Hepatic circadian gene transcription is tightly coupled to feeding behavior, which has a profound impact on metabolic disorders associated with diet-induced obesity. Here, we describe a genomics approach to uncover mechanisms controlling hepatic postprandial gene expression. Combined transcriptomic and cistromic analysis identified hundreds of circadian-regulated genes and enhancers controlled by feeding. Postprandial suppression of enhancer activity was associated with reduced glucocorticoid receptor (GR) and Forkhead box O1 (FOXO1) occupancy of chromatin correlating with reduced serum corticosterone levels and increased serum insulin levels. Despite substantial co-occupancy of feeding-regulated enhancers by GR and FOXO1, selective disruption of corticosteroid and/or insulin signaling resulted in dysregulation of specific postprandial regulated gene programs. In combination, these signaling pathways operate a major part of the genes suppressed by feeding. Importantly, the feeding response was disrupted in diet-induced obese animals, which was associated with dysregulation of several corticosteroid- and insulin-regulated genes, providing mechanistic insights to dysregulated circadian gene transcription associated with obesity. The liver is an essential organ regulating metabolic homeostasis in response to fluctuations of metabolites induced by daily rhythms of food intake. Homeostasis is maintained by precise dynamic regulation of signaling pathways controlling a wealth of enzymatic reactions involving lipid, bile acid, amino acid and glucose synthesis, storage, and redistribution in hepatocytes. Precise temporal expression of hepatic enzymes is crucial for metabolic homeostasis; a major part of circadian hepatic protein expression is regulated by precisely timed gene transcription. Here, we use a genomics approach to identify genes and regulatory regions of the genome involved in feeding-regulated gene expression. We find that transcription factors acting downstream of glucocorticoid and insulin signaling are enriched at regulatory regions repressed by feeding. Importantly, insulin and glucocorticoid signaling operate to cooperatively control the majority of feeding-mediated gene repression, and these signaling pathways are dysregulated in diet-induced obesity impacting dynamic hepatic gene expression. Precise temporal expression of hepatic enzymes is crucial for metabolic homeostasis, and a major part of hepatic circadian protein synthesis is regulated by precisely timed gene transcription and mRNA translation . This isHousing rodents in a 12-hour light/dark cycle and restricting feeding to the active phase (nighttime) is associated with rhythmic hepatic chromatin remodeling , transcrBmal1, Cry1, Reverba, and Dbp were not significantly different from levels observed in fed mice. In contrast, the level of mRNAs coding for key metabolic enzymes  and a protein involved in lipoprotein and triglyceride metabolism angiopoietin-like 4 (ANGPTL4) was dependent on food intake  and the physical active phase  with and without access to food . Livers d intake .n = 472) and repressed (n = 432) at a false discovery rate (FDR) < 0.01 by the transition from ZT10 to ZT14-fed , fatty acid metabolism , and cholesterol uptake . Q4 and Q5 contain genes such as Gck, Srebp1, Fasn, and Agpat2 (up-regulated by feeding) involved in glucose uptake and fatty acid synthesis and storage and genes such as Pck1 and G6pc involved in gluconeogenesis (down-regulated by feeding). Gene ontology (GO) analysis showed that genes regulated independent of feeding are involved in protein folding, response to heat, and circadian regulation of gene expression  and unfed (n = 2) mice at ZT14. To account for possible differences in the digestion efficiency of DNase, we sequenced libraries from nuclei digested with two different concentrations of DNase I (60 U and 80 U) and subsequently combined all the sequencing data to identify DNase hypersensitive sites (DHSs) irrespective of treatment. . In addition, we found enrichment of DHSs associated with feeding–up-regulated H3K27Ac near feeding-induced genes compared to DHSs associated with unchanged H3K27Ac . Likewise, DHSs associated with feeding–down-regulated H3K27Ac was enriched near feeding-repressed genes compared to DHSs associated with unchanged H3K27Ac . Collectively, this indicates that the identified DHSs are involved in regulating nearby gene expression, and to uncover transcription factors involved in the feeding response, we mined enriched DNA sequences at DHSs associated with feeding-regulated H3K27Ac.DNase-accessible regions of chromatin harbor putative binding sites for transcription factors regulating gene expression . To iden feeding . Genome-g . H3K27Ac ChIP-seq tags were subsequently quantified at these DHSs from livers isolated at ZT10 (n = 3), ZT14-unfed (n = 3), and ZT14-fed (n = 3) and by hierarchical clustering grouped into two major clusters according to the circadian rhythm and four subclusters according to the feeding status  . This anThe DHSs associated primarily with feeding-regulated H3K27Ac (clusters 2 and 4) were enriched for motifs known to interact with the GR, cAMP Responsive Element Binding Protein (CREB), Forkhead box transcription factors (FOX), GATA, and direct repeats (DR-1) known to interact with transcription factors such as Hepatocyte Nuclear Factor 4 (HNF4), Retinoid X receptor (RXR), and peroxisome proliferator-activated receptor (PPAR) . QuantifCollectively, the DNA motif analysis indicated that circadian H3K27Ac is regulated by a combination of core clock transcription factors , heat shock responsive transcription factors, and transcription factors regulated by endocrine signaling .To correlate motif enrichment analysis to transcription factor occupancy, we chose to map transcription factors potentially interacting with DHSs associated with feeding-repressed H3K27Ac . The ideChIP-seq identified more than 10,000 GR peaks and more than 8,000 FOXO1 peaks in livers from unfed mice at ZT14. De novo motif analysis of the individual transcription factor ChIP-seq peaks identified their cognate DNA-binding motif in addition to motifs for the linage-determining transcription factors HNF4 and C/EBP , suggestPck1, Angptl4, Tat, and Insig2). Notice that most regions are associated with considerable co-occupancy of GR and FOXO1.Correlation with feeding-regulated genes demonstrated that more than 80% of the feeding-repressed genes were associated with at least one GR and/or FOXO1-binding site within 50 kb of the TSS , correspIn summary, these data indicate that a large fraction of DHSs associated with feeding-repressed H3K27Ac are occupied by GR and FOXO1 in the preprandial state. Feeding leads to reduced occupancy of GR and FOXO1, possibly resulting in postprandial repression H3K27Ac and attenuated transcription of nearby genes.Pck1 and Insig2 in response to feeding was reversed by dex injection  after dex injection. We observed a general trend of increased H3K27Ac at the DHSs occupied by GR, in contrast to DHSs not occupied by GR . This suaffected . Similarreatment , indicatTo systematically compare the constituents of DHSs associated with differential H3K27Ac in response to glucocorticoid treatment, we divided DHSs occupied by GR into three groups depending on the H3K27Ac responsiveness to dex . The DHSTat, Fkbp5, and Pck1 expression was restored or partially restored upon dex treatment . Coinjection resulted in hyperglycemia and hyperinsulinemia and suppressed corticosterone levels as a result of negative feedback inhibition of the HPA axis   and prevluster 4 , correspluster 4 . Interesluster 4 , suggestCircadian transcription in liver from diet-induced obese animals is severely disrupted by a number of metabolic pathways interacting with the intrinsic circadian clock machinery ,37. It iPpara, Insig2, Acot1, and Angptl4 expression by feeding in lean animals was decreased in obese animals as a result of elevated mRNA expression in the fed obese animals compared to lean controls  and subsequently performed hierarchical clustering of all biological replicates (n = 3 for each condition) from fed and unfed chow and diet-induced obese animals. This approach is independent of a specific FDR cutoff, which allowed us to group genes despite some variability between biological replicates. Hierarchical clustering revealed eight distinct clusters of feeding–up-regulated and feeding–down-regulated genes , and feeding behavior. Here, we demonstrate that a large fraction of the circadian transcriptome in the liver is regulated by feeding, and we identified thousands of DNase accessible regions differentially acetylated at H3K27 in response to feeding at the light/dark transition. Importantly, feeding-regulated transcription correlated with differential H3K27Ac DNase-accessible regions. Moreover, we could divide regulatory regions into two major groups: one group regulated by feeding and one group controlled independent of feeding. Both groups had a similar overall circadian H3K27Ac profile. Extensive DNA motif analysis of feeding-regulated enhancers as well as diurnal regulated enhancers uncoupled from feeding uncovered putative transcription factor networks operating at the transition between the unfed and fed state of a circadian rhythm.In this study, we functionally addressed postprandial repression of gene expression and H3K27 acetylation. We found enrichment of GR, FOXO1, and CREB DNA–binding motifs specifically within DHSs associated with feeding-repressed H3K27Ac and observed that GR and FOXO1 occupancy of chromatin was significantly suppressed by feeding. In addition, the GR and FOXO1 cistromic analysis suggested considerable coregulation of enhancer activity and gene expression by upstream signaling pathways regulating GR and FOXO1 activity. The surge of circulating insulin observed after feeding leads to protein kinase B (PKB/AKT)-dependent FOXO1 phosphorylation and subsequent nuclear exclusion  in agreePck1, Tat, Insig2, and G6pc, regulated primarily by glucocorticoids (Pck1 and Tat) or insulin receptor signaling (G6pc and Insig2). Yet studies using primary hepatocytes and/or conditional KO models have shown that Pck1 expression can be regulated by insulin receptor signaling, and G6pc and Insig2 expression can be regulated by GR [G6pc, Angplt4, and Insig2 [Injection of an insulin receptor antagonist identified postprandial repressed genes controlled predominantly by insulin receptor signaling. Interestingly, several of these insulin-regulated genes were not affected by dynamic glucocorticoid signaling, suggesting that postprandial suppression of circulating corticosterone and increased insulin levels independently regulate the mRNA levels of a subset of feeding-regulated genes in the liver. This includes genes such as ed by GR –44. Thused by GR , which cd Insig2 .When postprandial insulin and glucocorticoid signaling were independently disrupted, we observed partial disruption of postprandial repression of gene expression; however, combined disruption of these signaling pathways resulted in a postprandial expression profile approximating preprandial gene expression. This demonstrates cooperative actions of insulin and corticosterone signaling to repress postprandial gene expression in the liver and emphasizes that signals operating independent of insulin receptor signaling are involved in postprandial repression of transcription in the liver. These signaling pathways may be involved in hepatic metabolic homeostasis of animals lacking both FOXO1 and upstream components suppressing FOXO1 activity such as AKT, IRS, or IR ,42,47,48Fasn and Aacs) and disrupted preprandial gluconeogenic gene expression  was blunted as a result of reduced preprandial expression.Consistent with other studies, we observed increased preprandial activity . Becauseof Ppara , found tof Ppara  and statof Ppara . Howeverob/ob) mice have elevated circadian corticosterone levels [ob/ob mice and diet-induced obese C57BL/6 mice. Yet ob/ob mice have reduced 11beta-hydroxysteroid dehydrogenase (11β-HSD) activity, likely leading to reduced production of active corticosterone in the liver [Unbiased clustering uncovered a group of feeding-regulated genes suppressed in the preprandial state of diet-induced obese animals. This group of genes was particularly enriched for glucocorticoid-sensitive genes. This correlated with reduced preprandial corticosterone levels in obese animals. Dampened circadian corticosterone levels have been reported in diet-induced obese mice  and obese levels , demonsthe liver , suggesthe liver , demonstCollectively, this study identified hepatic circadian–regulated genes and enhancers controlled by feeding. Specifically, we show that two specific signaling pathways control postprandial repression of hepatic gene expression. On one hand, corticosterone levels decrease in response to food intake, leading to reduced expression of specific genes. This is governed by selective regulation of H3K27Ac by GR, mediated by GR recruitment to canonical GREs. In parallel, food intake leads to increased insulin levels, resulting in reduced expression of a set of glucocorticoid independent genes. Both pathways are disrupted during a feeding response in diet-induced obese animals, and impacting postprandial gene regulation in the liver. Thus, a major part of the hepatic circadian–regulated gene program, controlled by feeding, is operated by combined dynamic glucocorticoid and insulin signaling.All mouse work was approved by the Danish Animal Inspectorate (case number 2014−15−0201−00437 and 2017-15-0201-01232), the Danish Environmental Protection Agency, and the Children’s Hospital Boston Institutional Animal Care and Use Committee.Ten-week old C57BL/6N (Taconic Biosciences) male mice were maintained in 12-hour light–dark cycle with lights on at 6 AM (ZT0) and lights off at 6 PM (ZT12), with ad libitum access to chow (Altromin 1324) and water. Four days prior to the experiments, mice were single caged and trained to NRF for which chow was present during the dark period only. On the day of the experiment, one group of mice was euthanized at ZT10, one group of mice was presented with food at ZT12 and was euthanized at ZT14 (ZT14-fed), and one group of mice remained unfed and was euthanized at ZT14 (ZT14-unfed). All mice were euthanized by cervical dislocation. Livers were isolated and frozen in liquid nitrogen.Ten-week old C57BL/6N were subjected to night-restricted feeding as described above. On the day of the experiment, vehicle (PBS), water-soluble dex (1 mg/kg in PBS) (Sigma D2915), and/or S961 (44 nmol/kg in PBS) (generous gift from Novo Nordisk) were injected intraperitoneal (i.p.) 30 minutes before ZT12. Livers were isolated from unfed and fed mice at ZT14.L-IRSdKO (C57BL/6J background) mice were generated as previously described  and subj11 GC per mouse. Specifically, 100 μl AAV diluted in PBS was injected in the tail vein using 23-G needle into homozygote adult GRfl/fl mice (Nr3c1tm2Gsc [A liver-specific adeno-associated virus (AAV) containing CRE recombinase driven by the liver-specific Tbg promoter  or AAV containing GFP driven by Tbg  as control was diluted in sterile PBS and delivered to mice at a titer of 10c1tm2Gsc  on a C57Five-week old male mice were subjected to HFD  for 10 or 20 weeks and were then subjected to the NRF routine. Livers were isolated from unfed and fed mice at ZT14.IPGTT was performed by i.p. D-glucose (Sigma G8270) injection at 2 g/kg to mice fasted for approximately 5 hours and measuring blood glucose at 0, 5, 10, 20, 60, and 120 minutes from injection time. The blood glucose was measured with a glucometer (FreeStyle Freedom Lite) from a tail puncture with a needle.Approximately 300 μl of blood was collected postmortem and stored on ice for further analysis. The blood was centrifuged at 10,000 rcf for 10 minutes at 4°C and prepared for insulin, corticosterone, and NEFA measurements, as indicated by UltraSensitive Mouse Insulin ELISA kit , the Corticosterone ELISA kit (Enzo Life Sciences), and the NEFA quantification kit using the ACS-ACOD method  according to manufacturer instructions. Liver triglyceride levels were measured as described previously .Approximately 5 mg of liver tissue was homogenized using Ultra-Turrax, and RNA was purified using TRIzol-RNA lysis reagent (Thermo Fisher) in EconoSpin columns (Epoc Life) according to manufacturer instructions. The amount of 1 μg of total RNA was exposed to 10 U DNAse I (Thermo Fisher) for 15 minutes at 37°C, followed by cDNA synthesis using random primers and Moloney murine leukemia virus reverse transcriptase (Thermo Fisher). Expression levels were measured by qPCR using SYBR Green reagent mix (Roche 06924204001) and primers listed in Approximately 20 mg of liver was shortly homogenized in 700 μl lysis buffer  and treated with benzonase (Sigma E1014). Protein concentration was determined using the Pierce BCA protein assay kit (Thermo Fisher 23225). A total of 80 μg protein was mixed with laemmli buffer and separated by SDS-PAGE and blotted onto a PVDF membrane . The membrane was probed with primary antibody against GR , FOXO1 , TFIIB  or β−Tubulin (05–661 Merck Millipore), and secondary HRP conjugated antibody (DAKO).3) and decross-linked over night at 65 °C. DNA was phenol/chloroform purified and ethanol precipitated. Recovery was analyzed by qPCR using primers listed in In short, ChIP was performed as described previously  with min2 and 750 mM NaCl) containing 40 U, 60 U, or 80 U of DNase I (Sigma). Digestions were incubated for 3 minutes at 37 °C, and reactions were terminated by addition of 1 volume of stop buffer . Digested chromatin was incubated at 55 °C for 2 hours and stored at 4 °C until further use. DNase I digestion efficiency was evaluated by qPCR, and samples with optimal digestion efficiency were incubated with 90 μg/ml RNase A (Sigma) for 30 minutes at 37 °C before 50- to 500-bp DNA fragments were purified using ultracentrifugation. DNA was subsequently phenol/chloroform purified and ethanol precipitated. Samples treated with 60 U and 80 U of DNase I were sequenced.Livers were isolated from 3–4 mice in each treatment group (ZT14-fed or ZT14-unfed), and nuclei were immediately purified from a pool of 200–300 mg liver tissue using a previously described protocol . This waRNA quality was assessed using the Fragment Analyzer (AATI). Total RNA (1 μg) was prepared for sequencing using polydT enrichment or ribosome depletion according to manufacturer (Illumina) instructions. Subsequent library preparation was performed using the NEBNext RNA library prep kit for Illumina. Library quality was assessed using the Fragment Analyzer followed by library quantification (Illumina library quantification kit). Sequencing was carried out on a HiSeq1500 platform (Illumina).ChIP-seq and DNase-seq libraries were constructed essentially as described previously  using thn = 2–4 [Sequenced reads were normalized to RPKM (RNA-seq), and differentially regulated genes were identified using DESeq2 with n = 2–4 . Heatmapn = 2–4 .Sequenced tags were normalized to 10 million reads using HOMER . DHSs weSequenced tags were normalized to 10 million reads using HOMER . QuantifDe novo motif analysis, log odds motif score, and enriched motifs were identified using HOMER . A set ot test, Mann–Whitney–Wilcoxon test, and Kolmogorov–Smirnov test, as indicated in figure legends. FDR for NGS-read counts at genes, DHSs, and ChIP-seq peaks between different conditions were calculated using DESeq2 [Statistical analysis was performed using Student g DESeq2 . Enrichmg DESeq2  and IMAGg DESeq2 . GO enrig DESeq2 .All sequencing data can be found at GEO: GSE119713. Previously published sequencing data used for analysis include the following: Circadian RNA-seq: GSE73554 ; and CRES1 FigSequenced tags from DNase-seq libraries generated from 60 U and 80 U DNase I digestions of nuclei isolated from mouse liver tissue are quantified at the 83,592 identified DHSs. Red line represents the linear regression, and Pearson correlation coefficient is indicated for pairwise correlation of replicates (r1 and r2). Numerical values are available in (TIF)Click here for additional data file.S2 FigSequenced tags from H3K27Ac ChIP-seq libraries generated from mouse liver tissue are quantified at 1,000 bp surrounding the 83,592 identified DHSs. DHSs with less than 20 H3K27Ac ChIP-seq tags are excluded from the analysis. Red line represents the linear regression, and Pearson correlation coefficient is indicated for pairwise correlation of replicates. (A) Correlation between three biological replicates (r1–r3) at ZT10. (B) Correlation between three biological replicates (r1–r3) at ZT14-unfed. (C) Correlation between three biological replicates (r1–r3) at ZT14-fed. Numerical values are available in (TIF)Click here for additional data file.S3 FigDe novo motifs analysis was performed using HOMER on 1,437 and 1,896 DHSs associated with feeding-induced and feeding-repressed H3K27Ac, respectively. The five most enriched motifs are shown together with the frequency of the motifs within the DHSs (percent target) and the transcription factors likely to interact with the motifs. DHS, DNase hypersensitive site; H3K27Ac, histone 3 lysine 27 acetylation; HOMER, hypergeometric optimization of motif enrichment.(TIF)Click here for additional data file.S4 Fign = 6). (E) Number of GR, FOXO1, and CREB ChIP-seq peaks located within 50 kb of TSS of Ind. and Rep. genes. The number of GR, FOXO1, and CREB ChIP-seq peaks within 50 kb of TSSs of 200 randomly selected genes is included as control. Statistical significance is calculated using a Mann–Whitney–Wilcoxon Test. (F) Tag density of GR, FOXO1, and CREB occupancy at DHS within 50 kb of TSS of Ind. genes and Rep. genes. Statistical significance is calculated using a Mann–Whitney–Wilcoxon Test. Numerical values for panels C–F are available in (A) De novo motif analysis of regions occupied by GR and FOXO1 (ZT14-unfed). The three most enriched motifs are displayed. (B) Evaluation of FOXO1 antibody by western blotting using liver protein extracts from WT and FOXO1 KO animals. (C) Co-occupancy of GR, FOXO1, and CREB using CREB-binding sites from GSE72084. (D) Frequency of Rep. genes with at least one GR, FOXO1, or CREB peak within 50 kb of the TSS. Frequency is relative to GR, FOXO1, and CREB binding within 50 kb of TSS of sets of 300 randomly selected genes. Data is presented as mean ± SEM ((TIF)Click here for additional data file.S5 Fig(A) Correlation of dex-regulated H3K27Ac with feeding-regulated H3K27Ac at GR-binding sites. (B) Correlation of dex-regulated H3K27Ac with feeding-regulated GR occupancy at GR-binding sites. (C) Correlation of dex-regulated H3K27Ac with the level of GR occupancy in unfed condition. (D) Correlation of dex-regulated H3K27Ac with the GRE motif score. The degree of correlation between each of the two variables in panels A–D was tested by a Pearson correlation (r) and the red line represents a linear regression. (E) ROC analysis of GR, FOXO1, and CREB occupancy together with GR, FOXO1, and CREB motif scores within DHSs associated with dex-regulated H3K27Ac. Numerical values are available in (TIF)Click here for additional data file.S6 Fign = 8–12). Statistical significance compared to fed-veh is calculated using Student t test. ***p < 0.001. (D–G) Examples of H3K27Ac and GR occupancy near genes regulated by dex or S961 injection. Numerical values for panels A–C are available in (A) FOXO and CREB (B) occupancy of DHS acetylated at H3K27 in response to dex treatment. Differential H3K27Ac in response to dex is indicated with green color variance in the figure. Statistical analysis is performed by a Mann–Whitney–Wilcoxon test. (C) RT-qPCR analysis of gene expression in the livers of mice injected with vehicle (PBS), dex, or S961. Livers were isolated from unfed or fed mice at ZT14. Data are presented as mean ± SEM ((TIF)Click here for additional data file.S7 Figfl/fl mice. (C) RT-qPCR analysis of GFP, CRE, and GR expression two weeks post AAV injection. Data are presented as mean ± SEM (n = 4). (D) Western blot analysis of GR expression. (E) Quantification of mRNA expression (RNA-seq) in livers from GRfl/fl mice injected with AAV–GFP and AAV–CRE. Feeding-repressed genes regulated by dex, S961, or dex + S961 were analyzed separately. Log2 RPKM is visualized from four biological replicates (R1–R4). Statistical significance is calculated using a Mann–Whitney–Wilcoxon test of the mean of four biological replicates. (F) Quantification of mRNA expression (RNA-seq) in livers from WT and L-IRSdKO. Feeding-repressed genes regulated by dex, S961, or dex + S961 were analyzed separately. Log2 RPKM is visualized from four biological replicates (R1–R4). Statistical significance is calculated using a Mann–Whitney–Wilcoxon test of the mean of four biological replicates. Numerical values for panels B, C, E, and F are available in (A) Experimental setup of S961 injection and subsequent isolation of livers at ZT14. (B) Experimental setup of AAV–GFP and AAV–CRE injection of GR(TIF)Click here for additional data file.S8 Fign = 16) and HFD fed (n = 16). (B) Experimental setup of NRF and indicated endpoints for the experiment. Livers were isolated at ZT14 from fed and unfed animals. (C) Preprandial (ZT14-unfed) blood was extracted from animals trained to night-restricted feeding at 10 and 20 weeks after initiation of HFD feeding. Glucose, insulin, and corticosterone were measured from at least five independent animals. Individual data points are marked in each panel. (D) Gene expression analysis of genes differentially expressed in obese animals. For each cluster, the percentage of differentially induced  and repressed genes  at FDR < 0.05 is indicated at the top. (E) Expression of Srebp1c and Srebp1c target genes , measured by RNA-seq (n = 3). Data in panels A, C, and E are presented as mean ± SEM. Statistical significance is calculated using Student t test. *** indicates p < 0.001 or otherwise indicated in figure. Numerical values for panels A and C–E are available in (A) Weight gain of diet induced obese animals compared to chow-fed controls. NRF was initiated 10 weeks after the start of HFD feeding. Chow fed ((TIF)Click here for additional data file.S9 Fign = 5–6). Statistical significance is calculated using Student t test. Numerical values for panels are available in (A) Occupancy of GR at seven different GRBS (1–7) and one negative ctrl. (B) Occupancy of FOXO1 at seven different FOXO-binding sites (FOXO #1–7) and one negative (ctrl). Data are presented as mean ± SEM ((TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 TableqPCR, quantitative PCR.(PDF)Click here for additional data file.S1 DataPanels 1B, 1C, 1D, 1E, 1F, 1G, 1H, and 1I.(XLSX)Click here for additional data file.S2 DataPanels 2A, 2B, 2C, 2D, 2E, 2F, and 2G.(XLSX)Click here for additional data file.S3 DataPanels 3A, 3B, 3D, and 3E.(XLSX)Click here for additional data file.S4 DataPanels 4A, 4B, 4C, 4D, 4E, 4F, 4G, and 4H.(XLSX)Click here for additional data file.S5 DataPanels 5A, 5C, 5D, 5E, 5F, 5G, 5H, 5I, 5J, 5K, 5L, 5M, 5N, and 5O.(XLSX)Click here for additional data file.S6 DataPanels 6A, 6B, 6C, 6D, 6E, 6F, 6G, 6I, and 6J.(XLSX)Click here for additional data file.S7 DataPanels 7A, 7B, 7C, 7E, 7G, 7H, 7I, and 7J.(XLSX)Click here for additional data file.S8 Data(XLSX)Click here for additional data file.S9 Data(XLSX)Click here for additional data file.S10 DataPanels S4C, S4D, S4E, and S4F.(XLSX)Click here for additional data file.S11 DataPanels S5A, S5B, S5C, and S5E.(XLSX)Click here for additional data file.S12 DataPanels S6A, S6B, S6C, S6D, S6E, S6F, and S6G.(XLSX)Click here for additional data file.S13 DataPanels S7C, S7E, and S7F.(XLSX)Click here for additional data file.S14 DataPanels S8A, S8C, S8D, and S8E.(XLSX)Click here for additional data file.S15 DataPanels S9A and S9B.(XLSX)Click here for additional data file.


In addition, flow cytometry analysis reveals that cell cycle and anti-apoptotic enhancing capability of cells changed after RNAi treatment. These results suggested CIAPIN1 may participate in breast cancer MDR by regulating MDR1 and P53 expression, changing cell cycle and enhancing the anti-apoptotic capability of cells.Cytokine-induced apoptosis inhibitor 1 (CIAPIN1), initially named anamorsin, a newly indentified antiapoptotic molecule is a downstream effector of the receptor tyrosine kinase-Ras signaling pathway. Current study has revealed that CIAPIN1 may have wide and important functions, especially due to its close correlations with malignant tumors. However whether or not it is involved in the multi-drug resistance (MDR) process of breast cancer has not been elucidated. To explore the effect of CIAPIN1 on MDR, we examined the expression of P-gp and CIAPIN1 by immunohistochemistry and found there was positive correlation between them. Then we successfully interfered with RNA translation by the infection of siRNA of CIAPIN1 into MCF7/ADM breast cancer cell lines through a lentivirus, and the expression of the target gene was significantly inhibited. After RNAi the drug resistance was reduced significantly and the expression of MDR1mRNA and P-gp in MCF7/ADM cell lines showed a significant decrease. Also the expression of P53 protein increased in a statistically significant way ( Breast cancer is one of the common cancers all over the World . There aCytokine induced apoptosis inhibitor 1 (CIAPIN1) is a novel antiapoptotic molecule. Compared with the Bcl-2 family, caspase family and signal transduction molecules, it is a distinct apoptosis regulatory molecule and it affects the RAS signaling pathway as a mediator . Most imp < 0.05). P-gp protein was expressed in cytoplasm and cell membrane, while CIAPIN1 was in the cell nucleus (p < 0.01) and of P53 (p < 0.025) , CIAPIN1 of 34.1% (14/41), P53 of 41.5% (17/41), which had a significant difference comparing with the normal breast tissue around the cancer ( nucleus . The P-g< 0.025) . ImmunohTo investigate the differences of CIAPIN1 levels in various breast cancer cell lines, we analyzed by Western blot the amount of CIAPIN1 protein. Results showed the significant increase of CIAPIN1 protein level in MCF7/ADM cells possessing MDR properties compared with MCF7 cells . In otheDNA sequencing was conducted on every siRNA and the sequences were proved to be the same as designed, which proved the oligonucleolide fragments were successfully inserted into the pSIH1-H1-copGFP vector. We transiently transfected recombined plasmid into 293 cells and observed cell growth condition with a fluorescent microscope. In the fluorescent visual field, we observed transfection efficiency was 90% 48 h after transfection. Among three siRNAs targeting CIAPIN1, CIAPIN1mRNA and protein expression are the lowest in CIAPIN1-siRNA1 which is the best interference siRNA sequence and was chosen for use in the next experiment .We infected lentiviral expressed vector into MCF7/ADM cells (MOI = 6) and obtained a stably expressed cell line after screening. The gene CIAPIN1 silencing efficiency is 88% as detected by Real Time-PCR while the inhibition efficiency of protein expression level is 83% by Western blot, which demonstrated that we successfully accomplished RNA interference targeting CIAPIN1 through the lentivirus. We also found the expression of Green Fluorescent Protein (GFP) and target gene showed no change at various clone ages, which proved the MCF7/ADM-CIAPIN1 RNAi cell line is of good quality .50 values of MCF7/ADM cells exposed to several clinical chemotherapeutics  and observed that they decreased significantly after RNAi to the same extent as MCF7 cells (We measured the ICF7 cells . The drup ≤ 0.01) exposure. These results indicated that CIAPIN1 may affect MDR-1 to inhibit P-gp expression in drug-resistant MCF7/ADM cells % before RNAi to (75.30 ± 4.80)% after RNAi, while those in S phase decreased from (42.09 ± 6.04)% to (18.81 ± 5.18)% . These rWe postulated that the effect of CIAPIN1siRNA on MCF7/ADM was related to its impact on apoptosis. To test this assumption, we stably transfected CIAPIN1siRNA into MCF7/ADM cells. Apoptosis of cells were determined by flow cytometry analysis. Compared with the cells without the CIAPIN1 siRNA treatment, the apoptosis rate increased significantly from (17.83 ± 2.24)% before RNAi to (73.52 ± 7.95)% after RNAi . These rWe detected the influence of RNA interference targeting CIAPIN1 on P53 by Western blot. The results indicated that the protein expression of P53 in MCF7/ADM cell lines increased after RNAi which means that CIAPIN1 may participate in MDR of breast cancer by regulating P53 expression .As we have described, breast cancer is one malignant tumor which endangers the health of women. Many routine chemotherapies achieve poor therapeutic effects as well as bad prognosis, both of which cause huge clinical problems. It is believed that MDR is the key factor in the failure of breast cancer treatments. There are many complicated mechanisms for causing MDR ,19,20,21First of all, we tested CIAPIN1 expression in breast cancer tissues and adjacent normal tissues from 41 patients by immunohistochemistry, and the results revealed a positive expression rate of CIAPIN1 (34.1%), which was significantly lower than that of normal group. This result is similar to results from studies on renal cell carcinoma  and lungin vitro enzymatic synthesis, expression vector may consistently produce siRNA by transcription within cells. Therefore the time of action of siRNA may be prolonged, which leads to silencing of the target gene. Additionally it is more reliable to select a stable cell line by lentiviral transfection. Owing to the fact lentivirus have almost no immunogenicity, therefore gene intervention by lentivirus should be one of the most effective methods [in-vivo study [RNA interference is post-transcriptional gene silencing mediated by double-stranded RNA with a specific sequence . As a si methods . Comparevo study ,31. Our 50 value changes. Doxorubicin, paclitaxel, gemcitabine were selected as drugs commonly used in treating breast cancer, all of which have MDR characteristics and MDR1 gene plays a vital role in their resistances, therefore they are often used in studies of MDR in breast cancer [After successfully performing RNA interference on the CIAPIN1 gene, we studied the changes of cell resistance of an MCF7/ADM cell line towards chemotherapy by ICt cancer ,33,34. TAs mentioned above, the most important mechanism affecting MDR of breast cancer is drug resistance-associated proteins on the tumor cell membrane, especially P-gp encoded by MDR1. By the action of chemotherapy, expression of MDR1 on tumor cell membrane is up-regulated through many signal transduction pathways, and expression of P-gp which is encoded by MDR1 increases to protect tumor cells from apoptosis caused by chemotherapy . Inhibitp < 0.001). This indicated that DNA synthesis was suppressed, and most cells were arrested in the G1 phase. Therefore we could confirm that CIAPIN1 may participate in MDR of breast cancer by regulating the cell cycle directly or indirectly. However there is a study finding that after CIAPIN1 gene expression was down-regulated by RNAi, S-phase cells increased significantly, which indicated that CIAPIN1 gene played the role of tumor suppressor gene and this was inconsistent with what we found [Abnormal proliferation is a basic characteristic of tumor cells, and the fundamental reason for uncontrolled proliferation lies in an imbalance of cell cycle regulation. Studies on the cell cycle of tumor cells have revealed that resistant cell lines have more S-phase cells, which promoted proliferation of tumor cells. Results from our study also found that MCF7/ADM cell line had more S-phase cells comparing to parental cells, but after RNA interference, G1-phase cells increased significantly with S-phase cells decreasing significantly , its regulation on apoptosis also becomes abnormal ,41. Apop2 incubator at 37 °C, supplemented with 10% fetal bovine serum  and antibiotics.Forty-one breast cancer and adjacent benign tissue samples were obtained from patients who underwent surgical treatment at the Affiliated Tumor Hospital of Harbin Medical Hospital from August, 2009 to May, 2010. All samples were obtained from patients who gave informed consent to use excess pathological specimens for research purposes only. All patients had undergone no chemoradiotherapy or endocrine therapy preoperation. The multidrug resistant human breast carcinoma cell line MCF 7/ADM and along with their parental sensitive cell lines MCF7 were obtained from Shanghai Jiao Tong University and the CAS cell storeroom respectively. MCF7 and MCF7/ADM cells were cultured in DMEM  in a 5% COhttp://www.ambion.com/techlib/misc/siRNA_finder.html). The designed CIAPIN1 siRNA sequences are: 5'-GATCCGGAGCCAGTAGAGACAGCTCTTCCTGTCAGAAGCTGTCTCTACTGGCTCCTTTTTG-3'(CIAPIN1siRNA1), 5'-GATCCGTGGGTTCTTCTAGGCAGCCTTCCTGTCAGAGCTGCCTAGAAGAACCCACTTTTTG-3' (CIAPIN1siRNA2) and 5'-GATCCGTCAGCTTGTGGAAACTGCCTTCCTGTCAGAGCAGTTTCCACAAGCTGACTTTTTG-3'(CIAPIN1siRNA3). The forward and reverse sequences were synthesized, annealed and coloned into the BamHI/EcoR I of pSIH1-H1-copGFP vector , yielding recombinant plasmids psiCIAPIN1-1, psiCIAPIN1-2 and psiCIAPIN1-3. The inserted sequences were confirmed by DNA sequencing. These recombinant plasmids and controls (empty plasmid and siRNA-Negative-plasmid) were transfected into 293 cell with LipofectmaineTM 2000 (Invitrogen) following the manufacturer’s instruction to determine the most efficient interfering sequence.The complementary DNA sequence of CIAPIN1 (NM_020313.2) was obtained from Genbank. The potential target sequences for RNA interference (RNAi) were scanned with the siRNA Target Finder and Design Tool available at the Ambion Web site (4 IFU/μL) packaging of green fluorescent protein (GFP) was infected into MCF7/ADM at various volume to determined the best MOI value at which concentrations no virus toxicity effect on cells was found. Then the experimental group (MCF7/ADM + CIAPIN1-siRNA1) and control group (MCF7/ADM + Lv-Negative) were added viruses at MOIs of 6 and incubated in normal condition. 96 h after infection we selected cells in two holes of which the GFP brightness is the strongest and proceeded intermediate clone culture in experimental group. Lentivirus Package plasmids mix (System Biosciences) and selected psiCIAPIN1-1 were cotransfected into 293TN cells to package and produce lentiviral vector and viral titer was determined according to the gradient dilution method. Lentivirus (1 × 10TRIZOL reagent (Invitrogen) was used to extract total RNA according to the protocol of the manufacturer. Reverse transcription was done by reverse transcriptase to synthesis cDNA. The polymerase chain reaction (PCR) primers used were as follows: As for CIAPIN1, 5'-CCTGTACGCCA ACACAGTGC-3' (forward), 5'-ATACTCCTGCTTGCTGATCC-3' (reverse) and for β-actin, 5'-CCTTCGGCCTGGTGGATGTCTTT-3' (forward), 5'-CTCCCGCTGCAGCTCTTTCACTTC-3' (reverse), while for MDR1, 5'-CCGTGGGGCAAGTCAGTTCA (forward), CCGGTCGGGTGGGAT AGTTG-3' (reverse) and for β-actin, 5'-CCTGTACGCCAACACAGTGC-3' (forward), 5'-ATACTCC TGCTTGCTGATCC-3' (reverse). PCR products were separated on a 1% agarose gel, visualized and photographed under ultra violet light. In relative quantitation measurement the date was analyzed by CT value compare to β-actin mRNA.For protein analysis, the cell lysates were harvested and detected by western blots. The antibodies used were monoclonal antibodies against CIAPIN1 and P-gp , anti-P53 and anti-β-actin  antibodies, Anti-mouse HRP-linked Antibody (Santa Cruz) and Anti-rabbit HRP-linked Antibody . Densitometry analysis of protein levels was performed by using Scion-Image 4.0.2 software .2. Each well was added various chemotherapeutics  in different doses. OD values of the cells were tested by the method of MTT after 24 h incubation. Cell Growth inhibition ratio =  × 100%. IC50 value was calculated. Each group of cells  in logarithmic phase was seeded in culture plates of 96 wells at 37 °C, 5% CO2 with the final cell density of 1 × 105 per well. Adherent cells then were collected by trypsinization and fixed with 70% ethanol overnight at 4 °C after 24 h culture. After washing with phosphate-buffered saline (PBS), the cells were added 100 μL PBS containing 100 μg/mL RNase A  and 50 μg/mL propidium iodide  and incubated for 30 min at room temperature. The samples were analyzed using a FACS flow cytometer . The cell cycle distribution was established by plotting the intensity of the propidium iodide signal, which reflects the cellular DNA content. Findings from at least 20,000 cells were collected and analyzed with the Cell Quest software (Becton Dickinson). Standard fluorescence-activated cell sorter analysis was used to determine the distribution of cells in cell cycle. Briefly, cells in logarithmic phase were seeded in culture plates of 6 wells containing DMEM + 10% FBS at 37 °C, 5% CO2 for 24 h. Cells were washed twice with ice-cold PBS and then resuspended in 500 μL binding buffer at a concentration of 1 × 106 cells/mL. 5 μL AnnexinV-FITC and 5 μL propidium iodide were added to these cells in order. The fluorescence was immediately determined by flow cytometry. Excitation wave length is 488 nm. Green fluorescence of Annexin V-FITC was detected by FITC channel l (FL1) while red fluorescence of PI (FL2) was detected by PI channel.Apoptotic MCF7/ADM cells were quantified by annexin V-FITC staining, using a kit purchased from Becton Dickinson. In brief, cells in logarithmic phase were seeded in culture plates of 6 wells containing DMEM + 10% FBS for 24 h and DMEM without FBS for 8 h. Then cells were maintained in medium containing doxorubicin (5 μg/μL) at 37 °C, 5% CO4 cells/mL) was harvested after trypsinization and seeded in 6 wells and cultured for 24 h. Then we taken out coverslip and dropped Rh123 buffer (2 µM) on it. After 45 min incubation 4% paraform-aldehyde solution was then added. We observed the staining condition of cells using fluorescence inverted microscope. We paved coverslipd treated with 37% sulphuric acid on the bottom of culture plates of 6 wells. Cell suspension (5 × 10t-test by SPASS13.0 software and statistical significance was expressed as * p < 0.05.All experiments were performed at least three times. Statistical analysis was performed using Student’s MDR of breast cancer is an extremely complicated and consistently changing process, which is regulated by a series of genes and factors. In our study we confirmed that CIAPIN1 gene participates in this process, which was accomplished by regulation of MDR1 and P53 as well as influencing cell cycle and apoptosis. Meanwhile we also confirmed that performing RNAi on CIAPIN1 gene by a viral transfection approach may effectively reverse MDR of breast cancer, which provides a new way for improving therapeutic effects. This represents a promising gene therapy.


Idd) loci and candidate genes, one of them being Cd101. CD101 is a heavily glycosylated transmembrane molecule which exhibits negative-costimulatory functions and promotes regulatory T (Treg) function. It is abundantly expressed on subsets of lymphoid and myeloid cells, particularly within the gastrointestinal tract. We have recently reported that the genotype-dependent expression of CD101 correlates with a decreased susceptibility to T1D in NOD.B6 Idd10 congenic mice compared to parental NOD controls. Here we show that the knockout of CD101 within the introgressed B6-derived Idd10 region increased T1D frequency to that of the NOD strain. This loss of protection from T1D was paralleled by decreased Gr1-expressing myeloid cells and FoxP3+ Tregs and an enhanced accumulation of CD4-positive over CD8-positive T lymphocytes in pancreatic tissues. As compared to CD101+/+ NOD.B6 Idd10 donors, adoptive T cell transfers from CD101−/− NOD.B6 Idd10 mice increased T1D frequency in lymphopenic NOD scid and NOD.B6 Idd10 scid recipients. Increased T1D frequency correlated with a more rapid expansion of the transferred CD101−/− T cells and a lower proportion of recipient Gr1-expressing myeloid cells in the pancreatic lymph nodes. Fewer of the Gr1+ cells in the recipients receiving CD101−/− T cells expressed CD101 and the cells had lower levels of IL-10 and TGF-β mRNA. Thus, our results connect the Cd101 haplotype-dependent protection from T1D to an anti-diabetogenic function of CD101-expressing Tregs and Gr1-positive myeloid cells and confirm the identity of Cd101 as Idd10.Type 1 diabetes (T1D) is a chronic multi-factorial disorder characterized by the immune-mediated destruction of insulin-producing pancreatic beta cells. Variations at a large number of genes influence susceptibility to spontaneous autoimmune T1D in non-obese diabetic (NOD) mice, one of the most frequently studied animal models for human disease. The genetic analysis of these mice allowed the identification of many insulin-dependent diabetes . Despite T1D being one of the most common and most studied polygenic autoimmune disorders, the mechanisms underlying the immune-mediated destruction of the insulin-producing pancreatic beta cells are still largely unknown. Genetic association studies identified many DNA sequence variants that confer risk to or protect from autoimmune disease. In this regard, we have identified a single gene,  Type I diabetes T1D) is a complex autoimmune disease driven by multiple genetic traits and facilitated by various immune cells infiltrating the pancreatic islets. In rodent models such as the frequently studied non-obese diabetic (NOD) mouse, myeloid cells including macrophages, dendritic cells (DCs) and neutrophils are the first cells to accumulate in the pancreas D is a co and contin vitro suppression assays and reveal subtle defects in the expression of distinct genes [Tregs are pivotal for the maintenance of immune homeostasis. Their ability to suppress other immune cells maintains tolerance to self-antigens and prevents autoimmune disease. The depletion of Tregs promotes the development of T1D while their transfer or therapeutic enhancement exhibits protective effects –10. Compct genes , althougct genes –16.Various myeloid cell populations and myeloid cell responses are frequently altered and impeded in NOD mice . Thus, tin vitro [In vitro, CD101+ Tregs are more suppressive than their CD101− counterparts [In vivo, CD101 perpetuates the suppressive function of Tregs and reduces the development of T1D and chronic colitis [+ myeloid cells release more IL-10 than CD101− myeloid cells [Cd101 gene have been suggested to underlie the reduced CD101 expression in some T1D patients [CD101 is a negative costimulatory molecule expressed on subsets of myeloid and lymphoid cells –33. Uponin vitro . In vitrterparts . In vivo colitis , 31, 35.id cells . Rare popatients .Cd101 as a T1D candidate gene within the Idd10 region using multiple Idd10 congenic strains [+ Tregs, CD11c+ dendritic cells, and Gr1+ myeloid cells [Idd10 and Idd10/Idd18 regions from a B6 CD101 KO strain onto the NOD background and observed that T1D protection mediated by the B6-derived Idd10 and Idd10/Idd18 regions was lost in CD101−/− NOD.B6 Idd10 and CD101−/− NOD.B6 Idd10/Idd18 mice. The loss of CD101 expression reduced the frequency of Tregs and transformed anti-inflammatory Gr1-expressing myeloid cells into an inflammatory, disease-promoting subset. Thus, our data further confirm the identity of Cd101 as Idd10 and provide cellular mechanisms by which the molecule mediates its protection from T1D.We have identified  strains . Susceptid cells . To evalIdd10 congenic strains [Cd101 gene variation on the distribution of immune cells in peripheral lymph nodes as compared to spleen. In both lymph nodes and spleen CD101 expression was observed on a portion of T cells and myeloid cells  promoting protection from T1D, we assessed the distribution of myeloid and lymphoid cells in the organs of CD101-expressing and CD101-deficient NOD.B6 phocytes  and few phocytes . There wterparts . While tph nodes , Tregs wph nodes , but notph nodes  of CD101centages . Thus, tIdd10 and NOD.B6 Idd10/18 mice. Similar to B6 CD101−/− mice [−/− NOD.B6 Idd10 and CD101−/− NOD.B6 Idd10/18 mice have a reduction of Gr1-positive cells in the bone marrow compared to CD101-expressing congenic controls  [−/− as compared to CD101+/+ NOD.B6 Idd10 mice  –43, wered10 mice .−/− and CD101-expressing NOD.B6 Idd10 mice and transferred the CD4- and CD8-positive T cell population into lymphopenic NOD scid recipients. The combined transfer of CD4- and CD8-positive T lymphocytes increased T1D frequency in recipients of donor T cells originating from CD101−/− NOD.B6 Idd10 mice compared to donor T cells originating from CD101-expressing NOD.B6 Idd10 controls  when T cells from CD101-expressing NOD.B6 Idd10 donors were transferred into NOD.B6 Idd10 scid as compared to NOD scid recipients indicating that in the presence of the CD101 protein encoded by the B6 Cd101 allele in the T cell compartment, the status of the Cd101 allele expressed by myeloid cells determines the level of protection from T1D  was observed in a repeat of the same transfer combination  impairment in the output of neutrophils from the bone marrow and/or the differentiation of neutrophils; 2) increase in peripheral consumption/destruction; 3) tissue sequestration. Based on our previous studies [Our observation that CD101 affects Gr1-expressing cells is also of clinical relevance as reduced neutrophil counts in the peripheral blood and enhanced neutrophil activity have been reported in T1D patients –49. Neut studies , we suspIdd10 mice compared to parental NOD mice [+/+ NOD.B6 Idd10 compared to CD101−/− NOD.B6 Idd10 mice, confirming the positive effect of CD101 on Treg differentiation and function [Cd101 allele primarily affects Tregs within the T cell compartment. These animal studies are also in line with a recent report on distinct T1D patient cohorts raising the possibility of CD101 being a susceptibility gene for human T1D [+ Tregs in NOD mice carrying the B6 Cd101 allele likely contributes to the protection from T1D.Decreased T1D frequency has been shown to be associated with enhanced CD101 expression on splenic Tregs of congenic NOD.B6 NOD mice . In the function , 35, 50.function , 51–53, uman T1D . In addiuman T1D  and CD10+/+ NOD.B6 Idd10 mice. In particular, CD8-positive T cells might be interesting to study further since recent reports claimed altered functions between CD101-expressing CD8-positive T lymphocytes and their CD101-negative counterparts [CD101 expression restrains the accumulation and expansion of diabetogenic CD4- and CD8-positive T lymphocytes and reduces T1D frequency in lymphopenic recipient mice upon mixed CD4/CD8 T cell transfers from CD101terparts , 56. ThuThe experiments were conducted according to the Institutional Animal Care and Use Committee guidelines of the Cincinnati Children’s Hospital (IACUC protocol number Protocol 8D02011) and approved by the Animal Welfare Committee of the local government . Daily inspections were performed to minimize animal suffering. Mice with signs of discomfort or disease were euthanized immediately by C02 and cervical dislocation.scid mice were obtained from Taconic Farms . The development of the NOD.B6 Idd10 (N16) (Taconic line 3538) and NOD.B6 Idd10/18 (N10) (Taconic line 7754) strains were described previously [Idd10 and NOD scid mice were intercrossed and F2 mice homozygous for the Idd10 and scid-containing regions selectively bred to develop the NOD.B6 Idd10 scid strain. B6 CD101−/− mice [−/− NOD.B6 Idd10 (N11) and CD101−/− NOD.B6 Idd10/18 strains (N10). Polymorphic markers near and within the Idd10 and Idd18 regions were used to define recombination events as similar as possible to the boundaries of these regions (−/− NOD.B6 Idd10 and CD101−/− NOD.B6 Idd10/18 strains were free of B6-derived genetic segments outside of the selected areas as defined by screening with a 1449 polymorphic marker panel as described previously [NOD/MrkTac (NOD) and NOD eviously , 39. NOD−/− mice  were bac regions  as previeviously . All micMice were euthanized and pancreata were perfused with a 1.5 mg/mL solution of collagenase P , dissected from surrounding tissues and cut into small pieces. The digestion buffer was supplemented with 1 mM PMSF, 100 μM leupeptin and 1 μM pepstatin A . Pancreata were digested at 37°C for 10 min in a shaking water bath. The digestion was stopped by adding HBSS containing 5% FCS. The tissue suspension was washed three times and centrifuged through a discontinuous Ficoll gradient  at room temperature. The purified islets were disrupted by adding 1 mL of cell dissociation buffer  for 10 minutes at 37°C. The obtained cells were washed, resuspended and used for analyses.7 spleen cells enriched in TCRβ-positive T cells (consisting of about 2/3 CD4-positive T cells and of about 1/3 CD8-positive T cells) from 6-8-week-old donor female mice were transferred intraperitoneally into 6-8-week-old NOD scid or NOD.B6 Idd10 scid recipients. B cells, NK cells, DCs, granulocytes or macrophages were depleted using Auto-MACS  and PE- or APC-fluorescence coupled beads against CD19, NKp46, Gr1, CD11c or F4/80 from NOD mice before transfer following the manufacturer's instructions with purity control by FACS.5x10For cell division studies donor T cells were labeled with 5 μM CFSE prior to transfer according to the manufacturer's instructions .Single-cell suspensions were prepared from the spleen, lymph nodes, pancreas and bone marrow. Red blood cells were not removed. Cell-surface expression of CD45.1 (clone A20), CD45.2 (clone 104), CD11c (clone N418), CD11b (clone M1/70), Ly6C (clone HK1.4), Ly6G/Gr1 (clone RB6-8C5), F4/80 (clone BM8), B220 (clone RA3-6B2), the β-chain of the TCR (clone H57-597), CD3 (clones 145-2C11 and 17A2), CD4 (clone GK1.5) and CD8a (clone 53–6.7) was detected using fluorescently labeled mAbs obtained from eBioscience . PE-labeled anti-CD101 (clone 307707) was obtained from R&D Systems. Intracellular Foxp3 was detected with a staining kit following the manufacturer´s instructions (eBioscience). Cells were analyzed on an LSR II or a BD FACS Canto II  with FlowJo software . Gr1-expressing cells were purified on a FACS Aria II  (purity of > 98%).All diabetes cumulative frequency studies were conducted using female mice. The presence of T1D was tested every 14 d beginning at 84 d of age by the detection of urinary glucose >500 mg/dl using Diastix . Overt diabetes was confirmed by a blood sugar level of >200 mg/dl. Studies were terminated at 196 d of age. Kaplan–Meier survival curves were plotted for each mouse strain, and these were compared using the log rank test .Pancreatic tissue was fixed in 10% buffered formalin, embedded in paraffin, and cut into 5 μm thick sections. Pancreas sections were deparaffinized, stained with H&E by the Department of Pathology and the Medical Department I of the FAU Erlangen-Nürnberg, and evaluated microscopically in a double-blinded manner. H&E–stained sections were scored for insulitis. At least 10 islets per mouse present on two or three non-adjacent pancreas sections were scored as either 0, no infiltration; 1, peri-insulitis; 2, mild-invasive insulitis; or 3, severe invasive insulitis. The average score of each pancreas was calculated and used for statistical analysis.cDNA was synthesized using a High-capacity cDNA Reverse Transcription Kit  following the manufacturer’s instructions. Quantitative (q) -PCRs were performed as described  using spSamples were analyzed for normal distribution by a Kolmogorov-Smirnov test. According to the results, statistical significance in normal distributed samples were analyzed by one-way ANOVA with posthoc test (Bonferroni) and Student’s t-test, and samples failing the normal distribution test by Kruscal-Wallis Test with posthoc (Dunn’s multiple comparison) or Mann-Whitney U test as indicated in the respective experiments. A sample size of at least three (n = 3) was used for each sample group in a given experiment, and a p value of 5% , 1% , 0.1%  or 0.01%  was considered significant to accept the alternate hypothesis. GraphPad Prism software was used for statistical analysis.S1 FigIdd10 mice were determined by flow cytometry. All cells were pre-gated on CD45. Representative FACS plots are shown for CD101 versus CD11b, following the gating out of TCRβ-positive T cells (A). The percentage of CD101-expressing CD11b-positive myeloid cells (B) and the distribution of myeloid (CD11b+) cells and T lymphocytes (CD3+) among CD101-expressing, CD45-positive cells (C) in the indicated organs was compiled from 5 and 3 individual NOD.B6 Idd10 mice, respectively. Error bars indicate the SD of the mean.The cell composition and the distribution of CD101 expression in the indicated organs of NOD and NOD.B6 (TIF)Click here for additional data file.S2 Fig+/+ NOD.B6 Idd10 mice and CD101-/- NOD.B6 Idd10 mice. Representative staining panels for each mouse strain and organ are displayed.The expression of CD101 and FoxP3 on TCRβ-positive T cells was assessed by flow cytometry in the spleens, pancreatic and popliteal lymph nodes of 4-week-old CD101(TIF)Click here for additional data file.S3 FigIdd10 mice in inguinal lymph nodes (A) as well as the summaries for the number of CD101-expressing T cells (B) and the mean fluorescence intensities for CD101 (C) in 5 individual mice per group are displayed. Comparisons between groups were performed using the Mann–Whitney nonparametric test . Error bars indicate the SD of the mean.Representative FACS dot plots for the expression of CD101 on T cells from NOD and NOD.B6 (TIF)Click here for additional data file.S4 FigThe percentage of CD101-expressing Tregs (A) as well as the percentage of FoxP3-positive Tregs (B) was compiled from the popliteal lymph nodes of 4 individual mice at 4, 8, 12 and 14 weeks. Comparisons between groups at the indicated time points were performed using the Mann–Whitney nonparametric test. Error bars indicate the SD of the mean.(TIF)Click here for additional data file.S5 Fig+ (A), Gr1+ (B), F4/80+ (C) or TCRβ+ CD44+ (D) from the spleens and pancreatic lymph nodes of 6 individual NOD and NOD.B6 Idd10 mice are summarized. Groups of mice were compared by non-parametric Mann-Whitney tests. Error bars indicate the SD of the mean.The genotype-dependent expression of CD11c(TIF)Click here for additional data file.S6 Fig+/+ NOD.B6 Idd10, CD101+/− NOD.B6 Idd10 and CD101−/− NOD.B6 Idd10 mice bred from CD101+/− NOD.B6 Idd10 heterozygous breeders. Data from the CD101+/+ NOD.B6 Idd10 and CD101+/− NOD.B6 Idd10 progeny are also shown in The frequency of T1D was assessed by the analysis of urinary glucose concentration in the indicated number of female CD101(TIF)Click here for additional data file.S7 Fig−/− NOD.B6 Idd10 and CD101+/+ NOD.B6 Idd10 female mice (A) as well as for individual insulitis scores (B) are displayed.Representative pictures of H&E-stained pancreas sections from 10-week-old CD101(TIF)Click here for additional data file.S8 FigThe percentage of FoxP3-positive Tregs was compiled from the popliteal lymph nodes of five individual mice per time point. Comparisons between groups were performed using Student´s t-tests. Error bars indicate the SD of the mean.(TIF)Click here for additional data file.S9 Fig+ cells from 17 individual female mice at the age of 10–15 weeks are compiled from four independent experiments. Statistical differences were determined using Mann-Whitney tests . Error bars indicate the SD of the mean.The cell composition in the bone marrow (A) and the spleens (B) of the indicated mouse strains was assessed by flow cytometry. Data for the percentage of Gr1(TIF)Click here for additional data file.S10 Fig+/+ NOD.B6 Idd10 and CD101-/- NOD.B6 Idd10 mice are displayed. Comparisons between groups were performed using Student´s t-tests. Error bars indicate the SD of the mean.The percentages for the distribution of F4/80- (A) and CD11c- (B) expression within the CD11b-positive Gr1-negative myeloid cell subset in the pancreatic lymph nodes of four individual CD101(TIF)Click here for additional data file.S1 TableThe table contains the markers used to define the mouse lines in this study. The marker name, GRC38 coordinate and primer sequences are provided, as well as the method for assessing the polymorphism.(DOCX)Click here for additional data file.


Defective clearance of apoptotic cells in MFG-E8 deficient mice results in lupus-like disease in the mixed B6x129, but not pure B6 background. The lack of overt autoimmunity in MFG-E8-/- B6 mice suggests that accumulation of apoptotic cells is not sufficient to break central tolerance. However, the delayed clearance of apoptotic cells in the follicles of MFG-E8-/- B6 mice provides an excellent opportunity to investigate how B cells respond to excessive apoptotic cells in the periphery under relatively non-inflammatory conditions. In MFG-E8-/- B6 mice, we found increased IgG2c production against apoptotic cells and oxidized LDL. Apoptotic cell induced antibody responses depended on MyD88 signal and T cell help. In addition, MFG-E8-/- B6 mice had enlarged MZ B cell compartments as well as an enhanced antibody response to NP-Ficoll. Moreover, a significant percentage of MZ B cells in aged MFG-E8-/- B6 mice migrated into follicles. Injecting apoptotic cells or oxidized LDL into wild type mice as well as physiological accumulation of LDL in ApoE-/- mice recapitulated the translocation of MZ B cells. To determine how MFG-E8 deficiency affects the functions of autoreactive B cells specific for nucleic acids in the periphery under non-inflammatory conditions, we utilized BCR transgenic mice to bypass central selection and compared the differentiation of TLR9 dependent anti-dsDNA 56R B cells and TLR7 dependent anti-ssRNA H564 B cells in MFG-E8-/- mice. In MFG-E8-/- 56R mice, anti-dsDNA specific 56R/Vκ38c B cells differentiated into MZ B cells but not AFCs. On the contrary, in MFG-E8-/-H564 mice, anti-ssRNA specific H564 B cells further differentiated into GC B cells and AFCs. Adoptive transfer of activated autoreactive B cells confirmed that H564 B cells were more sensitive to apoptotic cell antigens than 56R B cells. Our observations provide new insights about the MZ B cell translocation in lupus patients as well as the dichotomy of TLR9 and TLR7 signals in the pathogenesis of lupus. Both central and peripheral tolerance play critical roles in controlling autoreactive B cells . Most anSpleen B cells consist of two major populations: MZ  B cells and FO (follicular) B cells. Under normal conditions, MZ B cells and FO B cells are separated by the marginal zone, which also includes various types of macrophages. Because of their location, marginal zone macrophages and B cells are the first line to capture and to respond to circulating antigens. An intact marginal zone is required to maintain an effective defense against both foreign and self antigens. Consistent with their innate-like immunity, the antibody repertoire of marginal zone B cells is enriched in poly-reactivity–5. Moreoin vivo are associated with apoptotic cells. The lipid components of apoptotic cell membranes are oxidized [In the well-established HEL model system, how antigens are presented determines the fate of HEL specific B cells . Recent oxidized . These ooxidized . Moreoveoxidized , 12. Theoxidized . HoweverNumerous mouse studies also demonstrated the dichotomy of TLR9 and TLR7 in lupus pathogenesis. While genetic deletion of TLR9 reduced the production anti-dsDNA, it exacerbated disease. On the contrary, deletion of TLR7 inhibited the production of anti-ssRNA antibody and prevented lupus . These cNot only do apoptotic cells provide antigens to stimulate self-reactive B cells , they alAlthough bolus injection of exogenous apoptotic cells has been commonly used to investigate immune responses against apoptotic cells, most of the injected materials are trapped within marginal zone macrophages and excluded from the follicle and FDCs . 56R anti-dsDNA BCR (B cell receptor) transgenic mice in a B6 background were from Dr. Prak (University of Pennsylvania). H564 anti-ssRNA B cell receptor transgenic mice in a B6 background were originally from Dr. Imanishi-Kari (Tufts University) and kindly provided by Dr. Keith Elkon (University of Washington). TCRα-/-, MyD88-/-, ApoE -/-, and LDLR-/- mice in a B6 background were purchased from Jackson Laboratory (Maine). All animal (mice) usage and procedures in this study were carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the Institutional Animal Care and Use Committee of the University of Washington (IACUC Protocol Number: 3380–02). No surgery was performed in this study. Death of animal was not used as outcome or experimental endpoint in this study. All mice were euthanized with COAntibodies against F4/8 (A3-1), CD169 (3D6.112), MADCAM (MECA-367) were from Serotec. FITC conjugated polyclonal goat anti-mouse C3 was from MP Biomedicals. HRP conjugated goat anti-mouse IgM, IgG, IgG1, IgG2b, IgG2c, and IgG3 were from Southern Biotech. Alexa 647 labeled anti-mouse IgG2c was from Jackson Immunoresearch laboratory. Antibodies against CD21 (7E9), CD23 (B3B4), CD1d (1B1), B220 (RA3-6B2), Ki67 (11F6), GL7 (GL7), CD1d (1B1), CXCR5 (L138D7) were from Biolegend. Fas (Jo2) antibody was from BDbiosciences. PNA was from Sigma-Aldrich. Idiotype specific antibodies against 56R/Vκ38c and 56R/Vκ21D were kind gifts from Dr. Tsubata (Japan) [MDA-LDL was purchased from Academy Bio-Medical. Two micrograms per ml MDA-LDL was used to coat ELISA plates (Nunc). Serum samples were diluted 1/100 in PBS/BSA and incubated overnight at 4°C. The binding of IgG2c was detected by HRP conjugated goat anti-IgG2c antibody. Anti-dsDNA ELISA was performed as previously described . BrieflyMultiscreen filter plates (Millipore) were coated with 1μg/ml idiotype specific antibody (B6.265) overnight at 4°C. The coated plates were blocked with RPMI/10%FBS for 1 hour. Serial dilutions (1/2) of spleen cells were dispensed onto the plate and cultured overnight at 37°C. IgG producing AFCs were visualized using HRP conjugated goat anti-mouse IgG antibody, followed by one-step NBT/BCIP substrate (Pierce). The number of positive cells in each well was counted using ImmunoSpot (CTL).6 cells/ml. CXCL13 (Peprotech) diluted in 600 μl RPMI/0.5% BSA  was added to the bottom of each well of a 24 well plate. One hundred micro liters of spleen cells were added to a 5nm pore size transwell (Corning), then placed on the top of the well. After a 4 hour incubation at 37°C, migrated cells were collected from the bottom and enumerated by flow cytometry. MZ B cells and follicle B cells were distinguished by their expression of CD21 and CD23.Spleen cells were first plated on petri-dishes at 37°C for 30 minutes to deplete macrophages. Non-adherent cells were then re-suspended in RPMI + 10% FBS at a density of 5 x10Spleen and kidney samples were snap-frozen in OCT. Five micron thick sections were stained using various antibodies. The intensity of antibody binding was quantified by image J.6 per mouse) were transferred to reconstitute the irradiated mice. Spleen cells and bone marrow cells from the recipients were analyzed at 3–4 month after reconstitution.Recipient mice were irradiated with 1,000 rad. One day later, T and B cell depleted bone marrow cells  was i.v. injected into w.t. B6 mice. Forty eight hours later, spleens were collected and snap-frozen in OCT. Five micron thick spleen sections were stained with anti-CD1d to locate MZ B cells.In most experiments, a non-parametric student t test was used. For comparisons between multiple groups, one way A-NOVA was used. P values less than 0.05 were considered significant. * p<0.05, ** p<0.01, *** p < 0.001, **** p<0.0001, n.s. = not significant.Fig 1A, serum samples from MFG-E8-/- mice had elevated level of total IgG, which could be attributed to the increased levels of IgG2b and IgG2c subclasses. Immunofluorescence staining of the spleen sections using IgG2c specific antibody showed increased numbers of IgG2c+ plasma cells in both follicles and red pulp . When serum samples from 4 month old MFG-E8-/- females were incubated with apoptotic cells, we found a significant increase of IgG2c binding to dying cells , suggesting accumulation of apoptotic cells was able to induce spontaneous B cell responses, including class switching. On the other hand, repeated injection of exogenous apoptotic cells failed to induce anti-apoptotic cell IgG2c in 4 month old w.t. mice . Since apoptotic cells share similar epitopes with oxidized LDL [Fig 1D, sera from MFG-E8-/- mice had increased amounts of IgG2c against MDA-LDL. Consistent with the increased production of autoantibodies against apoptotic cells, 4 month old MFG-E8-/- female mice had increased numbers of GL7+Fas+ GC B cells and PD1+CXCR5+ T follicular helper cells . The elevated antibody responses to various self antigens in MFG-E8-/- mice are most evident at 4 months of age and we no longer detected significant differences between w.t. and knock-out in mice older than 12 months . As old mice generally have less organized splenic architecture, and activated T cells accumulate in the spleens of old MFG-E8-/- mice, we mainly used 4 month old mice in subsequent studies to avoid the effects caused by these changes.MFG-E8-/- mice in a B6 background did not develop overt autoimmunity , 25. To ized LDL , we asse, the IgG2c response to apoptotic cells in MFG-E8-/- mice was completely abrogated in MFG-E8-/-MyD88-/- mice. This response was also significantly reduced in MFG-E8-/-TCRα-/- mice. On the other hand, unlike IgG2c but similar to the response to foreign antigens, MyD88 deficiency increased the IgG1 response to apoptotic cells .The TLR-MyD88 pathway and T cell help are required to generate autoreactive IgG responses in autoimmune mice. Nucleic acids contained within immune complexes are known to provide endogenous TLR9 and TLR7 ligands to co-stimulate B cells. Although anti-dsDNA and anti-ssRNA antibodies are absent in MFG-E8-/- B6 mice, apoptotic cells may provide other TLR stimuli to B cells to facilitate autoantibody development . To deteFig 5A). One important function of MZ B cells is to mediate the T cell independent antibody response. When challenged with the Type II T independent antigen NP-Ficoll, MFG-E8-/- mice produced significantly more anti-NP IgG, in particular IgG3, IgG2c, and IgG2b subclasses than w.t. mice .MZ B cells include many poly-reactive B cells that can be stimulated by self antigens released from apoptotic cells. Defective clearance of apoptotic cells in MertK-/- mice increased the percentage of MZ B cells . Like MeFig 6A, whereas most CD1d+ MZ B cells remained in the marginal zone in old w.t. mice, a large fraction of them in age matched MFG-E8-/- mice were found in the follicle. In w.t. mice, the ratio of CD1d+ cells in the follicle to those in the MZ zone was about 0.75:1. On the contrary, in MFG-E8-/- mice, the same ratio was increased to 2:1.Although the majority of MZ B cells are found in the marginal zone, they can shuttle between the MZ zone and follicle. After stimulation by TLR ligands, MZ B cells were released from the MZ zone and their translocation into the follicles was accelerated . Since a6 apoptotic cells. As shown in  after the injection of exogenous apoptotic cells, the ratios of follicular to MZ zone CD1d+ B cells were significantly increased in w.t. mice. One possible TLR ligand derived from apoptotic cells is the oxidized LDL mimetope [Fig 6A, similar to exogenous apoptotic cells, exogenous oxidized LDL significantly increased the follicular/MZ CD1d+ B cell ratio from 0.75 to 3.5. To further demonstrate the effect of LDL on MZ B cells, we asked whether a physiological increase of LDL could also induce MZ B cell translocation. To this end, we examined the location of CD1d+ MZ B cells in 3–5 month old ApoE-/- and LDLR-/- mice [Fig 6B, the mean ratio of follicular CD1d+ cells to MZ CD1d+ cells was increased from 0.5 in w.t. mice to 1.5 in age matched ApoE-/- mice. LDL mediated MZ B cell translocation was only partially mediated by the LDL receptor, as LDLR deficiency only caused a modest reduction of CD1d+ MZ B cells in the follicles .To confirm that the translocation of MZ B cells in MFG-E8-/- mice is caused by the accumulation of apoptotic cells, we injected 3 month old w.t. mice with 20 x 10mimetope , 30. To in vitro. As shown in Fig 7A, splenic B cells from MFG-E8-/- mice, in particular MZ B cells are more responsive to CXCL13 induced trans-migration. These B cells also expressed higher levels of CXCR5 on their surface than w.t. MZ B cells .Since the migration of B cells into the follicle is mainly mediated through chemokine CXCL13 and its receptor CXCR5 , we nextFig 8A, compared to w.t. 56R mice, autoreactive 56R/Vκ38c but not non-autoreactive 56R/Vκ21D B cells were significantly increased in the spleens of MFG-E8-/-56R mice. Immunofluorescence staining of the spleen sections revealed that most of the expansion of 56R/Vκ38c B cells occurred within the MZ. However, unlike the polyclonal MZ B cells in old MFG-E8-/- B6 mice, most of 56R/Vκ38c B cells in MFG-E8-/- 56R mice remained outside of the follicles, suggesting dsDNA is unlikely to be the ligand that induced MZ B cells to translocate. Interestingly, although Mertk deficiency promoted the expansion of total MZ B cells, we did not observe any increase of 56R/Vκ38c B cells in Mertk-/- 56R transgenic mice .In addition to oxidized LDL, apoptotic cells also release blebs containing DNA and RNA. Although in the non-autoimmune B6 background, MFG-E8 deficiency did not break central tolerance and old MFG-E8-/- B6 mice did not develop anti-dsDNA and ssRNA antibodies, nucleic acids from apoptotic cells can provide both self antigens and TLR signals in the periphery to stimulate autoreactive B cells that have escaped bone marrow selection. To determine how apoptotic cells in MFG-E8-/- mice promote the differentiation of autoreactive anti-dsDNA B cells in the periphery, we crossed MFG-E8-/- with 56R transgenic mice whose production of anti-dsDNA antibody was shown to be TLR9 dependent . 56R BCRFig 8C, in both bone marrow and spleen, the mean ratio of 56R/Vκ38c to 56R/Vκ21D was significantly higher in MFG-E8-/- hosts than in w.t. hosts. Moreover, greater than 50% of 56R/Vκ38c B cells had differentiated into CD21high/ CD23low MZ B cells, whereas most of non-autoreactive 56R/Vκ21D B cells were either CD21low/CD23high follicle B cells or CD21high/CD23high T2 transitional B cells [). In agreement with the preferential selection of autoreactive B cells, MFG-E8-/- BMCs (bone marrow chimeras) had higher levels of anti-dsDNA antibody than w.t. BMCs . However, despite the expansion of 56R/Vκ38c B cells, GC B cells and antibody producing AFCs (antibody forming cells) were absent in MFG-E8-/- 56R mice, nor did we detect any significant deposition of autoantibody in the kidneys. These observations suggest that although TLR 9 signaling derived from apoptotic cell DNA can promote the positive selection of anti-dsDNA B cells, it is not sufficient to drive them to differentiate into AFCs.Since the dominance of transgenic B cells can skew the selection of B cells , we want B cells  . On the other hand, the percentages of id+ MZ and id+ GC B cells were increased in MFG-E8-/-H564 mice , suggesting MFG-E8 deficiency might accelerate the differentiation of H564 B cells. The increase of GC B cells in MFG-E8-/- mice was confirmed by immunofluorescence staining of the spleen sections with PNA as well as the proliferation marker Ki67 . Coincidentally with their accelerated differentiation, immature B cell marker, CD24, on id+ B cells was substantially down regulated on MFG-E8-/-H564 B cells . To further demonstrate the effect of MFG-E8 deficiency in a poly-clonal condition, we directly transferred spleen cells from H564 BCR mice into w.t. and MFG-E8-/- host. Seven days later, we evaluated the phenotype of id+ B cells in the recipients. In MFG-E8-/- hosts, we found the ratio of MZ to FO B cells was significantly increased in id+ but not id- B cells .In addition to DNA, defective clearance of apoptotic cells can also release cytoplasmic RNA to engage TRL7 on B cells. The dichotomy of TLR9 and TLR7 pathways in lupus suggests anti-dsDNA B cells and anti-ssRNA B cells may respond differently to their respective autoantigens. To determine how MFG-E8 deficiency drives the differentiation of ssRNA specific autoreactive B cells in the periphery, we crossed MFG-E8-/- mice with H564 BCR transgenic mice. The production of autoantibodies in H564 mice depends on TLR7 signaling . In H564Fig 10A). The increase in autoantibody producing B cells was confirmed by immunofluorescence staining of the spleen sections using an idiotype specific antibody. As shown in Fig 10B, most of the autoantibody producing id+ cells in MFG-E8-/- mice were in the red pulp. We also confirmed the increase of IgG producing plasma B cells in MFG-E8-/- H564 mice by ELISPOT assay. As shown in Fig 10C, the mean number of id specific IgG producing cells was increased from 55/ 106 in w.t. mice to 320/106 in MFG-E8-/- mice. Consistent with the increased number of plasma cells, the level of id specific IgG, in particular the IgG2b subclass, was substantially higher in MFG-E8-/-H564 mice than in w.t. H564 mice . In addition, we detected a significantly higher amount of id specific autoantibody and C3 deposited in the kidneys of MFG-E8-/-H564 mice than in w.t. H564 mice .The reduction of id+ H564 B cells in MFG-E8-/- mice prompted us to investigate whether these cells had differentiated into autoantibody producing plasma cells (AFCs). B cell receptor and other typical B cell markers such as B220 and CD19 are down-regulated in plasma cells. In w.t. H564 mice, we found a small percentage of id+ B cells expressing low levels of B220 as well as high levels of the plasma cell marker CD138, suggesting they were autoantibody producing plasma B cells. In the absence of MFG-E8, the numbers of id+, B220low/CD138high plasma cells were significantly increased . Consistent with the enhanced differentiation of plasma cells, MFG-E8-/- recipients also had significantly more id+ IgG and C3 depositions in their kidneys than in w.t. recipients .To demonstrate the direct effect of excessive apoptotic cells on plasma cell differentiation in the periphery, we transferred activated autoreactive B cells into w.t. and MFG-E8-/-mice. We first activated 56R and H564 B cells with a low dose of LPS for 3 days. Both 56R and H564 B cells stimulated by this method remained IgMa+ before the transfer. After extensive washes, we transferred these activated B cells into w.t. and MFG-E8-/- hosts. At day 5 after the transfer, we evaluated the phenotype of id+ cells in the circulation. As shown in Fig 4). Previous studies have firmly linked anti-dsDNA and anti-ssRNA antibody responses in murine lupus models to the TLR-MyD88 pathway [Fig 3). The strength of costimulatory signal(s) provided by non-nucleic acid stimuli might be weaker than those provided by nucleic acids.In our study, we found MFG-E8 deficient mice had higher levels of IgG2b and 2c antibodies against apoptotic cells and oxidized LDL than w.t. mice. The class switching we observed is different than reported by Chikazawa et al., who described an increase of anti- IgM but not IgG against peroxidized lipids in MFG-E8-/- mice . Althoug pathway , 14. DsD pathway , 38, to  pathway , 39, 40. pathway . It is iFig 8C). The coincidence of the follicular location of T2 cells [Both MFG-E8-/- mice and other strains deficient in apoptotic cell removal have an expanded MZ B cell population. Due to their anatomical location, various poly-reactive B cell clones in the MZ can be positively selected by different self antigens released by apoptotic cells in circulation. In fact, both anti-dsDNA 56R/Vκ38c and anti-ssRNA H564 B cells were induced to differentiate into MZ B cells in MFG-E8-/- mice. The positive selection of these cells is likely to occur at the immature T2 B cell stage within the follicles, as we found in MFG-E8-/- 56R bone marrow chimera mice, in which, autoreactive 56R/Vκ38c B cells differentiated into FO and MZ B cells, whereas a significant percentage of non-autoreactive 56R/Vκ21D B cells retained the CD21high/ CD23high T2 B cell phenotype  T2 cells  and the T2 cells  supportsFig 8A), dsDNA is unlikely to be the ligand that induces MZ B cell migration into the follicles. Since increased antibody responses to oxidized LDL and MZ B cell migration into follicles have been reported in lupus patients, our observations hereby identified a missing link between these two phenomena. Since other stimuli such as IFN-α, can also induce MZ B cell translocation [MZ B cells migrated into the follicles in old MFG-E8-/- mice. Apoptotic cells can release endogenous TLR ligands to trigger this response. Since injection of exogenous oxidized LDL and physiological accumulation of LDL in ApoE-/- and LDLR-/- mice induced a similar translocation, oxidized LDL mimetopes on the surface of apoptotic cells could be one of these ligands. The effect of oxidized LDL on MZ B cells is supported by a recent study. In that study, Grasset et al. demonstrated repeated injection of apoptotic cells or oxidized LDL, as well as ApoE deficiency, increased the percentage of MZ B cells . Althouglocation , we cannFig 12B). In a recent study by Nundel et al., using AM14 cells as a model system, the RNA-containing immune complex BW4R but not DNA-containing PA4 complex was capable of inducing AFC formation in vitro. More intriguingly, using an immune complex containing both TLR7 and TLR9 ligands, they demonstrated TLR9 signaling prevented TLR7 driven AFC formation [Fig 12A). BCR/TLR9 signaling may also actively prevent the down-regulation of BCR on their surface. Indeed, Nundel et al. found that deficiency in TLR9 allowed sustained down-regulation of BCR components in vitro [In MFG-E8-/- mice, ssRNA specific id+ H564 B cells differentiated into AFCs, whereas dsDNA specific 56R/Vκ38c B cells remained relatively quiescent in the MZ. Although generalization of our observations is limited by the nature of transgenic B cells, their different sensitivities to apoptotic cell associated antigens is consistent with the dichotomy of the TLR9 and TLR7 pathways observed in murine lupus. Two possibilities can explain why H564 B cells are more sensitive to apoptotic cells than 56R B cells. First, RNA associated antigens may distribute differently than DNA associated antigens in MFG-E8-/- mice. It is conceivable that cytosolic RNA components are directly released into the micro-environment whereas most DNA components remain insulated within intact apoptotic bodies or apoptotic blebs. H564 B cells may have easier access to their antigens than 56R B cells. Secondly, BCR/TLR9 signaling on 56R/Vκ38c B cells may inhibit their differentiation into AFCs. In fact, MFG-E8 deficiency inhibited anti-dsDNA IgG2b production by activated 56R B cells (ormation . Anotherormation . As 56R in vitro . Despitein vitro .


MEIS2 has been identified as one of the key transcription factors in the gene regulatory network in the development and pathogenesis of human cancers. Our study aims to identify the regulatory mechanisms of MEIS2 in hepatocellular carcinoma (HCC), which could be targeted to develop new therapeutic strategies.The variation of MEIS2 levels were assayed in a cohort of HCC patients. The proliferation, clone-formation, migration, and invasion abilities of HCC cells were measured to analyze the effects of MEIS2C and MEIS2D (MEIS2C/D) knockdown with small hairpin RNAs in vitro and in vivo. Chromatin immunoprecipitation (ChIP) was performed to identify MEIS2 binding site. Immunoprecipitation and immunofluorescence assays were employed to detect proteins regulated by MEIS2.The expression of MEIS2C/D was increased in the HCC specimens when compared with the adjacent noncancerous liver (ANL) tissues. Moreover, MEIS2C/D expression negatively correlated with the prognosis of HCC patients. On the other hand, knockdown of MEIS2C/D could inhibit proliferation and diminish migration and invasion of hepatoma cells in vitro and in vivo. Mechanistically, MESI2C activated Wnt/β-catenin pathway in cooperation with Parafibromin (CDC73), while MEIS2D suppressed Hippo pathway by promoting YAP nuclear translocation via miR-1307-3p/LATS1 axis. Notably, CDC73 could directly either interact with MEIS2C/β-catenin or MEIS2D/YAP complex, depending on its tyrosine-phosphorylation status.Our studies indicate that MEISC/D promote HCC development via Wnt/β-catenin and Hippo/YAP signaling pathways, highlighting the complex molecular network of MEIS2C/D in HCC pathogenesis. These results suggest that MEISC/D may serve as a potential novel therapeutic target for HCC. Hepatocellular carcinoma (HCC) is a primary liver cancer with high mortality. It is one of the most common malignancies in the world, especially in Asia, Africa, and Southern Europe . AlthougMeis homeobox 2 (MEIS2) belongs to the three amino acid loop extension (TALE) superfamily –5. In vePrevious studies have shown that miR-1307 may be a therapeutic target for ovarian cancer . Also, mThe Hippo signaling pathway inhibition promotes cirrhosis and tumorigenesis in liver . Yes-assTo investigate the role of MEIS2 in HCC, we examined the expression of MEIS2 in HCC samples and adjacent noncancerous livers (ANL) and found that the level of two alternatively spliced MEIS2 isoform, MEIS2C/D, are up-regulated in HCC tissues. In addition, MEIS2C/D are associated with poor prognosis in HCC patients. Importantly, knockdown of MEIS2C/D could inhibit proliferation and diminish migration and invasion of hepatoma cells in vitro and in vivo. Mechanistically, MEIS2D suppressed Hippo pathway by promoting YAP nuclear translocation via miR-1307-3p/LATS1 axis, while MESI2C activated Wnt/β-catenin pathway in cooperation with CDC73. Interestingly, the interaction between CDC73 and MEIS2C/β-catenin or MEIS2D/YAP depend on its tyrosine-phosphorylation status. Collectively, our studies indicate that MEIS2C/D promote HCC progression and may serve as a novel prognostic biomarker for HCC.We collected 118 paired tumorous and adjacent noncancerous liver samples from April 2016 to MAY 2018 in The First Affiliated Hospital of Xi’an Jiaotong University and Xijing Hospital. Detailed clinical pathological parameters were listed in Additional file 2 incubator at 37 °C, and routinely passaged when 80–90% confluent.HCC-LM3 and MHCC97H cell were routinely culture in DMEM medium supplemented with 1X MEM, 1X Sodium pyruvate, 1X Glutamine + 25 mM HEPES +1X 2-ME (from 55 mM stock 1000X) + 10% FBS and antibiotics. All cultures were maintained in a humidified 5% COTotal RNA was extracted using TRIzol (Invitrogen) according to the manufacturer’s instructions. Reverse transcription was carried out using oligo-dT primers. MiR-1307-3p mRNA levels were detected by using qRT-PCR. 18 s RNA and U6 were used as internal controls. Real-time PCR was performed in an Applied Biosystems 7500 system using Power SYBR Green PCR Master Mix (Applied Biosystems).The cells were lysed in RIPA buffer in presence of protease inhibitor cocktail (Roche). Whole cell lysates were prepared and subjected to 12% SDS-PAGE and transferred to NC membrane (Bio-Red). The membranes were incubated overnight at 4 °C with the specific antibodies. Membranes were washed and incubated for 1 h at room temperature with secondary antibody conjugated with peroxidase. Membrane-bound immune complexes were detected using Super ECL detection reagent on Amersham Imager 600.2/well were seeded into 96-well plates and cultured in 100 μl of DMEM containing 10% FBS for 5 days. Ten microliter of CCK8 solution was added to each plate, and the cells were incubated for 3 h at 37 °C. The absorbance value (OD) of each well was measured at 450 nm.Cell viability was analyzed using the Cell Counting Kit-8 (CCK-8) (Dojindo). Cells at a density of 5 × 10Cells were plated in 6-well culture plates. After incubation for 12 days at 37 °C, the cells were washed twice with PBS and stained with 0.1% crystal violet solution. The number of colonies was counted under a microscope.Cell motility was assessed by cell invasion and migration assays using Transwell chambers with or without Matrigel . Cells in medium without FBS were seeded on Transwell chambers with or without Matrigel and incubated at 37 °C for 15 h. Medium containing 2% FBS was put in the lower chamber. The invasive cells attached to the lower surface of the membrane insert were fixed, stained using Giemsa and quantified.ChIP assay was carried out using Chromatin Immunoprecipitation Kit (Sigma-Aldrich) according to the manufacturer’s protocol. IP was performed using specific antibodies, anti-RNA Pol II or normal IgG. Experiments were repeated three times independently.Cells were transfected with reporter constructs containing the promoter together with expression vector or empty vector using Lipofectamine 3000 (Thermo Fisher Scientific). After 48 h, the luciferase activities of whole cell lysates were measured using the dual-luciferase reporter assay system (Promega). For all samples, the assays were repeated at least three times.6 cells/mouse) or MHCC97H (1.0 × 107 cells/mouse) shMEIS2C/D and control cell lines were subcutaneously injected into the mice to form the xenograft model. The mice were randomly divided into indicated groups (5–10 mice/group) before inoculation, and double-blinded evaluation was performed. Mouse survival was analyzed using a survival analysis. The mice were sacrificed at endpoint, tumors and their lungs were removed. Tumor volume and weight were measured. To evaluate the potential of the cells to metastasize to livers, nude mice spleens were inoculated with shMEIS2C/D or control HCC-LM3 cells (8 × 105), and the metastatic tumor colonies in the liver were measured 12 weeks later.All animal studies were approved by the Institutional Animal Care and Use Committee of Xi’an Jiaotong University .Eight-week-old male nude mice Nude mice were housed five mice per cage in a specific pathogen-free room. HCC-LM3  samples. The results showed that MEIS2 mRNA was not significantly changed in HCC tissues when compared with ANL , indicating that LATS1 might be a target gene of miR-1307-3p. In order to confirm this, we transfected HEK293T cells with miR-1307-3p mimics and detected the luciferase activity of LATS1 3′ UTR reporter. We found that the luciferase activity of LATS1 mRNA reporter was significantly inhibited when miR-1307-3p was overexpressed. By contrast, when we mutated the predicted binding site sequence for miR-1307-3p, the expression of LATS1 was no longer affected by miR-1307-3p . Herein, we suggest that the activation of these genes exerts the carcinogenic effect of MEIS2C/D and eventually contributes to the development of HCC.After we established the link between β-catenin, YAP, CDC73, and MEIS2C/D, we sorted to determine the downstream target genes of MEIS2C/D in HCC. From database mining and screening , we idenDue to the molecular mechanism of HCC pathogenesis remain unclear, many HCC patients are diagnosed as metastasis and advanced stage, therefore missed the opportunity for surgical treatment with good prognosis. Deciphering the molecular mechanisms of carcinogenesis and metastasis is crucial for the development of new therapeutic strategies in HCC. Most recent research indicated that MEIS2D has the effect of promoting cancer growth in Neuroblastoma , 15. HowMiR-1307-3p is a member of the miR-1307 sub-family and plays an important role in breast cancer, colorectal cancer and ovarian cancer, but the effect in HCC remain unclear , 33, 34.Although MEIS2C and MEIS2D play similar proliferative role in tumor progression , it is iSHP2, also known as PTPN11, has been elucidated its crucial role in liver cancer stem cell expansion . ReductiOur clinical investigation revealed that the protein level of MEIS2A/B was generally higher than that of MEIS2C/D. So we speculate that MEIS2A/B also performs important biological functions in HCC. Considerable evidences indicate that MEIS2A inhibits the development of neuroblastoma , and alsTaken together, our study shows that MEIS2D promotes the development of HCC by miR-1307-3p/LATS1/YAP circuit. On the other hand, MEIS2C bind to dephosphorylated CDC73 and activate β-catenin in a trimeric complex. Although these data imply that MEIS2C/D might be a potential biomarker for HCC treatment, further clinical investigation and more data analysis are warranted to establish this point. The significance of MEIS2C/D in HCC personalized medicine is deserved to be further investigation.Given Hepatocellular Carcinoma (HCC) is the third leading cause of cancer death worldwide, defining the regulatory mechanism is essential to decipher the pathogenesis of HCC. Recent efforts have identified MEIS2 as one of the key transcription factors in human cancers. However, the regulatory mechanisms of MEIS2 activity in HCC remain obscure. Herein, we describe that two of MEIS2 alternatively spliced isoforms, MEIS2C and MEIS2D, expression dramatically increased in HCC patient, and negatively correlated with the prognosis of HCC patients. Using an in vivo and in vitro approach, we show that MEIS2C and MEIS2D promote the proliferation and metastasis of hepatoma cells via Hippo/YAP and Wnt/β-catenin signaling. This provides further insights into the complex regulatory network of MEIS2 and further support for developments of MEIS2 isoforms–specific inhibitors for HCC treatment.Additional file 1 : Figure S1. (A) siMEIS2 efficiency measured by western blot in HEK293T cells. (B) Relative MEIS2C/D mRNA levels were measured by q RT-PCR in different cell lines. Figure S2. (A) Three predicted MEIS2 binding sites detected by ChIP in HEK293T cells. Input DNA were used as positive controls. Immuno-precipitated DNA by anti-IgG antibody was used as negative controls. PCR was used to find out the MEIS2D and PBX1 binding site for miR-1307 gene. (B) Results of ChIP of M2 sites DNA fragments performed with Flag-MEIS2A/B/C. (C) Results of ChIP of three predicted MEIS2 binding sites DNA fragments performed with Flag-MEIS2B. Figure S3. (A) HCC-LM3 cells were transfected with indicate siRNA, miRNA or controls. Then, immunoblotting was performed to examine SHP2. (B) YAP intracellular distribution detected by immunofluorescence staining.  HCC-LM3 cells were transfected with indicated plasmids, siRNAs and controls. Then, Immunoblotting and immunofluorescence staining were performed to examine LATS1 and YAP expression and localization. Figure S4. (A) MHCC97H cells were transfected with indicated siRNA and vectors. YAP localization investigated by immunofluorescence staining. (B) Lysates were detected by indicated antibody. HCC-LM3 and MHCC97H cells were transfected with siMEIS2 and indicated rescue vectors. Then, proliferation function of MEIS2C or MEIS2D was measured by CCK-8 Kit(C). Relative YAP and β-catenin mRNA levels were measured by q RT-PCR after 48 h (D). Figure S5. RNA expression correlation between MEIS2A/B and genes were investigated in HCC patients. Table S1. Correlations between clinic pathological features and relative MEIS2C/D expression. Table S2. Predicted putative MEIS2 binding site sequence and position on miR-1307 Promoter (3 KB) by using JASPAR (jaspar.genereg.net)