identify individuals who are at higher risk of all-cause, cardiovascular and cancer mortality.Our results confirm the findings of previous studies that indicated positive associations between plasma cystatin C concentrations and the risks of all-cause and cardiovascular mortality25. In contrast, Toft and colleagues13 found that cystatin C concentrations were positively associated with in a female population but not in a male population. We speculate that the difference in these findings may be explained by different study populations, diverse cutoff levels, various controlled confounders, or insufficient statistical power. Our study also showed that the association of cystatin C concentrations and mortality appeared to be similar in participants aged < 65 years and those aged ≥ 65 years, consistent with previous studies12. Moreover, the associations of cystatin C concentrations with all-cause, cardiovascular and cancer mortality did not differ substantially when participants were stratified by BMI, current smoking status, current alcohol consumption, and regular exercise. These findings imply that cystatin C may be a useful marker for all-cause, cardiovascular and cancer mortality risk estimation, which does not differ by subgroups of sex, age, BMI, current smoking status, current alcohol consumption, and regular exercise.Our result is consistent with previous studies demonstrating that positive associations between cystatin C and all-cause mortality in both males and females8. Finally, although we carefully adjusted for several confounders, such as sociodemographic characteristics and lifestyle factors, the potential for residual confounding factors, such as other unmeasured or unknown covariates, likely remained.The major strengths of the current study are the community-based, prospective design, the large sample of middle-aged and older participants, the adjustments for several identified and potential confounders, and the robust findings of the subgroup and sensitivity analyses. However, our study has several potential limitations that should be considered. First, the measurements of plasma cystatin C concentrations were only single baseline examinations, which may not accurately reflect the long-term plasma cystatin C concentrations of the study participants. Repeated plasma cystatin C measurements might reduce the variability; however, repeated longitudinal measurements of cystatin C concentrations in large-scale community-based cohort studies are impractical and expensive. Second, we cannot be confirming whether the strong association of cystatin C with the mortality is due solely to its relationship with kidney function. Cystatin C may have potential toxic effects that also help to the strength of its association with mortalityIn conclusion, this study indicates that an elevated plasma cystatin C concentration is associated with the risk of all-cause, cardiovascular and cancer mortality both men and women among the middle-aged and elderly individuals. The results demonstrate the potential value of cystatin C as a biomarker for risk prediction in middle-aged and older people.Supplementary Information.


Argonaute (Ago) proteins play a central role in post-transcriptional gene regulation through RNA interference (RNAi). Agos bind small RNAs (sRNAs) including small interfering RNAs (siRNAs) and microRNAs (miRNAs) to form the functional core of the RNA-induced silencing complex (RISC). The sRNA is used as a guide to target mRNAs containing either partially or fully complementary sequences, ultimately leading to downregulation of the corresponding proteins. It was previously shown that the kinase CK1α phosphorylates a cluster of residues in the eukaryotic insertion (EI) of Ago, leading to the alleviation of miRNA-mediated repression through an undetermined mechanism. We show that binding of miRNA-loaded human Ago2 to target RNA with complementarity to the seed and 3’ supplementary regions of the miRNA primes the EI for hierarchical phosphorylation by CK1α. The added negative charges electrostatically promote target release, freeing Ago to seek out additional targets once it is dephosphorylated. The high conservation of potential phosphosites in the EI suggests that such a regulatory strategy may be a shared mechanism for regulating miRNA-mediated repression. Proteins are the chemical ‘workhorses’ of the cell: some help maintain a cell’s shape or structure, while others carry out the chemical reactions necessary for life. Organisms therefore need to keep tight control over the production of proteins in their cells, so that the right amount of each protein is made at the right time, in the right place.Instructions for making new proteins are encoded in a type of molecule called messenger RNA. Each messenger RNA contains the instructions for one protein, which are then ‘read’ and carried out by special cellular machinery called ribosomes. The cell can control how much protein it produces by regulating both the levels of different messenger RNA and the amount of protein ribosomes are allowed to make from those instructions.The main way to regulate the levels of messenger RNA is through their transcription from the genome. However, this needs fine tuning. Cells can do this in a highly specific way using molecules called microRNAs. A microRNA works by directing a protein called Argonaute to the messenger RNA that it targets. Once Argonaute arrives, it can call in additional ‘helper proteins’ to shut down, or reduce, protein production from that messenger RNA, or alternatively to break down the messenger RNA altogether.Cells can use an enzyme called CK1α to attach bulky chemical groups onto a specific part of the Argonaute protein, in a reaction termed phosphorylation. The ability to carry out this reaction (and to reverse it) also seems to be important for microRNAs to do their job properly, but why has remained unknown. Bibel et al. wanted to determine what triggers CK1α to phosphorylate Argonaute, and how this affects interactions between microRNAs, Argonaute and their target messenger RNAs.A series of ‘test tube’ experiments looked at the interaction between purified CK1α and Argonaute under different conditions. These demonstrated that CK1α could only carry out its phosphorylation reaction when Argonaute was already interacting with a microRNA and its corresponding messenger RNA. Further measurements revealed that phosphorylation of Argonaute made it detach from the messenger RNA more quickly. This suggests that phosphorylation might be a way to let Argonaute seek out new messenger RNAs after blocking protein production at its first ‘target’.These results shed new light on a fundamental mechanism that cells use to control protein production. Bibel et al. propose that this mechanism may be shared across many different species and could one day help guide the development of new medical therapies based on microRNAs. RNAi isKoff . It alsoKoff . More coKoff .Ago proteins are part of a larger Ago superfamily, which includes Piwi- and Wago-clade proteins. Members of the superfamily show high structural conservation throughout evolution and have four main structural domains: N, PAZ, MID, and PIWI . The MIDAlthough the core architecture is conserved among all Ago proteins, they are subject to multiple types of post-translational modification, including ubiquitylation, PARylation, and phosphorylation  . For exdecreased EI phosphorylation led to an increase in target RNA association with the Ago-guide complex in cell culture, as measured by qt-RT-PCR of immunoprecipitated hAgo2, whereas increased EI phosphorylation or its mimicking had the opposite effect   . Previouctively) . This suctively) . To detectively) . This guctively) , suggestctively) . We did ctively) . Howeverctively) . No phosctively) , confirmctively) . This isctively) .Because of the observed effects of target binding, we decided to further investigate what features of the target RNA affect EI phosphorylation. In order to determine the minimum target length sufficient to trigger it, we performed in vitro phosphorylation assays with a series of ZT1 target RNAs, starting with an 8 nt target complementary to the seed region and extending the 5’ end (corresponding to the 3’ end of the guide) up to a target length of 30 nt. No significant phosphorylation was detectable up to a target length of 13 nt, however, phosphorylation increased dramatically once the target length reached 14 nt, with further increases in phosphorylation observed at longer lengths . These dIt is likely that 14 nt represents the shortest length of target capable of establishing stable pairing in the supplementary region. Therefore, to further investigate the importance of supplementary pairing, we tested phosphorylation of hAgo2-guide-traget ternary complexes with varying amounts of complementarity to the guide miRNA. Length-matched (30 nt) target with complementarity to the seed region alone was incapable of stimulating robust hAgo2 phosphorylation . HoweverThese findings may be explained by the unique conformations Ago adopts to accommodate varying amounts of base pairing. Binding to short targets is known to lead to a shift in hAgo2’s PAZ domain , which cThe EI itself is unresolved in all Ago structures determined to date. In order to obtain structural information regarding conformational changes that the EI might be undergoing during these events, we turned to hydrogen-deuterium exchange mass spectrometry (HDX-MS), which measures conformational dynamics and solvent accessibility by analyzing the exchange of hydrogens for deuterium over time. The measured deuterium uptake corresponds primarily to exchange from backbone amides, and thus regions with stable secondary structure have high levels of protection (low deuterium uptake) whereas more flexible and/or exposed regions are less protected and thus have higher deuterium uptake . SamplesSeven peptides covering the EI were detected in all datasets, the shortest being 811–842 and 812–842. These peptides were consistent with each other, as would be expected given the almost complete overlap between the two. Importantly, they showed no statistically significant differences between the G-bound and the GT-bound at any timepoint (p < 0.01) . The G-bThe lack of differences between the RF and G-bound states within the EI is in stark contrast to the large differences observed outside of the EI. The most substantial protection upon guide-binding occurred in regions known to interact directly with the miRNA, such as the 5’ binding pocket . Howevern-x-x-S/T*-x where ‘p’ indicates a phosphorylated site, * indicates the site to be phosphorylated, and ‘x’ indicates any amino acid ino acid . Thus, pino acid , howeverino acid .In order to determine which EI residues get phosphorylated in vitro, we addressed this ambiguity by performing in vitro phosphorylation assays on hAgo2 constructs in which we prevented phosphorylation at specific sites by mutating each potentially phosphorylatable serine or threonine to alanine, individually or in various combinations. Since we had previously determined that target binding is required for phosphorylation , we carrTo examine the possibility that CK1α-mediated phosphorylation of S828 may serve a priming role for additional EI phosphorylations, we first tried an S828 phosphomimetic (S828E). This failed to prime for further phosphorylation , howeverTo determine whether pS831 is subsequently capable of priming for further phosphorylation, we created ‘triple o’ mutants: 824o;828o;831o [Ago2]; 828o;831o;834o [Ago2]; and 828o;830o;831o [Ago2]. We saw an increase in phosphorylation in all three cases, suggesting that, after the second phosphorylation at S831, the EI phosphorylation pattern can follow different routes and is more heterogenous than the initial S828 followed by S831 phosphorylation pattern . Individafter target binding, we conducted target release assays in which we phosphorylated hAgo2 bound to the guide RNA and radiolabeled target RNA (ZT1). We then used a time course filter-binding assay to measure release after dilution into a 250-fold excess of unlabeled target. CK1α-mediated phosphorylation of wt hAgo2 significantly increased offk by ~7.5-fold, and thus decreased the half-life of the RISC/target complex  with target RNA. Because, as shown above, phosphorylation can only be achieved  complex . These e complex . The ‘tr complex , suggestIt was proposed that the negative charge of the added phosphates could clash with the negative charge of the target RNA backbone, leading to loosening of hAgo2 binding to the target by charge repulsion . To testmiRNA-mediated gene repression is a widespread mode of regulation in metazoans. Most human genes contain at least one evolutionarily conserved miRNA target site, and many genes are under regulation by multiple families of miRNAs. Each miRNA family, in turn, typically has hundreds of targets; the 90 most broadly conserved miRNA families have over 400 conserved targets each . At the This may help explain discrepancies between the in vitro and in vivo effects of 3’ supplementary pairing. In vitro, 3’ supplementary pairing can significantly enhance the stability of Ago/target interactions, with 3–4 contiguous canonical base pairs in the supplementary region increasing affinity over 20-fold for some miRNA/target pairs . This efafter repression is established, freeing RISC to repress additional targets, would allow for the most efficient use of supplementary pairing for such discriminatory purposes.However, as we have shown in this study, supplementary pairing triggers phosphorylation of the EI, which could offset added binding affinity. Therefore, in vivo, the overall effects of supplementary pairing on target repression would appear to be less pronounced. This would be consistent with supplementary pairing functioning primarily to distinguish between target sites for the same miRNAs. Phosphorylation of targets with supplementary pairing CK1α phosphorylation likely occurs in a distributive manner . BecauseRecently, a study linked a variety of germline single amino acid mutations in hAgo2 to RNAi deficits and neurological symptoms . These mThere are multiple examples in the literature where substrate tertiary structure has been shown to be critical for promoting CK1-mediated phosphorylation. For example, T-antigen is phosphorylated by CK1 at non-canonical sites at its N-terminus in a manner that is dependent on proper folding and an intact C-terminus . SimilarAs we show in this study, target binding triggers the CK1α-mediated phosphorylation of S828 . HoweverThe need for target binding could explain findings from previously reported in vitro phosphorylation assays testing CK1α’s ability to phosphorylate peptide substrates spanning hAgo2’s EI region . Golden C. elegans hAgo2 homolog ALG-1 (S992) to alanine led to severe developmental defects similar to those seen when mutating all EI phosphorylation sites to alanine , which in turn recruits deadenylation complexes (PAN2-PAN3 and/or CCR4-NOT) and decapping complexes to promote target degradation . Previou-/- cells, indicating that the phosphorylation cycling process itself is important, not merely the presence or absence of phosphorylation.Because Ago must be dephosphorylated by PP6 before it can optimally repress additional targets, phosphorylation also has the potential to serve as a global regulatory measure. Knocking out PP6 in human cell lines led to a global decrease in RISC binding to mRNA . Under nonly S828 can be phosphorylated in our in vitro system without priming phosphorylation, and that this phosphorylation only occurs after binding to targets meeting certain criteria reveal novel structural and sequence determinants of highly specific CK1α-mediated phosphorylation. We therefore propose that target binding serves as a means for regulating CK1α-mediated phosphorylation of Ago, which, in turn, regulates RISC turnover and thus miRNA-mediated mRNA repression. The presence of multiple phosphorylation sites with decreasing target affinity may merely reflect the biophysical requirements for establishing sufficient negative charge to repel the target RNA. However, it might also provide a way for a cell to titrate the Ago/target affinity and/or to serve as a ‘checkpoint’ in order to ensure that targets aren’t spuriously released. Our work doesn’t address the temporal dynamics of phosphorylation, dephosphorylation, and repression. However, given the previous in vivo findings showing widespread regulatory defects with both hyper- and hypophosphorylation  but not among siRNA-specialized Agos (e.g. dmAgo2), and our work provides a mechanistic explanation. With siRNA, slicing of the fully complementary target promotes its release by destabilizing the guide/target duplex  . Aliquots were frozen at –80°C, 2 mg/mL, 10% glycerol. hAgo1 and hAgo3 were prepared in a similar manner.Recombinant hAgo2 was prepared as previously described , with thHuman CK1α (isoform 1) was expressed in Sf9 insect cells with an N-terminal StrepII_SUMO fusion tag using the MultiBac system. Following Strep-Tactin affinity chromatography , the tag was removed using TEV protease and CK1α was further purified by cation exchange chromatography  and size exclusion chromatography  . Aliquots were frozen at –80°C, 0.5 mg/mL, 50% glycerol.E. coli. It was induced with 1 mM IPTG and expressed overnight at 18°C in TB media. It was then purified by Ni-NTA affinity chromatography (Qiagen)  followed by size exclusion chromatography (Superdex75) . Activity was verified using a colorimetric pNPP assay and aliquots were frozen at –80°C in 50% glycerol, 2.7 mg/mL.λPP was cloned into a pET28 vector with an N-terminal His tag and expressed in BL21(DE3) 2, 2.5 mM DTT, 0.5 mM Na3VO4). CK1α was then added and reactions were incubated at 37°C for 90 min at which time they were quenched with a stop buffer containing 25 mM EDTA and 25 mM unlabeled ATP. Aliquots were spotted on phosphocellulose paper, washed three times (5 min each) in 75 mM phosphoric acid, one time in acetone, and then air-dried and measured using liquid scintillation counting. Moles of phosphate per aliquot were calculated by comparison to spotted (unwashed) reaction buffer. This value was divided by the number of moles of Ago in the aliquot to determine the mole phosphorylation detected per mole Ago.In vitro phosphorylation was carried out with hAgo2:guide:target at 1 μM and CK1α at 20 nM. Prior to adding CK1, Ago was incubated 1:1 with guide RNA for 30 min, followed by incubation with target RNA (1:1:1 molar ratio) for 30 min, both steps were carried at room temperature (RT). The complex was then mixed with kinase reaction buffer , 25 mM Tris pH 7.4, 10 mM MgCl32P-labeled target RNA (50–100 pM). After 1 hr incubation to come to equilibrium, protein (including RNA-bound protein) and free RNA were separated by slot blot. Results were obtained through phosphorimaging  and quantified using GeneTools (SynGene). Kinetic parameters were fit using GraphPad Prism (Version 9), one site-specific binding.Equilibrium target-binding assays were performed using a double-membrane filter-binding setup with a slot blot vacuum filtration device (Bio-Rad SF) containing an upper nitrocellulose membrane (to capture protein and protein/RNA complexes) and a lower nylon membrane (to capture free RNA) as previously described. Briefly, hAgo2 and guide were mixed at a 1:1 molar ratio and incubated at RT for 30 min, then serially diluted in 10 mM Tris pH 8, 100 mM NaCl, 5 mM DTT, and added to 5’ For competition target-binding assays, hAgo2 was mixed 1:1 with miR-200 and allowed to bind for 30 min at RT. This RISC complex was then added to a serial dilution mixture of radiolabeled ZT1 (30 nt), which was held constant at 50 pM, and unlabeled competitor target which was 1:3 serially diluted, starting at 750 nM for the seed-only complementary target (ZT1.som) and 500 nM for all others. The mixture was allowed to equilibrate for 1 hr at RT before separating protein from free RNA using a filter-binding assay as above. Data was quantified in GeneTools (SynGene) and Ki was fit using GraphPad Prism.32P-labeled miR-200 (25 pM). After 1 hr incubation to reach equilibrium, protein and protein-RNA complex were separated from free RNA by slot blot and quantified as above.hAgo2 and guide were mixed at a 1:1 molar ratio and incubated at RT for 60 min, then serially diluted in 10 mM Tris pH 8, 100 mM NaCl, 5 mM DTT, and added to 5’ 32P-labeled ZT1 target RNA (30 nt) was added and incubated for a further 30 min. In vitro phosphorylation was then carried out with 500 nM hAgo2/guide, 200 nM labeled ZT1, 300 nM unlabeled ZT1, and 20 nM CK1α for 60 min at 37°C followed by 30 min at 10°C. An aliquot was then diluted with a high concentration of unlabeled target to a final concentration of 5 nM hAgo2, 2 nM labeled ZT1, 500 nM unlabeled ZT1, in either standard buffer  or high salt buffer  at 10°C. An initial sample was taken immediately after mixing (at 15 s) and set as the ‘0’ timepoint. Aliquots were taken out to 30 min and proportions bound were compared to the proportion bound in the ‘0’ sample. At each timepoint, free and protein-bound RNA were separated via slot blot, followed by autoradiography and quantification using GeneTools. Data were fit to a One-Phase Exponential Decay equation using GraphPad Prism and plotted ± SE. Reactions carried out in triplicate.hAgo2 was mixed 1:1 with miR-200 guide RNA and incubated for 30 min at RT. A mix of unlabeled and 2, and 10% glycerol. hAgo2 protein was loaded with at miR-200 at a 1:1 ratio and incubated for 30 min at at RT. 20 μL slicing reactions were initiated by mixing 5’ 32P-labeled target RNA  in the reaction buffer with 8 nM loaded hAgo2:miR200 complex. After 60 min, the reaction quenched in formamide loading buffer and incubated at 95°C for 5 min. The radiolabeled slicing products were separated using urea PAGE, visualized by phosphorimaging, and quantified with GeneTools.Slicer assays were carried out as previously described with slight modifications . Briefly2O buffer  for 0, 0.5, 1, 2, or 5 min. The exchange was quenched with an equal volume of quench solution .HDX-MS was carried out by the HDX Core of the University of California, San Diego Biomolecular/Proteomics Mass Spectrometry Facility (UCSD BPMSF) (NIH shared instrumentation grant S10 OD016234). Hydrogen/deuterium exchange mass spectrometry (HDX-MS) was performed using a Waters Synapt G2Si equipped with nanoACQUITY UPLC system with H/DX technology and a LEAP autosampler. Individual proteins were purified by size exclusion chromatography in 10 mM Tris pH 8, 200 mM KCl, 5 mM DTT, 10% glycerol immediately prior to analysis. The final concentrations of proteins in each sample were 5 μM. For each deuteration time, 4 μL complex was equilibrated to 25°C for 5 min and then mixed with 56 μL DE, ESI + mode instead.The quenched sample (50 μL) was injected into the sample loop, followed by digestion on an in-line pepsin column  at 15°C. The resulting peptides were captured on a BEH C18 Vanguard pre-column, separated by analytical chromatography  using a 7–85% acetonitrile gradient in 0.1% formic acid over 7.5 min, and electrosprayed into the Waters SYNAPT G2Si quadrupole time-of-flight mass spectrometer. The mass spectrometer was set to collect data in the Mobility, ESI + mode; mass acquisition range of 200–2000 (m/z); scan time 0.4 s. Continuous lock mass correction was accomplished with infusion of leuenkephalin (m/z = 556.277) every 30 s . For peptide identification, the mass spectrometer was set to collect data in MSE analyses of 10 μM solution of protein in , and data were analyzed using PLGS 3.0 (Waters Corporation). Peptide masses were identified using a minimum number of 250 ion counts for low energy peptides and 50 ion counts for their fragment ions. The peptides identified in PLGS were then analyzed in DynamX 3.0 (Waters Corporation) and, for displaying uptake, the deuterium uptake was corrected for back-exchange as previously described :pUAAUACUGCCUGGUAAUGAUGA-3’ validation of miR-200 ZT1 sites: https://www.nature.com/articles/ncb17225’-ZT1 (miR-200-binding site corresponds to position 1243–1250 of ZEB1 3’UTR):ACAUUAGCUGAUUUUUACCUAUCAGUAUUA-3'5'-ACAUUAGCUCAUCAUUACCUAUCAGUAUUA-3'ZT1e3c (extended 3’ complementarity): 5'-ACAUUAGCUCAUCAUUACCAGGCAGUAUUA-3'ZT1s (sliceable (fully complementary)): 5'-AAAAAAAAAAAAAAAAAAAAAACAGUAUUA-3'ZT1som (seed-only match): 5'-AUUUUUACCUAUCAGUAUUA-3'ZT1.20: 5'-UUACCUAUCAGUAUUA-3'ZT1.16: 5'-ACCUAUCAGUAUUA-3'ZT1.14: 5'-CCUAUCAGUAUUA-3'ZT1.13: 5'-CUAUCAGUAUUA-3'ZT1.12: 5'-UAUCAGUAUUA-3'ZT1.11: 5'-AUCAGUAUUA-3'ZT1.10: 5'- This paper provides well documented and solid biochemical data to show how phosphorylation of hAGO2 modulates RISC-target mRNA binding dynamics. The results explain how hAGO2 is released from a target allowing a limited pool of Ago proteins to target a very large repertoire of mRNA molecules. The new data and discussion support the key claims of the manuscript. public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Pablo A Manavella as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Kevin Struhl as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Andrea Ventura (Reviewer #2); Jeremy Dufourt (Reviewer #3).Thank you for submitting your article "Target binding triggers hierarchical phosphorylation of human Argonaute-2 to promote target release" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:As you will see from the reviewer's comments we are all positive about your manuscript and the suggestions are, from my point of view, helpful and simple. I do believe you will be able to address all of them without problems. Still, if you consider that some of them are not feasible in a reasonable amount of time or that are unlikely to yield a meaningful outcome don't hesitate to point it.You will also find some requests for in vivo experiments. We discussed this point with the reviewers and even when we agreed that these experiments would be a great addition to the paper we are conscious that it may demand way too much time and effort. If you feel that you can contribute with some experiments in this direction we encourage you to add them but those experiments are not essential for the paper acceptance.Reviewer #1 (Recommendations for the authors):The results in figure 2 are quite interesting. Overall, you suggest that EI phosphorylation favour charge repulsion to release the miRNA/target association; however, this is especially true for some pairing degree with neither an extensive pairing nor a low pairing being the ideal. Can you discuss this better? Why do you think miRNA/target resolution depend on EI phosphorylation in some case more than others? Wouldn't all the cases need a negative charge to release the interaction? How do you think extensive pairing is resolved?Figure 5, what happens if you only mutate S828 to Alanine, leaving the rest open? Can you prevent EI phosphorylation in vitro, and ideally in vivo, by mutating only S828? Even when it may be a little bit hard to test, it would be interesting to see whether S828 priming occurs in vivo.Would it be possible to reanalyze data from ref 41 and see whether there is a bias toward the extent of miRNA/target pairing? Based on your hypothesis and discussion, one could expect more targets with 3' supplemental pairing in non-phosphorylated AGO2 mutants than in WT? If the reasoning of your discussion paragraph starting at Line 389 is correct, the in vivo results in this mutant should mimic better the in vitro data showing an increased affinity for more extensive pairing.The main open question here is the in vivo dynamics. When does the EI phosphorylation initiate and when the miRNA/target association is resolved? one would expect this is not immediate as the main RISC function is to suppress gene translation. Thus, quick phosphorylation and resolution wouldn't be ideal. Studying this aspect is beyond the scope of this paper and will need extensive analysis, but it would be nice if you discuss this point further.Out of personal curiosity, do you know how is EI Serine conservation in plant' AGOs (AGO1)? miRNA/target pairing is extensive in plants, so I would expect that this mechanism is not conserved? There is no need to discuss this on the manuscript.Reviewer #2 (Recommendations for the authors):I have a few suggestions for the authors:a) The use of purified components in an in vitro system is certainly a strength of this work, but it is also a limitation, since in vivo additional factors are known to interact with Argonaute (GW182 proteins as well as other effectors) and these interactions could significantly affect Ago phosphorylation. It would be perhaps useful to confirm the hyerarchical phosphorylation of Ago protein in a cell based experiment, for example by measuring phosphorylation of ectopically expressed Ago2 harboring various combinations of mutations in the 5 phosphorylation sites. The model predicts that the S828A and, to lesser extent, the S831A mutant should be resistant to phosphorylation, while mutants in the other three sites should still be at least partially phosphorylated.b) In the introduction (line 136), the authors mention ChIP-seq as the method used By Golden and colleagues to show reduced coverage of individual targets in the absence of phosphorylation. I think in the Golden paper the method used was eCLIP, not ChIP-seq.c) While this manuscript conclusively shows that S828 is the first residue to be phosphorylated by CK1 in a hierarchical fashion using full length Ago, a key role for S828 and S831 had been already suggested by Golden and colleagues using in vitro phosphorylation of various peptides corresponding to the EI region of Ago2 . In fact, Golden et al., wrote: "Unphosphorylated peptide was a poor substrate for CSNK1A1 under these conditions, suggesting that initial phosphorylation of this region is facilitated by contextual features present in full-length AGO2. pS824 only weakly stimulated further phosphorylation. Prior phosphorylation of S828, however, robustly promoted phosphorylation of S831 (but not T830), while pS831 efficiently primed phosphorylation of S834. Taken together with our earlier data demonstrating a critical role for S828 in phosphorylation of AGO2 in cells , these findings support a model whereby initial phosphorylation of S828, and potentially S824, stimulates efficient hierarchical phosphorylation of S831 followed by S834, rendering AGO2 incompetent for target binding until returned to an active state by ANKRD52-PPP6C phosphatase activity." It would be important to mention this in the discussion.Reviewer #3 (Recommendations for the authors):Line 165 Please explain why you choose miR-200bFigure 1c why mutating all residue at the same time and not testing simple mutation and combination? this experiment is done in figure 5 and could maybe be positioned in figure 1.Is hAgo2 plus guide phosphorylation in the expected background or it could reflect a first low round of phosphorylation? Maybe by doing the same experiments with Ago1 to 3 the authors could see if just hAgo with miRNA are phosphorylated even if its low?In Figure 2 is it possible to quantify remaining not bound mRNA to reinforce the idea that 14nt are the shortest length to establish base pairing?The HDX-MS experiments show an important point: the target do not protect the EI site which was the simplest explanation. The results are also really interesting as it is suspected that free Argonaute are unstable but it’s one beautiful demonstration I saw in this direction.Is it possible to test if phosphorylated hAgo2 loaded and with its target have a mRNA release decrease during a time course in presence of PP6, this would be demonstrated that when the phosphatase remove phosphorylation we observed a decreased of Koff. Reviewer #1 (Recommendations for the authors):The results in figure 2 are quite interesting. Overall, you suggest that EI phosphorylation favour charge repulsion to release the miRNA/target association; however, this is especially true for some pairing degree with neither an extensive pairing nor a low pairing being the ideal. Can you discuss this better? Why do you think miRNA/target resolution depend on EI phosphorylation in some case more than others? Wouldn't all the cases need a negative charge to release the interaction? How do you think extensive pairing is resolved?1. Targets with extensive 3’ pairing, but bulged central regions, can induce TDMD in vivo, which resolves the interaction through degradation of the RISC complex. We have added further discussion of this in the Discussion section .Figure 2 describes the ability of various targets to induce phosphorylation, rather than the ability of phosphorylation to promote target release. As we show in the figure, different targets promote phosphorylation to different extents. This would confound target release rate measurements, and therefore we were unable to compare the relative contributions of phosphorylation to target release between targets. However, because phosphorylation must occur to have any effect, targets that fail to induce robust phosphorylation would be expected to rely less on phosphorylation to aid in miRNA/target resolution and more on alternative mechanisms. Consistent with this, targets that failed to induce such phosphorylation either have less need for affinity-lowering  or have alternative mechanisms to promote target release. In the latter category, targets with full complementarity can be sliced by hAgo2, which has been shown to enhance target release63,64, and therefore these targets would not need phosphorylation-promoted release to resolve RISC/target interactions.”“However, we found that extending 3’ pairing in the absence of central pairing also decreased EI phosphorylation . Such targets can induce TDMD in vivo, which resolves the interaction through degradation of the RISC complexFigure 5, what happens if you only mutate S828 to Alanine, leaving the rest open? Can you prevent EI phosphorylation in vitro, and ideally in vivo, by mutating only S828? Even when it may be a little bit hard to test, it would be interesting to see whether S828 priming occurs in vivo.We see no appreciable phosphorylation if S828 is mutated to alanine, even if all other sites are left open. We have added a figure showing this . Although the in vivo experiments suggested are outside the scope of the current study, results from Golden et al., and Huberdeau et al., are consistent with S828 priming in vivo and we have added the following language to the Discussion section .2. The central importance of S828 is also reflected in functional data from in vivo experiments. Huberdeau et al., found that mutating the corresponding serine in the C. elegans hAgo2 homolog ALG-1 (S992) to alanine led to severe developmental defects similar to those seen when mutating all EI phosphorylation sites to alanine3. Furthermore, Golden et. al reported that expression of hAgo2(S828A), but not wt hAgo2, was able to rescue repression of a miR-19 EGFP reporter in ANKRD52-deficient cells. Phosphorylation of S828 thus appears to serve as a key gatekeeper regulating further phosphorylation and its consequent functional effects, implying its regulation would be critical. We now show that this gatekeeper is directly regulated by target binding.”“This was further supported by their finding that S828A mutation, but not a single A mutation at any of the other phosphorylatable residues in the EI, eliminated detectable phosphorylation of hAgo2 in HCT116 cells lacking expression of ANKRD52, a regulatory subunit of PP6Would it be possible to reanalyze data from ref 41 and see whether there is a bias toward the extent of miRNA/target pairing? Based on your hypothesis and discussion, one could expect more targets with 3' supplemental pairing in non-phosphorylated AGO2 mutants than in WT? If the reasoning of your discussion paragraph starting at Line 389 is correct, the in vivo results in this mutant should mimic better the in vitro data showing an increased affinity for more extensive pairing.4.We thank the reviewer for their suggestion. We looked into the possibility of doing this analysis. Unfortunately, the processed eCLIP data in Golden et al., only yields target peaks (corresponding to hundreds or thousands of nucleotides) rather than precise miRNA binding sites. In that way, the eCLIP data are useful for comparisons at the mRNA level but not for miRNA/site-specific analyses. The eCLIP peaks typically encompass multiple predicted miRNA-binding sites, any of which could be bound. Additionally, the dataset lacks the identity of the corresponding bound miRNAs. We need this information for the requested analyses because members of the same miRNA family can differ in their extent of supplemental pairing. In order to directly compare wt- and 5XA-bound targets at the site level we would need miRNA/target site-specific data, such as CLEAR-CLIP results linking the Ago-bound miRNA to the target site to which it is bound The main open question here is the in vivo dynamics. When does the EI phosphorylation initiate and when the miRNA/target association is resolved? one would expect this is not immediate as the main RISC function is to suppress gene translation. Thus, quick phosphorylation and resolution wouldn't be ideal. Studying this aspect is beyond the scope of this paper and will need extensive analysis, but it would be nice if you discuss this point further.We agree with the reviewer on this point and have added further discussion of this in the Discussion section to clarify our thinking. Additionally, we have now performed additional experiments showing that GW182 binding does not impact Ago phosphorylation, supporting our model that phosphorylation occurs after repression is established. These are described below in response to reviewer #2.Out of personal curiosity, do you know how is EI Serine conservation in plant' AGOs (AGO1)? miRNA/target pairing is extensive in plants, so I would expect that this mechanism is not conserved? There is no need to discuss this on the manuscript.Arabidopsis thaliana Ago proteins MAGO1 and MAGO2 are subject to phosphorylation in vivo, and are hypophosphorylated upon heat stress . We do not know at this juncture what the role is for EI phosphorylation in Arabidopsis. Although the responsible kinase was not identified in that study, another putative Arabadopsis CK1 target, the transcription factor DREB2A, gets stabilized upon heat stress due to decreased phosphorylation.We thank the reviewer for their interest. Serine-rich EI’s are conserved in plant Ago’s. However, the sequences and lengths of the EI vary. Interestingly, it was recently discovered that the EI’s of the Phosphorylation normally occurs on DREB2A, leading to DREB2A degradation. But heat stress inhibits the phosphorylation, allowing DREB2A to accumulate and regulate stress response genes . Perhaps CK1α-mediated phosphorylation of hAgo could be reduced upon various stresses. However, this is only speculative. So far, although EI phosphorylation has been found to occur in a variety of organisms, the responsible kinase has only been identified in humans.Reviewer #2 (Recommendations for the authors):I have a few suggestions for the authors:a) The use of purified components in an in vitro system is certainly a strength of this work, but it is also a limitation, since in vivo additional factors are known to interact with Argonaute (GW182 proteins as well as other effectors) and these interactions could significantly affect Ago phosphorylation.2,3. However, it remains a possibility that GW182 (or other recruited factors) could influence phosphorylation. Because GW182 plays a pivotal role in establishing target mRNA repression, binding directly to Ago and recruiting additional downstream effectors, we investigated the potential impact of GW182 binding on hAgo2 phosphorylation. We measured hAgo2 phosphorylation in the presence and absence of the GW182 Ago Binding Domain (GW ABD) (residues 455-860 of human TNRC6A)5 and found that GW ABD binding had no qualitatively detectable impact on endpoint phosphorylation of hAgo2 by CK1α. These results are compatible with our model that phosphorylation likely occurs after repression is established, thereby allowing effective repression without sequestering Ago longer than necessary. For these experiments, we had to use qualitative SDS-PAGE analysis of phosphorylation products instead of our quantitative scintillation counting method used in the experiments reported in our manuscript because we discovered that CK1α phosphorylates the GW ABD as well, confounding the measurement of total phosphorylation. Interestingly, although Ago phosphorylation was not impacted by GW ABD, GW ABD phosphorylation was greatly enhanced by the presence of hAgo2 (both wt and 5XA). As the GW ABD can bind up to 3 Ago molecules5, we suspect that, in these assays, hAgo2 is localizing CK1α to GW182, leading to its phosphorylation. However, we do not know where on GW this phosphorylation is occurring, what effects it might have on GW function, or whether it is physiologically relevant. Because of the issue of quantification, and since proper investigation of these questions requires further experiments that are outside the scope of the current paper, we have chosen not to include these preliminary results in the manuscript. However, we are providing them here to show that the immediate downstream factor associating with Ago does not interfere with Ago’s phosphorylation by CK1α, supporting the theory that Ago phosphorylation can occur after repression is established.We appreciate the reviewer’s suggestion and agree that it is important to keep in mind the effects additional factors, such as GW182, might have on Ago phosphorylation. Previous studies have found that EI phosphorylation does not impact hAgo2/GW182 interactionIt would be perhaps useful to confirm the hyerarchical phosphorylation of Ago protein in a cell based experiment, for example by measuring phosphorylation of ectopically expressed Ago2 harboring various combinations of mutations in the 5 phosphorylation sites. The model predicts that the S828A and, to lesser extent, the S831A mutant should be resistant to phosphorylation, while mutants in the other three sites should still be at least partially phosphorylated.This concern was also raised by reviewer #1. We now address this issue and added a new figure 5d. Please see our response to reviewer #1 above.b) In the introduction (line 136), the authors mention ChIP-seq as the method used By Golden and colleagues to show reduced coverage of individual targets in the absence of phosphorylation. I think in the Golden paper the method used was eCLIP, not ChIP-seq.We thank the reviewer for catching this typo! We were indeed referring to eCLIP experiments and we have corrected the text.c) While this manuscript conclusively shows that S828 is the first residue to be phosphorylated by CK1 in a hierarchical fashion using full length Ago, a key role for S828 and S831 had been already suggested by Golden and colleagues using in vitro phosphorylation of various peptides corresponding to the EI region of Ago2 . In fact, Golden et al., wrote: "Unphosphorylated peptide was a poor substrate for CSNK1A1 under these conditions, suggesting that initial phosphorylation of this region is facilitated by contextual features present in full-length AGO2. pS824 only weakly stimulated further phosphorylation. Prior phosphorylation of S828, however, robustly promoted phosphorylation of S831 (but not T830), while pS831 efficiently primed phosphorylation of S834. Taken together with our earlier data demonstrating a critical role for S828 in phosphorylation of AGO2 in cells , these findings support a model whereby initial phosphorylation of S828, and potentially S824, stimulates efficient hierarchical phosphorylation of S831 followed by S834, rendering AGO2 incompetent for target binding until returned to an active state by ANKRD52-PPP6C phosphatase activity." It would be important to mention this in the discussion.This is indeed a good point and in order to underscore the previous findings and clarify the added findings in this work, we have now added the following paragraphs in the Discussion section contextualizing our findings :2. Golden et al., reported that unphosphorylated EI peptide could not be phosphorylated by recombinant CK1α, leading them to propose that contextual features in the full-length hAgo2 were required in order to make S828 a suitable CK1α substrate. Our work shows that it is not only full-length hAgo2 that is required, but rather hAgo2 bound to a guide and a target RNA with seed and supplemental region pairing.“The need for target-binding could explain findings from previously reported in-vitro phosphorylation assays testing CK1α’s ability to phosphorylated peptide substrates spanning hAgo2’s EI region2. Golden et al., showed that peptides phosphorylated at S828 were able to be phosphorylated at S831 and those phosphorylated at S831 were able to be phosphorylated at S834. They suggested that pS828 primes for hierarchical phosphorylation of the EI at S831 and S834, consistent with our experiments with full-length hAgo2. This was further supported by their finding that S828A mutation, but not a single A mutation at any of the other phosphorylatable residues in the EI, eliminated detectable phosphorylation of hAgo2 in HCT116 cells lacking expression of ANKRD52, a regulatory subunit of PP62. The central importance of S828 is also reflected in functional data from in vivo experiments. Huberdeau et al. found that mutating the corresponding serine in the C. elegans hAgo2 homolog ALG-1 (S992) to alanine led to severe developmental defects similar to those seen when mutating all EI phosphorylation sites to alanine3. Furthermore, Golden et al., reported that expression of hAgo2(S828A), but not wt hAgo2, was able to rescue repression of a miR-19 EGFP reporter in ANKRD52-deficient cells. Phosphorylation of S828 thus appears to serve as a key gatekeeper regulating further phosphorylation and its consequent functional effects, implying its regulation would be critical. We now show that this gatekeeper is directly regulated by target-binding.”All the in vitro phosphorylation experiments that have been reported point to a central importance of S828. Our finding that S828 phosphorylation is required for subsequent hierarchical phosphorylation by CK1α in full-length hAgo2  is consistent with previous experiments using phosphorylated peptide substratesReviewer #3 (Recommendations for the authors):Line 165 Please explain why you choose miR-200bWe have added the following :2, suggesting it was sensitive to EI phosphorylation in vivo. It was also chosen because of its functional relevance in helping regulate epithelial to mesenchymal transitions6.”“This guide/target combination was chosen because the target’s genomic location was identified as bound to 5XA but not wild-type hAgo2 in previous eCLIP experimentsFigure 1c why mutating all residue at the same time and not testing simple mutation and combination? this experiment is done in figure 5 and could maybe be positioned in figure 1.We understand the logic behind this suggestion, however, the aim of Figure 1c is to show that target binding triggers CK1α-mediated phosphorylation and that this phosphorylation is occurring in the eukaryotic insertion, hence the use of the 5XA mutant in this situation. As we do not discuss the precise locations of the phosphorylations until later in the paper, we have left the experiments showing the effects of single A mutations and combinations in Figure 5. We have also added a figure showing the effects of each single A mutation .Is hAgo2 plus guide phosphorylation in the expected background or it could reflect a first low round of phosphorylation? Maybe by doing the same experiments with Ago1 to 3 the authors could see if just hAgo with miRNA are phosphorylated even if its low?The levels of phosphorylation in guide-bound Ago1/2/3 are within the expected background accounting for artifacts of the experimental system . These experiments are performed to measure endpoint or near-endpoint phosphorylation, after 90 minutes, so multiple rounds of phosphorylation are possible. However, the phosphorylation with guide-bound alone does not exceed the expected background even with the long incubation time.In Figure 2 is it possible to quantify remaining not bound mRNA to reinforce the idea that 14nt are the shortest length to establish base pairing?We don’t believe one needs 14-nt of target to establish base-pairing per se. As we show in Figure 2 —figure supplement 1, the affinity for a target of 13-nt in length is very similar to that of 14-nt long. However, the differences in the amounts of phosphorylation triggered by these targets are striking. Therefore, the requirements for phosphorylation shown in Figure 2 go beyond simple base pairing.The HDX-MS experiments show an important point: the target do not protect the EI site which was the simplest explanation. The results are also really interesting as it is suspected that free Argonaute are unstable but it’s one beautiful demonstration I saw in this direction.Is it possible to test if phosphorylated hAgo2 loaded and with its target have a mRNA release decrease during a time course in presence of PP6, this would be demonstrated that when the phosphatase remove phosphorylation we observed a decreased of Koff.We thank the reviewer for this suggestion. The proposed experiments would be difficult to interpret conclusively, unfortunately, because the timescales of dephosphorylation and target release would be confounding one another. Furthermore, in vivo, PP6 functions as a heterotrimer and although 2 of the subunits were identified in Golden et al.,’s CRISPR screen (ANKRD52 and PPP6C), the identity or identities of the third subunit involved remain unknown.


Recent studies have shown that IgE glycosylation significantly impacts the ability of IgE to bind to its high-affinity receptor FcεRI and exert effector functions. We have recently demonstrated that immunizing mice with IgE in a complex with an allergen leads to a protective, glycan-dependent anti-IgE response. However, to what extent the glycans on IgE determine the induction of those antibodies and how they facilitate serum clearance is unclear.Therefore, we investigated the role of glycan-specific anti-IgE IgG autoantibodies in regulating serum IgE levels and preventing systemic anaphylaxis by passive immunization.Mice were immunized using glycosylated or deglycosylated IgE-allergen-immune complexes (ICs) to induce anti-IgE IgG antibodies. The anti-IgE IgG antibodies were purified and used for passive immunization.Glycosylated IgE-ICs induced a significantly higher anti-IgE IgG response and more IgG-secreting plasma cells than deglycosylated IgE-ICs. Passive immunization of IgE-sensitized mice with purified anti-IgE IgG increased the clearance of IgE and prevented systemic anaphylaxis upon allergen challenge. Anti-IgE IgG purified from the serum of mice immunized with deglycosylated IgE-ICs, led to a significantly reduced elimination and protection, confirming that the IgE glycans themselves are the primary drivers of the protectivity induced by the IgE-immune complexes.IgE glycosylation is essential for a robust anti-IgE IgG response and might be an important regulator of serum IgE levels. IgE and its effector cells, such as basophils and mast cells, help eradicate pathogens, like parasites and helminths, and degrading venoms . HoweverIgE’s shorter serum half-life of 2-2.5 days, compared to serum IgG, which has a half-life of roughly three weeks in humans, is a crucial aspect of IgE control . In addiIn mice, the equivalent of N394 is N384. Consistent with human findings, IgE mutated or lacking oligomannose could not elicit an anaphylactic reaction in a passive cutaneous anaphylaxis mouse model . In addiInterestingly, the body can produce anti-IgE IgG antibodies itself. Atopic and healthy individuals express endogenous anti-IgE IgG antibodies, which may define another way of IgE regulation , 25. AltThe production of recombinant Fel d 1 and monoclonal Fel d 1-specific IgE F127 antibody used in these experiments have been described previously .Briefly, the sequence encoding a fusion of chains 1 and 2 of Fel d 1 spaced by a 15aa-linker (GGGGS) 3 was linked to a histidine tag and then cloned into the plasmid pET42 . Recombinant Fel d 1 was generated at 20°C for 20 hours after the plasmid was transformed into Escherichia coli C25661 . A Ni2+ affinity column purified the supernatant after the cells had been sonicated. Size-exclusion chromatography was used with a Superdex 75 column  to separate monomers and dimers from multimers.The monoclonal IgE F127 was produced in CHO cells  and purified by affinity chromatography over a protein L or protein G Sepharose column , respectively.®  and purified by immunoaffinity using a CaptureSelect XP C‐tag column (Thermo Fisher).The anti-Ara h2 IgE sequence (P12P3D08) was obtained from Croote et al. . It was Roasted peanut extract (Ara R) was prepared according to the protocol of Koppelman et al. Antibodies were deglycosylated using PNGase F deglycosylation kit (Thermo Fisher) under native conditions according to the supplier’s protocol, except that the protein was deglycosylated at 37°C and overnight. Zeba™ Spin Desalting Columns  were used to purify the antibodies. PNGase F treated IgE is from now on called IgE(PNG).® serum tubes  or in PBS containing 10mM EDTA . Blood was collected from naïve mice and from IgE injected mice 30 minutes, 2 hours, and 24 hours after injection.Mice were kept at the central animal facility  and used for an experiment between the ages of 8 and 12 weeks. BALB/c mice were purchased from Envigo . The Swiss Federal Veterinary Office approved all protocols used to treat experimental animals. Prof. J. Ravetch kindly provided CD23-/- mice. FcγRIIb -/- and Fcγ common chain KO (FcγR KO) mice  were purchased at 6 weeks and bred in our facility. All animals were acclimatized to the facility for at least one week. IgE-Fel d 1 complexes were formed for immunizations by incubating 25μg IgE and 5μg Fel d 1 for 1h at 37°C dissolved in 100μl PBS before intravenous (i.v.) injection into mice. To analyze IgE clearance, mice were injected with or without 25μg anti-IgE IgG or anti-IgE(PNG) IgG 1h before receiving 25μg IgE intravenously. Blood from tail veins was collected using Microtainer6 cells from BM and spleen from triple immunized mice were seeded per well. The plate was incubated at 37°C (5% CO2) for 20h. Next, goat anti-mouse IgG biotin primary Ab  diluted in PBS-0.1% BSA (1:1000) was incubated for 2h at RT. Then, streptavidin-550 (Mabtech) diluted in PBS-0.1% BSA (1:200) was added for 1h at RT. Next, fluorescence enhancer-II (Mabtech) was added for 15 min at RT. The plate was dried at RT overnight. Finally, the plate was read at 550nm using the Fluorospot reader (Mabtech IRIS).Fluorospot assay was performed according to the manufacturer’s protocol. The Fluorospot plate (Mabtech) was coated with 50μg/mL IgE per well at 4°C overnight. First, 1x10® 6 10 kDa MWCO (Cytiva).According to the manufacturer’s manual, total IgG was purified by Protein G column chromatography  from pooled sera (5ml) obtained by terminal bleeding. For isolating Fel d 1-specific IgG, Fel d 1 was coupled to the HiTrap NHS-Activated HP 1ml column (Cytiva) according to the manufacturer’s manual. The total IgG was applied. The flow-through and the eluate were collected. Buffer exchange to PBS was performed using VivaspinRed blood cells were lysed using ACK buffer (Thermo Fisher). Unspecific binding was blocked by using mouse Fc gamma block (BD Bioscience). Basophils were marked with APC anti-mouse CD49b  and PE anti-mouse IgE . Antibody staining were carried out at 4°C for 30min. After the staining, the cells were washed 3x with PBS. Flow cytometry was performed with CytoFLEX S 4L 13C (B2-R3-V4-Y4) plus 96 DW plate loader  and analyzed using FLOWJO software .Mice were injected with 25µg anti-IgE IgG, 25µg anti-IgE(PNG) IgG, or 25µg control IgG  in 100μl PBS i.v. 24 hours later, mice were sensitized with 5µg IgE F127 or 5µg anti-Ara h2 IgE in 100µl PBS. The following day, the MiniTemp rectal probe for mice  was used to measure the baseline body temperature. Rectal temperature was monitored every ten minutes for an hour after intravenous injections of 20µg of roasted peanut extract (Ara R) or 5µg of Fel d 1 in IgE-sensitized mice.Primary mouse B cells were isolated from the spleen of Balb/c and CD23 KO mice. The B cells were isolated using EasySep™ Mouse B cell isolation Kit  according to the manufacturer’s manual. The B cells were kept in RPMI1460 medium with 10% FBS at a density of 100’000 cells in 100µl. IgE anti-IgG complexes were formed by incubating 2µg/ml of 4µg/ml of anti-IgE IgG in medium for 1h at 37°C. Next, the medium of the B cells was removed and 5µl of complexes were added per well. Supernatant was taken and used for ELISA after 10min and 30min of incubation time. After removing the supernatant, the cells were immediately stained with rat anti-mouse IgE-FITC (Clone R35-72 (RUO), BD Bioscience) and goat anti-mouse IgG-APC (ThermoFisher Scientific) as described above. The cells were washed twice with PBS and fixed with 4% formaldehyde in PBS for 15min at room temperature. Flow cytometry was performed as described above.2O2 and stopped with 1mol/L sulfuric acid after 10 minutes. OD was measured at 450 nm.96-well Nunc Maxisorp™ ELISA plates (Thermo Fisher) were coated with 2µg/ml antibody in PBS at 4°C overnight. After blocking with PBS/0.15% Casein solution for 2h at room temperature, plates were washed 5x with PBS. Incubation of antibodies or sera was performed for 1h at RT. Afterward, plates were washed 5x with PBS/0.05% Tween. ELISAs were developed with TMB  and HPlates were coated with mouse IgE F127, IgE(PNG), or Fel d 1. Serial dilution of sera  was added. HRP-labeled goat anti-mouse IgG (The Jackson Laboratory) antibodies were used to detect IgG (1:2’000). To detect IgG subclasses, HRP labeled rat anti-mouse IgG1 (BD Pharmingen), goat anti-mouse IgG2a (Bio-Rad), goat anti-mouse IgG2b , and goat anti-mouse IgG3  were used in a 1:2’000 dilution.Anti-mouse IgE STAR110 (Bio-Rad) was coated. Then, serial dilution of sera , or supernatant from the B cells were added. Goat anti-mouse IgE-HRP STAR110P (Bio-Rad) was used to detect mouse IgE (1:2’000), and HRP-labeled anti-mouse IgG was used to detect IgE-IgG complexes (1:2’000).Plates were coated with IgE, IgE(PNG), or Fel d 1. The eluate and flow-through of the protein G and Fel d 1-column were tested starting with 2μg/ml and further serially diluted 1:3. HRP-labeled goat anti-mouse IgG (The Jackson Laboratory) antibodies were used for detection of IgG (1:2’000).IgE F127 was coated. Isolated anti-IgE IgG or anti-IgE(PNG) were applied at 2μg/ml and were further serial diluted (1:3). After 1h incubation, the plates were washed 3 times for 5min either with 7M urea in PBST (PBS mixed with 0.05% Tween20) or PBST only. To detect mouse IgG antibodies, HRP-labeled goat anti-mouse IgG (The Jackson Laboratory) was used. The formula used to determine the avidity index (AI) was AIx = OD (dilution x) + urea/OD (dilution x)–urea.Statistics were carried out using GraphPad Prism 9.0 . To determine the statistical significance between two groups, a student’s t-test was used. More than two groups were examined by one-way ANOVA. Two-way ANOVA was used to compare variables that depended on concentration and time, and then Tukey testing was applied. All data are presented as mean SEM in graphs. The signs for statistical significance are ns = not significant, p ≤ 0.05 (*), p ≤ 0.01 (**), p ≤ 0.001(***), and p ≤ 0.0001 (****).We first investigated the IgE-specific IgG response induced by immunization with glycosylated (IgE-ICs) or deglycosylated (IgE(PNG)-IC) IgE in a complex with Fel d 1 (IgE-specific plasma cells were quantified in lymphoid organs upon IgE-ICs or IgE(PNG)-ICs vaccination. For that, spleen and bone marrow (BM) were collected two weeks after the third injection (day 42) and analyzed for the presence of IgE-specific IgG-secreting plasma cells. Bone marrow and spleen contained anti-IgE IgG-secreting plasma cells , IgE-IC, and IgE(PNG)-IC from serum, and observed that IgE disappears from the serum faster than IgE(PNG). Furthermore, compared to free IgE antibodies, IgE-IC are eliminated more quickly, whereby no difference was found between glycosylated and deglycosylated complexes -IC , HoweverIn conclusion, triple vaccination with IgE-ICs without adjuvant elicited a solid systemic humoral immune response against IgE, which was significantly stronger when glycosylated IgE was used as the immunogen. These results indicate that glycans play a role in modulating anti-IgE IgG responses that are probably FcγR dependent.We next wanted to investigate the effects of anti-IgE IgG and anti-IgE(PNG) IgG antibodies on the serum clearance of secondarily administered IgE and their ability to prevent sensitization of effector cells. Therefore, we isolated IgG antibodies from pooled sera by Protein G chromatography and analyzed them by ELISA. As expected, these antibodies reacted against IgE and Fel d 1 (The purified anti-IgE IgG or anti-IgE(PNG) IgG antibodies were injected into mice 1h before IgE administration. Serum IgE was measured 30min, 2h, and 24h after IgE injection by ELISA. Additionally, Basophil surface IgE was measured one week after IgE injection  IgG, or a control IgG prior to IgE sensitization can protect against the Fel d 1 challenge  with IgE-anti-IgE IgG complexes  antibodies to clear IgE from serum and prevent binding to effector cells. The results show that anti-IgE IgG antibodies are significantly better at controlling the binding of IgE to FcεRI of basophils than anti-IgE(PNG) antibodies. This indicates that IgE glycosylation affects the quantity of anti-IgE antibodies generated and their quality. An explanation for this could be the difference in affinity since it is higher for the anti-IgE IgG antibodies than anti-IgE(PNG) antibodies. It could be that glycans are essential for interacting with anti-IgE IgG to IgE. Thus, in the case of missing glycans, the anti-IgE IgG binding site could be altered, resulting in decreased affinity. Another explanation could be that deglycosylation leads to a conformational change . This chvia FcγRIIb  IgG allowed us to see if the difference in serum clearance is also reflected in the ability to protect mice from anaphylaxis upon allergen challenges. Our results show that both anti-IgE IgG antibodies protect BALB/c WT mice compared with controls. However, protection was always better in the anti-IgE IgG group than in the anti-IgE(PNG) group. These results are consistent with the clearance experiment results, where significantly more IgE was found on the basophils of the anti-IgE(PNG) IgG group than in those of the anti-IgE IgG group. To better understand the protection mechanism, allergen challenges were also performed in FcγRIIb KO and CD23 KO mice. Previous studies have shown that co-aggregation of FcγRIIb with FcεRI inhibits IgE-mediated degranulation of effector cells . Moreove FcγRIIb . HowevergE alone  and coul IgE-ICs . A lack via CD23 in a mouse model. Further research is needed to investigate the effects of IgE glycosylation on anti-IgE IgG antibodies and serum IgE levels in humans. In particular, the extent to which different IgE glycosylation patterns affect anti-IgE IgG antibodies should also be investigated. More insights into the role of IgE glycosylation for anti-IgE IgG antibodies could help to find even more efficient strategies against type I hypersensitivity diseases.In conclusion, we have demonstrated the importance of IgE glycosylation for the anti-IgE IgG response and a possible pathway to eliminate IgG-IgE complexes The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by Swiss Federal Veterinary Office.KP designed, performed, and interpreted experiments. ZG and SZ helped perform experiments. MB, PE, and MV supervised, designed, and interpreted experiments. KP and MV wrote the manuscript. All authors contributed to the article and approved the submitted version.This project was supported by funding from the following grants: SNF grant 310030_179165/1 to MV; SNF grant 310039_185114 to MB.We acknowledge Marianne Zwicker and Aleksandra Nonic for technical assistance. Further, we thank Professor Jeffrey Ravetch for providing CD23 knockout mice.MB has a financial relationship with Saiba AG involving stock ownership or payments for research activities.The remaining 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.