S1pr4 deficiency aggravated the OVA/LPS-induced pulmonary inflammation in mice along with a significant up-regulation in M1 macrophage activation. Mechanistic studies showed that S1PR4 was strongly connected to bioactive oxylipins concurrent with bounding to formyl peptide receptor 2 to influence the phosphorylation of JNK and contributed to the macrophage M1 program, which in turn secreted amounts of inflammatory cytokines associated to the inflammatory response of neutrophilic asthma. Furthermore, treating mice with S1PR4 agonist CYM50308 was characterized by less pulmonary inflammatory infiltration. Our research indicates S1PR4 a promising therapeutic target for non-eosinophilic phenotypes of asthma.Patients with eosinophilic asthma react well to conventional treatment of asthma while individualized therapy for non-eosinophilic endotypes have yet to be developed. Dysregulated sphingosine metabolites are associated with the pathophysiology of different asthma endotypes with their receptors involved. However, whether the sphingosine-1-phosphate receptor 4 (S1PR4) contributes to disease progression of asthma remains underappreciated. In this study, we demonstrated that sphingosine metabolism was disturbed in asthma while it could not be used to distinguish between different endotypes of asthma. S1PR4, a vital receptor of bioactive sphingosine metabolites and mainly expressed in macrophages, exhibited lower expression both in patients and experimental mice with neutrophilic airway inflammation. Additionally,  Asthma is a heterogeneous disease characterized by chronic inflammation in the airway and affects over 350 million people worldwide. Although a decline in hospitalization and deaths from asthma has arisen in some countries, a significant subpopulation of patients is refractory to conventional treatments, putting a heavy burden on families of patients and health care systems Sphingolipids, building blocks of eukaryotic cell membranes, are a large group of lipids ubiquitously distributed in both animals and plants S1P and some other bioactive sphingosine metabolites (such as dihydro-S1P (dhS1P) and phytosphingosine-1-phosphate (P1P)) are predominantly mediated in a receptor dependent way, through G-protein coupled receptors (GPCRs) including S1PR1-5, following activating of several downstream signaling pathways http://www.metware.cn/) based on the AB Sciex QTRAP 6500 LC-MS/MS platform. Clinical data of targeted lipidomics analysis is provided in Table S1.For the untargeted lipidomics analysis, patients with asthma (n = 24) and healthy control (HC) subjects (n = 20) were enrolled from Tongji Hospital  as previously reported S1pr4 knockout (S1pr4-KO) mice (JAX stock #005799) were procured from Jackson laboratory . Wild type (WT) (C57BL/6) mice were procured from the Animal Experimental Center of Hubei province . The mice were all maintained in a specific pathogen-free animal center at the Tongji Hospital and subjected to a 12 h light-cycle environment with clean water and irradiated food. All the experiments were approved by the Animal Care and Use Committee of Tongji Hospital.S1pr4 (S1pr4-OE) or control vector on day 18 before the challenge as described hereafter when research needed. From days 20 to 22, all mice were challenged to daily intranasal administration of OVA or saline, as reported previously with a few alterations Mice were sensitized intranasally (i.n.) with ovalbumin (OVA) and lipopolysaccharide (LPS) in saline on days 0, 1, 2, and 13. Mice were infected with adenovirus  expressing Sphingosine, sphinganine, S1P, dhS1P, P1P, OVA grade V and LPS were procured from Sigma-Aldrich . Murine recombinant IFN-γ was obtained from PeproTech . Antibody against S1PR4 and mouse IL-1β, IL-6, and IL-12b ELISA kit were procured from Boster . Fluorescent antibody against S1PR4 was obtained from Affinity Biosciences . Antibodies against iNOS and formyl peptide receptor 2 (FPR2) were purchased from Abcam . Antibodies against p38, p-p38, p65, p-p65, JNK, P-JNK, Erk, p-Erk, FLAG and magnetic beads were procured from Cell Signaling Technology . Antibodies against CD68 was purchased from Santa Cruz Biotechnology . Antibodies against Arg-1, IL-1β, and β‐Actin were procured from the Proteintech Group . Anti-mouse CD45-APC/Cy7, F4/80-PE, CD11b-V450, and CD86-FITC were procured from BD Biosciences . Anti-mouse CD206-PE/Cy7 and murine recombinant IL-4 were procured from BioLegend . CYM50358 was obtained from Tocris Bioscience . All other reagents were obtained from MedChem Express , except stated otherwise.The left lung was first inflated and transferred for 24 h to fresh 4% neutral-buffered paraformaldehyde at standard room temperature, then we performed paraffin embedding and histological analysis as reported previously. Anti-S1PR4 was used for immunostaining of lung tissue sections as described in the manufacturer's instructions. For immunofluorescence, the lung sections and smear were probed with the first antibody and then the fluorescent secondary antibodies of corresponding species were used for staining . Nuclei were counterstained blue with 4'-6-diamidino-2-phenylindole (DAPI). Images were scanned with fluorescence  as well as a confocal microscope .The concentration of IL-6, IL-1β, and IL-12b in the bronchoalveolar lavage fluid (BALF) and cell culture supernatant was determined with the ELISA kits described above following the manufacturer's instructions.Primary bone marrow derived macrophages (BMDMs) were procured from male mice as previously reported S1pr4-KO and WT mice. When transferred into single cell suspension of mice lung tissue by sterile collagenase I, cells were placed in 35×15 mm tissue culture dishes leaving to set for about 1-2 h and then the medium was changed. LPS/IFN-γ or IL-4 were administrated the following day.Primary lung macrophages were obtained from both RIPA lysis buffer was applied to homogenize the lung tissues and cultured cells. Then the proteins underwent western blotting with the primary antibodies mentioned above by established techniques. To analyze the gray values, Image J software was used.Table S2 shows the primers that were used for each target gene.TRlzol reagent was applied for the isolation of total RNA from lung tissues and macrophages following the manufacturers' instructions. A reverse transcriptase kit was used to conduct complementary DNA synthesis. The SYBR Premix Ex Taq was used for quantitative RT-PCR and β-actin was used to normalize the relative expression of every target gene as reported previously. All the reagents mentioned above were obtained from Takara . Previously established techniques were used to isolate single cells from mice lung tissue S1PR4-related asthma phenotype genes, we used microarray analysis datasets from the Gene Expression Omnibus (GEO) database as described following. The heatmap analyses were performed with R software (version 4.1.3), and correlation clustering heatmap was analyzed with Metaboanalyst 3.0 . Network diagram of interrelated differentially expressed genes (DEGs) were performed by Cytoscape (version 3.9.1). Metabolic pathway analysis of oxylipins and their critical lipid metabolizing enzymes were based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.To identify Whole-cell lysate was used to perform immunoprecipitation as described in a previous protocol * p<0.05; ** p<0.01; *** p<0.001; and **** p<0.0001.Data as a result of the experiments are reported as mean ± standard error of the mean (SEM). GraphPad Prism v7.0 software was used for comparisons between groups of at least three independent replications. Comparisons between two experimental groups were performed with Student's t test in case of paired data or Student's t test with Welch's correction in case of unpaired data. For comparisons between three groups or more, one-way ANOVA with Bonferroni's correction was applied. In all analyses, p< 0.05 was defined as statistical significance and expressed as Fig.  indicates, 23 sphingolipids changed in asthma patients (|Fold change|≥1) compared to HCs, which was distributed in sphingosine, ceramide, sphingomyelin, etc. The correlation clustering‐heatmap indicates a clear correction between different types of sphingolipids Fig. B. To further investigate the sphingosine metabolism in asthma patients with different endotypes, targeted lipidomics analysis was conducted in which 16 EA patients, 15 NEA patients and 10 HCs were included. Clinical data is provided in Table S1. The results indicated that sphingosine and sphinganine were elevated in the plasma Fig. C whereas in the induced sputum it exhibited decreased in both EA and NEA patients Fig. D. S1P, dhS1P, and P1P, phosphorylated by sphingosine kinase (SKs), are the active terminal derivative of sphingosine metabolism Fig. E. Subsequently, we discovered that in asthma patients, the concentration of sphingosine metabolites in plasma and induced sputum were highly associated with clinical parameters of asthma Fig. F-H including Asthma Control Test (ACT), serum total IgE concentration, fractional exhaled nitric oxide (FENO) and index of pulmonary function FEV1/FVC (data not shown), indicating the potential impact of sphingosine metabolism on the pathogenesis of asthma.The untargeted lipidomics analysis included 24 asthma subjects and 20 HC subjects as previously described S1PR1 and S1PR4 were the main receptors expressed in asthmatic PBMCs Fig. A. Furthermore, the expression changes in PBMCs before and after asthmatic treatment were compared and the results indicated that S1PR4 was the only elevated receptor after standardized management and treatment of asthma Fig. A. To verify these results, we examined the expression of S1PR4 in the lungs of asthma patients and HC subjects. As shown in Fig. , S1PR4 was expressed mainly in the alveoli and the majority of macrophages. After assorting the results according to different inflammatory endotypes based on the sputum analyses, we found a surprising observation that S1PR4 declined greatly in the induced sputum smear of NEA patient Fig. D. We further evaluated the expression of S1PR4 in mice lungs with experimental models and demonstrated that S1PR4 exerted reduced expression in asthmatic mice which was more remarkable in the OVA/LPS treated group . Subsequently, we evaluated the receptor's expression in the primary macrophages. S1pr1, S1pr2, and S1pr4 were mainly expressed in BMDMs Fig. G and S1pr4 was obviously increased after stimulation of bioactive sphingosine metabolites B. Macrophages have two different forms of polarizations: either the classically activated phenotype (M1) or the alternatively activated phenotype (M2), either form is determined by the micro-environment in vivo or different stimulus in vitroFig. H and lung macrophages C.S1P is proven to employ most of its functions in immunity through activation of its distinct GPCR S1pr4-KO and WT mice Fig. A-B with OVA/LPS induction. Compared with WT mice, S1pr4-KO mice showed more inflammatory cell infiltration Fig. C, especially macrophages and neutrophils Fig. D. Predictably, the severity of inflammatory response following OVA/LPS induction was significantly elevated in S1pr4-KO mice Fig. E. Next, we compared inflammatory cytokine levels in BALF measured by ELISA Fig. F and significantly increased IL-12b levels were observed in S1pr4-KO mice treated with OVA/LPS while IL-6 secretion also tended to be enhanced by S1pr4 deficiency (the concentration of IL-1β was undetectable in most mice). Airway hyperresponsiveness (AHR) is proven to be an important feature of asthma. Therefore, we measured the respiratory system resistance (Rrs), airway tissue elasticity (Ers), and compliance (Crs) to aerosolized methacholine by applying an invasive method 24 h following the last challenge which was performed by using the flexiVent setup . We demonstrated that S1pr4 deficiency produced significant enhancement in resistance and elasticity parameters Fig. G.On the basis of the findings above, we aimed to dissect the effect of S1PR4 on asthma by treating S1pr4 (S1pr4-OE) or control vector A. Inversely, significantly attenuated pulmonary inflammatory response and less inflammatory cell infiltration were noted in S1pr4-OE mice following OVA/LPS treatment B-D while proinflammatory cytokines and parameters reflecting airway responsiveness showed no significant changes E-F. We further explored the impact of S1PR4 on eosinophilic asthma. The results showed that S1pr4-KO had no effect on eosinophilic airway inflammation after OVA/Alum induction A-D. Type-2 (T2) inflammatory response plays an important role in eosinophilic asthma. We observed that T2 cytokines had the same expression in S1pr4-KO mice and WT mice after OVA/Alum induction E.To support the above findings, mice were infected with adenovirus expressing S1pr4-KO mice had significantly higher nitric oxide synthase 2 (Nos2) and Cd86 mRNA expression after OVA/LPS induction Fig. H. This result was also established by flow cytometry analysis of single cell suspension of mice lung tissue. S1pr4-KO mice exhibited a significantly enhanced percentage of lung M1 macrophages (CD45+CD11b+F4/80+CD86+ CD206-) than WT mice, however, it seems unlikely that S1pr4 deficiency affected the induction of M2 macrophages as we were not able to detect an evident difference in the number of CD45+CD11b+F4/80+CD206+ CD86- macrophages Fig. A. RT-PCR analysis of the two M1 markers in S1pr4-OE mice following OVA/LPS treatment demonstrated corresponding results A, while the percentage of lung M1 macrophages remained unchanged B.Since primary macrophages stimulated with LPS/IFN-γ were associated with a reduced expression of S1PR4, we evaluated whether S1PR4 participated in regulating the functionalities of proinflammatory macrophages. First, we conducted RT-PCR analysis of indexes of M1 macrophage polarization. S1pr4-KO and WT mice were applied. LPS/IFN-γ induced significantly higher levels of iNOS and IL-1β protein Fig. B as well as pro-inflammatory cytokines release in S1pr4-KO BMDMs than in WT BMDMs Fig. D, and a substantial increase in expression of M1 macrophages related to the pro-inflammatory gene was noted upon LPS/IFN-γ stimulation in S1pr4-KO primary lung macrophages . Given that S1PR1 and S1PR2 are closely related to NF-κB S1pr4-KO induced remarkable phosphorylation of c-Jun NH2-terminal kinase (JNK) instead of other pathways , implying that S1PR4 has an impact on the oxylipins metabolic pathway. As exhibited in Fig.  almost all of the selected oxylipins belonged to AA-derived metabolites and numerous enzymes were involved. Therefore, we detected the expression changes of these critical lipid metabolizing enzymes in S1pr4-KO BMDMs. Unfortunately, no apparent expression changes of the enzymes were observed .Next, we aimed to clarify the mechanisms underlying M1 macrophage programming regulated by S1PR4. Based on previous studies indicating that S1PRs participated in the metabolic processes of oxylipins such as arachidonic acid (AA), which controls many physiological and pathological processes and are upstream of inflammatory activity Fig.  shows. Nineteen genes were screened out  and most of them were also DEGs in the validation cohort (GSE45111 and GSE137268) Fig. C. Further analyses of the interrelated DEGs  and BMDMs  and significant up-regulated expression was observed. Co-Immunoprecipitation  and laser confocal double immune-fluorescence staining  were conducted to prove the interaction between S1PR4 and FPR2 in BMDMs. Finally, the FPR2 antagonist WRW4 was applied to reaffirm that FPR2 signaling played a part in S1PR4-induced M1 macrophage programming. Decline in parameters of macrophage polarization, phosphorylation of JNK, as well as proinflammatory cytokines release were observed in S1pr4-KO BMDMs treated with WRW4 following stimulating by LPS/IFN-γ . Overall, the results of this study support the hypothesis that FPR2 signaling participates in S1PR4-induced M1 macrophage programming.Subsequently, we filtered out gene arrays concerned with asthma endotypes in the GEO database followed by a comprehensive bioinformatics analysis as Fig. A. CYM50308 treatment significantly weakened the pulmonary inflammatory response as well as immune cell infiltration, particularly of neutrophils Fig. B-D. The treatment-group mice showed a decline in resistance parameters Fig. E while Ers and Crs remained no significant changes. Additionally, the inflammatory cytokines levels found in BALF were consistent with the assessment of inflammation levels above (the concentration of IL-1β was undetectable in most mice) Fig. F. Consistently, administered with CYM50308 showed significantly lower levels of Nos2 and Cd86 expression in the lungs Fig. G, combined with a significant decrease in the percentage of lung M1 macrophages Fig. H. Moreover, the expression of FPR2 and the phosphorylation of JNK Fig. I were also declined as expected. Whereas, CYM50308 seemed had marginal effect on OVA/Alum-induced eosinophilic airway inflammation .Finally, we aimed to facilitate the translation of above findings to a therapeutic approach for NEA. For this purpose, experimental mice were administered with S1PR4 agonist CYM50308 or equal volume SBE-β-CD the day before challenge and each time prior to challenge starting on day 19 Asthma is a heterogeneous pulmonary disease comprised of several different endotypes which depict various pathways of the inflammatory and immune response S1pr4 deficiency aggravated asthmatic mice with neutrophilic inflammation as characterized by a reduction in M1 macrophages. Mechanistic studies showed that S1PR4 was strongly connected to bioactive oxylipins mainly generated from AA while no apparent changes in expression of the relevant enzymes were observed in S1pr4-KO BMDMs. Further research showed that S1PR4 bound to FPR2 to influence the phosphorylation of JNK and then contributed to the macrophage M1 program, which in turn led to the secretion of a great number of inflammatory cytokines involved in the inflammatory response of neutrophilic asthma endotype  and chemokines , indicative of a leading function in the recruitment and activation of Th1 cells as well as clearance of intracellular pathogens, it has been referred to as the potential major effector in non-allergic asthma and associated with the pathophysiology of severe asthma, especially in those with a poor reaction to systemic corticosteroids S1pr4-KO mice were shown to promote the functionalities of proinflammatory macrophages upon LPS/IFN-γ stimulation, which were further confirmed by S1PR4 agonist CYM50308. Next, we investigated the essential question of how S1PR4 affected the M1 program in macrophages. Previously published studies have indicated that S1P inhibits the 5-lipoxygenase product formation, while the effect was simulated by S1PR4-specific agonists and confined to cells expressing S1PR4 S1pr4-KO BMDMs. Lastly, we selected FPR2, which serves as the key connection between S1PR4 and the M1 program by means of bioinformatics analysis. FPR2 is a member of the GPCR family expressed by many cells including most if not all immune cells. It attaches to several types of ligands consisting of chemotactic formyl peptides, bioactive lipid metabolites of AA or DHA , as well as urokinase-type plasminogen activator receptor S1pr4-KO BMDMs treated with the FPR2 antagonist WRW4, which further elucidates the role of FPR2 signaling in S1PR4-induced M1 macrophage programming.Macrophages, the most commonly found immune cells in the lung, are vital elements of innate and adaptive immunity and have a significant impact on tissue homeostasis S1pr4-KO as well as S1PR4 agonist CYM50308 had limited role on OVA/Alum-induced eosinophilic airway inflammation. It is possible that differences are observed due to inflammatory environment skew in distinct populations or from differences in protocols. What is more, in our study, administered CYM50308 in vivo significantly weakened the airway inflammatory response as well as AHR, while no significant decline of lymphocytes was observed. As a result, administration of CYM50308 protected mice from OVA/LPS induced neutrophilic inflammation in asthma. Despite the promising results of our study, more studies are needed for dosage and drug safety evaluation.FTY720 (known as Fingolimod or Gilenya) functions as a high-affinity agonist of four of the five known S1PRs (except for S1PR2) and employs strong anti-inflammatory effects, received approval in 2010 to be used as immunomodulatory drug for multiple sclerosis A few limitations exist in our study that should be addressed. Firstly, we employed a relatively small asthma cohort and more asthma patients with different endotypes are needed to verify the disturbance of sphingosine metabolism as well as the expression of S1PR4. Secondly, although we demonstrated that S1PR4 interacted with FPR2 and exerted an effect on the M1 program, the specific underlying mechanisms should be explored further. Thirdly, we illustrated that S1PR4 has an impact on inflammation-associated oxylipin's metabolism, but in-depth studies are needed between S1PR4 and related metabolic enzymes. Lastly, further research is necessary to completely elucidate the effects of S1PR4 on the function of other immune cells in the pathogenesis of asthma.S1pr4 had aggravated OVA/LPS-induced lung inflammatory response and AHR. Mechanistic studies revealed that S1PR4 interacted with FPR2 to influence the JNK pathway and following macrophage M1 program. Oxylipin's metabolism including PG may be involved in this process. Moreover, administration of the S1PR4 agonist CYM50308 substantially protected mice from OVA/LPS-induced lung inflammation. In brief, the findings of this study substantiate the hypothesis that targeting S1PR4 may be a promising therapeutic approach for non-eosinophilic phenotypes (refractory or ICS-insensitive) of asthma in clinical settings.In summary, we have demonstrated that a disturbance in sphingosine metabolism existed in asthma patients independent of different endotypes while the crucial sphingosine receptor S1PR4 was altered in patients and experimental mice, especially those with neutrophilic airway inflammation. Therefore, mice deficient in Supplementary figures and tables.Click here for additional data file.


While expression of the corresponding G6PD and plastidic TRX genes was marginally affected by salt, it impaired root growth of several of the corresponding mutant lines. Using an in situ assay for G6PDH, G6PDH2 was found to be the major contributor to salt-induced increases in activity, while data from ROS assays further provide in vivo evidence that TRX m acts in redox regulation during salt stress. Taken together, our data suggest that regulation of plastid G6PDH activity by TRX m may be an important player regulating NADPH production in Arabidopsis roots undergoing salt stress.Plants contain several NADPH-producing enzymes including glucose-6-phosphate dehydrogenases (G6PDH) with different sub-cellular localizations. The activity of plastidial G6PDHs is redox-regulated by thioredoxins (TRX). Although specific TRXs are known to regulate chloroplastic isoforms of G6PDH, little information is available for plastidic isoforms found in heterotrophic organs or tissues. Here, we investigated TRX regulation of the two G6PDH plastidic isoforms of Arabidopsis roots during exposure to a mild salt stress. We report that  Plants use NADPH in many metabolic processes, such as assimilation of carbon and nitrogen and biosynthesis of essential compounds  for growth and development. NADPH is also a source of reducing equivalents for reactive oxygen species (ROS) scavenging enzymes . In planG6PD gene family comprises six members (G6PD5 and G6PD6) encode cytosolic enzymes. The other G6PD genes code for proteins with an N-terminal chloroplast targeting peptide but only three of them  are functional  the activity of the two homologous G6PDH isoforms preferentially expressed in non-photosynthetic plastids of Arabidopsis. We show that m-type TRXs are the best regulators of G6PDH2 and G6PDH3 trxm3 mutant obtained in the Landsberg (Ler) ecotype. The g6pd single mutants, g6pd2 (SAIL_1240_G11), g6pd3 (SALK_139479), g6pd5 (SAIL_97_F06) and g6pd6 (SALK_016157C) mutants were already genetically described . The genetic details of the trx mutants were previously described. The trx mutants with single or multiple mutations used in this work were: trxf1.trxf2 (trxf1.f2) (SALK_128365/SALK_123826) (trxy1.trxy2 (trxy1.y2) (SALK_103134/SALK_028065) (trxm1.trxm2.trxm4 (trxm1.2.3) (WiscLox375F05/SALK_130686/SALK_023810) (trxm3 (ET3878) (trx x (SALK_128906) (trx z (SALK_059334C) (All Arabidopsis mutants used are in the Columbia (Col-0) ecotype except the escribed . Becauseedundant , the cor_123826) ; trxy1.t_028065) ; trxm1.t_023810) ; trxm3 ((ET3878) ; trx x (_128906) ; and trx059334C) .Arabidopsis thaliana) wild-type  and mutant (detailed above) seeds were surface sterilized and sown on agar (0.6% w/vol) containing standard half Murashige and Skoog medium (½MS). For salt stress conditions, the agar medium was supplemented with 100 mM NaCl, causing a mild salt stress. Germination was synchronized by a cold treatment at 4°C for 72 hours. Short-day growth conditions were used (growth chamber): 8-hr day photoperiod, 80-100 µmol/m2/s, 20°C. For experiments, seedlings were carefully removed from the slurry agar medium (with or without NaCl) for analyses. For root growth monitoring, plants were positioned horizontally on the surface of solid agar medium and the length of primary roots was measured. For in situ G6PDH activity assays (NBT reduction) and ROS measurements (H2-DCFDA probe) roots were further incubated in chemical reagents, as described below.Arabidopsis  as previously described (+ was added to G6PDH protein preparations (G6PDH2 and G6PDH3 isoforms were produced in escribed . TRX proescribed . G6PDH aarations .TRX genes and in G6PD genes), as previously described  to remove soluble carbohydrates. Staining for G6PDH activity was done by incubating seedlings for 10 min at 30°C in the enzyme assay mixture containing: 10 mM glucose-6-phosphate, 1 mM NADP+, 5 mM MgCl2, 0.7% (w/vol) BSA, protease inhibitor cocktail  and 0.05% NBT (w/v). Finally, roots were rinsed in HEPES buffer and mounted between a slide and a coverslip for observation using a multizoom microscope (AZ 100 NIKON) equipped with a camera. Images were captured and treated using the NIS-Elements BR software. The intensity of staining in root tips was quantified using Image J (8 day-old seedlings were fixed and permeabilized in 7.5% (w/v) paraformaldehyde in MTSB (MicroTubules Stabilization Buffer): 50 mM PIPES, 5 mM EGTA, 5 mM MgSO Image J  and exprExperiments with the various genotypes were performed using at least two different seed batches. Mutants were always compared to wild-type of the corresponding ecotype using seeds from parent plants grown in the same time and in the same conditions. Arabidopsis seedling images were scanned at the resolutions of 600–800 dots per inch. Primary root lengths were measured using ImageJ .Imaging was performed using a fluorescence microscope (ZEISS Axiolmager Z2) fitted with a GFP filter.All chemical reagents used were from Sigma-Aldrich or LifeTechnologies, except the reagents for real-time quantitative PCR obtained from Roche Applied System.vs. wild-type for a given growth condition, or salinity vs. control for a given genotype).Two-tailed Student’s t-tests were used for two-group comparisons  . When we tested and compared various plastid TRX proteins of the different types for their capacity to redox-regulate G6PDH activity, we found that both G6PDH2 and G6PDH3 are efficiently activated by TRX m1, m3 and m4 . In reducing conditions, TRX m1 and m4 were the most effective inhibitors of plastid G6PDH activity , while TRXm3 was less potent towards G6PDH2  and an inefficient inhibitor  of both G6PDH2 and G6PDH3. As previously found with G6PDH1 , although it showed a good or moderate capacity to activate G6PDH2 and G6PDH3, respectively . Overall, these data obtained in vitro using recombinant proteins suggest that m-type TRXs are the most efficient regulators of the activity of plastid G6PDH isoforms occurring in non-photosynthetic tissues.G6PDH2 and G6PDH3 proteins were recombinantly produced in their mature form and purified by affinity chromatography (strep-tag added at the C-terminus) . They shh G6PDH1 , TRX x dh G6PDH1 Figure 1in vitro for the different plastid TRX isoforms could have a physiological significance in planta. In Arabidopsis, the two genes encoding heterotrophic plastid G6PDH isoforms are mainly expressed in roots  mutants had shorter roots than Col-0 plants (g6pd2 and g6pd5.6 mutants grew significantly more slowly compared with the wild-type (Col-0 ecotype) and the g6pd3 mutant  triple mutant had shorter roots from 6 days after seed sowing    compared to the control condition (Col-0 roots ca. 40% longer than Ler roots) , but at a higher salt concentration (200 mM NaCl), Ler showed a clearly higher sensitivity than Col-0 to salinity  a better root growth capacity , while the root growth of the trxm1.2.4 and the trxz mutants were more severely affected by salt stress , the G6PD genes, in the leaves and in the roots of Arabidopsis plants cultivated in our growing conditions. We found that G6PD5 was comparably strongly expressed in both organs, and that, among the genes encoding plastid isoforms, G6PD1 and G6PD3 were the most highly expressed in leaves and roots, respectively  in presence of 100 mM NaCl, the expression levels of G6PD genes were not significantly impacted  in this area of the root tip, validating the specificity of the signal for measuring in situ G6PDH activity. In the roots of WT seedlings grown in the presence of 100 mM NaCl, we found a marked increase of the NBT staining signal. Thus, despite the weak responses to salt at the transcript level .g6pd mutants compared to Col-0  in control conditions (ca. 52% less than Col-0) under salt stress . Deficiency of other TRX isoforms did not significantly affect root G6PDH activity.To establish whether TRX isoforms were involved in the induction of G6PDH by salt, we measured G6PDH activity in the root tips of the Taken together, these results suggest that m-type TRXs are important to modulate G6PDH activity in Arabidopsis root tips, especially under salt stress conditions.g6pd3 mutant exhibited comparable ROS levels, the g6pd5.6 mutant showed decreased ROS signals in both control and salt conditions, and g6pd2 showed an increased root ROS content in presence of NaCl  condition  or indirect (TRX contributing to maintain cellular redox homeostasis), we measured ROS levels as an indicator of the cellular oxidative situation in root tips. This analysis revealed a strong increase in signal in the root tips of Arabidopsis exposed to 100 mM NaCl, confirming previous findings (G6PD2 function had no significant effect on root ROS levels in the control condition, but it provoked a strong increase under salinity (In darkened roots, we found that salt has no effect on either n levels Figure 4n levels . In barln levels . The absfindings , and revsalinity , respecttrxy1.y2 mutant. Instead, we found constitutively decreased ROS levels in the roots of this mutant (trxz mutant (in vitro (trxz mutant exhibits the RNA editing defects found in the rice mutant (trxm1.2.4 mutant (g6pd2 and g6pd3 mutants no significant increase of ROS was measured (Under oxidative conditions, induction of plastidial G6PDH activity requires the specific action of oxidized TRXs potentiated by ROS. Based on the known antioxidant properties of TRXs y , and thes mutant Figure 3s mutant , and ABAs mutant . Taken ts mutant , the prein vitro . TRX z iin vitro , and a rin vitro . In soybin vitro . Based oe mutant  and whetmeasured  suggest In an earlier study, we showed that the regulation of G6PDH1 activity by TRX occurs through redox-driven structural changes modifying substrate accessibility and cofactor binding . The priThe original contributions presented in the study are included in the article/EI-B, GNé, GNo and FW designed research. GC-I, EJ, AM, GNé, HV and FW performed research. EI-B, GNé, HV and FW analyzed data. And EI-B, GNé and GNo wrote the paper.


KRAS status and support the development of selective RAF1 degraders rather than RAF1 inhibitors for clinical use in combination therapies.More than 30% of all human cancers are driven by RAS mutations and activating KRAS mutations are present in 40% of colorectal cancer (CRC) in the two main CRC subgroups, MSS (Microsatellite Stable) and MSI (Microsatellite Instable). Studies in RAS-driven tumors have shown essential roles of the RAS effectors RAF and specifically of RAF1, which can be dependent or independent of RAF’s ability to activate the MEK/ERK module. In this study, we demonstrate that RAF1, but not its kinase activity, plays a crucial role in the proliferation of both MSI and MSS CRC cell line-derived spheroids and patient-derived organoids, and independently of KRAS mutation status. Moreover, we could define a RAF1 transcriptomic signature which includes genes that contribute to STAT3 activation, and could demonstrate that RAF1 ablation decreases STAT3 phosphorylation in all CRC spheroids tested. The genes involved in STAT3 activation as well as STAT3 targets promoting angiogenesis were also downregulated in human primary tumors expressing low levels of RAF1. These results indicate that RAF1 could be an attractive therapeutic target in both MSI and MSS CRC regardless of their  RAS drive 30% of all human cancer types [KRAS, the most frequently mutated RAS isoform (85%), is found predominantly in pancreatic, lung and colorectal cancer. Promising clinical data are emerging for KRASG12C inhibitors [RAF , two MEK (MEK1 and MEK2) and two ERK (ERK1 and ERK2) genes encoding for proteins with specific functions. Several studies have demonstrated that RAS-driven cancer are addicted to RAF proteins, but the mechanisms underlying their essential roles are different depending on the cancer type [The RAS/RAF/MEK/ERK pathway is a highly conserved signaling cascade that regulates cell morphology, migration, proliferation, differentiation and survival in a tissue and molecular context-dependent manner . Oncogener types . KRAS, thibitors , but treisoform 8%, is foucer type , 7, somecer type –11. RAF1cer type , prolifecer type , 15 and cer type . Recent cer type .APC (Adenomatous Polyposis Coli), while the MSI phenotype (about 15% of CRC) is due to an accumulation of mutations in the microsatellite sequences caused by a defect in the DNA mismatch repair system [Little is known about the mechanistic role of RAF proteins and especially of RAF1 in colorectal cancer (CRC). CRC is the third most common cancer worldwide in terms of incidence and the second in terms of mortality . It is ar system . In CRC,r system . Underste about 1% of CRC KRAS in MSI and MSS CRC, or whether it might have a role involving other pathways. Here, we demonstrate a crucial role of RAF1 in the proliferation of CRC cell lines both in 2D and 3D cultures. This role is independent of KRAS and MS status and requires an intact dimerization surface but not RAF1 catalytic activity. The decrease in proliferation caused by RAF1 loss is potentiated by MEK inhibition. Loss of RAF1 in CRC spheroids deregulates a group of genes that impact the transcription factor STAT3 and its downstream targets implicated in angiogenesis in human primary CRC. The data indicate that selective degraders of RAF1 might be more effective than selective inhibitors.A crucial role of RAF proteins in KRAS-mutated CRC has been postulated previously. On one hand, silencing of RAF and autophagy inhibition leads to cell cycle arrest and cell death in KRAS mutant cells , a phenoMUT/MSI; CMS1), SW1116  and KM12  cell lines  cell line, less cells were observed . Downregulation of RAF1 by two specific shRNA or one siRNA also impacted the size and metabolic activity of spheroids derived from the CMS3 group  phenotype  or consenes Fig. . In the ved Fig. . Howeverved Fig. . In lineved Fig.  and decrved Fig. . We measved Fig. . The fouved Fig. , in the In line with the observed growth defect, RAF1 KO spheroids displayed a reduced number of proliferating (KI67+) cells Fig. . RAF1 haRAF1 has been shown to have both kinase-dependent and -independent functions. To assess the role of RAF1’s enzymatic activity, we re-expressed RAF1 full length  or the kinase-dead mutant D486A, in which aspartic acid residue 486 within the DFG motif of the activation segment was converted to alanine , in two MUT/MSI; CMS1), Colo_131 , Colo_198 , Colo_176  or by siRNA  (Supplementary Table WT/MSI) and a slight decrease in ERK activity in Colo_176 (KRASWT/MSS)  either by stable expression of two independent doxycycline-inducible RAF1 shRNA (Colo_312 (KRASSS) Fig. . Also siSS) Fig.  and had SS) Fig. . These rTo gain insight in the role of RAF1 in CRC, we performed transcriptomic analysis of 3D spheroids from parental DLD1, SW1116, KM12 and Caco2 cell lines and the three independent RAF1 KO clones derived from them. We selected significantly deregulated genes from each cell line by comparing the three independent clones to their parental cell line  impacted by RAF1 ablation, we performed a Proteome Profiler™ Array of human phospho-kinases for the parallel determination of the relative levels of protein phosphorylation. Analysis of the four WT and RAF1 KO CRC lines showed that a number of phosphoproteins were impacted by RAF1 ablation , probably due to the small number of patients for which we obtained clinical history  [BHLHE40, EMP1 and LDLR as well as of three STAT3 target genes  in tumors expressing low levels of RAF1  had a localized primary tumor resected by surgery within 1 or 2 months after diagnosis and received (stage III) or not (stage II) adjuvant chemotherapy. Patients were divided into four groups  according to RAF1 mRNA expression levels  –52 were nd MMP2) , 17. AnaAF1 Fig. . These oAF1 Fig. . Taken tAF1 Fig. .In the present study, we investigated the role of RAF1 in colorectal cancer by using human 3D models as spheroids from CRC cell lines and patient-derived organoids. First, we demonstrated that complete ablation of RAF1 by CRISPR/cas9 genome engineering or RAF1 silencing with shRNA reduces the proliferation of human colorectal cancer cell lines and patient-derived organoids, respectively. This is in line with previous studies reporting a role of RAF1 in CRC , 23, lunIn CRC colonospheres , inhibitBHLHE40, LDLR or EMP1. Importantly, we could establish a positive correlation between the expression levels of these genes and those of RAF1 expression in human primary CRC. BHLHE40, LDLR and EMP1 encode proteins that enhance STAT3 activation [BHLHE40, LDLR and EMP1, as well as the STAT3 target genes involved in the control of angiogenesis in human primary LUAD. RAF1 exerts dual roles in STAT3 activation; in hepatocellular carcinoma, RAF1 acts as a cell-autonomous tumor suppressor by negatively regulating STAT3 activation [In addition and in line with similar studies performed with RAF1 shRNA in pancreatic cancer , bladdertivation –36. Analtivation –52, a crtivation , while itivation . Here, wtivation , 62.Be that as it may, low expression of BHLHE40, LDLR or EMP1 and a weak STAT3 activity are associated with a good prognosis in several cancers , 38, and2.Colon cancer cell lines were cultured in DMEM high glucose  supplemented with 10 % FBS, 100 U/ml penicillin G, and 100 lg/ml streptomycin at 37 °C and 5% COSpheroid cultures were established as described  with 300Patient-derived organoids were cultured as previously described  in 80% C48138; RRID:Addgene_48138)) [Generation of RAF1 KO cell lines was performed by the ProTech facility at Vienna BioCampus Facility. Briefly, CRC cell lines were electroporated with cas9 protein and pSpCas9(BB)-2A-GFP (PX458) plasmid )  containi®, Austria).Cells were plated in 96-well plates and were fixed for 15 min with ice-cold methanol at day 5, washed with PBS and stained with 0.5% Crystal Violet for 30 min at RT. After three washes with PBS, plates were air-dried and Crystal Violet was eluted with 10% Acetic Acid. Absorbance was measured at 595 nm using a microplate reader (TecanCells were plated at low density (1000 cells/well) in 6-well plates and let grow for 12 days. After Crystal Violet staining (see above), plates were air-dried and colonies were counted.Whole cell lysates from spheroids or organoids were extracted in RIPA lysis buffer  supplemented with PMSF 1 mM, NaF 1 mM, Na3VO4 1 mM and protease cocktail inhibitor 1X . For SDS-Page analysis, PVDF membranes were incubated overnight at 4 °C with the appropriated primary antibodies, all diluted 1:1000: BRAF F-7 (#sc-5284), ARAF C-20 (#sc-408), β-actin (#sc-1616), all from Santa Cruz Biotechnology, RAF1 (#610152) from BD Biosciences, MEK (#9122), pMEK (#9121), ERK (#9102), pERK (#9101), pSTAT3 Tyr705 (#9145), STAT3 (#8768) and GAPDH (#5174) from Cell Signaling Technology and Tubulin (#T9026) from Sigma-Aldrich. Immunoblots were acquired using ChemiDoc Imaging Systems and quantified using the Image Lab software .Spheroids and patient-derived organoids were treated with 1 µM or 10 µM U0126  and/or 1 µM GW5074 (MedChemExpress #HY-10542), or with napabucasin (BBI608) (MedChemExpress #HY-13919) at the indicated concentrations. Pictures were taken at the beginning and at the end of treatment to calculate the ratio between the initial and the endpoint volume.111177; RRID: Addgene_111177) [For silencing experiments, two different shRNA sequences were cloned in the LT3GEPIR vector  .shRNA-2: TGCTGTTGACAGTGAGCGCTGGCACGGAGATGTTGCAGTATAGTGAAGCCACAGATGTATACTGCAACATCTCCGTGCCATTGCCTACTGCCTCGGAshRNA-4: TGCTGTTGACAGTGAGCGATCCCTCAATTATGTTATTTTATAGTGAAGCCACAGATGTATAAAATAACATAATTGAGGGACTGCCTACTGCCTCGGA19319; RRID: Addgene_19319) [For reconstitution experiments, RAF1 full length (RAF1 WT), kinase-dead (D486A), phosphoablative (S338A) or dimer deficient (DIF) mutants  were cloe_19319) . LentiviLipofectamine RNAiMax (Invitrogen) was used to transfect the CRC cell line LS174T and the PDO Colo_324 with 30 nM RAF1 siRNA  , 68. esi® EdU Alexa Fluor 488 Kit , following the manufacturer’s instructions. Spheroids were exposed to EdU  at 37 °C for 2 h. Thereafter, spheroids were trypsinized and the cells were FACS-analyzed. Dapi was used to stain total DNA and forward scatter to determine cell size.Cell cycle analysis was carried out using the Click-iT® 3D  according to the manufacturer’s protocol. Luminescence was measured with a microplate reader .Apoptosis was assessed by flow cytometry using the Annexin A5/7-AAD kit . The metabolic capacity of cells was determined using CellTiter-GloACTIN as housekeeping gene. The primers are from Eurofins  (Supplementary Table RNA was extracted from 3D spheroids with the RNeasy kit from Qiagen (#74104) following manufacturer’s instructions, and reverse transcribed with the High-Capacity cDNA Reverse Transcription Kit . qPCR was performed in the Applied Biosystems 7900HT Fast Real-Time PCR System, using Go Taq qPCR Master mix . Relative expression was calculated by the ΔΔCT method using 2O2-PBS to inhibit endogenous peroxidase. After blocking in 3% BSA-PBS, sections were incubated for 1 h at room temperature with antibodies against Ki67  or cleaved caspase-3 , washed, incubated with the Leica Bond Polymer Detection kit  and counterstained with hematoxylin.For histological analysis, spheroids were fixed in 4% paraformaldehyde, molded in 1% agarose gel and embedded in paraffin. Hematoxylin/eosin and KI67 staining were performed on 4 µm-thick paraffin sections. Antigen retrieval in citrate buffer (pH6.0) was performed before immunostaining, and sections were treated with 3% HLevels of phosphorylated sites were determined using the Proteome Profiler™ Array, Human Phospho-Kinase Array Kit (R&D Systems # ARY003C). In total, 100 µg of protein lysates were incubated on the membranes spotted with antibodies specific of 37 kinase phosphorylation sites. Experiment was performed according to manufacturer’s recommendations. After background substraction, average of the duplicated spots was normalized on the loading control . Final samples pooled library prep was sequenced on ILLUMINA Novaseq6000 with SP-100 cartridge (2 × 800 Millions of 50 bases reads), corresponding to 2 × 33 Millions of reads per sample after demultiplexing.http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Poor quality sequences were trimmed or removed with fastp software to retain only good quality paired reads. Star v2.5.3a [The quality of raw data was evaluated with FastQC . After chloroform separation, RNA extractions were performed using the miRNeasy Mini Kit (Qiagen) on a QIACube instrument (Qiagen) following the manufacturer’s instructions including DNAse treatment. RNA integrity was assessed on a Bioanalyzer 2100 (Agilent), the average RIN (RNA Integrity Number) calculated for tumor and normal adjacent tissues was equal 8.1 and 7.2, respectively. Downstream RNA sequencing experiments were performed on samples with a RIN ≥ 7. mRNA sequencing has been performed by the «Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA». Libraries were prepared using the “TruSeq Stranded mRNA Library Prep Kit” from Illumina, according to the manufacturer’s instructions and with an input of 1 µg (selection of poly(A) RNAs). Sequencing was performed on an Illumina HiSeq 2000 sequencer as paired-end 100 bp reads. Libraries were generally pooled by 4 samples per lane. Sequencing quality control was checked with FASTQC and reads were then aligned against GRCh38 reference genome using Star v2.7.2.Gene counts were obtained using htseq-count, normalized by an UpperQuartile procedure and logged on a base 2.p values were calculated using the Student’s t test (two-tailed), and were considered statistically significant when <0.05. For transcriptomic analysis on human CRC spheroids, multiple hypothesis adjusted p values were calculated with the Benjamini–Hochberg procedure to control FDR which was set up with a significance of 0.05. For proteome profiler™ array analysis, a two-tailed Student’s t tests were performed between the log2 ratios of the parental cell lines and log2 ratios of RAF1 KO cell lines for each antibody. p values were adjusted using the Benjamini–Hochberg method. The heatmap was plotted with the pheatmap package v1.12.0 (https://CRAN.R-project.org/package=pheatmap) using R.Quantitative data are presented as mean ± SEM of at least three independent experiments, as indicated in the figure legends. Statistical analysis of the gene expression experiments (in-house cohort and LUAD TCGA cohort) was performed using R and gene expression comparisons were performed using the Wilcoxon Mann–Whitney test with a significance cut-off of 0.05.Supplemental informationSupplementary Table 3


Multiple myeloma is characterized by clonal proliferation of plasma cells that accumulate preferentially in the bone marrow (BM). The tumor microenvironment is one of the leading factors that promote tumor progression. Neutrophils and monocytes are a major part of the BM tumor microenvironment, but the mechanism of their contribution to multiple myeloma progression remains unclear. Here, we describe a novel mechanism by which S100A8/S100A9 proteins produced by BM neutrophils and monocytes promote the expansion of megakaryocytes supporting multiple myeloma progression. S100A8/S100A9 alone was not sufficient to drive megakaryopoiesis but markedly enhanced the effect of thrombopoietin, an effect that was mediated by Toll-like receptor 4 and activation of the STAT5 transcription factor. Targeting S100A9 with tasquinimod as a single agent and in combination with lenalidomide and with proteasome inhibitors has potent antimyeloma effect that is at least partly independent of the adaptive immune system. This newly identified axis of signaling involving myeloid cells and megakaryocytes may provide a new avenue for therapeutic targeting in multiple myeloma.We identified a novel mechanism by which myeloid cells promote myeloma progression independently of the adaptive immune system. Specifically, we discovered a novel role of S100A8/S100A9, the most abundant proteins produced by neutrophils and monocytes, in regulation of myeloma progression via promotion of the megakaryocyte expansion and angiogenesis. Tasquinimod, an inhibitor of S100A9, has potent antimyeloma effects as a single agent and in combination with lenalidomide and with proteasome inhibitors. The tumor microenvironment (TME) is one of the leading factors that promote tumor progression. We and others have previously demonstrated that multiple myeloma progression is associated with accumulation in the BM of myeloid-derived suppressor cells , an oral quinoline-3-carboxamide, binds to S100A9 in the presence of Zn in vivo . TQ has  in vivo . TQ prol in vivo  and a ra in vivo , demonstin vivo, as well as our surprising observation that part of the effect of S100A8/S100A9 on multiple myeloma progression is independent of the adaptive immune system and instead mediated by Toll-like receptor 4 (TLR4)- and STAT5-driven expansion of megakaryocytes (MK) and increased angiogenesis.Here, we report that S100A8/S100A9 promotes multiple myeloma progression and that blockade of S100A9 with TQ has antimyeloma activity Collection of samples from patients with multiple myeloma at the Abramson Cancer Center at the University of Pennsylvania  was approved by the Institutional Review Board (IRB) of the University of Pennsylvania . Studies were conducted in accordance with the U.S. Common Rule. All patients signed IRB-approved consent forms.l-glutamine, 10% FBS, and 50 units/mL of penicillin and 50 μg/mL of streptomycin. DP42 cells were also supplemented with 0.5 ng/mL murine IL6 (BioLegend). Cell lines were maintained at 37°C with 5% CO2 for a maximum of 6 weeks and were Mycoplasma negative as detected using Universal Mycoplasma Detection Kit (ATCC).The mouse myeloma cell lines DP42 and 5TGM1 (RRID:CVCL_VI66) were gifts from Dr. Van Ness  and Dr. Babatunde Oyajobi , respectively. The human multiple myeloma cell lines NCI-H929 (RRID:CVCL_1600), RPMI8226 (RRID:CVCL_0014), and MM1.S (RRID:CVCL_8792) were purchased from the ATCC and authenticated by short tandem repeat profiling. Upon receipt, cell lines were expanded, early passages were frozen, and vials were stored in liquid nitrogen. Cells used in all experiments were in culture for no longer than 2 months. All multiple myeloma cells were cultured in RPMI1640 medium (Corning) supplemented with Antibodies used are listed in 2 for 5–6 days. Human MKs were cultured from CD34+ cells isolated from the BM of patients with multiple myeloma. Mononuclear cells were isolated using Ficoll-paque gradient centrifugation. CD34 cells were isolated using CD34 MicroBead kit  according to manufacturer's instructions. The isolated cells were plated in Iscove's modified Dulbecco's medium (Invitrogen) supplemented with 20% BIT9500 serum substitute and 1 × StemSpan Megakaryocyte Expansion Supplement (both from StemCell Technologies). The cultures were incubated at 37°C with 5% CO2 for 14 days. Cultured murine MKs were isolated using a BSA gradient as described previously (BM cells were isolated from mouse femurs and plated in DMEM containing Glutamax (Invitrogen) supplemented with 10% FBS (GE Hyclone), 50 units/mL of penicillin, and 50 μg/mL of streptomycin and indicated concentration of murine Thrombopoietin . Cells were incubated at 37°C with 5% COeviously .Femur and tibia bones were collected from wild-type (WT) or S100A9 knockout (KO) mice and flushed with either 1 mL RPMI1640 media (used as supernatant for BM cells) or 500 μL PBS (used for soluble factors measurement) following by centrifugation at 1,500 rpm for 5 minutes. Cell pellets were discarded; supernatants were collected and used in experiments.3 cells). RAGE KO mice were provided by Dr. John Hoidal . TLR4 KO (B6(Cg)-tm1.2KarpTlr4/J, strain # 029015, RRID: IMSR_JAX:029015) mice were obtained from The Jackson Laboratory and C.B-17 scid mice from Charles River . The colony of NSG  mice was maintained in house. Tumors were established by subcutaneous injection of 10 × 106 RPMI8226 or 5 × 106 H929 cells into the right flanks of the mice or intravenous inoculation of 5 × 106 RPMI8226 or MM1.S cells into the tail vein.All animal experiments were carried out in accordance with institutional guidelines and were approved by the Institutional Animal Care and Use Committee of The Wistar Institute . All mice were housed in pathogen-free conditions. Male and female mice ages 6–8 weeks were used in experiments. C57BL/6 and FVB/N mice were purchased from Charles River Laboratories and were crossed to obtain F1 progeny of mixed C57BL/6xFVB/N background. S100A9-deficient mice were described previously . Multiplin vivo treatment studies, DP42, H929, RPMI8226, or MM1.S-bearing mice were split into two groups and treated with TQ at a dose of 30 mg/kg ad libitum in drinking water. Treatment started on days 1–3 after tumor cell injection in DP42 and subcutaneous xenograft models, on day 5 in RPMI8226 intravenous model and on day 14 in MM1.S intravenous model. TQ was given continuously until mice reached the endpoint. Control mice received vehicle in drinking water. Survival of mice was determined as they were euthanized at the humane endpoint. In in vivo combination treatment studies with other agents, RPMI8226- and H929-bearing NSG mice were split into four groups and treated with TQ (30 mg/kg ad libitum in drinking water beginning 8 hours after tumor cell injection), lenalidomide , bortezomib , ixazomib  or their combination. Treatment with anti-multiple myeloma agents started on days 13–14 after tumor cell injection. Growth of tumors on the flank was tracked with measurements using calipers twice a week. Mice were euthanized when tumors reached 400 mm2. Tumor growth rate was calculated for each mouse by determining the change in tumor size between initial measurement and measurement at the endpoint and dividing this difference by the number of days.For in vivo overexpression experiments, mice were injected with 100 μg of each mouse S100a8 and S100a9—encoding DNA plasmids pMV101-mS100A8-His and pMV101-mS100A9-His (synthesized by GenScript) in sterile water intramuscularly in the tibialis anterior muscle of both legs and subsequently electroporated using the CELLECTRA 3P adaptive electroporation device  as described previously  and the indicated specific antibodies for 20 minutes at 4°C in the dark. For detection of apoptosis, Annexin V /DAPI staining was performed according to the manufacturer's protocol. At least 10,000 events were acquired using LSRII flow cytometer (BD Biosciences). Analyses were performed using FlowJo software (BD Biosciences). MK ploidy analysis was performed using propidium iodide staining.RNA was extracted using E.Z.N.A. Total RNA purification kit (Omega Bio-Tek) and cDNA was synthesized using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Quantitative PCR was performed using SYBR Green PCR Master Mix and primers listed in Cells were lysed using RIPA buffer (Sigma-Aldrich) supplemented with 1 × Halt Protease and Phosphatase Inhibitor cocktail (Thermo Fisher Scientific). Lysates were subjected to 10% SDS-PAGE followed by transfer to nitrocellulose membrane (Bio-Rad). Membranes were blocked with 5% nonfat dry milk and incubated with primary antibodies overnight at +4°C followed by incubation with secondary horseradish peroxidase–conjugated antibodies for 2 hours at room temperature. The following primary antibodies were used: anti-His-tag (RRID: AB_2744546), anti-S100A9 (RRID: AB_2734726), anti-phospho-STAT5 (Tyr694) (RRID: AB_10544692), anti-STAT5 , anti-β-actin .Levels of S100A8/S100A9 proteins and TPO were measured using human S100A8/S100A9 and mouse S100A8/S100A9 heterodimer ELISA kits and mouse TPO ELISA kit (R&D Systems) according to manufacturer's instructions.Mouse femurs were isolated and fixed overnight in 10% formalin. The bones were then placed in a 70% ethanol solution for at least overnight before being decalcified and embedded in paraffin. Sections were cut and stained with hematoxylin and eosin (H&E) or anti-CD31 antibody .t test or Mann–Whitney test. To compare three or more groups, ANOVA with post hoc Tukey for between group comparisons were performed. Differences in kinetics of tumor growth were analyzed using two-way ANOVA. Survival was analyzed using log-rank test. P value of less than 0.05 was considered statistically significant.Statistical analysis was performed using GraphPad Prism 9 software. Tumor growth rate for each animal was calculated by its tumor size at last follow-up minus tumor size at starting treatment with antimyeloma agents and then divided by the days during this period. The average tumor growth rates were compared between groups. Differences between two experimental groups were determined using two-tailed Student The data generated in this study are available within the article and its Supplementary Data.+Gr-1+ MDSC in the BM . To determine the possible role of these receptors in S100A9-mediated MK expansion, BM cells from WT, TLR4-, or RAGE-deficient mice were cultured with S100A9 and TPO for 5 days. S100A9 caused a significant accumulation of MKs differentiated from WT BM cells. This effect was absent in BM cells from TLR4 KO mice . In contfl/fl RosaCre+ and control STAT5fl/flRosaCre− littermates were cultured with recombinant S100A9 protein for 5 days in the presence of TPO. Consistent with previous results, S100A9 caused a significant increase in MK differentiation from BM cells isolated from control STAT5fl/flRosaCre− mice. In contrast, no increase in megakaryopoiesis was observed during differentiation of STAT5-deficient progenitors , but also directly from multipotent progenitor (primarily MPP2), or long-term hematopoietic stem cell . It appe+Gr1+ cells (MDSC) as well as increased production of S100A8/S100A9 by these cells contributed to the elevated levels of S100A8/S100A9 proteins in multiple myeloma–bearing hosts. These data are in disagreement with previously reported results showing no difference in production of S100A9 protein between neutrophils and monocytes from tumor-free and 5T33 multiple myeloma–bearing mice (An increased number of BM CD11bing mice . The lacing mice . These dThe levels of S100A8/S100A9 in the BM of patient with multiple myeloma were significantly elevated when compared with those in peripheral blood of these patients as well as to the S100A8/S100A9 levels reported in healthy donors . PreviouInterestingly, we did not observe the blocking effect of TQ on megakaryopoiesis in tumor-free mice. Recent data demonstrated that while S100A8/S100A9 dimers bind and mediate their effects via TLR4, formation of S100A8/S100A9 tetramers induces conformational changes that prevent binding to this receptor . There iin vivo. Nevertheless, evaluation of HDAC4 function in multiple myeloma–bearing WT and S100A9 KO mice during disease progression as well as in vitro studies demonstrating dose-dependent response to TQ would contribute to better understanding the role of S100A8/S100A9 proteins in multiple myeloma biology. Ghavami and colleagues demonstrated that S100A8/S100A9 proteins used at a concentration of 10 μg/mL induced growth of several breast tumor cell lines including MCF-7, MDA-MB231, and SHEP, whereas at higher concentrations it did not enhance cellular proliferation (Intracellular S100A8/S100A9 is involved in the suppressive activity of MDSC and macrophages . In contferation . Low conferation . We did in vivo with the small-molecule inhibitor ABR-238901 reduced angiogenesis (The BM microenvironment in multiple myeloma is characterized by increased microvessel density. The production of proangiogenic molecules is increased and the production of angiogenic inhibitors is suppressed, leading to an “angiogenic switch.” Current data suggest that the increased BM angiogenesis in multiple myeloma is due to the aberrant expression of angiogenic factors by multiple myeloma cells and cells in the TME . A previogenesis . The mecogenesis .Our results demonstrated a novel mechanism by which S100A8/S100A9 can regulate BM TME in multiple myeloma via upregulation of MKs. MKs are not only precursors of platelets but are known to regulate production of multiple cytokines that promote angiogenesis. Our data suggest that targeting S100A9 with TQ has strong antitumor effects that are mediated by a blockade of MK expansion and inhibition of angiogenesis. This effect, which is independent of the adaptive immune system, supports the further development of S100A9 inhibition with TQ in the clinic.Supplementary Tables S1 and S2Supplementary Table 1. Antibodies used in the study.Supplementary Table 2. Primers used in the study.Click here for additional data file.Figure S1MK count in the BM of tumor-free mice treated with TQ.Click here for additional data file.Figure S2Expression of S100A8 and S100A9 proteins using in vivo electroporation technique.Click here for additional data file.Figure S3Effect of TPO and S100A9 on in vitro MK differentiation.Click here for additional data file.Figure S4Effect of S100A9 protein on mouse MKs.Click here for additional data file.Figure S5BM angiogenesis in tumor-free and MM-bearing mice treated with TQ.Click here for additional data file.Figure S6Mechanism of S100A9 effect on MK differentiation.Click here for additional data file.Figure S7Effect of TQ in S100A9KO MM-bearing mice.Click here for additional data file.Figure S8Effect of TQ on MM cells.Click here for additional data file.


Background: Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of macrophage phenotype transformation.Method: Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSORT, ESTIMATE, support vector machine (SVM), random forest (RF), and weighted correlation network analysis (WGCNA) were applied to bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO).Result: Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages and M2 macrophages can be transformed into M1 macrophages. The ROC curve values of the six genes in the test group were statistically significant (AUC (IL1RN): 0.899, 95% CI: 0.764-0.990; AUC (NRP1): 0.817, 95% CI: 0.620-0.971; AUC (TAGLN): 0.846, 95% CI: 0.678-0.971; AUC (SPARCL1): 0.825, 95% CI: 0.620-0.988; AUC (EMP2): 0.808, 95% CI: 0.630-0.947; AUC (ACTA2): 0.784, 95% CI: 0.591-0.938). The atherosclerosis prediction model showed significant statistical significance in both the train group  and the test group .High M1, NRP1High M2, ACTA2High M2/M1, EMP2High M1/M1, SPACL1High M2/M1 and TAGLNHigh M2/M1 macrophages play key roles in the occurrence and development of arterial atherosclerosis. These marker genes of macrophage phenotypic transformation can also be used to establish a model to predict the occurrence of atherosclerosis.Conclusions: IL1RN Atherosclerosis (AS) is a local chronic inflammatory disease of the artery wall . In AS, With the improved understanding of atherosclerosis by researchers, traditional lipid-lowering and anti-inflammatory treatments are being replaced by targeted treatments . ResearcIn this study, we analyzed the phenotypic transformation of macrophages in atherosclerosis through pseudotime analysis. We identified a class of macrophages that simultaneously express M1 and M2 macrophage marker genes and can transform into M1 or M2 macrophages. Finally, we selected the genes with the most obvious differential expression to build an atherosclerosis prediction model based on the results of macrophage pseudotime analysis. These genes may provide new ideas for the targeted treatment of atherosclerosis.https://www.ncbi.nlm.nih.gov/). We used the “WGCNA” package [We downloaded GSE43292 (training group) and GSE28829 (test group) from the GEO database . We removed cells with fewer than 200 genes, more than 7,000 genes, or more than 10% mitochondrial genes. Analysis was performed on 49576 filtered cells. Using the “LogNormalize” method, gene expression was normalized and scaled. In each sample, the top 2000 highly variable genes (HVGs) were identified using the “vst” method after data normalization. After identifying significant principal components (PCs), PCA was applied. Batch correction was performed using the “Harmony” R package (version 0.1.0) to avoid batch effects resulting from sample identity that could disrupt downstream analysis. Finally, 50 PCs were selected for t-distributed stochastic neighbor embedding (t-SNE) analysis. We set “FindClusters” with a resolution of 2.0 to divide cells into 45 different clusters, which were divided into 9 cell types, and conducted manual inspection according to the results of “FindAllMarkers”.We downloaded the GSE159677 single-cell dataset from the GEO database  were visualized, and a heatmap of macrophage subtypes was drawn.We analyzed the trajectory of M1 macrophages and M2 macrophages with the “Monocle” package  and drewThe authors agree for publication.https://www.ncbi.nlm.nih.gov/geo/).The data for this study were derived from the GEO database (https://panglaodb.se/); and DCs: clusters 26, 41 and 42, expressing CD1C [https://panglaodb.se/).Forty-five clusters could be assigned to known cell lineages according to the marker genes defined in a previous study . We useding CD1C , CLEC9A ing CD1C , LILRA4 Thirteen clusters could be assigned to known cell lineages on the basis of marker gene expression . We usedAccording to the trajectory analysis of M1 macrophages and M2 macrophages, we found that M2 macrophages can transform into M1 macrophages over time and that this trajectory can be divided into 5 states –3C. By aAccording to the trajectory analysis of M1 macrophages and M2/M1 macrophages, we found that M2/M1 macrophages can transform into M1 macrophages over time and that the trajectory could be divided into 5 states –4C. By aAccording to the trajectory analysis of M2 macrophages and M2/M1 macrophages, we found that M2/M1 macrophages can transform into M2 macrophages over time and that the trajectory could be divided into 5 states –5C. By aA total of 1086 AS-characteristic genes  from WGCNA and 223 DEGs in the macrophage trajectory analysis were obtained. Of these, we identified 50 intersecting genes –6C. The The nomogram indicated that the probability of atherosclerosis increased to 90% when the total score of 6 disease-characteristic genes reached 160 and 10% when it reached 120 . The calThe NRP1 and IL1RN genes were significantly upregulated in both the training group and test group, while TAGLN, SPARCL1, EMP2 and ACTA2 were significantly downregulated in both the training group and test group , 8B. TheAtherosclerosis plays an important role in cardiovascular disease. Its pathological mechanisms include dysfunction of the endothelial cell barrier, lipid accumulation, abnormal angiogenesis, and local chronic inflammatory reaction caused by immune cell infiltration , among others –39. AmonHigh macrophages, as a subtype of proinflammatory macrophages, are the main source of MMPs and inflammatory cytokines, which strengthens the formation of thoracic aortic aneurysm [High M1 macrophages.The IL1RN gene has been found to have variable numbers of an 86 base pair (bp) tandem repeat in intron 2 , and thianeurysm . It was High M2 macrophages may be a major risk factor for the formation and stability of atherosclerosis.Neuron-1 (NRP1) belongs to the neurotransmitter family . NRP1 isHigh M2/M1 macrophages and found that they can transform into M1 and M2 macrophages and that the expression of ACTA2 decreased significantly during this period. This indicates that ACTA2High M2/M1 macrophages may be involved in the development of atherosclerosis.According to previous studies, ACTA2 is a marker gene of vascular smooth muscle cells . Some stin vitro, the more obvious the expression of pathological angiogenesis-related pathways was [High M2/M1 macrophages can not only promote the formation of pathological blood vessels, resulting in the destruction of plaque stability, but also become proinflammatory macrophages (EMP2Low M1 macrophages) through phenotypic transformation.EMP2 is expressed at a high level in a large number of human tissues, including adult ovarian, heart, lung and intestinal tissues and fetal lung tissues . The proways was –65. Someways was . Based oHigh M2/M1 macrophages may play a role in inhibiting the formation of carotid atherosclerosis and maintaining the stability of carotid plaques by inhibiting angiogenesis.Secreted acidic cysteine-rich protein-1 (SPARCL1) belongs to the matrix cell protein SPARC family and is an extracellular matrix (ECM) glycoprotein . At presHigh macrophages (in the M2/M1 macrophage subgroup) may be similar to ACTA2High macrophages and originate from vascular smooth muscle cells. TAGLNHigh M2/M1 macrophages can transform into TAGLNLow M1 and TAGLNLow M2 macrophages, and the expression of TAGLN decreases significantly during this period.It is well known that the smooth muscle cell marker TAGLN (SM22α) is downregulated in the pathogenesis of atherosclerosis, restenosis, abdominal aortic aneurysm and other arterial diseases . Here, wHigh M1, IL1RNHigh M1, NRP1High M2, ACTA2High M2/M1, EMP2High M1/M1, SPACL1High M2/M1 and TAGLNHigh M2/M1 macrophages. This study is the first to use these macrophage marker genes to construct a model for predicting atherosclerosis. The expression trend of these genes in bulk transcriptome data is consistent with the expression trend of macrophage pseudotime analysis, which again proves the accuracy of these genes as disease-characteristic genes in atherosclerosis.We identified 6 kinds of macrophages that may be related to the occurrence and development of atherosclerosis: IL1RNHigh M1 macrophages, NRP1High M2 macrophages, ACTA2High M2/M1 macrophages, EMP2High M1/M1 macrophages, SPACL1High M2/M1 macrophages and TAGLNHigh M2/M1 macrophages play a key role in the occurrence and development of arterial atherosclerosis. These macrophages may become target cells for treating atherosclerosis in the future. These macrophage marker genes can also be used to build a model to predict atherosclerosis.IL1RNSupplementary Table 1Supplementary Table 2Supplementary Table 3Supplementary Table 4Supplementary Table 5Supplementary Table 6


The modestly efficacious HIV-1 vaccine regimen (RV144) conferred 31% vaccine efficacy at 3 years following the four-shot immunization series, coupled with rapid waning of putative immune correlates of decreased infection risk. New strategies to increase magnitude and durability of protective immunity are critically needed. The RV305 HIV-1 clinical trial evaluated the immunological impact of a follow-up boost of HIV-1-uninfected RV144 recipients after 6–8 years with RV144 immunogens . Previous reports demonstrated that this regimen elicited higher binding, antibody Fc function, and cellular responses than the primary RV144 regimen. However, the impact of the canarypox viral vector in driving antibody specificity, breadth, durability and function is unknown. We performed a follow-up analysis of humoral responses elicited in RV305 to determine the impact of the different booster immunogens on HIV-1 epitope specificity, antibody subclass, isotype, and Fc effector functions. Importantly, we observed that the ALVAC vaccine component directly contributed to improved breadth, function, and durability of vaccine-elicited antibody responses. Extended boosts in RV305 increased circulating antibody concentration and coverage of heterologous HIV-1 strains by V1V2-specific antibodies above estimated protective levels observed in RV144. Antibody Fc effector functions, specifically antibody-dependent cellular cytotoxicity and phagocytosis, were boosted to higher levels than was achieved in RV144. V1V2 Env IgG3, a correlate of lower HIV-1 risk, was not increased; plasma Env IgA , a correlate of increased HIV-1 risk, was elevated. The quality of the circulating polyclonal antibody response changed with each booster immunization. Remarkably, the ALVAC-HIV booster immunogen induced antibody responses post-second boost, indicating that the viral vector immunogen can be utilized to selectively enhance immune correlates of decreased HIV-1 risk. These results reveal a complex dynamic of HIV-1 immunity post-vaccination that may require careful balancing to achieve protective immunity in the vaccinated population.Trial registration: RV305 clinical trial . ClinicalTrials.gov Identifier: NCT00223080. One strategy for improving vaccine-elicited antibody durability is booster immunization. However, the impact of boosting on the quality of the polyclonal antibody response is not fully understood and may alter vaccine efficacy. We discovered that canarypox vector boost (ALVAC-HIV vectored vaccine component only) drove the recall of HIV-1-specific inverse correlate of risk (V2 IgG) and promoted more durable immunity. We found that delayed boosting increased the concentration of putative protective V1V2-specific IgG circulating in blood, enabling 80% of vaccinees to achieve this level in RV305 compared to 63% in RV144. In contrast to Env IgG1 and IgA1, Env IgG3 was not boosted. However, Env IgG1 correlated with the magnitude of the ADCP response, demonstrating that antibody function can be elevated independent of IgG3 and IgA1. By including a delayed boost as part of a HIV-1 prime-boost vaccine strategy, vaccine-elicited antibodies can reach the putative protective threshold in a larger proportion of the population. However, a second immunogen boost within a 6-month interval shifts the antibody isotype/subclass profile, resulting in decreased antibody functions. A canarypox prime regimen can drive antibody specificity and function. Our study informs selection of immunogen types and immunization intervals for HIV-1 vaccine developers to elicit protective immunity. Elicitation of durable, broadly protective immune responses is a key goal for human immunodeficiency virus type-1 (HIV-1) vaccine development. Results from the modestly protective phase III RV144 HIV-1 vaccine efficacy trial in Thailand  catalyzed efforts to define immune correlates of risk, which lent insights into the mechanistic underpinnings of protection  and variIn a previous study comparing two ALVAC vector-prime/protein-boost vaccine regimens, utilizing different strains for both the vector and protein immunogens , we found that the viral sequence influenced antibody specificity, with higher elicitation of V2-specific antibodies observed in HVTN 097  compared to HVTN 100 (used an adapted clade C regimen) . These r4β7 integrin binding, which has been postulated as a potentially protective mechanism to inhibit viral transmission : RV144 week 26: AE.A244 V1V2 tags , gp70_B.CaseA_V1_V2 , gp70_B.CaseA2 V1/V2/169K , RV305 week 2: AE.A244 V1V2 tags , gp70_B.CaseA_V1_V2 , gp70_B.CaseA2 V1/V2/169K , RV305 week 26: AE.A244 V1V2 tags , gp70_B.CaseA_V1_V2 , gp70_B.CaseA2 V1/V2/169K  (S4 Table). IgG V1V2 concentrations were not boosted compared to RV144 by the ALVAC-HIV only regimen, consistent with the expectation for protein (RV144) versus ALVAC (RV305) immunizations . After protein boosting, a higher percentage of vaccinees had IgG gp70_B.CaseA_V1_V2 concentrations above the putative protective threshold associated with vaccine efficacy (2.98 μg/mL) compared to RV144   co-administered with AIDSVAX B/E  [a recombinant bivalent combination of HIV-1 gp120 subtype B (MN strain) and subtype E (A244 strain) proteins adjuvanted with alum] (group 1), (2) AIDSVAX B/E alone (group 2), or (3) ALVAC-HIV (vCP1521) alone (group 3) delivered intramuscularly at weeks 0 and 24.The RV305 clinical trial   is a ranAll assays were performed blinded to treatment status. All 162 clinical trial participants were studied for the presence of IgG subclass binding antibody responses using enzyme-linked immunosorbent assays (ELISA). The first 70 subjects enrolled in this study were profiled for vaccine-induced humoral responses in binding antibody multiplex assays (BAMA), linear peptide microarray assays, ADCP assays, and ADCC assays as outlined below. Infectious virion capture assays were performed on samples from 15 subjects. Selection of study subjects was done by block randomization. The study arms were relatively well distributed, with the cohort of 70 participants consisting of 20 vaccine and 3 placebo recipients from Group 1 [ALVAC-HIV/AIDSVAX B/E (combination) regimen], 18 vaccine and 6 placebo recipients from Group 2 (AIDSVAX only regimen), and 19 vaccine and 4 placebo recipients from Group 3 (ALVAC-HIV only regimen).Plasma was assessed for HIV-1 Env binding IgG1-IgG4 by enzyme linked immunosorbent assay (ELISA). Briefly, U-bottom 2HB plates (Thermo Fisher Scientific) were coated with A244 gD gp120, gp70 V1V2 92TH023 and gp70 V1V2 case A2 scaffold proteins at 3 μg/mL in Dulbecco’s phosphate buffered saline (D-PBS) (Sigma-Aldrich) at 4°C overnight. Wells were washed three times with wash buffer  using Microplate Washer ELx405 (BioTek) and blocked with 220 μL/well of blocking buffer  for two hours at room temperature. Plasma samples were initially diluted at 1:100 (A244 gD gp120) or 1:25 (gp70 scaffold proteins) in blocking buffer and two-fold serial dilutions were performed. Each well received 100 μL of diluted specimen and plates were incubated for 2 hours at room temperature. All wells were washed 5 times with wash buffer and 100 μL/well of mouse anti-human IgG1, IgG2, IgG3, or IgG4 (1 μg/mL) (Bethyl Laboratories) was added and incubated for 1 hour at room temperature. Plates were washed with wash buffer and horseradish peroxidase (HRP)-conjugated anti-mouse IgG (Bethyl laboratories) was added and incubated for 1 hour at room temperature. Wells were washed and ABTS ELISA substrate (KPL) was added for 1 hour and then plates were read at 405 nm absorbance on a Spectramax 340 PC ELISA reader (Molecular Devices). Geometric mean titers (GMT) were calculated from final dilutions giving a positive result  from individual samples.th percentile MFI-Blank of all baseline samples [and a minimum of 100], and three-fold over the MFI [before and after blank bead subtraction] of the matched baseline sample. HIV-1 Env gp120, gp140, and V1V2 breadth scores were calculated as the mean of the MFI-Blank of the individual antigens in a given panel, for samples that had data for all antigens in the panel. For calculations of area under the magnitude breadth curves (AUC-MB) MFI-Blank values for negative responses were set to 1, and values greater than 22000 were set to 22000, to help analyze data from positive responses, and those within the linear range of the assay.Plasma binding antibody reactivity to HIV-1 Envelope gp120, gp140, and V1V2 breadth panel antigens, representing geographic and global HIV-1 diversity , was detth percentile of all baseline samples and three-fold over participant baseline. Magnitude breadth (MB) scores for binding to linear epitopes were computed in R using the mdw package using the maximum diversity weight method.Mapping of plasma IgG to linear epitopes was performed by peptide microarray as previously described ,82, withDepletion and purification of IgG antibodies from plasma samples was performed using a Protein G HP MultiTrap column  as previously described .92TH023-Tomato [th percentile baseline antigen-specific cutoff and three times over the participant-specific baseline. If no participant-matched baseline sample was available to test, a cutoff of three times over the median of all baselines was used. CD4 binding-site-specific mAb CH31 was included as a positive control, and influenza receptor binding site mAb CH65 was used as a negative control. Assays were performed in duplicate or triplicate for each sample.ADCP assays were performed as previously described, with modifications . Uptake 3-Tomato ,87  phagocytosis scores were calculated using a 5 point, 5-fold dose response curve from 50 μg/mL to 0.08 μg/mL. AUC values from vaccination groups 1 and 2 were aggregated and analyzed for correlation with Con S gp140 IgG subclass BAMA MFI.CM235-tdTomato fluorescently labeled virions in human monocytes [Native IgG3 monoclonal antibodies were isolated by antigen-specific single memory B cell sorting of peripheral blood mononuclear cells from RV305 vaccinees using A244 gp120 fluorescently labeled probes as previously described . Immunogonocytes ,90.TH023 virions to form antibody-virion immune complexes, which were passed through a protein G column. Flow through virus was added to TZM-bl cells and capture was calculated as the percentage of flow through virus infection of TZM-bl cells relative to a no antibody control. Positive controls included HIVIG, V1V2-directed quaternary mAb PG9 IgG1, CD4 binding site-directed mAb CH31 IgG1, and gp41-directed mAb 7B2 IgG1. Respiratory Syncytial Virus (RSV)-specific mAb Palivizumab IgG1 was included as a negative control in each assay. Assays were performed in duplicate for each study participant. The positivity cutoff for each virus was defined as the mean plus two standard deviations of the fold change from baseline (RV305 week 0) to week 2 and week 26 (combined) for the placebo group.Infectious virion capture assays were performed as previously described . BrieflyCCR5 CD4+ target cells (NIH AIDS Reagent Program) infected with HIV-1 AE.TH023.6, AE.427299, AE.CM235 infectious molecular clone (IMC) viruses  containing a Renilla Luciferase (Luc) reporter gene [The ability of plasma samples to mediate killing of CEM.NKRter gene  was measter gene . Plasma ter gene  were useter gene .+ and CD8+ T cell function was assessed using intracellular cytokine staining as previously described [http://github.com/RGLab/COMPASS) [The RV305 T cell data set, published in a prior manuscript , was useescribed . A set oCOMPASS) .The RV305 neutralization data set, originating from a prior publication , examinehttps://www.R-project.org/). R package ggplot2 was used for generating plots.A pre-specified statistical analysis plan outlined the primary analysis hypotheses and objectives for this study. For comparison of response magnitude, between two time points, the Wilcoxon signed rank Test was used, and for comparisons between groups, the Wilcoxon rank sum test was used. The Benjamini and Hochberg (1995) false discovery rate method was used to correct for multiple comparisons for the 70 tests of the pre-determined comparisons included in the primary analysis. All tests were two-sided, and differences were considered statistically significant for FDR-corrected p < 0.05. Primary analyses were performed in SAS (Copyright (c) 2002–2012 by SAS Institute Inc., Cary, NC, USA. SAS (r) Proprietary Software 9.4 (TS1M3)) or R statistical software (R Core Team (2018). URL S1 FigA) Heatmap of median RV305 week 2 (left panel) and week 26 (right panel) plasma binding to peptides of different gp120 strains (median for 70 RV305 participants). Each row represents a single strain included in the epitope mapping peptide library. Group median binding magnitude to each strain is shown. Color intensity is proportional to binding intensity, with the darker colors indicating higher binding and the lighter colors indicating lower binding. (B) Spider plots demonstrating breadth of C1.2, V2 hotspot (V2.hs), V3, and C5.2 targeting against consensus and virus strain peptides for each vaccine group at RV305 week 2 (top panel) and week 26 (bottom panel). (C) Log2 fold difference in linear peptide binding to vaccine strain sequence (B.MN) at RV305 week 26 compared to RV305 week 2. Horizontal bar pointing to the left of the x = 0 line  indicates a higher response magnitude measured at RV305 week 2 compared to RV305 week 26; horizontal bar pointing the right indicates a higher response magnitude measured at RV305 week 26 versus RV305 week 2. (D) Log2 fold difference in B.MN linear peptide binding of group 1 versus group 2 plasma at RV305 weeks 2 and 26. Horizontal bar pointing to the left of the x = 0 line indicates a higher response magnitude measured in the AIDSVAX B/E only group; horizontal bar pointing to the right indicates a higher response magnitude measured in the Combination group.((TIF)Click here for additional data file.S2 Figth percentile of all baseline sample binding to the peptide and the binding signal (log 2 fold difference over baseline) was greater than 1.58, which represents a 3-fold difference post- and pre-immunization. Filled circles represent positive responders, and open triangles represent non-responders.A response was considered positive if the intensity of binding to each peptide was greater than the 95(TIF)Click here for additional data file.S3 FigPlasma IgG antibodies to the CD4 binding site (CD4bs) region of gp120 were assessed by BAMA using resurfaced stabilized gp120 core (RSC3) and CD4 binding site knockout mutant (RSC3 delta371/P363N) proteins that detect CD4bs antibodies of the VRC01 class. Differential binding plots display BAMA FI-Bkgd-Blank values for IgG binding to RSC3 (y-axis) and RSC3 delta371/P363N mutant (x-axis) proteins at RV144 week 26 and RV305 weeks 0, 2, 24, 26, 48, and 72. The diagonal dashed gray line indicates a wild-type to mutant binding ratio of 2.5 (cut-off for positivity). The CD4bs broadly neutralizing antibody VRC01 was used as a positive control for RSC3/RSC3 delta371/P363N differential binding. The glycan-specific monoclonal antibody 2G12 was used as a negative control, which showed equivalent binding to wild-type versus mutant. Open gray triangles represent non-responders with differential binding ratios of ≤ 2.5, indicating the lack of RSC3-reactive CD4bs specificities. Response rate  is shown at the top of each plot.(TIFF)Click here for additional data file.S4 FigPrevalence of CD4-induced (CD4i) IgG antibodies among RV305 vaccine and placebo recipients. Differential binding plots displaying BAMA FI-Bkgd-Blank values for IgG binding to YU2 gp120 WT (y-axis) and YU2 gp120 I420R mutant (x-axis) proteins at RV144 week 26 and RV305 weeks 0 and 2. The diagonal dashed gray line indicates a wild-type to mutant binding ratio of 2.5 (cut-off for positivity). The CD4-induced (CD4i) monoclonal antibody 17b was used as a positive control for YU2 gp120 WT/I420R differential binding. Colored symbols represent positive responders with differential binding ratios of ≥ 2.5, indicating the presence of CD4i specificities. Response rate  is shown at the top of each plot.(TIFF)Click here for additional data file.S5 Figth and 75th percentiles among positive responses.V1V2 concentrations were extrapolated by 4-parameter logistic (4-PL) regression of V2-specific monoclonal antibody CH58 standard curve titrations run in each BAMA. Concentrations are plotted in μg/mL for (A) placebo recipients (i.e. RV144 vaccine group only) and (B) for each RV305 vaccine group across the studied immunogenicity time points, with each dot representing the concentration for a single plasma sample. The midline of the box plot denotes the median concentration, and the ends of the box plot denote the 25(TIFF)Click here for additional data file.S6 FigMB plots characterizing IgG breadth (response rate) (y-axis) and magnitude (log2 fold difference post second boost / post first boost binding intensity) (x-axis) against a cross-clade panel of 11 V2 hotspot peptides measured by linear peptide microarray. Solid curves are the median MB at RV305 week 2 (red) and week 26 (green). AUC values summarize the MB at a given time point across the entire range of binding values on the x-axis.(TIFF)Click here for additional data file.S7 FigA) HIV-1-specific plasma IgG levels to vaccine-matched gp120 Envelope  and V1V2 (AE.A244 V1V2 tags) primary antigens determined by BAMA. Response rates (top panel) and binding magnitudes (bottom panel) are plotted for each group at two weeks post final RV144 vaccination (week 26) and two weeks post first and second RV305 boosts . Box plots (bottom panel) denote the median (midline) and interquartile ranges among positive responses. Solid dots depict positive responders, and open gray triangles depict non responders. (B) IgG breadth scores against the global gp120 breadth panel, calculated for each participant as the mean of the MFIs across the 8 antigens in the panel. Box and whisker plots show the median and interquartile ranges of scores across the Combination and AIDSVAX B/E only groups. Differences in median breadth scores (aggregated for the Combination and AIDSVAX B/E only groups) across post RV144 boost (week 26) and RV305 boost time points (weeks 2 and 26) were assessed using the two-sided Wilcoxon Signed Rank Test (C) Magnitude-breadth plot of IgG binding antibody responses to the gp120 breadth panel among Combination and AIDSVAX B/E only positive responders at 2 weeks post final RV144 vaccination (week 26) and 2 weeks post first and second RV305 boosts (weeks 2 and 26). Breadth is defined as the proportion of antigens in the 8 antigen gp120 breadth panel (y-axis) with log10 (MFI-blank) greater than the threshold on the x-axis. Dashed lines display MB curves for each individual plasma sample measured at RV144 week 26 (turquoise), RV305 week 2 (pink), and RV305 week 26 (orange). Solid bold lines show the median MB among positive responders at each immunization time point. AUC values summarize the MB at a given time point across the entire range of MFI values. (D) Vaccine-elicited IgG1 binding antibody response rates and binding magnitudes to the four antigens in the primary analysis measured by BAMA. (E) gp120 and (F) gp140 (G) gp70 V1V2 IgG1 MB plots, comprising data combined for Combination (ALVAC-HIV + AIDVAX B/E) and AIDSVAX B/E positive responses.(ank Test . (C) Mag(TIF)Click here for additional data file.S8 Fig2 fold change, with the midline of the box plots indicating median and ends of the box plots indicating the 25th and 75th percentiles. The whiskers denote the minimum and maximum data points no more than 1.5 times the interquartile range (IQR). Data points that lie outside of the median ± 1.5 times the IQR are shown as black dots. Criteria for the fold (wk26/wk72) calculation: 1) response is positive at week 26, 2) MFI < 23000 at week 26, 3) MFI > 100 at week 72. Antigens with greater than or equal to 6 data points meeting this criteria for both the Combination (ALVAC-HIV/AIDSVAX B/E) and AIDSVAX B/E only groups are plotted for each vaccine boost regimen. Proximity of the bar to the y-axis indicates better durability.Fold decline in IgG antibody binding magnitude to gp120 antigens from two weeks post last RV305 boost (week 26) to 12 months post last boost (week 72). Results are presented as log(TIFF)Click here for additional data file.S9 FigELISA IgG1-IgG4  reciprocal titers to A244 gD, gp70V1V2 92TH023 scaffold, and gp70V1V2 Case A2 scaffold are shown for RV305 recipients (n = 162) randomized to receive two additional boosts of either ALVAC-HIV + AIDSVAX B/E , AIDSVAX B/E , or ALVAC-HIV , 6–8 years post last RV144 vaccination (RV305 regimen). Arrows indicate time of immunizations. Error bars depict 95% confidence intervals.(TIF)Click here for additional data file.S10 FigDot plots illustrating IgG3 positive responders at RV305 weeks 26 and 72 . Vertical lines separate Env (gp140 +gp120), V1V2, and other (V3 and Gag) antigens.(TIFF)Click here for additional data file.S11 Figth and 75th percentiles, and the whiskers denote minimum and maximum data points no more than 1.5 times the interquartile range (IQR). Data points that lie outside of the median ± 1.5 times the IQR are shown as black dots. The criteria for the percent decline calculation are that the response is positive at week 26 and the MFI is less than 23,000 at week 26. Antigens with at least three data points meeting this criteria for the Combination (ALVAC-HIV/AIDSVAX B/E) and AIDSVAX B/E only groups are plotted. Proximity of the bar to the y-axis indicates better durability.Percent decline of IgG3 response magnitude (MFI) to V1V2, gp120, and gp140 antigens from RV305 week 26 to week 72 (2 weeks post second boost to 12 months post second boost). Box plots depict the median, 25(TIFF)Click here for additional data file.S12 FigA) IgG2 and (B) IgA2 responses to vaccine strain immunogens in the RV144 prime (92TH023 gp120) and boost  and CRF01_AE A244 V1V2 are plotted for RV305 recipients in each group at RV144 peak (week 26) and two weeks after the first and second RV305 boosts (weeks 2 and 26). The number of positive responders for each subclass is shown over the total number of individuals analyzed at each time point, represented as a bar graph displaying percent responders. Box plots depict the median (midline) and 25th and 75th percentiles, with the colored symbols indicating the response magnitude for each positive responder. Open gray triangles indicate non-responders.((TIF)Click here for additional data file.S13 Figth and 75th percentiles for positive responses. Solid dots depict positive responders, and open gray triangles depict non responders. Gray lines connect samples from the same donor.A luciferase-based ADCC assay was used to profile the ability of plasma antibodies from 70 RV305 participants to mediate killing of cells infected with AE.CM235, AE.TH023, and AE.427299 HIV-1 infectious molecular clones. RV305 baseline and post first and second boost  plasma was diluted 5-fold, and results are reported as AUC for each time point, plotted for each vaccine boost regimen. Box plots show the distribution of AUC values; the midline denotes the median and the ends of the box plot denote the 25(TIFF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.S8 Table(PDF)Click here for additional data file.S9 Table(PDF)Click here for additional data file.S10 Table(PDF)Click here for additional data file.S11 Table(PDF)Click here for additional data file.S12 Table(PDF)Click here for additional data file.S13 Table(PDF)Click here for additional data file.S14 Table(PDF)Click here for additional data file.S15 Table(PDF)Click here for additional data file.