Sc) of the normal cellular prion protein (PrPC). Identification of different PrPSc structures is crucially important for understanding prion biology because the pathogenic properties of prions are hypothesized to be encoded in the structures of PrPSc. However, these structures remain yet to be identified, because of the incompatibility of PrPSc with conventional high-resolution structural analysis methods. Previously, we reported that the region between the first and the second α-helix (H1∼H2) of PrPC might cooperate with the more C-terminal side region for efficient interactions with PrPSc. From this starting point, we created a series of PrP variants with two cysteine substitutions  forming a disulfide-crosslink between H1∼H2 and the distal region of the third helix (Ctrm). We then assessed the conversion capabilities of the C;C-PrP variants in N2a cells infected with mouse-adapted scrapie prions (22L-ScN2a). Specifically, Cys substitutions at residues 165, 166, or 168 in H1∼H2 were combined with cysteine scanning along Ctrm residues 220–229. We found that C;C-PrPs are expressed normally with glycosylation patterns and subcellular localization similar to WT PrP, albeit differing in expression levels. Interestingly, some C;C-PrPs converted to protease-resistant isoforms in the 22L-ScN2a cells, but not in Fukuoka1 prion-infected cells. Crosslink patterns of convertible C;C-PrPs indicated a positional change of H1∼H2 toward Ctrm in PrPSc–induced conformational conversion. Given the properties of the C;C-PrPs reported here, we propose that these PrP variants may be useful tools for investigating prion strain–specific structures and structure–phenotype relationships of PrPSc.Prions are composed solely of the pathological isoform (PrP Sc)C) devoid of any nucleotide genome. Prions cause fatal neurodegenerative disorders in various mammalian species, e.g. Creutzfeldt-Jakob disease (CJD) in humans, scrapie in sheep and goat, chronic wasting disease (CWD) in cervids, and bovine spongiform encephalopathy in cattle -resistant fragments (PK-res)  , structu(PK-res) , 11, and(PK-res) . As anot(PK-res) .Sc, high water-solubility and small molecular size of PrPC allowed detailed structural analysis by NMR spectroscopy. The global three-dimensional structures of PrPC are highly conserved among different species with the same secondary-structure components, i.e. two short β strands  and three α helices  (–Unlike PrP and H3) –16. Inteand H3) –, and affand H3) –, 19. Forand H3) –. Moreoveand H3) –.C–PrPSc interactions  substitutions , one in H1∼H2 and the other in Ctrm. This crosslinks the two regions by an artificial disulfide bond. Effects of these additional bonds on PrPC–PrPSc conversion were monitored in prion-infected cells. Disulfide-crosslink is particularly useful in combination with Cys scanning, systematically tying up the two regions in various fashions. Those intramolecularly crosslinked PrPs were normally expressed on the cell surface when expressed in N2a cells persistently infected with mouse-adapted scrapie (22L-ScN2a), some of them converted into PK-resistant isoforms in a PrPSc-dependent manner. Interestingly, convertibility of the mutants crucially depended on certain patterns of crosslinks. Furthermore, the convertibility of C;C-PrP seemed to be strain-dependent, suggesting that this region is involved in creating prion-strain diversity. Our unique approach provides novel insights into the structural requirements for PrPc–PrPSc conversion.We previously demonstrated that efficiencies of dominant-negative inhibition by mutant PrPs with internal deletions in the H1∼H2 region (ΔPrP) correlated with the deletion sizes, proposing that this region might be an interaction interface for PrPractions . PositioC–PrPSc interactions and the subsequent conversion, we created a series of mutant PrPs that have two Cys substitutions, one in H1∼H2 and the other in Ctrm so that the two regions are crosslinked by an artificial disulfide bond (A), and tested their conversion to PK-res forms. For the Cys substitution in H1∼H2, we selected Val-165 and Asp-166 (residues were numbered according to mouse numbering unless otherwise noted), because they are close enough to Ctrm to form a stable disulfide-crosslink in a native PrPC conformation (PDB code 2L39) MoPrP) was used as the template for site-directed mutagenesis, every mutant PrP carries a 3F4 epitope tag.To assess the significance of the intramolecular interactions between H1∼H2 and Ctrm on PrPide bond A, and tede 2L39) . Indeed,de 2L39) , 26. TheFig. S1). Interestingly, the global structures of C;C-PrPs were not severely distorted by the crosslinks.To assess possible structural consequences of mutations and to estimate influences of the disulfide-crosslinks on PrP structure, we analyzed representative C;C-PrPs by short molecular dynamic simulations (A) to examine expression levels and glycosylation status of the mutant PrPs. Banding patterns of all mutants were similar to that of (3F4)MoPrP (B), typical of PrPC with complex-type N-linked glycans and glycosylphosphatidylinositol anchor, and lacked the dimeric forms . Their expression levels were varied . A C;C-PrP that has Cys residues at positions equivalent to those of the aforementioned human PrP mutant , presumably because its intramolecular disulfide-crosslink between the substituted Cys did not interfere with the native PrPC conformation. “Intramolecular” disulfide-crosslink of C;C-PrPs is implied by the absence of discernible dimeric forms. The mutant PrPs with a single Cys substitution formed substantial levels of dimeric forms that are presumably crosslinked by a intermolecular disulfide bond and disappear upon dithiothreitol (DTT) treatment  versus (+)). The 166C;C-series mutants showed similar banding patterns as 165C;C-series without discernible dimeric forms . 6C;1C and 6C;4C showed the highest expression levels among the 166C;C-series .We transfected N2a mouse neuroblastoma cells with plasmids encoding the 165C;C- and 166C;C-series A to examF4)MoPrP B, typicaP mutant , namely E, schematic). The banding patterns of those mutants were very different from that of WT PrP, reminiscent of PrP with high-mannose–type N-linked glycans . Absence of those features supported that C;C-PrPs form an intramolecular disulfide-crosslink between the substituted Cys without affecting the native disulfide and undergo normal folding and processing in ER and trans-Golgi network. In accordance with this view, immunofluorescence analysis demonstrated that C;C-PrPs were distributed on the cell surface  and in perinuclear regions as clusters  like WT PrP, corroborating normal intracellular trafficking and subcellular localization of C;C-PrPs. To further exclude aberrant localization of C;C-PrPs, we correlated the expression of transfected C;C-PrPs (mAb 3F4 positive) with cholera toxin B (CtxB) labeling of cell-surface lipid rafts using confocal microscopy   and analyzed the fragment patterns of V8 protease-digested products. A crosslink between H1∼H2 and Ctrm theoretically produces extra bands on immunoblots by bonding fragments (A). Indeed, V8-digested FLAG-tagged (3F4)MoPrP, 166C, 6C;3C, and 6C;9C (B) showed distinct banding patterns along with findings suggestive of intramolecular disulfide-crosslink. First, full-length 6C;3C-FLAG and 6C;9C-FLAG PrP molecules remained after the digestion , whereas full-length (3F4)Mo-FLAG and 166C-FLAG PrPs were completely digested . Relative protease resistance of C;C-PrPs was also implied by smaller amounts of fragments produced by endogenous proteolysis . These are attributable to steric effects caused by the crosslink of H1∼H2 and Ctrm, concealing protease-vulnerable regions. Second, the greatly improved immunoreactivity of the smallest fragments of 6C;3C-FLAG and 6C;9C-FLAG by DTT treatments  also indicates steric effects hiding the epitope, and its re-exposure by DTT, which breaks apart the crosslinked fragments. Third, the intermediate size fragments of V8-digested 6C;3C-FLAG and 6C;9C-FLAG , which disappeared by DTT  apparently represent the predicted “extra fragments” . Taken together, these findings strongly support the intramolecular crosslink formation between the introduced Cys residues.To demonstrate intramolecular disulfide-crosslink formation by the substituted Cys, we introduced a FLAG tag to C;C-PrPs A and anaragments A. Indeednd 6C;9C B showed A), whereas the 166C;C-series exhibited gradually increasing levels of PK-res from 6C;5C to 6C;9C (B). Just as PrPC isoforms, PK-res of C;C-PrPs lacked dimeric forms , whereas every single-Cys PrPs tested showed intense dimeric bands , which disappeared with DTT treatment . These data support the view that the PK-res molecules of C;C-PrPs were not derived from PrPC isoforms with free Cys residues, i.e. without crosslink, but from those with the intramolecular disulfide-crosslink. Absence of PK-res in noninfected N2a cells demonstrated that the conversion of the 6C;9C into PK-res isoform was PrPSc-dependent . We hypothesize that the nonconvertible C;C-PrPs, e.g. those from 6C;0C to 6C;4C, cannot convert because of their unsuitable positioning of H1∼H2 for efficient refolding as discussed later, but there also was the possibility that they cannot appropriately interact with the PrPSc template. We tested this possibility by assessing their dominant-negative inhibition efficiencies, as done previously by us for other PrP mutants MoPrP , confirming that these C;C-PrPs do interact with template PrPSc but cannot convert into PK-res isoforms.Next, we assessed conversion efficiencies of 165C;C- and 166C;C-series PrP mutants by expressing them in persistently infected 22L-ScN2a cells and evaluating their PK-resistant forms (PK-res). Among 165C;C-series, only 5C;8C and 5C;9C showed PK-resistant PrP A, whereato 6C;9C B. Just aSc and its dominant-negative inhibition on the coexisting WT PrP , whereas Q218K PrP showed much lower levels compared with WT PrP . This suggested that the artificial disulfide-crosslink of 6C;9C can suppress the effects of Q218K.Lysine at codon 219  is a polymorphism of human PrP well-known for protective effects against sporadic CJD . The equg WT PrP . As the g WT PrP  32), we, weSc anbona fide PrPSc indicated that they are results of refolding reaction induced by PrPSc. Tolerance of PK-res conversion reaction to specific disulfide-crosslinks, namely those of 6C;5C to 6C;9C, 5C;8C and 5C;9C, seemed to be reasonably explained with a model where H1∼H2 undergoes a positional change toward Ctrm during refolding into PK-res (A). This suggest that a disulfide-crosslink between Cys at positions 165 or 166 and Cys-229 does not interfere with the refolding process (B). This model predicted the existence of another disulfide-crosslink that might not interfere with the refolding reaction, bonding a more distal H1∼H2 residue and a more proximal Ctrm residue (C versus D). To test this hypothesis, we created 168C;C-PrPs (A) and assessed their conversion efficiencies in 22L-ScN2a cells. Expression levels of 168C;C-PrPs in N2a cells were similar to that of 165C;C- and 166C;C-series mutants (B): 8C;1C showed expression comparable with (3F4)MoPrP, and 8C;4C and 8C;5C showed a slightly higher expression. In 22L-ScN2a cells, only 8C;4C and 8C;5C converted into PK-res forms at detectable levels (C) in a PrPSc-dependent manner (D). When we combined 167C or 169C with Cys-scanning in Ctrm from 224 to 229 and 221 to 226, respectively, there were no detectable levels of PK-res.The dependence of PK-res conversion of C;C-PrPs on o PK-res A. This s process B. This mC;C-PrPs A and ass mutants B: 8C;1C e levels C in a Prt manner D. When wC–PrPSc interfaces including H1∼H2, and that usage of interfaces varies among different prion strains (E).We previously hypothesized that a PrP molecule has multiple PrP strains . To test strains E.Sc in prion conversion, potential prion strain differences, and anti-prion effects of the Q218K substitution. Following are detailed discussions.Our studies with C;C-PrP molecules provide new insights into the biology of cellular prion conversion, in particular into regional structures of PrPC in the native conformation MoPrP and others showing lower expression. What could explain this? As mentioned above, a disulfide-crosslink of human PrP between residues 166 and 221 or 225 (human numbering) maintained or even stabilized the global structure of PrPormation . Likewisde: 2L39 ), and thC and PrP fibrils as well  demonstrates that the positioning of H1∼H2 and Ctrm suitable for achieving the native PrPC conformation and for PrPSc conversion are distinct. Collectively, these results imply a substantial positional change of the H1∼H2 region, which is normally stabilized onto H2 and H3 by multiple hydrogen bonds and salt bridges, toward Ctrm in the prion conversion reaction in 22L-ScN2a cells, as illustrated in Fig. 6D. This point of view also would help explain why destabilization of the native PrPC conformation leads the way for conversion of PrP into PrPSc.The 165C;C-, 166C;C-, and 168C;C-series showed distinct patterns of convertible PrP mutants. This demonstrates that positioning of the disulfide-crosslink between H1∼H2 and Ctrm is a critical determinant of convertibility rather than positions of Cys itself. Because a disulfide-crosslink between two regions fixates their relative positioning and regional structures , the suc as well , 25, 26.et al. , PK, anti-PrP monoclonal antibodies (mAb) 4H11 and 3F4 (recognizing residues 108–111 of human PrP), and all secondary antibodies were as previously reported . IodoaceTable S1. Mutations were made with a QuikChange Site-directed Mutagenesis Kit  according to the manufacturer's instructions. Sequences of mutant PrPs were determined by Eton Bioscience, Inc. .All primers for site-directed mutagenesis were ordered from Integrated DNA Technologies, Inc.  and are listed in Sc levels of mutant PrPs. For evaluation of dominant-negative inhibition, 0.2 μg each of (3F4)MoPrP and mutant PrP were co-transfected. The Fukuoka1- and RML-infected N2a58 cells were also previously described , and procedures for preparation of samples of transfected N2a or 22L-ScN2a cells were as previously described  and then 1 ml/well of 1.5 mm IAA in PBS was overlaid and incubated for 10 min at 4 °C. After removal of IAA, cells were rinsed once with PBS without calcium and magnesium (Ca/Mg) and incubated in 700 μl/well of 3 mm EDTA in PBS without calcium and magnesium at 4 °C for 5 min. Then, the cells were mechanically detached by pipetting and collected in a tube. The cell suspension was centrifuged at 1,000 × g at 4 °C for 5 min and the supernatant was discarded. 400 μl of phosphate-buffered 2% Triton X-114 lysis buffer was added, cells were resuspended by vortexing for ∼10 s, and incubated on ice for 30 min, with a few seconds of vortexing from time to time. The lysate was then centrifuged at 16,100 × g at 4 °C for 1 min and the supernatant was transferred to a screw-cap tube as Triton X-114 lysate. PrP was concentrated by Triton X-114 extraction and methanol/chloroform precipitation as previously described , at 95 °C for 10 min with shaking at 1,400 rpm. After the pellet was completely dissolved, the solution was diluted with 4-fold volume of 200 mm sodium bicarbonate to dilute SDS concentration, so that V8-protease efficiently digests PrP. After addition of 2 μl of V8-protease (2.5 units/μl), the solution was incubated at 37 °C for 1 h. Finally, one-fourth volume of 5× sample buffer with or without DTT was added and boiled. For re-probing of the PVDF membrane, the membrane was incubated in 100% methanol for 20 min, washed in Tris-buffered saline-Tween, and incubated with another primary antibody in 5% milk in Tris-buffered saline-Tween.N2a cells, ∼60% confluent on 6-well culture plates, were transiently transfected with 1.0 μg/well of plasmid encoding the mutant PrP with Lipofectamine LTX. Next day, the medium was replaced with fresh medium and cells were cultured further at 37 °C in a COescribed . The pel3F4 expression related to CtxB labeling. Medium of N2a cells transfected with various C;C-PrP constructs for 72 h was replaced with ice-cold extracellular solution (ECS) for 5 min for pre-chilling prior to CtxB live cell labeling. Then cells were incubated with 2 μg/ml of 488-CtxB  in cold ECS for 30 min at 4 °C. After washing 3 times in cold ECS, cells were fixed in 4% paraformaldehyde for 30 min at room temperature. Fixed cells were then permeabilized in PBS containing 5% FBS and 0.5% Triton for 30 min. Primary antibody 3F4  was used at 1:1000 dilution for overnight incubation at 4 °C, and Alexa Fluor 555 goat anti-mouse secondary antibody (Thermo Fisher) was incubated for 30 min at room temperature. All images were taken under the same acquisition settings from a Zeiss 700 confocal microscope, and fluorescence was sequentially collected under standard 488 and Cy3 filters. 488-CtxB–labeled cell-surface lipid raft signal was used to define the “surface” contour, the same region of interest was copied to the Cy3 channel for quantifying surface 3F4 fluorescence intensity, and the whole cell fluorescence was measured from the same cell outline from Cy3 channel. For epifluorescence analysis, procedures for transient transfection of cells, fixation, permeabilization, and immunolabeling were as reported previously , except “Materials and Methods”.The detailed protocol is provided under the supporting Y. T., N. N., and H. M. S. conceptualization; Y. T. and H. M. S. resources; Y. T., N. N., and H. M. S. data curation; Y. T., L. L., C. M.-W., H. O., and N. N. formal analysis; Y. T. and H. M. S. supervision; Y. T., N. N., and H. M. S. funding acquisition; Y. T. and N. N. validation; Y. T., L. L., C. M.-W., H. O., and N. N. investigation; Y. T., L. L., C. M.-W., H. O., and N. N. methodology; Y. T., L. L., C. M.-W., N. N., and H. M. S. writing-original draft; Y. T., N. N., and H. M. S. project administration; Y. T., N. N., and H. M. S. writing-review and editing.


The regulation of paramyxovirus RNA synthesis by host proteins is poorly understood. Here, we identified a novel regulation mechanism of paramyxovirus RNA synthesis by the Hsp90 co-chaperone R2TP complex. We showed that the R2TP complex interacted with the paramyxovirus polymerase L protein and that silencing of the R2TP complex led to uncontrolled upregulation of mumps virus (MuV) gene transcription but not genome replication. Regulation by the R2TP complex was critical for MuV replication and evasion of host innate immune responses. The R2TP complex also regulated measles virus (MeV) RNA synthesis, but its function was inhibitory and not beneficial to MeV, as MeV evaded host innate immune responses in the absence of the R2TP complex. The identification of the R2TP complex as a critical host factor sheds new light on the regulation of paramyxovirus RNA synthesis. Paramyxoviridae includes several important human and animal pathogens such as mumps virus (MuV) and measles virus (MeV). Paramyxovirus RNA synthesis is strictly regulated by both viral and host proteins. In this study, we identified the R2TP complex as a novel host factor regulating paramyxovirus RNA synthesis. The R2TP complex is a Hsp90 co-chaperone and is involved in Hsp90-mediated assembly of large protein complexes. We showed that the R2TP complex precisely regulated MuV transcription by interacting with the polymerase L protein. This regulation was critical for MuV evasion of host innate immune responses and for viral replication. We also showed that the R2TP complex regulated MeV RNA synthesis, but that its function was inhibitory and not beneficial to MeV. Our findings support a novel regulation mechanism of paramyxovirus RNA synthesis that is directly relevant to its biology and life cycle, and provide the first evidence linking the R2TP complex to defense against viral infection.The family  Paramyxoviridae  [GCA_000001405.33]) using the RNA-Seq analysis tool in the CLC Genomics Workbench 9.0.1 (Qiagen). RNA-Seq analyses using the human genome were performed with GRCh38.91 annotation data. Differentially expressed genes between infected and uninfected cells were identified at combined cut-offs of as a false discovery rate <0.01 and |logng DAVID . A p-valt tests. Error bars indicate the standard deviations of triplicate measurements. Statistical significance was assumed at **p<0.01. n.s. = not significant.Differences between groups were evaluated using unpaired Student’s S1 FigA series of truncated mutants of HA-tagged MuV L protein were expressed in 293T cells, immunoprecipitated with anti-HA antibody, and immunoblotted with anti-HA and anti-Hsp90 antibodies. Asterisks indicate the bands corresponding to each mutant.(TIF)Click here for additional data file.S2 Fig1-900 in 293T cells, immunoprecipitated with anti-FLAG antibody and immunoblotted with the indicated antibodies.FLAG-PIH1D1 and its truncated mutants were co-expressed with HA-MuV-L(TIF)Click here for additional data file.S3 FigAt 48 h post-transfection with either siRPAP3 or siNC, A549 and A549/hSLAM cells were infected with rMuV/AcGFP and rMeV/EGFP, respectively, at an MOI of 0.05. At 48 hpi, cells were stained with rabbit anti-MuV N or mouse anti-MeV N antibody and AF594-conjugated anti-rabbit or -mouse IgG. The cell nuclei were stained with DAPI (blue).(TIF)Click here for additional data file.S4 Fig1-900 in 293T cells, immunoprecipitated with anti-FLAG antibody and immunoblotted with the indicated antibodies.FLAG-RPAP3 and its mutants were co-expressed with HA-MuV-L(TIF)Click here for additional data file.S5 Figt-test. n.s. = not significant.The levels of IFNβ mRNA in A549 cells at 48 h post-transfection with either siRPAP3 or siNC were measured relative to their expression in untransfected cells and normalized to levels of HPRT1 mRNA. Error bars indicate the standard deviations of triplicate wells. The significance of differences between means was determined using the Student’s (TIF)Click here for additional data file.S6 FigA) Scatter plots of differential gene expression following MuV infection at 48 hpi in RPAP3-knockdown and control cells. Each dot represents the mean expression value (log2-fold change of MuV-infected versus mock cells). x-axis: control cells, y-axis: RPAP3-knockdown cells. Genes with altered expression (>4-fold change) are colored in red and blue for upregulation and downregulation, respectively. (B) GO enrichment analysis of genes with altered expression (>4-fold change) between RPAP3-knockdown and control cells involved in the indicated biological processes. GO categories associated with immunity and inflammation are colored in red.At 48 h post-transfection with either siRPAP3 or siNC, A549/SeV-C and A549/Ctrl cells were infected with rMuV/AcGFP at an MOI of 0.05. ((TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.S8 Table(PDF)Click here for additional data file.S9 Table(PDF)Click here for additional data file.S10 Table(PDF)Click here for additional data file.


Cyclic adenosine monophosphate (cAMP) response element-binding protein (CREB) is overexpressed and has an oncogenic role in hepatocellular carcinoma (HCC). Interleukin enhancer binding factor 2 (ILF2) has become research hotspot in liver cancer recently. However, it is still unclear whether and how CREB and ILF2 interact with each other. And how this interaction exerts its role in occurrence and development of liver cancer is still unclear. Here, we found that ILF2 directly bound with CREB, and this binding was essential for the malignant phenotypes of liver cancer cells. Moreover, we found that ILF2 acted as one of the upstream proteins of CREB and promoted CREB only in the protein level, whereas ILF2 expression was not regulated by CREB. Mechanistically, ILF2 bound to the pKID domain of CREB and stimulated its phosphorylation at Ser133. Taken together, our study finds a novel interaction between CREB and ILF2 in liver cancer, and this interaction might play a role in the diagnosis and remedy of liver cancer. Liver cancer is the fifth most common cancer in the world and the third leading cause of cancer deaths . AlthougILF2 is one type of transcription factor and is also named as the nuclear factor of activated T cells (NF45). It regulates cell growth via regulating mRNA stability. Increased mRNA levels of NF45 were observed in lymphoma and leukemia cell lines . Liver cIn the current work, we emphasized the importance of CREB and ILF2 in stimulating malignant phenotypes of liver cancer cells. Our work also suggested that these two proteins had a positive relationship in tumor tissues, indicating that they might play key roles in liver cancer. In summary, our work summarizes a new relationship between these two proteins and uncovers the mechanism between them.2. Cells were treated with cycloheximide (CHX)  at a final concentration of 50 μg/ml. Tumorous and normal liver tissues were gained at Shanghai Tenth People's Hospital under institutional approval. Informed written consent in the study was gained from all participants. The short hairpin RNAs (shRNAs) against human CREB (hCREB) (sh1&sh2) (targeting CDS sequence), lentiviral-based hCREB-HA, and lentiviral-based human ILF2- (hILF2-) FLAG-expressing plasmids were purchased from Biolink . The shRNAs against hILF2 (sh1&sh2) (targeting 3'UTR sequence) were bought from GeneChem . Plasmids were transfected using Lipofectamine 2000 reagent following the manufacturer's instructions. WT-CREB, Del-pKID-CREB, and Del-bZIP-CREB were constructed by overlapping PCR using pcDNA3.1(+) as the backbone. Primers used were WT-CREB-F: ACTGGAATTCATGACCATGGAATCTGGAGCCGAGAACC and WT-CREB-R: ACTGGATATCTTAAGCGTAGTCTGGGACGTCGTATGGGTAATCTGATTTGTGGCAGTAAAGGTC; Del-pKID-CREB-F: GAAGAAGAGAAGTCTGAAGAGGAGA and DEL-PKID-CREB-R: AGACTTCTCTTCTTCCTGTGAATCTTCACTTTCTGCAATA; Del-bZIP-CREB-F: ACTGGAATTCATGACCATGGAATCTGGAGCCGAGAACC and Del-bZIP-CREB-R: ACTGGATATCTTAAGCGTAGTCTGGGACGTCGTATGGGTAATCTGATCGTGCTGCTTCTTCAGCAG.HEK-293T, Bel-7402, and SMMC-7721 cells obtained from the cell bank of the Chinese Academy of Sciences  were cultured in Dulbecco's modified Eagle's medium (DMEM)  supplemented with 10% fetal bovine serum (FBS)  and were incubated in 37°C and 5% COFor IHC, tissue sections were deparaffinized and hydrated in xylene and serial alcohol solutions, respectively. Endogenous peroxidase activity was blocked by incubation in sodium citrate at 100°C for 2 hours. The specimen was blocked by 5% normal goat serum at room temperature for one hour before being incubated with primary antibodies anti-CREB , Boston, MA, USA, #9197) or anti-ILF2  overnight at 4°C. The slices were incubated with secondary antibody signal stain (R) boost IHC detection reagent  at room temperature for one hour. Antigen-antibody reactions were detected with DAB  under the instructions. The stain was counterstained with hematoxylin, dehydrated in ethanol, cleared in xylene, coverslipped, and photographed by Leica camera.For WB, the cells were lysed in western/IP lysis buffer  on ice for 30 minutes and centrifuged at 15,000 g for 15 minutes at 4°C to collect whole cell lysates. Protein extracts were quantitated with BCA protein assay kit , subjected to electrophoresis on a 10% SDS-PAGE gel with 100–200 V, and transferred onto a nitrocellulose filter membrane  at 200 mA with cooling. The membrane was blocked with 5% nonfat milk dissolved in Tris-buffered saline Tween-20 (PBST) at room temperature for one hour. Membranes were incubated with anti-CREB , anti-p-CREB , anti-ILF2 , or anti-GAPDH  overnight at 4°C, washed with PBST for 10 minutes three times, and then incubated with anti-rabbit IgG, HRP-linked antibody  at room temperature for one hour. After washing, protein bands were visualized using enhanced chemiluminescence (ECL) coloring fluid, developer and fixer. The relative expression levels of proteins were determined by densitometry using ImageJ software and were normalized against GAPDH.For IF on cell cover slips, cells were seeded on the cover slips in 24-well cell culture plates, fixed with 4% paraformaldehyde (PFA) for 15 minutes after 24 hours, washed with PBS for 5 minutes three times, permeabilized with 1% Triton X-100/PBS for 15 minutes, blocked by 1% BSA for 30 minutes, then incubated with the primary antibodies anti-CREB  or anti-ILF2  overnight at 4°C. After washing, the cells were incubated with the secondary antibodies fluorescent Alexa Fluor 488 or Alexa Fluor 555  at room temperature for one hour and counterstained with DAPI . Images were obtained by Leica DMRA fluorescence microscope. For IF on tissue sections, after the antigen was repaired, the remaining steps were the same as those on the cell cover slips.μl antibodies, shook overnight at 4°C, washed with western/IP lysis buffer, and centrifuged at 3500 rpm for 1 minute at room temperature three times. The remaining steps were similar to western blotting. The antibodies used for IP were anti-CREB , anti-CREB , anti-ILF2 , anti-FLAG , and anti-HA . For in vitro reciprocal co-IP, the reagents used were purified protein CREB , protein ILF2 , and DTT  and the method has been described before [co-IP was performed as described previously . Brieflyd before , 19.Cell proliferation, caspase 3/7 activity, and colony formation capacity were measured using MTT-based assay, caspase 3/7 Glo luciferase reagent , and soft agar colony formation assay, respectively, which were described previously . The totThe protein ligation assay was carried out to identify the direct interaction between CREB and ILF2 or ILF3 using the Duolink™ in situ red starter kit (mouse/rabbit) . The cells were seeded on glass cover slips in 24-well plates. On the second day, the cells were fixed with 4% PFA for 15 min and blocked with the blocking buffer supplied by the manufacturer for 1 h. After blocking, the cells were incubated overnight at 4°C with the indicated suitable primary antibodies. The primary antibodies used were anti-CREB , anti-ILF2 , and anti-ILF3 . On the third day, the PLA probe solution  was added into each well for 1 h at 37°C, and the ligase-ligase solution (supplied by the manufacturer) was added into each well and incubated for 30 min at 37°C. After ligation, the amplification-polymerase solution (supplied by the manufacturer) was added into each well for another 100 min at 37°C and subjected to microscopic analysis. When the proximity of two PLA probes is less than 40 nm, the red fluorescent emissions can be detected .The specific method was described before . The part-test, one-way ANOVA test, and the Spearman rank-correlation analysis. P < 0.05 was considered statistically significant.Data were analyzed using SPSS 20.0. Tests used to examine the differences between groups included the Student Proteins pulled down by anti-CREB antibody were analyzed by the mass spectrometry analysis, and three transcription factors KAP1, ILF2, and ILF3 were identified via literature retrieval , 23, 24 R = 0.819, P < 0.001) (Supplementary vice versa (Supplementary in vitro (Supplementary To understand the expression of two proteins in liver tissues, we detected mRNA levels of CREB and ILF2 and observed that CREB and ILF2 mRNA levels were upregulated in liver cancer tissues compared to adjacent normal tissues (Supplementary We observed that overexpression or knockdown of CREB did not regulate the expression of ILF2, while knockdown of ILF2 resulted in a significant reduction of CREB in both Bel-7402 and SMMC-7721 cells Figures . Then weWe also observed that compared to separately knocked-down or overexpressed ILF2 and CREB, simultaneously knocked-down or overexpressed ILF2 and CREB more obviously inhibited or stimulated the proliferation and colony formation, whereas they stimulated or inhibited the caspase 3/7 activity of liver cancer cells Figures . MoreoveWe subsequently investigated how ILF2 regulates CREB expression. We eliminated the possibility that ILF2 could regulate the mRNA level of CREB by qPCR experiments . In addiCREB protein contains two critical function domains, pKID domain and bZIP domain , 28. We If not diagnosed early, the treatment of liver cancer patients would be very difficult. Despite decades of researches on its etiology and pathogenesis, our understanding of the molecular mechanisms of liver cancer remains superficial. Although we have reported the interplay of YAP and CREB in liver cancer , the intIn this study, we observed that CREB expression was positively associated with the malignant phenotypes of liver cancer cells, whereas ILF2 expression was not associated with the malignant phenotypes of liver cancer cells. Previous studies have reported that CREB stimulates the expressions of several cancer promoters like YAP , HULC 2, c-FLIP(We observed that pKID domain, which can play a transcriptional regulatory role and bind to other protein domains , played Taken together, our findings uncover a new phenomenon that the relationship between CREB and ILF2 promotes liver cancer growth, and ILF2 only stimulates CREB in the protein level. This interaction might be helpful to the diagnosis and treatment of liver cancer.


The checkpoint receptor PD-1 suppresses the functionality of virus-specific CD8+ T cells during chronic infection. However, the role of the PD-L1/PD-1 pathway during the acute phase of infections has not been well characterized. In the current study the effects of PD-1 or PD-L1 deficiency on the CD8+ T cell response against Friend retroviral (FV) infection of knockout mice was analyzed during acute infection. We observed an enhanced proliferation, functional maturation, and reduced apoptosis of effector CD8+ T cells in the absence of PD-1 or PD-L1. The knockout of PD-L1 had a stronger effect on the functionality of CD8+ T cells than that of PD-1. Augmented CTL responses were associated with an improved control of FV replication. The strong phenotype of FV-infected PD-L1 knockout mice was independent of the interaction with CD80 as an additional receptor for PD-L1. Furthermore, we performed a detailed analysis of the production of different granzymes in virus-specific CD8+ T cells and observed that especially the simultaneous production of multiple granzymes in individual T cells  was under the control of the PD-1/PD-L1 pathway. The findings from this study allow for a better understanding of the development of antiviral cytotoxic immunity during acute viral infections.Cytotoxic CD8 However, in several chronic viral infections, such as Human Immunodeficiency virus (HIV) and Hepatitis C virus (HCV) infection of humans or Lymphocytic Choriomeningitis virus (LCMV) and Friend virus (FV) infection of mice, virus-specific CD8+ T cells become functionally exhausted. There is compelling evidence that this T cell exhaustion contributes significantly to the establishment of viral chronicity. The functional impairment of CTLs is associated with the expression of inhibitory checkpoint receptors and is a result of signaling from these receptors after binding to their ligands   , Hepatitus (EBV) , or Hepaus (EBV)  as well us (EBV) . In expepoptosis . Further+ T cells up-regulate the expression of PD-1 but remain fully functional during the first 2 weeks of FV infection    and myel (Tregs)  were invAnimal experiments were performed in strict accordance with the German regulations of the Society for Laboratory Animal Science (GV-SOLAS) and the European Health Law of the Federation of Laboratory Animal Science Associations (FELASA). The protocol was approved by the North Rhine-Westphalia State Agency for Nature, Environment, and Consumer Protection (LANUV). All efforts were made to minimize suffering.b/b, Fv1b/b, Fv2r/r, Rfv3r/r. The B6 mice were obtained from Charles River Laboratories. B6-background PD-1 deficient (PD-1−/−) mice were generated in Dr. Honjo's lab (−/− (B7-H1-KO) mice were originally generated by L.C.  mice were maintained under pathogen free conditions. Experiments were performed using C57BL/6 (B6) mice. The relevant FV resistance genotype of B6 mice is H-2jo's lab . B6-back by L.C. . B6.SJL- epitope , 19. DbGThe FV stock used in these experiments was a FV complex containing B-tropic Friend murine leukemia helper virus (F-MuLV) and polycythemia-inducing spleen focus-forming virus free of lactate dehydrogenase-elevating virus , 21. TheCell surface staining was performed using Becton Dickinson or eBioscience reagents. Following antibodies were used: anti-CD3, anti-CD4 (RM4-5), anti-CD8 (53-6.7), anti-CD43 (1B11), anti-CD45.1 (A20), CD80 (16-10A1), anti-PD-1(J43), and IgG fluorochrome-conjugates as isotype controlls. Dead cells were detected by Fixable Viability Dyes (FVD) (ThermoFisher).FVD positive cells were excluded from the analyses. Intracellular granzyme A (GzA-3G8.5), granzyme B , granzyme K (orb102688), activated caspase 3, and Ki67 stainings were performed as described . Data web-GagL-specific CD8+ T cells, spleen cells were stained with PE labeled MHC class I H2-Db  tetramers specific for FV GagL peptide  microbeads  according to the manufacturer's instructions. Efficiency of cell separation was proven by flow cytometry (92% CD8+ T cells). Ten thousand purified cells were transferred into recipient WT or PD-L1−/− mice by i.v. injection in 100 μl PBS.CD8in vivo CTL assay described by Barber et al. (bGagL peptide (7 cells of each population) were transferred i.v. into naïve or 10 day FV-infected mice. One hour after adoptive transfer, the spleens and bone marrows from recipient mice were harvested and cell suspensions were prepared. Cell suspensions were stained with anti CD45.1 antibodies and measured by LSR II. Donor cells were distinguished from recipient cells and from one another based on CFSE positivity and on the expression of CD45.1. The percentage of killing was calculated as follows: 100 – ([(% peptide pulsed in infected/% unpulsed in infected)/(% peptide pulsed in uninfected/% unpulsed in uninfected)] × 100).The r et al.  was modir et al. . Splenoc peptide , 22. The−/− mice were infected with FV. 250 μg of anti CD80 or control rat IgG antibody (BioXCell) were administered i.p and treatment started at day 1 after infection and repeated every alternating day for a total of three injections.C57BL/6 or PD-1−/− mice were infected with FV. Z-VAD-FMK General Caspase Inhibitor (BD Pharmingen) was administered i.p used to inhibit apoptosis in vivo. Z-VAD-FMK (5 μg/kg) was administered i.p. at day 6 and day 7 after infection (C57BL/6 or PD-1nfection .mus musculus. Further search parameters matched previously reported ones (p < 0.05) were functionally annotated using the Database for Annotation, Visualization, and Integrated Discovery  (Cells were lysed by sonication (6 10-s pulses on ice) in sample buffer . Protein isolation, digestion, amino acid analysis, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis were performed by following previously described procedures . Progeneted ones . Non-unier. 6.8) , 27.t-test or Mann-Whitney t-test. When more than two groups were compared, a one-way ANOVA was used with a Tukey post-test. . For statistical analysis of proteomics data, normalized protein abundances were exported from Progenesis QI software and transformed using arcsinh-function. Using an in-house written R script , Benjamini–Hochberg corrected one-way ANOVA was used for the calculation of the FDR-corrected p-values as described earlier  were defined by their expression of a glycosylated form of the CD43 molecule (−/− and PD-L1−/− mice were infected with FV. In these mice the effector CD8+ CD43+ T cells and CD8+ T cells specific for the H-2Db–restricted Friend murine leukemia virus–glycosylated immundominant gag epitope (tetramer+) (+CD43+ T cells in WT mice and both knockout (KO) mouse strains started at day 6 after infection   were chatramer+) . Both thnfection . Howevernfection . At day + T cells specific for the FV gagL epitope was very similar to the kinetic of the total effector CD8+ CD43+ population. The first virus-specific cells were detectable in the spleens of WT mice at day 7 after infection  in spleen and BM of infected WT, PD-1−/−, and PD-L1−/− mice. The frequency of GzmB+ effector CD8+ CD43+ T cells was enhanced at day 7 after infection in spleens , GzmB, and granzyme K (GzmK) were determined in the spleen of WT and PD-L1−/− mice at day 8  and were transferred into WT or PD-L1−/− mice 1 day prior to FV infection . FV-specific CD8+ T cells were isolated from TCR-Tg-CD45.1 mice and transferred into WT or PD-L1−/− mice. One day after transfer the recipients were infected with FV. Expanded donor CD8+ CD45.1+ T cells were sorted from splenocytes at day 12 after FV infection. Cells were lysed and subjected to proteome analysis. 2673 proteins were quantitated and compared between CD8+ CD45.1+ T cells isolated from WT vs. PD-L1 KO mice . Thus, the CD80 expression on FV-induced effector CD8+ T cells was not involved in the PD-L1 dependent regulation of this population.Our current data show that both PD-1 receptor deficiency as well as PD-1 ligand deficiency influences CD8 T cells . In orde Figures . So therantibody  did not  Figures . The pro−/− and PD-L1−/− mouse strains for a kinetic analysis of CD8+ T cell responses and FV load. We observed an enhanced expansion of CD8+ effector T cells in both KO mouse strains during the early acute phase of FV infection (+ T cells. However, CD80 was not involved in the PD-L1-mediated suppression of CD8+ T cell responses. In previous studies it was shown that deficiency in the PD-1/PD-L1 pathway or the blockade of the interaction between these molecules resulted in an enhanced elimination of the adenovirus (The current study used the PD-1nfection . PD-L1/Penovirus , LP-BM5 enovirus , human menovirus , rabies enovirus , LCMV (2enovirus , and FV enovirus . On the enovirus , murine enovirus  or LCMV enovirus , 45 lead+ T cells remained high during late acute infection in PD-L1−/− mice, but not in WT or PD-1−/− mice. We therefore analyzed the role of another molecule as a possible receptor for PD-L1. Previously reverse signaling from CD80 after ligation to PD-L1 was described (+ T cells. However, the treatment of WT and PD-1−/− mice with anti-CD80 antibodies did not lead to a detectible modulation of CD8+ T cell responses. The regulation of the functionality of CD8+ T cells is one important aspect of PD-1/PD-L1 signaling. In the LCMV model it was previously noted that deficiency for PD-1 led to a reduced production of IFN-γ in virus-specific CD8+ T cells after stimulation with viral antigens (high CD8+ T cells, which also co-expressed other inhibitory receptors during the course of infection, produced significantly less cytokines in response to antigen re-stimulation than PD-1low CD8+ T cells (+ T cells. The co-expression of different inhibitory checkpoint receptors on terminally differentiated CD8+ T cells is an essential mechanisms for the control of potentially pathogenic CTLs. Interestingly, PD-1 also plays an important role in the regulation of longterm memory CD8+ T cells (+ T cell responses and how these molecules influence the differentiation of the memory pool of CD8+ T cells during the later phase of viral infections.It is interesting that the frequency of effector CD8escribed . Thus, bantigens . This ob T cells . In cont T cells . Current+ T cells is one of the known mechanisms regulating the numbers of CTLs in infected organ (+ T cells (+ T cells (+ CD8+ T cells was observed in melanoma patients successfully treated with anti-PD-1 antibodies (+ T cells was regulated by the PD-1 receptor. Effector cells that expanded without PD-1/PD-L1 regulation expressed reduced levels of activated caspase 3 in the cytoplasm. Cells with high levels of caspase 3 expression were predisposed to apoptotic death (+ T cells during the early phase FV infection. Thus, apoptosis was involved in regulating numbers of expanded effector T cells. The regulation of T cell apoptosis through PD-1/PD-L1 molecules is most likely an important mechanism determining the magnitude of the CTL responses in infected organs. The quantity of effector CD8+ T cells is one important aspect of the PD-1 regulation, whereas the functional maturation toward cytotoxic T cells is another. In the current study, we analyzed the role of PD-1 signaling for the ability of CD8+ CTLs to simultaneously produce the different cytotoxic effector molecules granzyme A, B, and K. Interestingly, effector CD8+ T cells that produced two or three granzymes simultaneously were impaired by the PD-1 checkpoint mechanism. Deficiency for PD-L1 clearly enhanced numbers and presence of polyfunctional cytotoxic cells in FV-infected organs. Thus, PD-1 signaling not only regulates the quantity of antiviral T cells through the inhibition of proliferation and the induction of apoptosis, but is also critical for inhibiting the differentiation of these cells into polyfunctional cytotoxic T cells. These observations from KO mice allow us to better understand the role of PD-1 during the early phase of antiviral immune responses and may provide new strategies for the development of successful immunmodulatotry treatments of viral infections or tumors and for the development of efficient prophylactic and therapeutic vaccines.The effect of the PD-1 receptor on the proliferation of effector CD8ed organ . Apoptos T cells . Apoptos T cells . In prev T cells . Moreovetibodies . Howevertibodies . This entibodies . Our finic death . The trePD and DM: data collection, data analysis and interpretation, drafting the article. TK and TW: data collection, data analysis and interpretation. JL: data collection, data analysis and interpretation, drafting the article. LC: supplied the animals, critical revision of the article. BS: data analysis and interpretation, critical revision of the article. UD: conception or design of the work, critical revision of the article. GZ: conception or design of the work, data analysis and interpretation, drafting the article, critical revision of the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The gene chCH25H is located on chromosome 6 and clustered in a distinct group with mammals CH25H in the phylogenetic tree. The core promoter region of chCH25H was located within −75/−1 sequence. We found that chCH25H was induced by chicken IFN-α and ALV-J in DF1 cells. The overexpression of chCH25H significantly inhibited ALV-J replication in DF1 cells at 48 h post infection (hpi). In addition, ALV-J replication was significantly enhanced in the chCH25H- knockout DF1 cells. Furthermore, we demonstrated that chCH25H restricted ALV-J infection through the production of 25-hydroxycholesterol (25HC), rather than type I and II interferon. Our results identified 152 potential anti-ALV-J chicken type I ISGs and revealed that 25HC, the product of chCH25H, could be used as a natural antiviral agent to control ALV-J infection.The avian leukosis virus subgroup J (ALV-J) belongs to the chicken retrovirus that causes enormous economic losses in the poultry industry. Interferon-stimulated genes (ISGs) are critical for controlling virus infections. Here, we identified 897 type I ISGs induced by interferon-α (IFN-α) in chicken peripheral blood mononuclear cell (PBMC) by RNA-Seq. In addition, we further identified 152 potential anti-ALV-J chicken type I ISGs. Among these potential anti-ALV-J ISGs, chicken cholesterol 25-hydroxylase ( The avian leukosis virus subgroup J (ALV-J) is a member of the a-retrovirus genus of retroviridae, causing tumor disease, immunosuppression, and other secondary diseases in chicken. ALV-J has caused enormous losses to the world poultry industry at the end of the last century . The preStimulation with interferon (IFN) induces the expression of hundreds of genes defined as IFN-stimulated genes (ISGs) ,3. HundrchCH25H). Previously, it has been reported that CH25H broadly inhibited viral entry by production of 25-Hydroxycholesterol (25HC) PKR [Mx [[Mx [ZAP , Viperin[Viperin  and IFITn [IFIT5  have been [IFIT5 . HoweverIn this study, 897 genes significantly up-regulated by chIFN-α in chicken PBMC were considered to be chicken type I ISGs. ISGs expression levels are often dependent on many factors such as treatment time, IFN and virus dose, and cell type . MeantimCH25H [chCH25H, an anti-ALV-J ISG candidate, was chosen to further explore its anti-ALV-J mechanism in DF1 cells. As an enzyme, CH25H catalyzes the cholesterol to form a soluble factor, 25HC [CH25H is broadly antiviral by producing 25HC to fight against several viruses such as mammalian reovirus [chCH25H inhibit the replication of the notorious chicken retrovirus ALV-J or not? In our latest study, we found that overexpression of chCH25H in chicken primary macrophage could restrict ALV-J infection [CH25H against ALV-J infection in chicken macrophages.Furthermore, given that the broad antiviral effects of CH25H ,19,20,21or, 25HC . Recent reovirus , hepatitreovirus , lassa vreovirus  and porcreovirus . The mecreovirus . Whethernfection . HoweverCH25H is a conserved ISG in mammals, but lacks enough description in the chicken, especially its antiviral function. In the present study, we demonstrated that chIFN-α and ALV-J induced expression of chCH25H in chicken PBMC and DF1 cells (chCH25H is an interferon-stimulated gene in chicken. ISGs activation followed the binding of transcriptional complex and ISRE or GAS [chCH25H analysis showed that 8 GAS were located in these regions, but no ISRE (chCH25H not only can be induced by IFN-α, but also might be induced by IFN-γ. The upstream unknown region of the chCH25H still needs to be identified, with the hope to find ISRE elements in those regions.F1 cells . Thus, cE or GAS . Of the E or GAS . In geneE or GAS . However no ISRE C. Our rechCH25H and its product, 25HC, both inhibited ALV-J replication in DF1 cells. Previous studies have found that administration of 25HC could inhibit HIV-1 and Zika virus infection in animal models [CH25H played an important physiologic role in antiviral defense. Given that no vaccine for ALV-J is currently available, chCH25H can be used as a new strategy to control ALV-J. 25HC could potentially be used as an anti-ALV-J therapeutic as it has in vitro activity against ALV-J. Although the antiviral mechanism of 25HC through affecting viral and cell membrane fusion has been widely found, other new antiviral mechanisms still need to be determined. However, the antiviral activity of 25HC against a number of viruses still highlights this oxysterol as a potential target for antiviral therapy. The further study on the underlying immunological mechanism of chCH25H and 25-HC in inhibiting ALV-J infection should be illuminated. Furthermore, transgenic chickens with overexpression of chCH25H in vivo deserve further research. These CH25H-transgenic chickens may have a broad-spectrum antiviral property.Furthermore, we found that l models ,17. TheschCH25H was a chicken ISG and that it could inhibit ALV-J replication through 25HC in DF1 cells. These findings characterized a new chicken ISG and provided new insights into the control of ALV-J infection.In this study, we first identified 152 potential anti-ALV-J chicken type I ISGs. In addition, we further demonstrated that


KRAS G12X mutations and KRAS dynamics we show that this assumption does not hold true. Instead, our findings revealed an outstanding mutational bias. We conducted a thorough mutational analysis of KRAS G12X mutations and assessed to what extent the observed mutation frequencies follow a random distribution. Unique tissue-specific frequencies are displayed with specific mutations, especially with G12R, which cannot be explained by random probabilities. To clarify the underlying causes for the nonrandom probabilities, we conducted extensive atomistic molecular dynamics simulations (170 μs) to study the differences of G12X mutations on a molecular level. The simulations revealed an allosteric hydrophobic signaling network in KRAS, and that protein dynamics is altered among the G12X mutants and as such differs from the wild-type and is mutation-specific. The shift in long-timescale conformational dynamics was confirmed with Markov state modeling. A G12X mutation was found to modify KRAS dynamics in an allosteric way, which is especially manifested in the switch regions that are responsible for the effector protein binding. The findings provide a basis to understand better the oncogenic properties of KRAS G12X mutants and the consequences of the observed nonrandom frequencies of specific G12X mutations.A mutated KRAS protein is frequently observed in human cancers. Traditionally, the oncogenic properties of KRAS missense mutants at position 12 (G12X) have been considered as equal. Here, by assessing the probabilities of occurrence of all  KRAS is frequently mutated in various cancers. When the amino acid glycine 12 is mutated, KRAS protein acquires oncogenic properties that result in tumor cell-growth and cancer progression. These mutations prevail especially in the pancreatic ductal adenocarcinoma, which is a cancer with an exceptionally dismal prognosis. To date, there is a limited understanding of the different mutations at the position 12, also regarding whether the different mutations would have different consequences. These discrepancies could have major implications for the future drug therapies targeting KRAS mutant harboring tumors. In this study, we made a critical assessment of the observed frequency of KRAS G12X mutations and the underlying causes for these frequencies. We also assessed KRAS G12X mutant discrepancies on an atomistic level by utilizing state-of-the-art molecular dynamics simulations. We found that the dynamics of the mutants does not only differ from the wild-type protein, but there is also a profound difference among the different mutants. These results emphasize that the different KRAS G12X mutations are not equal, and thereby they suggest that the future research related to mutant KRAS biology should account for these observations.The oncogene  KRAS is frequently mutated in various human cancers. The mutation is most often, in about 86% of the cases [KRAS G12X mutation are characterized by the deficiency of the intrinsic GTPase activity and the insensitivity for GTPase-activating proteins (GAPs) [The small GTPase protein KRAS is a signal-transducing protein, which binds GDP in its inactive state and GTP in its active state . The genhe cases , found as (GAPs) ,4. Theses (GAPs) . The bass (GAPs) .An interesting discrepancy among KRAS G12X mutants is observed in their intrinsic GTPase activity . The G12To bind RAS, the effector proteins use a ubiquitin (UB)-like fold: a RAS-binding domain (RBD) or a RAS-association domain (RA) ,12. WhilPrevious molecular dynamics (MD) simulation studies of KRAS at microsecond timescales have mainly focused on the dynamical differences between the three wild-type RAS isoforms  , differeWhat is the underlying cause for the broad range of different G12X mutations? How do these distinctly different mutations manifest themselves in the structure, dynamics, and function of KRAS? This knowledge is crucial to understand KRAS oncogenesis and to develop future therapies targeting mutant KRAS harboring tumors. Therefore, in the present study we first assessed to what extent G12X mutation frequencies are explained by mutation probability. Intriguingly, an outstanding mutational bias emerged from the data. We next employed state-of-the-art atomistic MD simulations  to study the dynamical behavior of KRAS with its natural ligands  bound, both in the wild-type KRAS and with all existing oncogenic G12X mutations. The results provided compelling evidence that mutations alter the dynamics of KRAS, that the alteration is mutation specific, displays allosteric characteristics, and that the alteration is manifested especially in the effector protein-binding interface. Furthermore, our data suggest that the observed mutational bias and the oncogenic properties of the individual KRAS G12X mutants are caused, at least in part, by mutation-specific altered dynamics.KRAS G12X missense mutation frequencies, we compiled data from the Catalogue of Somatic Mutations in Cancer [KRAS G12X missense mutation were found from the database. For our analysis, we included only tissues that exhibited these mutations >10%. This status is displayed in eight tissue types, which in total comprised 31,251 positive samples . The large intestine , the lung , and the pancreas  were observed to have numerous positive samples, whereas the biliary tract, the endometrium, the ovary, the peritoneum, and the small intestine comprised altogether only 2,085 positive samples.First, to perceive up-to-date data of KRAS G12X may result in one of six possible missense mutations . Meanwhile, in the pancreas the probability of the G>C mutation is increased (P < 0.001). Moreover, as all of the G12X mutations occur in the first or the second guanine of the codon   base in c.34G or c.35G is substituted to adenine (A), cytosine (C), or thymine (T) . This ba, c.35G) , we asce, c.35G) . In fact, c.35G) . A few e, c.35G) . As for , c.35G) . All tis, c.35G) . Above aWe evaluated how random the occurrences of the specific G12X mutations are. To this end, we used the transition:transversion mutation ratio as a figure of merit, and compared this figure to a value of 2.3, which is the ratio for missense mutations observed in large-scale genomic analyses ,35. If tGGT sequence lacks a typical hotspot mutation region, such as a CpG site [Since local DNA-sequences have clearly a major influence on the mutation probability, a sequence-dependent basis for the observed non-random mutations may exist. The TCpG site . HoweverCpG site ,38. The CpG site . Both guCpG site . The oxiCpG site , and theCpG site ,42. FinaCpG site . ConcludTo understand how G12X mutations affect KRAS functionality, we conducted a total of 170 μs (85 x 2 μs) atomistic MD simulations of wild-type KRAS and all G12X missense mutants, with GDP and GTP. Each individual system was replicated five to ten times starting from different initial conditions .In the simulations, we observed no differences in the dynamics of the residue 12 (or in its vicinity), which appeared to be extremely stable. In contrast, the switch regions (switch-I and switch-II) exhibited highly dynamic behavior demonstrated by the root-mean-square fluctuation (RMSF) analysis, which revealed major fluctuations in the protein in these regions  Figs. NeTo gain better insight into the protein dynamics, we conducted principal component analysis (PCA)  with an Notably, the α4-helix motion is only observed with GTP bound systems (PC2). This observation is in agreement with the experimental results by Mazhab-Jafari et al. . They obIn order to ascertain dissimilarities between the different systems, we next generated score plots for the principal components PC1-3 . The resWe extended the analysis by carrying out PCA for each system to illustrate the differences in their dynamics –S9 Figs.Even though there are no additional direct interactions from the mutated side-chains of G12X, a mutation in this position inflicts a change to the dynamics in the distant sites of KRAS that were highlighted by the PCA analysis. To investigate this, and to identify possible interaction network routes in KRAS, we conducted an interaction network analysis . InteresThis hub interaction network is highly distorted in G12A and G12S mutants  Figs. ThIn contrast to G12A and G12S, the other mutants  seem to follow more closely the wild-type’s interaction patterns. However, selected interactions are shifted even with these mutants, although not that extensively as observed with G12A and G12S. For instance, in the hub M72 located in the switch-II region the interaction patterns are shifted with G12C, G12R, and G12V . InteresWe also noticed that the frequency of the salt-bridge between the residues D154–R161 was altered in different systems . Both ofAs discussed above, the PCA and the interaction network analysis suggest that the protein dynamics is altered among the systems, yet in some obscure manner. To gain better insight into the origin of these differences in wild-type and mutant GTP-bound systems (active KRAS), we analyzed the simulation data by constructing Markov state models (MSMs) ,46 to exThe MSM analysis identified seven metastable states represented schematically in The states can be further divided in four groups based on their switch conformations . The staOf all the mutants, G12D displays the most similar metastable state population distribution compared to wild-type , Table 1KRAS G12X mutations poorly understood [KRAS G12X mutation probabilities, and to understand how they are associated with the observed mutation frequencies.Although frequently observed in cancer, not only is the basis for the specific frequencies of derstood , but alsOGG1), which is a base-excision repair enzyme for 8oxoG, exist in a catalytically active form for 8oxoG that is adjacent to guanine only in the 5’-position in -AGGT- sequences (KRAS sequence (-TGGT-) represents the c.34G position, thus suggesting that the c.34G position is more susceptible for DNA-repair. Nevertheless, this observation holds true only for the G>T transversion mutation. For the other mutations and their repair mechanisms, the positional bias needs to be investigated, especially for the G>A transition mutation, which holds the strongest bias in favor of c.35G mutations . Furthermore, exceptions or an enhanced preference in c.35G for specific mutations in particular tissues were observed. For instance, it seems that either the advantage for G12D or the disadvantage for G12S, or both, exists in the pancreas, given that there is a 28-fold preference for G>A mutations for c.35G over c.34G. Similarly, the G12R mutation displays an advantage in the pancreas, while G12A is perhaps disadvantageous, given that there is a 9-fold preference for c.34G over c.35G in the mutation probability in the G>C mutations. Altogether, these data suggest that specific mutations are advantageous or disadvantageous depending on the cellular and tissue environments. Therefore, we hypothesize that the biochemical and biophysical differences among mutants, resulting in signal-transducing differences, may explain, at least in part, the observed mutational bias.Generally, the mutation frequencies have an explanatory basis. For instance, chemical characteristics of c.35G explain the enrichment of the G12V mutations by oxidation. However, complex mutation distributions are displayed by the tissues, and we conclude that some of the observed frequencies cannot be explained simply by the mutation probability. For example, there is no clear explanation why, on average, a mutation occurs five times more probably in, e.g., c.35G than in c.34G. One plausible explanation is that the 3D-environment in the DNA-sequence may aid the c.35G mutations to evade DNA-repair mechanisms. In fact, the structures of DNA in complex with N-glycosylase/DNA lyase  are not radically different compared to the wild-type, although some alterations in the hub interactions are evident. However, even though a mutant, such as G12D, displays the same interaction frequencies as the wild-type, the characteristics of the interactions may still differ, as the exact characteristics of these interactions, unfortunately, cannot be derived from this analysis, only their frequencies.To highlight that the alteration in KRAS dynamics is also present with the mutants that display a minor shift in the hydrophobic hub interaction network compared to the wild-type, is the observed variability in the distribution among the metastable states of exceptional importance. The MSM confirmed the indirect effect of the mutation on the switch-region protein conformations and dynamics. As for MSMs one needs to have extended simulation data, we focused on the most important KRAS G12X mutants . In crystal structures these dynamic metastable states are not observed. This is due to the fact that in the structures the switch regions are disordered, if there are no crystal contacts to the switches. Based on the MSMs, the G12D mutant follows the dynamics of the wild-type more closely than of the G12R and G12V mutants. Intriguingly, this is in line with the findings of the interaction network analysis, where the G12D displayed the most similar profile with the wild-type. In particular, our MD results show that the effects of KRAS G12X mutants are mutation-specific, and suggest that the observed changes in protein conformations and dynamics may alter protein activity .We consider that the difference in the mutant dynamics, for instance the G12V dynamics with its inability to reach the metastable states I and V , may refAs a crucial factor for KRAS dimerization, the intermolecular D154–R161 salt-bridges between the dimers were recently identified . The KRAIn general, the mutational frequency data combined with the observation from the simulations suggest that at least in the pancreatic cancer, where a KRAS mutation is a key initiator , a majorIt has been clearly shown that the KRAS G12X mutation has an effect on the intrinsic GTPase activity and that it causes insensitivity for GAPs. However, it seems that the interpretation of the mutation effect on the oncoprotein’s behavior has been oversimplified. First, in specific tissues G12X mutation frequencies exhibit an inexplicable individual bias. Furthermore, the mutation inflicts individual changes in the protein dynamics, affecting the allosteric communication network that conveys the shift in dynamics to the remote sites within KRAS. Finally, this shift in protein dynamics may lead to modulated KRAS mediated signal transduction. We therefore suggest that altered dynamics among KRAS G12X mutants may promote the observed non-random frequencies in specific tissues. In order to establish successful therapies against mutant KRAS-harboring tumors, these discrepancies between the G12X mutants need to be reconsidered thoroughly. Concluding, KRAS G12X mutants are not equal, they are unique.2+. Water molecules were described with the TIP3P model [+ and Cl- ions. After energy minimization, the system preparation was done in four stages to obtain properly equilibrated and different initial structures for replica simulations  OPLS-AA force field –72. For 3P model . In eachThe RMSF were calculated using GROMACS tools . PrincipThe analysis of KRAS interaction networks  was conducted with PyInteraph  and visuMarkov state model generation was conducted with PyEMMA 2, following the general recommendations . As an iKRAS G12X mutation data was collected from COSMIC database v.79 (http://cancer.sanger.ac.uk/cosmic/) [KRAS G12X mutation probability, we included only single nucleotide substitutions. This choice was made based on the fact that more complex mutations and their probabilities  are not predictable with the existing knowledge. Fisher’s exact test was used to analyze the specific differences in mutation frequencies.The S1 FigA) Regardless of the bound effector protein, the RAS conformation in the HRAS–effector protein complexes remain identical. The superposed RAS structures have been taken from RAS-complexes as follows: RalGDS (PDB ID 4G0N), Raf-1 (PDB ID 1LFD) and PI3Kγ (PDB ID 1HE8). Highlighted in the figure are the switch-I (red) and switch-II (blue) regions, residue 12 (orange), and GNP-ligand . (B) The effector proteins bind RAS on top of the switch regions, indicating no direct contact between residue 12 (orange) and effector proteins. Shown is the RAS–PI3Kγ complex (PDB ID 1HE8), with PI3Kγ identified . The RAS surface is colored as in panel A, and GNP represented as CPK. (C) The effector protein-binding interface is identical with HRAS and KRAS. The hypervariable region (yellow) is not present in crystal structures (A and B). (D) The locations of the secondary structural elements in KRAS. Also, the positions of the Cα of residue 12 (cyan sphere), P-loop (cyan), γ-phosphate of the GTP , and the SAK-motif (black) are highlighted.((TIF)Click here for additional data file.S2 FigA) Distributions of KRAS G12X mutations calculated based on an assumption of random events dictated by a value of 2.3 for the transition:transversion ratio. The occurrence of mutations related to random mutation frequencies in (B) all tissues, (C) the pancreas, (D) the large intestine, (E) the lung, (F) the peritoneum, (G) the small intestine, (H) the biliary tract, (I) the endometrium, and (j) the ovary. Individual tissues (B-J) have been arranged in decreasing significance for the overall G12X mutation frequency (%), B displaying the highest and J the lowest. Mutation data have been collected from the COSMIC database v.79.((TIF)Click here for additional data file.S3 FigA) G12A, (B) G12C, (C) G12D, (D) G12R, (E) G12S, (F) G12V, and (G) wild-type. Error bars indicate the standard error (SE). The average of all GDP-bound systems is indicated with an orange line. RMSF has been calculated over a period of 300–2000 ns, with switch-I (residues 30–40) and switch-II (residues 58–72) identified as given here.Root-mean-square fluctuation (RMSF) of GDP-bound systems: ((TIF)Click here for additional data file.S4 FigA) G12A, (B) G12C, (C) G12D, (D) G12R, (E) G12S, (F) G12V, and (G) wild-type. Error bars indicate the standard error (SE). The average of all GDP-bound systems is indicated with an orange line. RMSF has been calculated over a period of 300–2000 ns, with switch-I (residues 30–40) and switch-II (residues 58–72) identified as given here.Root-mean-square fluctuation (RMSF) of GTP-bound systems: ((TIF)Click here for additional data file.S5 FigA) all GDP- and GTP-bound systems. (B) The contributions (%) of principal components 1–10 (PC1-PC10). PCA3 vs. PC1 score plots (heat map) of (C) GDP-bound and (D) and GTP-bound systems. Top-left boxes comprise all the systems with (C) GDP or (D) GTP. For conformational reference, the backbone conformation of RAS from the RAS–effector and RAS–GEF complexes is included in the plots, where switch-I and switch-II are in a totally closed conformation  or switch-I is in a fully open conformation . Reference RAS structures were obtained from HRAS–effector protein complexes  and from the HRAS–Sos complex (PDB ID: 4NYJ).Extreme movements of principal component 3 (PC3) given by PCA in ((TIF)Click here for additional data file.S6 FigA) all GDP-bound systems, and in individual GDP-bound systems: (B) G12A, (C) G12C, (D) G12D, (E) G12R, (F) G12S, (G) G12V, and (H) wild-type. Highlighted regions are position of G12X (orange), switch-I (red), and switch-II (blue).Extreme movements of principal component 1 (PC1) given by PCA in ((TIF)Click here for additional data file.S7 FigA) all GDP-bound systems, and in individual GDP-bound systems: (B) G12A, (C) G12C, (D) G12D, (E) G12R, (F) G12S, (G) G12V, and (H) wild-type. Highlighted regions are position of G12X (orange), switch-I (red), and switch-II (blue).Extreme movements of principal component 2 (PC2) given by PCA in ((TIF)Click here for additional data file.S8 FigA) all GTP-bound systems, and in individual GTP-bound systems: (B) G12A, (C) G12C, (D) G12D, (E) G12R, (F) G12S, (G) G12V, and (H) wild-type. Highlighted regions are position of G12X (orange), switch-I (red), and switch-II (blue).Extreme movements of principal component 1 (PC1) given by PCA in ((TIF)Click here for additional data file.S9 FigA) all GTP-bound systems, and in individual GTP-bound systems: (B) G12A, (C) G12C, (D) G12D, (E) G12R, (F) G12S, (G) G12V, and (H) wild-type. Highlighted regions are position of G12X (orange), switch-I (red), and switch-II (blue).Extreme movements of principal component 2 (PC2) given by PCA in ((TIF)Click here for additional data file.S10 FigA) V14, (B) M72, (C) F78, (D) L79, (E) F90, and (F) I100. The hydrophobic interactions that are present (>10%) at least in one system are shown.Hydrophobic interactions and their frequencies from hubs: ((TIF)Click here for additional data file.S11 FigA) V114, (B) A146, (C) A155, (D) F156, and (E) L159. The hydrophobic interactions that are present (>10%) at least in one system are shown. (F) The intramolecular salt-bridge D154-R161 frequency.Hydrophobic interactions and their frequencies from hubs: ((TIF)Click here for additional data file.S12 FigThe 8oxoG is oriented inside the catalytic site of N-glycosylase/DNA lyase enzyme. PDB ID: 2NOB.(TIF)Click here for additional data file.S13 FigA) The resulting timescales are constant with the used lag-time 40 ns. (B) The Chapman-Kolmogorov test shows that MSM (black line) follows the observed trajectory . (C) The spectral analysis revealed large timescale separation between the third and fourth, and sixth and seventh relaxation timescales.((TIF)Click here for additional data file.S14 FigA) G12D, (B) G12R, (C) G12V, and (D) wild-type.The resulting timescales are constant with the used lag-time 40 ns for individual MSMs: ((TIF)Click here for additional data file.S15 FigA) G12D, (B) G12R, (C) G12V, and (D) wild-type. Shown are data for MSM (black line) and the observed trajectory .The Chapman-Kolmogorov test for individual systems’ MSMs with the first six states: ((TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Pancreatic cancer remains one of the leading causes of cancer-related deaths worldwide. Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic tumor. Many circular RNAs (circRNAs) have proven to play vital roles in the physiological and pathological processes of tumorigenesis; however, their biogenesis in PDAC remains unclear. In this study, the expression profiles of circRNAs from 10 PDAC tissues and their paired adjacent nontumor tissues were analyzed through RNA sequencing analysis. An enrichment analysis was employed to predict the functions of the differentially expressed circRNAs. Sequence alignment information and mRNA microarray projects were used to predict the RNA regulatory network. The knockdown of circRNAs by small interfering RNAs followed by wound healing and western blot assays was used to confirm their functions in a PDAC cell line. A total of 278 circRNAs were identified as differentially expressed in PDAC tissue. Of these, we found that hsa_circRNA_0007334 was significantly upregulated and may serve as a competing endogenous RNA to regulate matrix metallopeptidase 7 (MMP7) and collagen type I alpha 1 chain (COL1A1) by the competitive adsorption of hsa-miR-144-3p and hsa-miR-577 to enhance the expression and functions of MMP7 and COL1A1 in PDAC. In vitro experiments confirmed these results. The present study is the first to propose two regulatory pathways in PDAC: hsa_circRNA_0007334–hsa-miR-144-3p–MMP7 and hsa_circRNA_0007334–hsa-miR-577–COL1A1. Pancreatic cancer remains one of the leading causes of cancer-related deaths worldwide. The number of global deaths caused by pancreatic cancers of all types was 411,600 in 2015 [Noncoding RNAs, including circular RNAs (circRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs), all play vital roles in physiological and pathological processes, as suggested in a growing number of studies –7. AlthoIn the present study, we analyzed the expression profiles of circRNAs in PDAC tissue through RNA sequencing to further investigate differentially expressed circRNAs and their biological roles in PDAC. Our findings indicate that hsa_circRNA_0007334 promotes the expression levels of matrix metallopeptidase 7 (MMP7) and collagen type I alpha 1 chain (COL1A1) by blocking the functions of miR-144-3p and miR-577 in PDAC. We propose two regulatory pathways in PDAC: hsa_circRNA_0007334–hsa-miR-144-3p–MMP7 and hsa_circRNA_0007334–hsa-miR-577–COL1A1. The circular RNA hsa_circRNA_0007334 can also be used as a potential biomarker in PDAC diagnosis and therapy.Ten PDAC tissues and ten paired adjacent nontumor tissues were provided by the Tissue Bank of China-Japan Union Hospital, Jilin University . The clinical information of the patients is shown in The Ethics Committee of the China-Japan Union Hospital of Jilin University was given detailed study information and approved all experimental protocols . All participants were informed of the use of their specimens, and written informed consent was obtained from each participant.Total RNA was extracted using TRIzol reagent  according to the manufacturer's instructions. The concentration and purity of the isolated RNA were determined by a NanoDrop 2000 instrument  by measuring the absorbance values at 260 nm (A260) and 280 nm (A280).μg of RNA per sample was used as input material for RNA sample preparation. Ribosomal RNAs were depleted by an Epicentre Ribo-Zero rRNA Removal Kit . rRNA-depleted RNAs were treated with RNase R  and then subjected to TRIzol extraction. Sequencing libraries were generated using the rRNA-depleted and RNase R-digested RNAs with an NEBNext Ultra Directional RNA Library Prep Kit for Illumina  following the manufacturer's recommendations. The remaining steps were performed according to the descriptions in previous articles [Five PDAC tissues and five paired adjacent nontumor tissues were employed for the circRNA sequencing analysis. A total of 5 articles , 13. TheClustering of the index-coded samples was performed on a cBot Cluster Generation System using a HiSeq PE Cluster Kit v4 cBot (Illumina) according to the manufacturer's instructions. The library preparations were sequenced on an Illumina HiSeq 2500 platform, and 125 bp paired-end reads were generated. Fold change values were calculated by the negative binomial distribution DESeq2 method using the expression level (read count data). We calculated the p value between the data of two groups by negative binomial distribution and corrected the multiple hypothesis by Benjamini-Hochberg (BH) correction to obtain the adjusted p value.Gene Ontology (GO) enrichment analysis was performed by GOseq (version 1.18.0)  to deterμg of total RNA was used for cDNA synthesis using EasyScript One-Step gDNA Removal and cDNA Synthesis SuperMix  and for RT-qPCR analysis using TransStart Top Green qPCR SuperMix , according to the manufacturer's instructions. The primers were designed by Primer Premier 5 and synthesized by Sangon Biotech, Inc. (China). The primer sequences are as follows: hsa_circRNA_0007334 exon sequence, forward: 5′-ATCATCATAGGAGTGGAGAA-3′, reverse: 5′-TAGCAAGGCAAAGAGTTG-3′; hsa_circRNA_0007334 potential intron sequences, forward: 5′-CTGGGAATACTGTGTTATGC-3′, reverse: 5′-TACATCCAAATAGTCTTCATT-3′; MMP7, forward: 5′-GCATCTCCTTGAGTTTGGCT-3′, reverse: 5′-GAGCTACAGTGGGAACAGGC-3′; COL1A1, forward: 5′-CACACGTCTCGGTCATGGTA-3′, reverse: 5′-AAGAGGAAGGCCAAGTCGAG-3′; and GAPDH, forward: 5′-GACAGTCAGCCGCATCTTCT-3′, reverse: 5′-TTAAAAGCAGCCCTGGTGAC-3′.For mRNA and circRNA, 1 For miRNA, 500 ng of total RNA was used for cDNA synthesis and for RT-qPCR analysis on an All-in-One™ miRNA RT-qPCR Detection System  according to the manufacturer's instructions. The primers were purchased from GeneCopoeia (USA) .−ΔΔCt method.RT-qPCR analysis was performed on a 7500 Fast Dx Real-Time PCR Instrument . RT-qPCR was repeated three times for each sample. The cycle threshold value (Ct) data were analyzed using the 25 cells per well in 24-well plates and incubated at 37°C in a 5% CO2 humidified atmosphere. After 24 hours, 50 nM siRNA transfection reagent was made according to the manufacturer's instructions and added to the cells. After an additional 24 hours, RNA and protein were extracted from the cells. The cells were divided into 4 groups: the si-circRNA_0007334 group was transfected with si-hsa_circRNA_0007334, the si-circRNA_0007334+miR-144-3p inhibitor group was transfected with both si-hsa_circRNA_0007334 and the hsa-miR-144-3p inhibitor, the si-circRNA_0007334+miR-577 inhibitor group was transfected with both si-hsa_circRNA_0007334 and the hsa-miR-577 inhibitor, and the negative control (NC) group was treated with only transfection reagents in the absence of the siRNA or miRNA inhibitors. The interfering RNA target sequence of hsa_circRNA_0007334 was 5′-GGAGAACATGCACAAGTCA-3′. The siRNA (Cat. #siG180808051115), miR-144-3p inhibitor (Cat. #miR20000436), hsa-miR-577 (Cat. #miR20003242), and transfection reagents (ribo FECT™ CP Transfection Kit Cat. # C10511-05) were purchased from RiboBio Co., Ltd. (China) and operated according to the manufacturer's instructions.PANC-1 cells were purchased from the National Infrastructure of Cell Line Resource of China and cultivated in DMEM basic  containing 10% fetal bovine serum . The cells were adjusted to a density of 1 × 10A wound healing assay was performed to detect the invasion ability of PANC-1 cells after the knockdown of hsa_circRNA_0007334. A Culture-Insert 2 Well  was used to prepare the scratch in 24-well plates. The Culture-Insert 2 Well was removed after 24 hours, and hsa_circRNA_0007334 knockdown was immediately performed as previously described. Microscopic cell images were collected at 0, 6, 12, and 24 hours after knockdown. The migration rate was analyzed by ImageJ software based on the scratch areas.RIPA lysis buffer  containing protease inhibitor cocktail  was used to extract total protein according to the manufacturer's instructions. Fifty micrograms of total protein from each sample was used for SDS-PAGE and then transferred to PVDF membranes . The antibodies used were anti-MMP7 , anti-COL1A1 , and anti-GAPDH . A luminescent and fluorescent biological image analysis system  was used to detect exposure after adding the enhanced chemiluminescent (ECL) reagent. Images were analyzed by ImageJ software to calculate relative expression levels.The quantitative data are shown as the mean±standard deviation (SD). Statistical analyses were performed using SPSS version 21 . Student's t-test was used to compare the expression levels of hsa_circRNA_0007334, MMP7, and COL1A1. Two-tailed Pearson's correlation analysis was used to determine the association between the expression levels of hsa-miR-144-3p and hsa-miR-577. P<0.05 indicates a statistically significant difference. Genes with a fold change ≥ 2 and a p value < 0.05 in the sequencing or microarray data were regarded as significantly differentially expressed.The circRNA expression profiles in PDAC tissues and adjacent nontumor tissues (5 PDAC tissues and 5 adjacent nontumor tissues) were revealed by hierarchical clustering. The variation in circRNA expression between PDAC tissues and adjacent nontumor tissues is presented in a volcano plot . Overallhttp://www.genome.jp/kegg/). KEGG pathway analysis can be used to identify pathways that are significantly enriched in the gene of interest. A KEGG pathway scatterplot is a graphical way to present KEGG enrichment analysis results  to predict all the miRNAs that are most likely to be associated with the chosen circRNAs. Then, we used TargetScan (http://www.targetscan.org/vert_71/) to predict the target genes. TargetScan allows miRNA-mRNA predictions based on solely the presence of seed sequences, which is considered the main influence on the biological function of a mRNA. All predicted target genes were ranked according to the total context score, and only the top 10 target genes were selected to construct the network. After removing duplicate items, there were a total of 173 miRNAs and 1,460 target genes in the ceRNA network  and the ten circRNAs with the smallest p value were chosen to construct the network. To enhance data reliability, the circRNAs that have not been recorded in ENCODE were removed. First, we used the Circular RNA Interactome database ( network . The ceRhttp://genome.ucsc.edu/), we presume that hsa_circRNA_0007334 has a genomic length of 15,456 nt and a spliced length of 224 nt. Its location in the genome is chr2:9083315-9098771. The mature sequence of hsa_circRNA_0007334 is GTCAACTTTGTAGTGTGCCAACTCTTTGCCTTGCTAGCAGCCATTTGGTTTCGAACTTATCTACATTCAAGCAAAACTAGCTCTTTTATAAGACATGTAGTTGCTACCCTTTTGGGCCTTTATCTTGCACTTTTTTGCTTTGGATGGTATGCCTTACACTTTCTTGTACAAAGTGGAATTTCCTACTGTATCATGATCATCATAGGAGTGGAGAACATGCACAA, and its specific junction sequence is CATCATAGGAGTGGAGAACATGCACAAGTCAACTTTGTAGTGTGCCAACTCTTT.The expression level of hsa_circRNA_0007334 in PDAC tissues was upregulated 4.18-fold. Although hsa_circRNA_0007334 was not the most differentially expressed, the significance of its difference ranked third among all the circRNAs. To verify the sequencing results, RT-qPCR was performed. The relative expression level results showed that the expression of hsa_circRNA_0007334 was upregulated 3.92-fold in PDAC tissues compared with adjacent nontumor tissues. According to the sequencing results and the human reference genome (GRCh37/hg19) obtained from the University of California at Santa Cruz (UCSC) genome database  to predict the miRNAs that are most likely associated with hsa_circRNA_0007334. We found 15 potential miRNA binding sites that can bind with 14 miRNAs (http://www.cuilab.cn/hmdd), miRWalk 2.0 , and MalaCards , to predict the miRNAs and their target genes that are related to pancreatic cancer. Next, we investigated three mRNA microarray projects  from the Gene Expression Omnibus (GEO) DataSets (https://www.ncbi.nlm.nih.gov/gds/?term=) with 163 PDAC tissues and 118 adjacent nontumor tissues in total to identify genes that are differentially expressed between tumor and adjacent nontumor tissues in PDAC patients. The differential expression data of the mRNA microarray were auto-analyzed by the GEO2R online tool. Only the genes with a differential expression fold change ≥ 2.0 and p < 0.05 were further analyzed. A comprehensive comparison of the above results by Venn analysis revealed that 17 of 3,179 genes were differentially expressed in PDAC tumor tissue (http://www.targetscan.org/vert_71/), miRanda (http://34.236.212.39/microrna/microrna/home.do), and RNA22 (https://cm.jefferson.edu/rna22/). Then, we overlapped the results with the 14 miRNAs mentioned earlier. All of these 14 miRNAs were further analyzed. Of the 17 predicted genes, 13 were predicted to be regulated by these 14 miRNAs and were further analyzed. Finally, we used hsa_circRNA_0007334, 14 miRNAs, and 13 target genes and constructed an hsa_circRNA_0007334-miRNA-target gene network using Cytoscape to visualize their interactions . The protein interactions between the predicted target genes and their related genes were constructed in the network, as shown in To verify the functions and interactions of these 13 target genes, we performed a protein-protein interaction (PPI) analysis with the GeneMANIA database . The top 25% of cases with high or low expression were selected for the survival analysis. As a result, 43 high expression cases and 43 low expression cases were included in the analysis. The results are presented as survival curves and are shown in To further clarify the relationship between the expression levels of hsa-miR-144-3p, hsa-miR-577, MMP7, and COL1A1 in PDAC, we conducted a survey of the survival time of PDAC patients with different expression profiles. The survival data were obtained from the Cancer Genome Atlas (TCGA) database and analyzed by the OncoLnc database ; they were not included in the subsequent analyses.We have made efforts to understand the gene expression profiles between PDAC and normal tissues. First, the results of the three databases  were summarized to predict miRNAs, their target genes, and elements relevant to pancreatic cancer. Then, three mRNA microarray projects  from GEO DataSets, with 163 PDAC tissues and 118 adjacent nontumor tissues in total, were investigated. The three gene expression profile microarray projects had several shared pathways that have been reported to be associated with the pathogenesis of PDAC. However, because of the differences in platforms and samples, the differentially expressed genes of the three projects showed differences as well. Next, a Venn analysis was conducted to identify the differentially expressed genes in both the databases and microarray projects. The results indicated that 17 genes were differentially expressed. Of all the 17 genes, MMP1, MMP7, MMP11, MMP14, COL1A1, COL1A2, FN1, LAMA3, NOX4, PLAU, CCL20, LEF1, and MET are highly expressed in PDAC tissues; BTG2, BNIP3, BACE1, and EGF are weakly expressed in adjacent nontumor tissues. As BACE1, CCL20, EGF, LEF1, and MET are not expressed in pancreatic tumors according to the NCBI-UniGene database  and in disease processes (such as arthritis and metastasis). Additionally, MMP7 is highly expressed in multiple human malignant tumors –31 and iOne hsa_circRNA_0007334-miRNA-target gene ceRNA network was established to research the potential interactions between the 13 genes and hsa_circRNA_0007334 . AccordiA survey on the survival time of PDAC patients with different expression profiles was performed to further substantiate the relationship between the expression levels of hsa-miR-144-3p, hsa-miR-577, MMP7, and COL1A1 in PDAC. The survival time of the low hsa-miR-144-3p and hsa-miR-577 expression group was remarkably shorter than that of the high expression group, whereas the survival time of the high MMP7 and COL1A1 expression group was significantly shorter than that of the low expression group. However, we have to note the limitation of the current study: merely ten circRNAs with the largest fold change (five upregulated and five downregulated) and ten circRNAs with the smallest p value were chosen to construct the ceRNA network, but the roles of other circRNAs remain unclear.In this study, we propose two regulatory pathways in PDAC: hsa_circRNA_0007334–hsa-miR-144-3p–MMP7 and hsa_circRNA_0007334–hsa-miR-577–COL1A1. The results indicate that by the competitive adsorption of hsa-miR-144-3p and hsa-miR-577, hsa_circRNA_0007334 functions as a ceRNA for MMP7 and COL1A1 to elevate their expression levels and plays an important role in PDAC.


The influenza virus protein PA-X modulates the host immune responses and viral pathogenicity through suppression of host protein expression. The endonuclease active site in the N-terminal region, the basic amino acid cluster in the C-terminal PA-X-specific region, and N-terminal acetylation of PA-X by NatB are important for the shutoff activity of PA-X. Here, we focused on the shutoff activity of PA-X derived from the A/California/04/2009 and A/WSN/33 viruses because these two PA-X proteins differ in their shutoff activity. Mutagenesis analysis revealed that proline and serine at positions 28 and 65, respectively, play a central role in this difference. Furthermore, we found that P28 and S65 also affect the shutoff activity of PA-X derived from other influenza virus subtypes. These data demonstrate that P28 and S65 contribute to enhanced shutoff activity of PA-X. However70-CA04 and WSN140-CA04, which possessed the N-terminal 70 or 140 amino acids of WSN PA-X, respectively, and the C-terminal region of CA04 PA-X, showed low shutoff activity like WSN PA-X. CA0470-WSN and CA04140-WSN, which possessed the N-terminal 70 and 140 amino acids of CA04 PA-X, respectively, and the C-terminal region of WSN PA-X, showed high shutoff activity like CA04 PA-X. WSN70-CA04 showed statistically higher shutoff activity than WSN140-CA04, whereas CA0470-WSN showed comparable shutoff activity to CA04140-WSN . This finding suggests that although the amino acids P28 and S65 are present in most avian isolates, these residues become L28 and L/P65 (low shutoff-type) upon adaptation to humans. We then examined the contribution of the amino acid residues at positions 28 and 65 to the activity of PA-X derived from H3N2 (WSN type), H5N1 (CA04 type), and H7N9 (CA04 type) viruses. To this end, we introduced the L28P and L65S mutations into PA-X derived from H3N2 virus, or the P28L and S65L mutations into PA-X derived from H5N1 and H7N9 viruses, and performed the shutoff assay. The H3N2 PA-X double mutant showed significantly higher shutoff activity than wild-type H3N2 PA-X . Each H5Here, we found that the amino acid residues at positions 28 and 65 of PA-X or PA affect the shutoff activity of PA-X or viral polymerase activity, respectively. Since PA-X shares its N-terminal 191 amino acids with PA , we mappWe identified two amino acids at positions 28 and 65 that are important for high PA-X shutoff activity. The amino acids at positions 51–114 of CA04 PA were previously reported to be important for the higher shutoff activity of CA04 PA than WSN PA . This reSince PA-X suppresses its own expression via its shutoff activity, the expression of PA-X is largely affected by its own shutoff activity . ExpressHere we reported that proline at position 28 and serine at position 65 contribute to enhanced shutoff activity of PA-X. Since these amino acid residues in PA also affect viral polymerase activity, they likely affect the mRNA cleavage step. The mechanism by which these amino acid residues contribute to enhanced shutoff activity of PA-X remains unknown. Further studies, such as determination of the crystal structure and cellular localization of PA-X, are necessary to elucidate this mechanism.Human embryonic kidney 293 cells (ATCC) were maintained in DMEM (Sigma) containing 10% fetal calf serum (FCS) and penicillin-streptomycin.Nucleotide sequences of PA-X derived from A/WSN/33 (H1N1), A/California/04/2009 (H1N1pdm09), A/Yokohama/ UT2017/2003 (H3N2), A/Vietnam/HN31604/2009 (H5N1), and A/Anhui/1/2013 (H7N9) were cloned into pCAGGS/MCS with a C-terminal FLAG tag (C-FLAG). Mutant PA-X with the C-FLAG was amplified with appropriate primers, and then cloned into the same plasmids. Primer sequences are available upon request. All constructs were sequenced to confirm the absence of unwanted mutations.n = 3). To analyze the expression of PA-X, the transfected cells in the remaining well were lysed in SDS sample buffer at 24 h post-transfection. The cell lysates were sonicated, incubated for 10 min at 95°C, and then loaded onto an Any KD Mini-PROTEAN TGX Gel (Bio-Rad). Separated proteins were transferred to Immobilon-P PVDF membrane (Millipore) and detected by using anti-DYKDDDDK (FLAG) tag antibody clone 1E6 (Wako) or anti-β-actin antibody clone AC-74 (Sigma), followed by a sheep anti-mouse IgG-HRP secondary antibody .Two hundred and ninety three cells in four wells of a 24-well plate were transfected with a plasmid encoding firefly luciferase together with an empty plasmid or a plasmid encoding wild-type or mutant PA-X possessing a C-terminal FLAG tag. At 24 h post-transfection, the transfected cells from three of the wells were analyzed for firefly luciferase activity by using the Bright-Glo luciferase assay system (Promega). Data are shown as the average luminescence ± standard deviation (Renilla luciferase activity. Data are shown as the average of the polymerase activity ± standard deviation (n = 3). To analyze the expression of PA, the transfected cells were lysed in SDS sample buffer and analyzed by western blotting using an anti-PA antibody  (PDB accession: 4AVQ) and A/Victoria/3/75 (H3N2) (PDB accession: 2W69) using the PyMOL molecular graphics system.t-test were performed using GraphPad Prism software. P < 0.01 were considered significantly different. No samples were excluded from the analysis.One-way analysis of variance (ANOVA) followed by Dunnett’s test or Tukey’s test and the two-tailed unpaired Student’s All datasets generated for this study are included in the manuscript.KO, SY, and YK designed the study, analyzed the data, and wrote the manuscript. KO performed the experiments. All authors reviewed and approved the manuscript.YK has received speaker’s honoraria from Toyama Chemical, has received grant support from Chugai Pharmaceuticals, Daiichi Sankyo Pharmaceutical, Toyama Chemical, Tauns Laboratories, Inc., Tsumura & Co, and Denka Seiken Co., Ltd., and is a co-founder of FluGen. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.