K14E7 Fancd2−/− and Fancd2−/− LTBMCs showed decreased duration of production of total nonadherent hematopoietic cells and progenitors forming day 7 and day 14 multilineage CFU-GEMM colonies in secondary cultures (7 wks and 8 wks respectively) compared to cultures from K14E7 Fancd2+/+ (17 wks) or control mice (18 wks) p < 0.0001. Marrow stromal cell lines derived from both K14E7 Fancd2−/− and Fancd2−/− cultures were radiosensitive, as were IL-3 dependent hematopoietic progenitor cell lines derived from K14E7 Fancd2−/− cultures. In contrast, Fancd2−/− mouse hematopoietic progenitor cell lines and fresh marrow were radioresistant. K14E7 Fancd2−/− mouse freshly explanted bone marrow expressed no detectable K14 or E7; however, LTBMCs produced K14 positive factor-independent (FI) clonal malignant plasmacytoma forming cell lines in which E7 was detected in the nucleus with p53 and Rb. Transfection of an E6/E7 plasmid into Fancd2−/−, but not control Fancd2+/+ IL-3 dependent hematopoietic progenitor cell lines, increased cloning efficiency, cell growth, and induced malignant cell lines. Therefore, the altered radiobiology of hematopoietic progenitor cells and malignant transformation in vitro by K14E7 expression in cells of the Fancd2−/− genotype suggests a potential role of HPV in hematopoietic malignancies in FA patients.We tested the effect of expression of the Human Papilloma Virus (HPV E7) oncogene on hematopoiesis in long-term bone marrow cultures (LTBMCs) derived from K14E7 (FVB) Fancd2 Fanconi Anemia (FA) patients display a variety of inherited and acquired phenotypes , which aHuman papillomavirus (HPV) is involved in genesis of squamous cell cancer of the head and neck, esophagus, and cervix –15; howe−/− (129/Sv) mice with cytokeratin 14 (K14) promoter controlled production of E7 onco-protein of HPV derived from genetic cross with K14E7 mice (FVB/n) were shown to be susceptible to both chemical carcinogen induced oral squamous cell tumors, and estrogen pellet induced cervix cancers [−/− mice and could induce malignant transformation of squamous epithelium in tissues that naturally express cytokeratin 14.Recently, Fanconi Anemia (FA) Fancd2 cancers . The dat−/− mouse marrow in LTBMCs [−/− mouse LTBMCs retained some Fancd2−/− phenotypes including: suppressed duration of hematopoiesis and radiosensitivity of marrow stromal cell lines, we discovered that culture-derived hematopoietic cell lines, as well as fresh marrow hematopoietic progenitors were also radiosensitive, a distinct difference from Fancd2−/− marrow. Furthermore, cytokeratin 14 and E7 were expressed in cultured K14E7 Fancd2−/− marrow and nonadherent cells subcultured in Interleukin-3 (IL-3) generated factor-independent (FI) malignant plasmacytoma cell lines.In the present studies, we determined whether culture of K14E7 Fancd2n LTBMCs  facilita−/−, K14E7Fancd2+/+ (FVB/N), Fancd2+/+ (129/Sv), and control (129/Sv X FVB) F1 mice [−/− mouse long-term bone marrow cultures. The cobblestone island numbers on the adherent layer of each flask  are shown in Figure +/+ and K14E7Fancd2+/+ mice showed greater numbers of cobblestone islands during weeks 1 through 14 compared to those detected in either K14E7Fancd2−/− or Fancd2−/− groups  [−/− (129/Sv) mouse LTBMCs [Long-term bone marrow cultures were established from the tibia and femur marrow of four mice (8 cultures) of each genotype: K14E7Fancd2 F1 mice , and maicd2+/+ 12/Sv, and s Figure . Cumulats Figure  also shocd2+/+ 12/Sv, and e LTBMCs .+/+ and K14E7 Fancd2+/+ mice  genetic background was similar to that of Fancd2−/− marrow from C57BL/6 mice [−/− marrow cultures.The weekly production of non-adherent cells Figure  and cumu+/+ mice . Results+/+ mice  were alsy Figure  and cumuy Figure  producticultures . Therefoferent 12/Sv genet−/− (129/Sv) and K14E7 Fancd2−/− mouse long-term bone marrow cultures. The production of both day 7 and day 14 colony forming cells was decreased with respect to both weekly and cumulative production by K14E7Fancd2−/− mouse marrow cultures.The production of multilineage hematopoietic cells forming colonies in secondary culture (scored as those with greater than 50 cells at day 7 or day 14) were next evaluated. As shown in Figure  Supplem, weekly +/+ mice showed an earlier plateau with respect to cumulative cell production of day 7  marrow cultures. The effects of the K14E7 genotype on Fancd2+/+ long-term marrow culture production of day 14 colony forming cells, weekly  LTMBCs  marrow derived cell lines and fresh marrow CFU-GEMM [−/− (C57BL/6) mice [We established clonal bone marrow stromal and hematopoietic progenitor cell lines from long-term marrow cultures of each mouse genotype. Clonal marrow stromal cell lines derived from K14E7 Fancd2e Figure , Table 1s Figure , Table 2s Figure , Table 3re −/− 12/Sv LTMBC−/− LTBMC culture-derived clonal IL-3 dependent cell lines  produced both adherent and nonadherent cells in IL-3 supplemented secondary cultures  or that these subcultures contained a novel bilineage mesenchymal/hematopoietic cell phenotype. To distinguish between these possibilities, clonal cell lines were derived from IL-3 dependent cell lines from LTBMCs of each mouse genotype. All clonal cell lines derived from K14E7 Fancd2−/− marrow cultures showed the same pattern of both adherent and nonadherent cells  than those obtained from K14E7 Fancd2+/+ IL-3 dependent secondary cell cultures (1/50) single cells.The observation of morphologic changes in K14E7 Fancd2s Figure . In cont−/− adherent stromal and the novel IL-3 dependent cell lines for expression of K14 and E7 and compared this data with that from freshly removed organs from the same K14E7 Fancd2−/−, as well as control K14E7 Fancd2+/+, and other control mice. As shown in Figure +/+ and K14E7 Fancd2−/− LTBMCs were positive for both K14 and E7, while Fancd2−/− and 129/Sv cell lines were negative  cell lines. In contrast, clonal K14E7 Fancd2+/+, (129/Sv X FVB/n) F1 and Fancd2−/− cell lines remained IL-3 dependent. The K14E7 Fancd2−/− clonal lines grew densely in culture . The tumor-inducing K14E7 Fancd2−/− clone 1 cell line . These results establish that the E7 oncogene of HPV induced malignant transformation of bone marrow from K14E7 Fancd2−/− mice when grown in LTBMCs in vitro.We next injected K14E7 Fancd2s Figure , Table 4s Figure  and spins Figure  regions.e Figure  and the e Figure  were pos−/−, IL-3 dependent, ) was markedly different from that observed with Fancd2−/− (129/Sv) IL-3 dependent cell line. There was an increase in SCA1, from 2.3 to 97.5% positive. Collagen IV decreased from 27.7 to 0.5%  and endothelial/sarcoma (Collagen IV)  cell lines, there was detectable nuclear E7, as well as both p53 and Rb , as well as hematopoietic progenitor cells. We next tested whether the E6 and E7 oncogenes of HPV could induce malignant transformation of hematopoietic cells independent of the marrow microenvironment. We utilized a plasmid containing both the E6 and E7 oncogenes of HPV and transfected Fancd2−/− and control IL-3 dependent hematopoietic progenitor cells in vitro as described in the Methods. Stromal and IL-3 dependent hematopoietic cell lines from each genotype culture were transfected with this plasmid containing both E6 and E7. Single cell derived clonal lines were selected for G418 resistance according to the methods. No difference in morphology or growth was detected with any transfected stromal cell lines (Table The above results establish that the E7 oncogene of HPV expressed in K14E7 Fancd2−/− cells showed an increase in cloning efficiency and IL-3 independent (factor-independent FI) cell lines were derived, which formed tumors in vivo. Tumor forming lines were detected with 8 of 164 single cell derived clonal lines . Malignant plasmacytoma cell lines in our studies were growth factor independent. Recent data indicates that at least 12 different genes in the JAK/STAT and MAP Kinase pathways can induce transposon mutagenesis of IL-3 factor dependent cell lines to factor independence [−/− cell lines to malignant FI cell lines is not known since the plasmid used contained both oncogenes. Further studies will be required to determine if E7 (or E6) alone is sufficient for malignant transformation of Fancd2−/− hematopoietic cells in the absence of stromal cells found in LTBMCs.The present K14E7 Fancd2myelomas . Thus, tod cells . Whetherpendence . Whether−/− long-term marrow cultures is not known.Complex effects of the HPV E6 and E7 oncogene in cell killing have been described –64. A roin vitro support capacity for hematopoiesis [The present studies expand the possible cell target of HPV E7 to include the bone marrow in patients with FA. Replication of HPV has recently been shown to require DNA repair by homologous recombination (HR) and involving RAD51 and BRCA1 . The HR opoiesis . HPV16 Eopoiesis .in vitro has not been reported. Evolution of B-cell and plasmacytoma-inducing tumors from adherent cells in culture has been reported with Epstein-Barr virus [−/− mouse marrow cultures is not known. Further studies will be required to determine whether the condition(s) of LTBMC and/or IL-3 suspension culture are required for malignant transformation with HPV-E7 transfected freshly removed marrow stem cells from K14E7 Fancd2−/− mice. The present results on the biology of K14E7 Fancd2−/− marrow in LTBMCs provide a new system in which to study effects of HPV on: 1) the mechanism of HPV E6/7 genes in tumorigenesis in an in vitro organ culture system; 2) the mechanism of the K14 promoter control of expression of E7 in mesenchymal and hematopoietic cells in culture; and 3) the effect of an absent Fancd2 protein on expansion of a subpopulation of primitive adult bone marrow cells to both hematopoietic and mesenchymal stromal cell phenotypes.Fresh human bone marrow derived mesenchymal stem cells have been reported to become radiosensitive after HPV-16 E6/E7 transfection , and shorr virus , and B-crr virus . The Frirr virus ; however−/− mice of both the 129/Sv [−/− and K14E7 Fancd2−/− marrow stromal lines in our studies were radiosensitive, only Fancd2−/−hematopoietic cell lines and fresh marrow colony forming progenitor cells were radioresistant. These data indicate that the Fancd2 protein has phenotype-specific effects on the ionizing irradiation response. The present data demonstrate that the E7 oncogene of HPV transforms Fancd2−/− hematopoietic cells in LTBMCs to malignant plasma cell tumors, and extend the spectrum of potential effects of HPV to the bone marrow of genetically susceptible patients with DNA repair defects including those with Fanconi Anemia.Fanconi Anemia patients may be at increased risk of cell transformation by HPV, in part attributable to defective DNA repair , 15, 53.e 129/Sv  and C57Be 129/Sv . While b−/−, Fancd2+/−, and Fancd2+/+ (129/Sv background [−/− mice [Fancd2ckground ) were ge−/− mice  as publi−/− mice: 1) the absence of Fancd2; 2) the E7 oncogene; and 3) exposure to the 4-NQO carcinogen.In subgroups of mice, the addition of 4-nitro-quinolone oxide (4-NQO)  to drinking water was carried out as published . Briefly−/− (129/Sv) [−/− (C57BL/6) [Bone marrow stromal cell lines and Interleukin-3 dependent cell lines from Fancd2129/Sv) , Fancd2−/Sv , FanC57BL/6)  and a C5+/+, Fancd2+/−, and (FVB/n background) K14E7Fancd2−/− mice according to published methods [−5 M hydrocortisone sodium hemisuccinate. Cultures were incubated at 33°C in 7% CO2. After 4 weeks, the horse serum was replaced with 25% FBS  [t-test was used to compare the number of cobblestone islands between each genotype cultures each week. P-values less than 0.05 were regarded as significant.Long-term bone marrow cultures (LTBMC) were established from the femur and tibia marrow of (129/Sv background) Fancd24 fresh bone marrow cells or nonadherent cells removed at week 4 from each genotype long-term marrow culture were plated in triplicate in semi-solid medium consisting of methylcellulose in IMDM, using a GelCount colony counter  and maintained in a high humidity incubator according to published methods and using growth factor supplements as described [Aliquot of 5 × 10escribed . Brieflyescribed .Non-adherent cells were harvested from each genotype mouse LTBMC at week 4 and cultured in six-well tissue culture plates in Iscove's Modified Eagles Medium (IMDM) supplemented with 20% fetal calf serum (FBS) and 1.0 ng/mL recombinant mouse IL-3 . The cell lines were passaged weekly for 12–14 weeks to establish primary IL-3-dependent cell lines using published methods .Clonal cell sub-lines were established from each of the genotype parent cell lines by expansion of single cell derived colonies. Cells were then replated in methylcellulose, colonies selected at 14 days, and cultured as above, to establish subclonal lines . Confirm°C in 5% CO2.Adherent cell layers from one 4-week old LTBMC from each genotype mice were trypsinized and expanded by passage into Dulbecco's Modified Eagle's Medium (DMEM) + 10% FBS to establish bone marrow stromal cell lines according to published methods . Cells w−/− and SV129 Fancd2−/− cells were prepared into single cell suspension and incubated with each FITC or PE conjugated antibody listed above at concentrations recommended by the manufacturer for one hour on ice. The cells were washed three times with phosphate buffered saline (PBS) and analyzed for positive cells by flow cytometry.Flow Analysis for CD3c, CD5, CD8, B220, GR1–Ter119, CD41, CD45, CD48, SCA-1, C-KIT, CD150, vimentin, adiponectin, collagen III, collagen IV, osteopontin, and osteocalcin  were carried out according to the methods section sorting 10,000 cells in triplicate experiments. Briefly, bone marrow stromal cells and IL-3 dependent hematopoietic cells from K14E7 Fancd2Cell lines were cultured in DMEM medium (Lonza Cat. #: 12-604F) with 10% Fetal Bovine serum (Gemini Cat.#: 100–500), 1% L-Glutamine (Lonza Cat. #: 17-605E) and 1% Antibiotics Antimycotic Solution (Corning Cat. #: 30-004-Cl). Total cellular protein was extracted using protein extraction buffer , containing protease inhibitor and phosphatase inhibitor cocktails (Thermo Scientific prod #: 78442). Mouse tongue and skin tissue were freshly taken and chopped to fine pieces and homogenized in protein extraction buffer (same as cell protein extraction buffer). Protein concentration was determined using the Bio-Rad protein assay system . The proteins (15 μg per lane) were separated on denaturing polyacrylamide gels  and then transferred to PVDF membranes  by electrophoresis. Blots were blocked with 5% Fat-free Dry Milk in TBST for 1 h and then incubated overnight with primary antibodies (see antibody table). The membranes were washed with TBST and processed with corresponding horseradish peroxidase-conjugated secondary antibodies (see antibody table). The proteins were exposed to x-ray film (5 to 30 seconds) using ECL detection reagent . To ensure equal protein loading, the same blot was subsequently developed for GAPDH expression.K6, K16, and K17 are found in oral mucosa and stratified epidermis of skin . K17 has−/− cells were seeded and grown in chamber slides and fixed with 100% methanol (5 min), permeabilized with 0.2% Triton X-100 for 10 minutes and blocked with 1% BSA/22.5 mg/ml glycine in 0.1% PBS-Tween for 30 minutes. The cells were then incubated overnight at +4°C with the antibody (ab92551) or (ab7800) at a 1/100 dilution, then incubated with secondary antibody  for 1 hour at a 1/500 dilution (shown in green). Nuclear DNA was labeled with DAPI (shown in blue). Images were obtained using a Nikon Eclipse E800 microscope.We used control anti-CK-13 antibody (ab92551) and anti-CK14 (ab7800) antibody for staining squamous cell specific Cytokeratins. For Kappa and Lambda staining, goat anti-Lambda light chain  and goat anti-kappa light chain , K14E7 Fanconi d2Tumors were fixed using 10% paraformaldehyde, embedded in paraffin, sectioned, and deparaffinized in xylene for 10 min twice and rehydrated in 100%, 95%, and 70% ethanol for 5 min. Antigens were unmasked by boiling for 12 min in 1 mM EDTA. Sections were blocked with 3% H2O2 at room temperature for 30 min, washed in PBS for 5 min × 3, incubating in 10% BSA at room temperature for 15 min. The sections were incubated with the primary antibody at 4°C overnight, and washed in PBS for 5 min × 3. Secondary antibody was added for 1 hr at room temperature and washed in PBS for 5 min × 3. The sections were incubated in Elite ABC Kit (Vector #PK-6100) at room temperature for 30 min, washed in PBS for 5 min × 3, incubated in DAB kit (Vector #SK-4100) at room temperature for 1 min, and washed in running water for 5 min. Hematoxylin was added for one followed by Methylene Blue Reagent Solution for 1 min. The sections were dehydrated in 70%, 95%, and 100% ethanol followed by xylene for 5 min. the slides were mounted and analyzed.IL-3-dependent non-adherent cells or whole bone marrow from each genotype mice were irradiated in suspension culture to doses between 0 and 8 Gy as described above. Cells were plated in triplicate in methylcellulose medium containing recombinant mouse stem cell factor (SCF), IL-3, IL-6, and recombinant human erythropoietin (EPO) . CFU-GM were scored on day 7–9 for the IL-3-dependent cell lines and CFU-GM, BFU-E, and CFU-GEMM were scored between days 10 and 13 for the whole bone marrow. In some experiments, colonies growing in plates containing cells irradiated to 6 Gy or 8 Gy were removed and expanded. Data were analyzed with single-hit multitarget models according to published methods [t-test was used as described above [In other experiments with fresh marrow, cells were plated in semisolid medium with Fetal Bovine Serum (FBS), 10% Bovine Serum Albumin (BSA), recombinant mouse IL-3, also containing L-glutamine, 3 U/mL erythropoietin, and 2-mercaptoethanol. Fresh marrow colonies were scored at day 7 and 14 and subdivided as colony forming unit granulocyte macrophage (CFU-GM), Burst Forming Unit Erythroid (BFUe), and (CFU-GEMM) granulocyte-erythroid-megakaryocyte-macrophage. Colony forming unit granulocyte-macrophage (CFU-GM) burst forming erythroid (BFUe) and (CFU-GEMM) of 50 cells or greater were counted on both days 7 and 14 after plating. A two-sided, two-sample ed above .137Cs ƴ-ray source . Cells were plated in quadruplicate in Linbro plates  and incubated at 37°C and 5% CO2 for 9–11 days, stained with crystal violet, and colonies of > 50 cells were counted.Bone marrow stromal cell lines generated from the trypsinized and repassaged LTBMC adherent layer at week 4  from eac+/+ (129/Sv) [−/− (129/Sv) [IL-3 dependent nonadherent cell lines derived from each genotype LTBMC or clonal stromal cell lines were transfected with the PLXSN16E6E7 plasmid containing both E6 and E7; PLXSN16E7  according to the manufacturer's directions. Selection of G418 resistant clones was carried out with transfected and control IL-3 dependent hematopoietic cell lines including cell lines: 32D cl3 , as well(129/Sv) , Fancd2−(129/Sv) , and cel+/+, 129/Sv Fancd2−/−, K14E7 Fancd2+/+, and K14E7 Fancd2−/− mice. We first studied bone marrow stromal cell lines and IL-3 dependent cell lines as well as freshly removed fresh tissue from K14E7 Fancd2+/+ and K14E7 Fancd2−/− mice. Protein was extracted using protein extraction buffer , containing protease inhibitor and phosphatase inhibitor cocktails (Thermo Scientific prod #: 78442). Protein concentration was determined using the Bio-Rad protein assay system . The proteins (15 μg per lane) were separated on denaturing polyacrylamide gels , and then transferred to PVDF membranes  by electrophoresis. Blots were blocked with 5% Fat-free Dry Milk in TBST for 1 h and then incubated overnight with primary antibodies to mouse anti-CK14 , or mouse anti-HPV E7 protein . The membranes were then washed with TBST and processed with a corresponding horseradish peroxidase-conjugated secondary antibodies . The blotted proteins were then exposed to x-ray film (5 to 30 seconds) using ECL detection reagent . To ensure equal protein loading, each blot was also subsequently developed for level of GAPDH  expression.Protein was extracted from fresh tissues or cell lines from each mouse strain including: 129/Sv Fancd2−/− clonal cell lines were tumorigenic, 1 × 106 cells from K14E7 Fancd2−/− clone 1 or K14E7 Fancd2+/+ clone 5 cell lines were injected subcutaneously in the flank of each of 5 (FVB X 129/Sv) F1 mice. Other groups of 5 mice received I.V. injection of the same cell numbers. Mice were followed for the development of tumors at which time they were sacrificed, tumors removed, fixed in 10% paraformaldehyde, sectioned, and then sections were stained with hematoxylin and eosin or antibodies to kappa and lambda light chains .To demonstrate that K14E7 Fancd2The primary antibodies used for co-localization studies included: a rabbit polyclonal antibody to p53 ; a rabbit polyclonal antibody to Rb ; and a mouse monoclonal antibody to E7 . Secondary antibodies used included: donkey anti-mouse 488 and donkey anti-rabbit 568 . DAPI was used as a nuclear fluorescent stain that binds strongly to A-T rich regions in DNA. Confocal images were obtained with an Olympus Fluoview 100 confocal microscope and companion software FV10-ASW1.6. Images were acquired at a resolution of 1024 × 1024 pixels.in vitro radiation survival curves were analyzed with the single-hit multi-target model, and were compared using D0  and ñ  [0 and ñ were presented as the mean ± standard error (SEM) from multiple measurements and compared with the two-sided two-sample t-test.The l curve) . Results6) per flask; percent confluence of adherent cells; day 7 colony forming progenitor cells; and day 14 colony forming cells were counted as described [+/+, K14E7 Fancd2−/−, control (129/Sv × FVB) F1 and Fancd2 −/− (129/Sv). Data were summarized as mean ± standard deviation, and p-values were calculated with the two-sided two-sample t-test.For the LTBMC data, weekly cobblestone island numbers; non-adherent cell numbers (×10escribed  and compP-values for the comparison between any two groups were calculated with the two-sided two-sample t-test.For Western blots data were analyzed by densitometry and summarized with mean ± standard deviation in each group. t-test if they were normally distributed, or with Wilcoxon rank sum test otherwise. In all these tests, a p-value of less than 0.05 was regarded as significant. As an exploratory analysis, we did not adjust p-values for multiple comparisons.For the other continuous endpoints, comparisons were also performed using a


Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration.CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL. Using MCF 10A cell line cells as an example, we demonstrated how to ontologically model LINCS cellular signatures such as their non-tumorigenic epithelial cell type, three-dimensional growth, latrunculin-A-induced actin depolymerization and apoptosis, and cell line transfection. A CLO subset view of LINCS cell lines, named LINCS-CLOview, was generated to support systematic LINCS cell line analysis and queries. In summary, LINCS cell lines are currently associated with 43 cell types, 131 tissues and organs, and 121 cancer types. The LINCS-CLO view information can be queried using SPARQL scripts.CLO was used to support ontological representation, integration, and analysis of over a thousand LINCS cell line cells and their cellular responses. Diverse, multi-dimensional datasets have been generated by LINCS groups and laboratories and used to generate extensive results and software programs. A major challenge is how to integrate large amounts of LINCS-generated data into a comprehensive integrative understanding of cellular signatures [Since immortalized cell lines were developed almost one century ago, various cell lines have been widely used to study various scientific biological and biomedical questions . The NIHgnatures . Given thttp://www.atcc.org/), HyperCLDB [https://catalog.coriell.org/), and Japan Riken cell lines (http://cell.brc.riken.jp/en/). CLO has been used in many projects such as BAO development [http://web.expasy.org/cellosaurus/). Among these resources, the ChEMBL database, a large-scale bioactivity database developed by the EBI [Co-developed by many groups and societies, including the Cell Type Ontology (CL) , OntologyperCLDB , Coriellelopment , Beta ceelopment , Chromoselopment , ChEMBL elopment , and Cel the EBI , 14, is In this study, we report our work on updating CLO to include all LINCS cell lines and additional information required by LINCS projects. Such a comprehensive and integrative representation makes CLO able to coherently represent and study all LINCS cell lines together. To support LINCS integrated study of cellular features and signatures, we have also updated CLO to include additional design patterns using the cell line model MCF 10A cell line cells.The overall workflow of this project Fig.  includesBased on the data types obtained from the mapping process, an updated CLO design pattern model was generated in order to accommodate new LINCS cell line data attributes.http://lincsportal.ccs.miami.edu/) [Two sources, including the LINCS Data Portal (mi.edu/)  and ChEMCell line-related data types or attributes were first compared between LINCS Data Portal and ChEMBL and then compared with the CLO knowledge base. To identify if a LINCS cell line found from the LINCS Data Portal and ChEMBL also exists in CLO, SPARQL scripts  were genThe mapped cell line data from CLO was also used to support LINCS cell line data integration. Following SPARQL-based identification of cell line names and synonyms within CLO, along with the corresponding Disease Ontology Identifiers (DOIDs), information for the LINCS cell lines was manually validated and curated to ensure accurate information matches. If existed, multiple members of the same cell line name or synonym were consolidated into a singular LINCS cell identifier.Based on the new design patterns, Ontorat  was usedhttps://raw.githubusercontent.com/CLO-ontology/CLO/master/src/ontology/LINCS-CLOview.owl. The LINCS CLO subset was also submitted to Ontobee [http://www.ontobee.org/sparql).OntoFox  was used Ontobee . The infNote that CLO and LINCS-CLOview are developed using the Web Ontology Language (OWL)  and contBased on the OWL-based classification and reasoning features, the CLO subset of LINCS cell lines was used for further analysis. The subset statistics was first generated and analyzed. Different types of LICNS cell line information were queried and studied. For example, the cell types of LINCS cell lines were studied based on the Cell Type Ontology (CL) , and theAs of June 15, 2017, 1097 cell lines were extracted from the LINCS Data Portal. Out of these LINCS cell lines, 794 cell lines could be directly mapped to CLO based on exact name matching and manual verification. A cell line may have different synonyms. The name matching used the default label and different synonyms for lexical mapping between these two resources. The data types related to these cell lines are listed in Fig. Among the 1097 LINCS cell lines each with a unique LINCS cell line ID , 466 had ChEMBL, LINCS, and CLO IDs, 279 had both LINCS and CLO IDs, and 352 LINCS cell lines did not have any CLO IDs.http://www.atcc.org/products/all/HB-8065.aspx) has the LINCS ID LCL-1925, and it is mapped to three CLO IDs: CLO_0003704 (term label: Hep G2 cell), CLO_0050856 (label: RCB1648 cell), and CLO_0050858 (RCB1886 cell). Although they are all for Hep G2 cell based on their annotations,CLO_0003704 was the originally assigned based on an annotation from the ATCC cell line repository, and the other two come from the Japan RIKEN cell line bank with different registry information. In current CLO, we assert the two Japan cell bank cell line cell terms as subclasses of the CLO_0003704 with the consideration that the two Japan cell bank cell line cell types may have genetic variations given their long time of passages. In this case, all the three CLO cell line cell terms have the same LINCS cell line ID, which is defined using an annotation property ‘Cell line LINCS ID’.Note that sometimes one LINCS ID maps to multiple CLO IDs. For example, the Hep G2 cell line , based on the updated design pattern, we added the following information to CLO: ‘: ‘is disease model for’ some ‘cervical adenocarcinoma’‘HeLa cell’ (CLO_0003684)Most LINCS cell lines were originally derived from human patients with some specific cancer diseases, and many of these diseases were not included in CLO. In this study, we imported corresponding disease terms from the Human Disease Ontology (DOID) . To reprhttp://www.ebi.ac.uk/cellline#is_model_for) [It is noted that in CLO, the new object property ‘is disease model for’ is equivalent to the original object property ‘is model for’, an object property originated by the EBI cell line project (del_for) . The EBI‘derives from’ some ))))‘HeLa cell’: The direct link between a disease and a cell line as a model to study the disease is required by LINCS data structure. In addition to this direct link, CLO also presents the origination of a cell line from a formalized ontological representation. The disease that is modeled by a cell line is often the disease of the particular human patient from whom the first passage of the cell line was originally generated. For example, the HeLa cell’s origin was the cervical adenocarcinoma cells separated from a cervical cancer patient, an African American woman in 1951 . To reprIt is noted that HeLa cell is listed in CLO as a subclass of ‘immortal human uterine cervix-derived epithelial cell line cell’ (CLO_0000636), where the relation between human and the cell is clearly stated.‘derives originally from patient having disease’ some ‘cervical adenocarcinoma’‘HeLa cell’: It is also noted from the above axiom that the long chain of axiom  shown above becomes technically inefficient to query the relation between the cell line cell and the disease ‘cervical adenocarcinoma’. A shortcut relation (or object property) is a relation that is used to replace the usage of a chain of multiple relations and classes to represent the complex relations between two classes. Therefore, a new shortcut relation  ‘derives originally from patient having disease’ Fig.  was geneAlthough ‘is disease model for’ and ‘derives originally from patient having disease’ both represent a relation between a cell line cell and a disease, these two relations differ in their meaning. The shortcut relation ‘derives originally from patient having disease’ represents that the cell line cell was originally derived from a patient with a specific disease. The relation ‘is disease model for’ indicates that the cell line can be used to study a specific disease, and the disease can but does not have to, be the same as the disease of the patient from whom the cell line cell was derived. For example, HeLa cell can be used as a cell line model to study cervical adenocarcinoma, but it can also be used to study many other diseases such as polio and NewCastle Disease , 22.In this study, we used the MCF 10A cell line cell as an example to show how CLO can be used to model cell features.has_qality some non-tumorigenic‘MCF 10A’: non-tumorigenic is represented as a quality, and the relation between MCF 10A cell line cell and the quality can be represented using the object property has_quality.where the MCF 10A cell line cells exhibit three dimensional growth in collagen and form domes in confluent cultures . We can ‘participates in’ some ‘MCF 10A’: MCF 10A cell line cell is non-tumorigenic . CLO rep‘three dimensional cell growth’ (CLO_0037311) is a process, and both MCF 10A cell line cell and collagen are participants of such a process. Since GO does not have such a ‘three dimensional cell growth’ term, we generated the term using a tentative CLO ID (CLO_0037311) and listed it as a subclass of the ‘cell growth’. Here the collagen is a component needed for the three dimensional cell growth. Collagen (CHEBI_3815) is a group of fibrous proteins of very high tensile strength that form the main component of connective tissue in animals.In this case, How to represent a cellular response of a cell line cell to a specific agent that is not part of regular cell culture media? Here we again use MCF 10A cell line cell response modeling as an example study.‘participates in’ some (‘apoptotic process’ and ‘preceded by’ some ‘actin depolymerization’ and (‘induced by cell culture reagent’ some latrunculin-A))‘MCF 10A’: It is known that MCF 10A mammary epithelial cells undergo apoptosis following actin depolymerization. The MCF 10A response can be represented in the following OWL SubClassOf axiom:apoptotic process is represented as a GO term (GO_0006915). This process in MCF10A cells occurs after actin depolymerization (GO_0030042) is induced by a cell culture reagent Latrunculin A (CHEBI_69136), a bicyclic macrolide natural product consisting of a 16-membered bicyclic lactone attached to the rare 2-thiazolidinone moiety [In this case, e moiety .‘is specified output of’ some (‘cell line cell transfection’ and (‘has specified input of’ some ‘MCF 10A cell’))‘MCF10A-Er-Src cell’: Sometimes, cell line cells were genetically engineered to generate a new cell line by a transfection process. Basically, a transfection process deliberately introduces naked or purified nucleic acids into eukaryotic cells such as cell line cells. For example, MCF10A-Er-Src cell line cell is a MCF10A cell derived cell through transfection. As a result, MCF10A-Er-Src cell has the part of ER-Src, a derivative of the Src kinase onco-protein that is fused to the ligand-binding domain of the estrogen receptor (ER). It is clear that MCF10A-Er-Src cell line cell is not a subtype of MCF 10A cell. The transfection process makes the new cell a MCF 10A–derived cell type instead of a subtype of MCF 10A per se. Specifically, CLO represents the new MCF10A-Er-Src cell line cell formation as shown in the following OWL SubClassOf axiom:Based on the mapping and the design pattern models Figs.  and 4, eExisting 795 CLO cell line cell items were added with newly obtained data Fig. , e.g., L352 LINCS cell lines unavailable in CLO were newly added to CLO. Each of these cell lines was assigned a new non-redundant CLO ID based on CLO cell line naming convention . The parThe new information added to CLO includes two parts:http://www.ontobee.org/ontostat/LINCS-CLOview.A CLO subset of LINCS cell lines, abbreviated as LINCS-CLOview, was generated. The LINCS-CLOview can be considered as a “community view”  or a sliAs a subset of CLO, LINCS-CLOview has the same hierarchical structure and design patterns as the CLO. BFO is the top-level ontology with which CLO is aligned. Since BFO is also the top-level ontology for over 100 ontologies , such an alignment makes LINCS-CLOview easily integrated with other ontologies, such as CL for cell types, and OBI for cell line related processes.The Ontobee SPARQL web query program can be used to conveniently query detailed information in LINCS-CLOview. For example, Ontobee SPARQL was used to query the number of cell line cells that have the LINCS cell line IDs  Fig. . The scrIn this study, different SPARQL scripts were developed and used to analyze the LINCS cell lines from various aspects. An example of such SPARQL analysis is illustrated in next section.With the availability of LINCS-CLOview, we were able to analyze LINCS cell lines from different aspects. The tools used in our analyses include SPARQL-based queries, Protégé OWL editor visualization, and Ontobee statistics display and queries. Below we describe our analyzed results from three main aspects: related diseases, cell types, and tissues/organs.Our study found that LINCS cell lines are associated with 121 diseases. These 121 diseases include three benign neoplasms, i.e., breast fibrocystic disease (associated with MCF 10A and MCF 10F cells), kidney angiomyolipoma (associated with 621–101 cell), and male productive organ benign neoplasm (associated with BPH-1 cell). The other 118 diseases are various types of cancers. Fig. The hierarchical structure of DOID Fig.  helped tTo further illustrate the usage of LINCS-CLOview, we generated a SPARQL script that queries the cell lines originally derived from human patients having more specific disease names under cervix carcinoma Fig. . ConsistWe also examined the tissue and organ types from which the LINCS cell lines were derived. In CLO, the multi-species anatomy ontology UBERON  is used The cell types of LINCS cell lines were analyzed. The Cell Type Ontology (CL)  was usedThe contributions of this study are multiple. First of all, we systematically annotated the LINCS cell lines and integrated the information of the cell lines from different resources to CLO. Second, two more object properties, including ‘is disease model for’ and ‘derives originally from patient with disease’, were newly generated in CLO in order to use CLO to represent the information of LINCS cell lines. Third, using MCF 10A, we show how to use CLO to represent cell line cell features and a cellular response to an extracellular agent. Fourth, we generated the LINCS-CLOview, a CLO community view for the LINCS research community, which will serve as a CLO standardized module for LINCS data integration and coordination. Fifth, useful information about the LINCS cell lines was obtained via analyzing LINCS-CLOview. Given well-defined class hierarchy and axiom assertions and OWL reasoning, our analyses showed that ontology SPARQL was also able to query results for different use cases. This study is timely updating and implementation of CLO for enhanced cell line data integration and analysis features.We have for the first time showed in this study how to use CLO to represent specific cellular responses to agents such as collagen, Latrunculin A, or transfection agents. Such treatments make the cells form 3D growth, apoptosis, or a new cell line cell type. Each cellular process is represented separately based on its own characteristics. More specifically, for each process, we typically use the pattern of ‘participates in’ some specific process which is either a term obtained from an existing ontology such as GO, or a term generated in CLO if such a process term cannot be found from any existing community-based ontology. After such modeling discussed and agreed by the manuscript reviewers and presentation audience, we plan to extend such design patterns to represent cellular responses of other CLO cell line cells.To our knowledge, this article is the first report of implementing CLO by developing a CLO community view (or slim) to serve a specific community, in this case, the LINCS research community. Since tens of thousands of cell lines have been represented in CLO, it is not efficient to use the whole CLO for LINCS cell line related research. The generation of LINCS-CLOview in this study allows the standardization and modularization of the LINCS cell lines, which facilitates the better analysis and reuse of the LINCS cell line information. Such a strategy can also be used to represent and study cell lines used by other communities.One advantage of this CLO-based LINCS cell line representation is to bring together different cell line resources  with the framework of CLO. Our integration of LINCS cell lines and CLO ensures the consistency and integrity of the cell line data across multiple resources. In many cases, a key challenge of systematically studying diverse systems biology signature data such as LINCS is the difficulty in integration of different data types and information related to various cell lines. LINCS-CLOview provides a cell line-oriented semantic framework and foundation for integrating different cell line study results and supporting systematical analysis of cellular signatures and network studies.Our future work will include different directions. One major direction is to apply the ontological representation of LINCS cell lines in LINCS-CLOview to systematically study cellular molecular markers. For example, we can study cellular markers based on different criteria such as disease, cell type, tissue, and organ. As illustrated in Figs. As a community-based ontology, the CLO team is also collaborating with other research projects that heavily use cell lines, such as the European Bioinformatics Institute (EBI) that uses many cell lines in their EBI projects. EBI uses the Experimental Factor Ontology (EFO) to represent various experimental factors such as cell line cells. We are now teaming with EBI to synchronize the cell line cells in EFO and CLO. We are also working with the China Cell Line Bank group to add their cell lines and their specific needs to CLO. Such activities will make CLO a more community-based centralized ontology source for cell line cell representation, supporting integrative cellular research to solve different scientific questions.In summary, we updated CLO by incorporating the information of all identified LINCS cell lines and used CLO to model cellular responses to different cell culture growth conditions and perturbations. LINCS-CLOview, a CLO subset of the LINCS cell line information, was generated and analyzed to better understand LINCS cell line information.


PXD005286. Data presented  proteomic analysis. The extracts were enriched for cellular signaling proteins using a mix of three different immobilized kinase inhibitors -3-(4-((1-Phenylethyl)amino)thienopyrimidin-6-yl)benzoic acid (SB6-060-05)) on sepharose bead columns. Raw data is deposited in the PRIDE database resented  shows ch Specifications Table 1Value of the data1.The data is from three well studied human cancer cell lines treated with commonly used chemotherapeutics, and can therefore be used by other researchers studying these cell lines or effects of these drugs.2.The data set describe the simultaneous pattern of change of hundreds of signaling proteins, and could be used for further modeling or network analysis.3.Researchers studying particular signaling pathways or networks can use the data set to find information on how levels of specific proteins change upon DNA stress or between cell lines.1This dataset has been produced in order to test and evaluate an updated method for targeted kinase proteomics. It contains data from MS analysis of three biological replicates of three human cancer cell lines A549, H460, and U2OS, treated with cisplatin or docetaxel, as well as their respective controls (3×3×3 samples). The raw data 22.1l-glutamine  and penicillin (100 units/mL)-streptomycin (0.1 mg/mL) . Cells were cultivated in a humidified atmosphere .H460  was grown in RPMI-1640 medium (Sigma-Aldrich). The cell lines A549  and U2OS  were grown in DMEM (Sigma-Aldrich). Both media were supplemented with fetal bovine serum (10%), amphotericin B (2.5 µg/mL), 2.250 at day 4) for 24 h and harvested by scraping in ice-cold PBS. The cells were washed once, pelleted, snap-frozen in liquid nitrogen and stored at −80 °C until use. For the lysis, the samples were thawed and mixed with 3×packed cell volume of lysis buffer , and 1X Halt™ protease and phosphatase inhibitor cocktail ). Samples were sonicated for 2 min on ice prior to centrifugation  and the supernatant collected for further analysis.Cells were treated with docetaxel (5 ng/mL) or cisplatin  was acquired at a resolution of 70,000 FWHM, followed by 10 MS/MS scans with isolation window 4.0 m/z, triggered for intensities above 1.7×104, at a maximum ion injection time of 100 ms for MS and 60 ms for MS/MS scans. A dynamic exclusion of 40 s was used as well as charge exclusion for unassigned, 1, and greater than 4. Thermo Sieve ™ was used to align MSMS spectra. Preview 2.3.5 (Protein Metrics Inc.) was used to determine optimal search criteria t-test by working over the Rank of the observation instead of observation value itself. Furthermore, it also makes it robust to outliers and extreme variations noticed in observed values.A modified multiplexed inhibitor bead (MIB) assay was used to enrich the cell lysates for kinases and other signaling proteins


Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography–mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine. Cancer is a very relevant health concern worldwide, both in terms of morbidity and mortality . ProstatThe most commonly used biomarker of PCa in clinical practice is serum prostate specific antigen (PSA). This biomarker reached the clinical practice as early as the 1990s and revolutionized the management of PCa, leading to an increase in the number of PCa cases diagnosed at the early stages , with a After a study published in 2009 which proved the concept that metabolomics have the potential to deliver a new biomarker for PCa with good sensitivity and specificity, the interest of the scientific community in metabolomics applied to PCa markedly increased. In this study, sarcosine was suggested as a potential biomarker for PCa which could be assessed in urine ,11,12,13Metabolomic studies can be performed using several matrices, including biofluids (commonly urine and serum/plasma), tissues, and cell lines . Each ofy (GC-MS) based methodology was applied to analyze one normal prostate cell line and four PCa cell lines with different metastatic potential and androgen receptor (AR) expression status.The main objective of this study was to prove the concept that a metabolomic profile is able to discriminate PCa cells from normal prostate cells by means of metabolic signatures of different cultured cancer cells, comparing them with a normal prostate epithelium immortalized cell line. Intracellular metabolites which were significantly increased or decreased as a consequence of PCa were also assessed. For this purpose, a gas chromatography–mass spectrometr In this study, we performed a GC-MS-based untargeted metabolomic approach to evaluate alterations in the intracellular metabolites of PCa immortalized cell lines compared with a normal prostate immortalized cell line. A total of 150 features were detected in the chromatograms, and a multivariate data analysis approach was applied to confirm that the alterations in endometabolome could be discriminated among the cell lines used in this study.The reproducibility of the analytical method was confirmed by the QCs cluster in a principal component analysis (PCA) model containing all acquired samples . FurtherTo evaluate which metabolites were responsible for this separation, all cancer cell lines were compared with the normal cell line, namely 22RV1 versus PNT2, PC3 versus PNT2, DU145 versus PNT2, and LNCaP versus PNT2. An optimal separation between each PCa cell line and the normal cell line was observed .The results of the permutation test showed that all models created were robust for the discrimination between each PCa cell line and the normal cell line . All metabolites with VIP values higher than one were considered potentially relevant for the separation among the cell lines. Hence, a total of 26 metabolites were considered relevant to differentiate 22RV1 from PNT2, 31 metabolites to differentiate PC3 from PNT2, 37 metabolites to differentiate DU145 from PNT2, and 32 metabolites to differentiate LNCaP from PNT2. After univariate analysis, a total of 18 metabolites were shown to differentiate 22RV1 from PNT2, 18 metabolites to differentiate PC3 from PNT2, 20 metabolites to differentiate DU145 from PNT2, and 23 metabolites to differentiate LNCaP from PNT2 . For allO-methyl-a-d-galactopyranoside was significantly increased in DU145 and in LNCaP but not in PC3. The significant increase of 2-butenoic acid levels was a characteristic alteration of the cell line with moderate metastatic potential (DU145); the significant increase of palmitic acid and of 13-octadecenoic acid were characteristic of LNCaP, a cell line with low metastatic potential. It was also possible to discriminate between androgen-responsive and androgen-unresponsive PCa cell lines using urea, since this metabolite was significantly decreased in androgen-unresponsive PCa cell lines . As previously mentioned, 22RV1 was originally an androgen-receptor-positive cell line, but since the cell culture was performed in the absence of androgen supplementation, we may hypothesize that this cell line developed androgen independency by a mechanism similar to that occurring in clinical practice after hormone deprivation therapy [From all evaluated metabolites, six stand out as important for the separation between all PCa cell lines and the normal cell line: ethanolamine, lactic acid, β-alanine, L-valine, L-leucine, and L-tyrosine. Considering different metabolites, it was also possible to distinguish PCa with different aggressiveness. For example, glycerol was significantly decreased in the low (LNCaP) and the moderate (DU145) metastatic potential cell lines, but not in the highly metastatic cell line (PC3), whereas methyl 2-acetamido-2-deoxy-3-Several other metabolites identified were also able to discriminate between different cancer cell lines and normal cell lines, namely L-alanine , 3-hydroxyisovaleric acid , glycine , phenylalanine , sorbose , cholesterol , glutamine (22RV1 versus PNT2 and LNCaP versus PNT2), and palmitoleic acid (22RV1 versus PNT2 and DU145 versus PNT2). Some unidentified metabolites were also important for the discrimination between cancer and normal cell lines .In this study, the potential of endometabolome investigation for discriminating between four PCa cell lines and a normal prostate cell line was explored, indicating that the endometabolome may be a valuable source for PCa biomarkers. Beyond allowing the discrimination between PCa cell lines and a normal prostate cell line, the study of alterations in intracellular metabolites also revealed that it was possible to discriminate among PCa cells with different aggressiveness and it was also possible to discriminate androgen-responsive from androgen-unresponsive cell lines.The prostate cell has a unique metabolic profile, as one of the major functions of these cells is the production and accumulation of citrate (a component of the prostatic fluid) . Unlike Another possible indication of alterations in the Krebs cycle associated with PCa observed in our study was the significant increase in glutamine levels in PCa cell lines 22RV1 and LNCaP, as well as in PC3, although this was not statistically significant. The conversion of glutamine to α-ketoglutarate, an intermediate of the Krebs cycle, takes place in two reaction steps: (1) The hydrolysis of the amino group of glutamine yielding glutamate, which can be excreted, or (2) may be further metabolized into α-ketoglutarate. Furthermore, glutamine is also important for lipogenesis ,28, so tO-methyl-a-d-galactopyranoside observed in our study. Mucins belong to the glycosylate protein family and the increase in their levels has been associated with cancer, as these compounds are involved in signaling, cell growth, and survival, prompting tumor progression . These iAs previously mentioned, the increase in sarcosine levels is one of the most studied metabolic alterations related with PCa and one of its most promising biomarkers . HoweverBeyond glycine, several other amino acids were significantly altered in PCa cells, namely L-alanine, β-alanine, valine, leucine, threonine, phenylalanine, and tyrosine, which may indicate a potential increase in protein synthesis. The increase in protein metabolism is important for cancer cells to maintain an elevated proliferative state as proteins are essential for cell division. The alteration in amino acid levels and, consequently, in protein metabolism was previously found in other PCa metabolomics studies ,33,34. AThe urea cycle uses ammonia to produce urea, as urea is less toxic than ammonia. The main source of ammonia is the degradation of proteins and, as previously explained, cancer cells have an increased requirement of proteins which may explain the significantly decreased levels of urea in PCa cells  observed in our study. Our results also revealed a significant increase of 3-hydroxyisovaleric acid levels in PCa cells . This leucine metabolite has an important role in protein metabolism once 3-hydroxyisovaleric acid stimulates protein synthesis and prevents protein catabolism . The significant elevation in the cholesterol levels observed in PCa cells  has been previously described in other metabolic studies using prostatic tissue from PCa patients ,37. The The alteration in lipid metabolism, particularly in phospholipid membrane constituents’ assembly and catabolism, is frequently associated with PCa . In our We observed significant alterations in organic acids in PCa cell lines, namely 2-butenoic acid in DU145) and also the significant increase in the levels of the fatty acid 13-octadecenoic acid (in LNCaP). Similar alterations were associated with PCa in previous metabolomic studies, performed in blood and urine 5 and als. Fatty aTo better understand the metabolic alterations associated with PCa, a metabolite set enrichment analysis   was alsoN-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and all analytical standards were purchased from Sigma-Aldrich Co. . The antibiotic mixture penicillin/streptomycin , heat inactivated fetal bovine serum (FBS), and trypsin 0.25%-EDTA were purchased from GIBCO Invitrogen . Sodium hydrogen carbonate was obtained from Merck  and methanol was from VWR .All the chemicals used in this study were of analytical grade. RPMI-1640 medium, phosphate buffered saline 1% (PBS), norvaline, methyl linolelaidate, desmosterol 2. PCa cell lines  and the normal prostate epithelium immortalized cell line (PNT2) were provided by the Portuguese Oncology Institute of Porto . 22RV1 ag for 10 min at 4 °C. Afterwards, the methanol with the extracted metabolites was separated from the pellet and immediately frozen at −80 °C until analysis. Four consecutive passages were used to evaluate the endometabolome. All cell lines were plated and grown to near confluence in RPMI-1640 medium. The cell culture medium was then rejected and the cells were washed with PBS solution twice. The PBS was also rejected and cells were carefully scraped with ice cold methanol, transferred to falcons on ice, and centrifuged at 3000× g for 10 min at 4 °C, transferred to a glass vial, and the internal standards (10 µL/mL)  were added. Each sample (1 mL) was evaporated under a nitrogen stream and 50 µL of dichloromethane plus 50 µL of the derivatization reagent, MSTFA, were added to the residue. The vial was vortexed and heated for 30 min at 80 °C. Fifty microliters of the remaining residue was transferred to the glass vial used for GC-MS analysis [Amino acids, fatty acids, sugars, and steroids cannot be analyzed directly by gas chromatography due to their low volatility and polarity and thus need to be derivatized prior to GC-MS analysis. The method used was previously developed by Pereira et al. (2012) with some adaptations. Briefly, the methanol with the extracted metabolites was centrifuged at 3000× analysis . All samm/z. The emission current was 50 µA and the electron multiplier was set in relative mode to an auto tune procedure. All mass spectra were acquired in the electron impact (EI) mode [The GC-MS conditions were based on those previously optimized by Pereira et al. (2012) with some adaptations. An EVOQ-436 gas chromatograph equipped with a Bruker Triple Quadrupole mass detector and a Bruker MS workstation software version 8.2 were used. The chromatographic separation was accomplished using a column Rxi-5Sil MS (30 m × 0.25 mm × 0.25 µm) (Restek). A CombiPAL automatic autosampler (Bruker) was used for all experiments. Sample extracts (1 μL) were injected using split mode (ratio 1/10). The carrier gas used was helium C-60  (flow of 1 mL/min) and the injector port was heated to 250 °C. The analysis was performed in full scan mode. The oven temperature was fixed at 70 °C for 2 min, then increased to 250 °C (rate 15 °C/min), held for 2 min, and finally increased to 300 °C (rate 10 °C/min) and held for 8 min. The transfer line temperature was 250 °C and the manifold temperature was 40 °C. The mass range was from 50 to 1000 EI) mode . All samTo ensure reproducibility of the methodology, quality control samples (QCs) were injected  every sim/z range (50–500), MS data noise level (1.0 × 104), m/z tolerance (0.3), chromatogram baseline level (2.0 × 104), and peak duration range (0.02–0.30 min). All ions (m/z) with a RSD higher than 50% [m/z) from the column, were removed. The data was normalized by the total area of the chromatograms and Pareto scaled. The multivariate analysis of the data included unsupervised (PCA) and supervised approaches (PLS-DA) used to evaluate the presence of relevant metabolic differences between the cell lines in the study. To confirm the robustness, all PLS-DA models were validated through a permutation test (200 random permutations of Y-observations and two components). To identify the compounds responsible for the discrimination of PCa cell lines from the normal cell line, the variable importance of projection (VIP) values obtained through PLS-DA were used. All metabolites with VIP values higher than one were considered potentially relevant for the separation of the studied cell lines. To confirm the importance of these metabolites in the discrimination between PCa cell lines and the normal prostate cell line and, consequently, their potential as PCa biomarkers, univariate analysis was performed using the Shapiro–Wilk test . To calculate the p value, the unpaired Student’s t-test with Welch correction  or the unpaired Mann–Whitney test  was used. The percentage of variation, uncertainty of the percentage of variation, effect size, and the standard error were calculated [p values for multiple comparisons by setting the significance cut-off of the p value. After this univariate analysis, the metabolites taken into account were those with p < 0.05, a percentage of variation superior to the calculated uncertainty, and an effect size superior to the calculated standard error. For all these metabolites, the AUC value was calculated using MetaboAnalyst 3.0 [Prior to statistical analysis, all chromatograms were pre-processed with Mzmine 2.2 software, including baseline correction, peak detection, chromatogram deconvolution, and alignment . The par/z range –500, MS lculated . A Bonfelculated  was usedlyst 3.0 . Finallylyst 3.0 . The identification of compounds selected by statistical approaches was achieved by using the National Institute of Standards and Technology (NIST 14) mass spectral library and Kovat’s indices, and these were confirmed using the injection of authentic standards, when available .In this study, we evaluated alterations in prostate cancer cells’ endometabolome using PCa cell lines with different aggressiveness and hormone-dependence status. The results showed that changes in the metabolomic profile are capable of discriminating cancer from normal prostate cells, enabling the discovery of new PCa biomarkers. Overall, we found alterations in the lipid, energy, and protein metabolisms of PCa cells. The dysregulations in these metabolic pathways might be explained by the well-known characteristics of cancer cells, namely their proliferative growth and migration capacity, as well as their resistance to apoptosis. To sustain these elevated proliferation rates, energy demands and protein synthesis increase. Lipid metabolism is involved in several cellular functions, like intercellular signaling, cell membrane synthesis, and energy production. The evaluation of alterations in these latter compounds  may allow for the discovery of novel biomarkers for PCa detection and a better understanding of the most important metabolic pathways altered because of cancer development and progression. This may lead to the discovery of new therapeutic targets and the development of new therapeutic approaches.


Pyrus betulifolia. PbeNAC1 were greatly induced by cold and drought, while salt stress had little effect on expression. PbeNAC1 was localized in the nuclei showed transactivation activity. Overexpression of PbeNAC1 conferred enhanced tolerance to multiple stresses, including cold and drought, as supported by lower levels of reactive oxygen species, higher survival rate, higher activities of enzymes, relative to wild-type (WT). In addition, steady-state mRNA levels of 15 stress-responsive genes coding for either functional or regulatory proteins were higher levels in the transgenic plants relative to the WT with drought or cold treatment. yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) assays showed that PbeNAC1 protein can physically interact with PbeDREB1 and PbeDREB2A. Taken together, these results demonstrate that pear PbeNAC1 plays an important role in improving stress tolerance, possibly by interacting with PbeDREB1 and PbeDREB2A to enhance the mRNA levels of some stress-associated genes.NAC  transcription factors are important regulator in abiotic stress and plant development. However, knowledge concerning the functions of plant NAC TFs functioning in stress tolerance and the underlying molecular basis are still limited. In this study, we report functional characterization of the NAC TF, PbeNAC1, isolated from  Plant growth and development are frequently threatened by environmental stresses such as drought and low temperature. To cope with these stresses, plants evolved a set of physiological and molecular defense mechanisms to adapt to adverse conditions . Over thStress-responsive genes are generally classified into two main groups based on their products, effector molecules or regulator molecules . Genes iATAF1 and ATAF2 increased susceptibility to fungal pathogens in Arabidopsis  genes, including CBF1/DREB1B, CBF2/DREB1C, and CBF3/DREB1A  genes, collectively called the CBF regulon, implying that they act as central hub in the cold signaling network  led to enhanced cold and drought tolerance in transgenic lines. Both yeast two-hybrid and BiFC assays revealed that the PbeNAC1 was associated with PbeDREB1/CBF and PbeDREB2A/AP2, and also enhanced the transcript levels of some stress-responsive genes. Taken together, our data demonstrate that PbeNAC1 is involved in the regulation of cold and drought tolerance via modulating the expression of stress-responsive genes through interacting with the PbeDREB1 and PbeDREB2A.sistance , making P. betulifolia plants grown in the seedling beds at Center of Pear Engineering Technology Research, Nanjing Agricultural University, were used to gene cloning and expression analysis of PbeNAC1 under different treatment. Uniform and healthy seedlings were inserted in a flask containing distilled water, which were kept for 1 day in a growth chamber at 25°C with 16-h light/8-h dark photoperiod (45 μmol m-2 s-1) being treated with various treatments. For cold stress, the seedlings were placed in the growth chamber set at 4°C for 72 h; the leaves were collected at 0, 5, 12, 24, 48, and 72 h after initiation of the treatment. For dehydration treatment, the seedlings were placed on dry filter papers above a work bench and dried at 25°C  for 0, 0.5, 1, 3, and 6 h. For the salt treatment, the seedlings were incubated in the 200 mM NaCl solution for 0, 1, 5, 12, 24, and 48 h. ABA treatment was applied by immersing the seedlings in 100 μM ABA solution for 0, 1, 6, 12, 24, and 48 h. In order to eliminate the effects of hypoxia or anoxia creased, we set up another experiments of water as the control corresponding to ABA or salt treatment. For each treatment, a minimum of 60 seedlings were used, and the sampled were then frozen immediately in liquid nitrogen and stored at -80°C super low temperature freezer until use for gene expression analysis.Fourty-five-day-old ® RT reagent kit  according to the manufacturer’s instructions. Quantitative real-time PCR was carried out with SYBR-Green PCR kit (TakaRa) using 20 μL of reaction mixture consisting 10 μL of 2 × SYBR-PreMix EX Taq, 100 ng of cDNA, and 0.25 μM of each primer . Approximately 1 μg of total RNA was reversely transcribed into cDNA using the PrimeScriptt method  of the s1. Based on the above sequence, a pair of gene-specific primers . PCR was performed in a total volume of 50 μL containing 300 ng cDNA, 10 μL of 1 × TransStart FastPfu buffer, 5 μL of 2.5 mM deoxyribonucleotide (dNTP), 0.4 μM of a pair of specific primers  and molecular weight were also identified by tools in an internet server, ExPASy .A pear sequence with a full-length, highly homologous to NAC1, was obtained by sequence search against the pear genome databaseArabidopsis mesophyll protoplasts by PEG method . After confirmation by sequencing, the fusion construct (p35S-PbeNAC1-GFP) and the control vector (pCAMBIA1302) was transferred into Agrobacterium tumefaciens strain GV3101 using the freeze-thaw method. Transient transformation of tobacco leaves was done as described by The whole ORF of the PbeNAC1 was restricted with BglII and BstEII, and the resulting product was cloned into BglII and BstEII sites of the binary vector pCAMBIA1301 to generate pCAMBIA1301-PbeNAC1, which was introduced into A. tumefaciens strain GV3101 by the freeze-thaw method. About 50-days-old tobacco seedlings were used for transformation based on a leaf disk transformation method (0 plants were maintained in a growth chamber at 25°C with a 16 h light/8 h dark photoperiod until they flowered and set seeds. Homozygous lines were harvested according to an earlier method (in vitro T0 plants and the WT using cetyltrimethyl ammonium bromide (CTAB). To verify the transgenic tobacco plants, the 25 μL PCR reaction conditions contained 2.5 μL10 × PCR buffer, 2 μL of 2.5 mM dNTPs, 0.25 μM of each primer, and 2.5 units of Taq polymerase. The PCR reaction conditions were performed at 94°C for 3 min, followed by 35 cycles of 30 s at 94°C, 30 s at 60°C, 1 min 30 s at 72°C, and a final extension at 72°C for 10 min. PCR products were electrophoresed on 1.2 % (w/v) agarose gel containing 0.5 μg/L ethidium bromide and visualized under UV transillumination. Overexpression of PbeNAC1 was analyzed by semi-quantitative RT-PCR according to 2 generation plants were used for a stress tolerance assay and physiological measurement.The pMD-18T-n method . Transger method . After o2 generation transgenic plants and wild type were sterilized for 30 s in 70% (v/v) ethanol and incubated in 2.5% (v/v) H2O2 for 5 min, followed by rinse with sterile distilled water for three times before they were sown on germination medium (GM) containing MS salts, 30 g L-1 sucrose and 0.8% agar (pH 5.8). For freezing treatment, the seedlings were first transplanted into plastic containers filled with a mixture of soil and sand (1:2) in the same chamber with a 16 h photoperiod and 40% relative humidity. 30-days or 60-days-old tobacco plants from WT and transgenic lines grown under normal conditions were directly treated for 24 h at 0°C without cold acclimation, and then moved to ambient environment for further growth. Survival rate was scored after 1 day recovery growth; photos were taken before and after the freezing treatment and after the recovery.Seeds of T-2s-1)  until the drought treatment. The plants were deprived of watering for 15 days, and then returned to regular irrigation for 5 days, and then the leaves were collected for analysis of antioxidant enzyme activity, cell death, relative water content (RWC), metabolite levels, and expression of stress-responsive genes.Dehydration stress was performed as described by 2O2 level, and anti-superoxide anion activity were quantified using the relevant detection kits (Nanjing Jiancheng Bioengineering Institute) based on the manufacturer’s instructions. Histochemical staining with DAB and NBT was used to analyze the in situ accumulation of H2O2 and O2- according to Electrolyte leakage (EL), MDA, and total chlorophyll content were measured according to previous studies . ProlinePbeNAC1, the full-length cDNA of PbeDREB1 and PbeDREB2A were amplified using primer pairs GSP6 and GSP7 (Supplementary Table To elucidate the molecular mechanisms underlying the enhanced stress tolerance of transgenic plants overexpressing Arabidopsis was carried out by For bimolecular fluorescence complementation (BiFC) analysis, the PbeDREB1 and PbeDREB2A ORF without a stop codon were PCR amplified with primer pairs GSP6 and GSP9, respectively, and subcloned into pUC-pSPYNE-35S containing the N-terminal fragment of yellow fluorescent protein (nYFP) to get PbeDREB1-nYFP and PbeDREB2A-nYFP. Meanwhile, the full-length cDNA of PbeNAC1 without a stop codon was amplified using primer pair GSP8 and inserted into pUC-pSPYNE-35S containing the C-terminal fragment of YFP (cYFP) to generate PbeNAC1-cYFP. Transient expression assay of PbeNAC1 in ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001 as significantly different.Each stress treatment was repeated at least three times with consistent results. Data are presented as means ± SE of at least three independent replicates from one representative experiment. The data were analyzed by Duncan’s multiple range tests in the ANOVA program of SPSS (IBM SPSS 22), taking PbeNAC1 gene, we first searched the pear genome database using the OsNAC1 sequence as a query, which yielded different outputs. Homology comparison in the NCBI database showed that the first output exhibited high sequence homology to NAC1. So, based on this output sequence a pair of primers was designed for RT-PCR to amplify the ORF of NAC1 gene in P. betulifolia. Analysis in ORF Finder indicates that it contained a complete ORF of 927 bp, flanked by a 246 bp 5′-untranslated region (UTR) and a 139 bp 3′-UTR. The cDNA, designated as PbeNAC1, contains an intact ORF and encodes a polypeptide of 308 amino acids with a calculated molecular mass of 35.6 kDa and an isoelectric point of 6.46. The gene has been deposited in NCBI and the accession number of KU663372. A phylogenetic tree constructed based on the sequences of PbeNAC1 and NACs of other plants, such as Arabidopsis thaliana, and rice. The phylogenetic tree indicated that PbeNAC1 was closely related to ANAC081 . Multiple sequence alignments indicated that PbeNAC1 shares a significant degree of sequence identity with seven other NAC proteins. The alignment showed that PbeNAC1 has a highly conserved sequence in their N-terminal regions, including five conserved subdomains (A–E), and PbeNAC1 possessed a conserved nuclear localization signal  .To get the PbeNAC1 under various abiotic stresses, including cold (4°C), dehydration, salt and ABA. Under normal growth conditions, transcript levels of PbeNAC1 underwent minor changes (data not shown). By contrast, PbeNAC1 was gradually induced within 1 day of cold treatment, but was sharply up-regulated at 2 days to nearly eightfold of its initial level and declined at the last day . When the seedlings were treated with dehydration, PbeNAC1 mRNA abundance was slightly induced at 0.5 h, followed by progressive elevation until reaching the peak value at 6 h, which was an approximately 12-fold increase relative to the initial level . We also examined the transcript levels to test whether PbeNAC1 is responsive to salt. As shown in Figure 3C, treatment with 200 mM NaCl led to a quick accumulation of PbeNAC1 mRNA level, which progressed until a maximum level was reached at 2 days. However, treatment with ABA did not change notably transcript level of PbeNAC1 except a slight decrease at 1 day, indicating that PbeNAC1 was not ABA-inducible . The results also showed that the effect of water occurred hypoxia or anoxia on plant was negligible during the 48 h .Real-time Quantitative PCR (qPCR) was used to analyze the expression profiles of Figures D), while the PbeNAC1–GFP fusion protein was observed exclusively in the nucleus , indicating that PbeNAC1 was a nuclear protein.Sequence analysis showed that PbeNAC1 contained a nuclear localization signal (aa 114–132), implying that it may be localized in the nucleus. To confirm this, the PbeNAC1 coding region was fused to the N-terminus of the GFP reporter gene under the control of the cauliflower mosaic virus 35S promoter. Microscopic observation showed that the control GFP was uniformly distributed throughout the whole cell (Luciferase (LUC) reporter gene driven by a minimal 35S promoter with the GAL4 DNA binding site (DBS) . The Renilla Luciferase (RNL LUC) gene under a control of a 35S promoter served as an internal control. These constructs were expressed transiently in protoplast cells from 5-week-old Arabidopsis plants under a 16-h-dark/8-h-light photoperiod. Expression of PbeNAC1 in the system significantly stimulated LUC expression, thus more effective activated LUC reporter gene activity, of the control was less than sixfolds of the those in the presence of PbeNAC1 . These data exhibited that PbeNAC1 had transactivation activity.To further identify if PbeNAC1 functions as a transcriptional activator, the transient expression assay system was used. For this purpose, the full-length PbeNAC1 coding region was fused to pMN6 vector to generate a fusion construct PbeNAC1-pMN6 under the control of the 35S promoter. The report construct contained a PbeNAC1 was induced by cold and dehydration in a stronger manner, we speculated that PbeNAC1 might play a key role in the regulation of cold and drought stress response. To examine this hypothesis, we first generated transgenic tobacco plants overexpressing PbeNAC1 via Agrobacterium-mediated transformation. Two independent overexpression lines of tobacco (OE3 and OE7) with high transcript levels of PbeNAC1 were used for cold and drought tolerance analysis . After recovery at room temperature for 10 days, the survival rate of WT plants was 0, significantly lower than that of the transgenic lines: 48.3% for OE3 and 41.6% for OE7 . When 60-days-old transgenic seedlings and WT tobacco plants were exposed to freezing stress, the leaves of the WT plants showed severe freezing injury, whereas the two transgenic lines were affected to a less extent . Cell death is a reliable indicator of cell damage caused by abiotic stresses. We can observe the comparably extent of staining by trypan blue in the leaves between the WT and the two transgenic lines without freezing stress, whereas deeper staining occurred in the leaves of the WT compared with the transgenic plants after the freezing stress for 20 h, demonstrating that more serious cell death occurred in the WT . In another experiment, 60-day-old plants were exposed to 20 h freezing stress. In order to compare the physiological differences, EL, chlorophyll and Pro content were measured in the samples collected after 20 h of freezing stress. EL of OE3 (33.9%) and OE7 (43.2%) was significantly lower than the 66.8% found in the WT . While total chlorophyll contents in the two transgenic lines were about 1.5 times higher than that of WT . We also measured proline contents in the transgenic lines and WT after freezing treatment, as this compound has been considered as an important metabolite indicating the relevance to stress tolerance. As shown in Figure 6G, the transgenic lines accumulated higher proline in comparison with the WT. These results revealed that transgenic overexpression of PbeNAC1improved freezing tolerance in tobacco plants.To evaluate the function of PbeNAC1 in drought tolerance, we performed a dehydration tolerance assay using T2 plants of the two lines (OE3 and OE7) as this gene exhibited a quick response to dehydration. When the 30-days-old in vitro seedlings were dehydrated in an ambient environment, a steady decrease in FW was observed in both the WT and the two transgenic lines. However, after 9 h of dehydration, the water loss rate in the WT was 46.6%, significantly higher than that of OE3 (27.7%), and OE7 (32.5%) . Although OE7 lost less water than OE3, the difference was not statistically significant after dehydration. At the end of dehydration, phenotype differences were prominent between the WT and transgenic lines, as the former lost its turgor to a greater extent . As EL is an indicator of membrane injury, the EL was compared between the WT and the transgenic plants after 9 h of dehydration. As shown in Figure 7C, the EL was significantly higher in the WT (49.7%) than in OE3 (30.8%) or OE7 (9.4%), indicating that the WT suffered from severe membrane damage. MDA, an important lipid oxidation product, can reflect the extent of damage of the membranes. The assay indicated that the MDA contents of OE3 (5.9 μmol/g FW) and OE7 (7.9 μmol/g FW) were significantly lower than the WT . In addition, slighter cell death staining was visualized in the two transgenic lines after dehydration for 9 h. These findings demonstrated that overexpression of PbeNAC1 could alleviate the membrane damage in the transgenic plants . These results showed that overexpression of PbeNAC1 led to an elevation of the dehydration tolerance in the transgenic tobacco.To evaluate the function of PbeNAC1 overexpression lines on drought tolerance, when 30-days-old tobacco plants were deprived of water for 15 days, followed by re-watering for 7 days. After 15 days without water, leaf wilting was observed in all tested plants; obviously the two transgenic lines showed better leaf turgor compared to the WT. After watering was resumed, the transgenic plants recovered their growth more rapidly than did the WT plants. The survival rates of the transgenic lines were significantly higher than that of WT . When 60-days-old tobacco plants were used for the drought treatment, similar results were obtained: leaf wilting was more evident in the WT relative to the two transgenic lines . Consistent with the enhanced drought tolerance phenotype, lower levels of EL, higher survival rates, and higher Pro content . These results suggest that overexpression of PbeNAC1 had a significant effect on the improvement of drought resistance in the transgenic tobacco plants.To evaluate the effect of PbeNAC1 exhibited enhanced tolerance to cold, dehydration and drought. It is well documented that abiotic stresses usually result in elevation of cellular ROS level; thus the ROS level is an indicator of stress tolerance. Histochemical staining by DAB and NBT was used to reveal in situ accumulation of H2O2 and O2-, respectively. After freezing stresses for 20 h, the WT leaves displayed deeper staining patterns when compared with OE3 and OE7, in line with the quantitative measurement of ROS . In addition, the ROS level in the leaves sampled from the 60-days-old potted plants exposed to drought for 10 days was also checked. Similarly, OE3 and OE7 exhibited clearly less intense DAB and NBT staining in comparison with the WT . Taken together, these data suggest that the transgenic plants accumulated lower levels of H2O2 and O2- under freezing and drought stresses. The above-mentioned results demonstrated that the two transgenic lines contained fewer ROS relative to WT. Since enzymatic and non-enzymatic antioxidants play critical role in detoxifying ROS activities of three significant antioxidant enzymes , were measured in the two transgenic lines and WT before and after freezing and drought stresses. As can be seen in Figure 9, the activities of the three enzymes in the two transgenic lines were higher than in the WT under normal conditions. After 20 h of freezing stress, it is noticeable that the two transgenic lines contained significantly higher enzyme activity than did the WT. When 60-days-old tobacco plants were used for the drought stress, similar results were obtained: the activities of the three detoxifying enzyme was higher in the transgenic lines than WT , consistent with the proportion to the ROS accumulation of these lines. These data revealed that overexpression of PebNAC1 greatly influenced the activities of the antioxidant enzymes in the transgenic plants.The above data suggest that the transgenic plants overexpressing PbeNAC1 in abiotic stress response, expression patterns of 15 stress responsive or ROS-related genes were compared between the WT and the transgenic lines before and after freezing stress for 20 h or drought treatment for 10 days by qPCR . These genes encode stress responsive proteins , enzymes for biosynthesis of proline (NtP5CS) or abscisic acid , or enzymes involved in ROS scavenging . As shown in Figure 10, transcript levels of these genes were evidently higher in the transgenic lines than in the WT under normal growth conditions. When exposure to freezing or drought stress caused up-regulation of the transcript levels of the analyzed genes in all lines, but OE3 and OE7 still had a higher expression level in comparison with the WT. These results suggests that PbeNAC1 may function in abiotic stress tolerances through regulating or interacting with the stress-related genes, although it remains unclear how such regulation or interaction can be established.It has been suggested that gene expression levels are likely to be correlated with the magnitude of stress tolerance in plants . To elucFigure 11, only yeast cells of the positive control and co-transformant with bait and prey grew normally on SD/–Leu/–Trp/–Ura medium, whereas the negative control did not survive.NAC TFs have been considered as a cofactor for transcription regulation in humans and yeast . To addrArabidopsis protoplasts, transformed with vectors containing PbeNAC1-pSPYNE and PbeDREB1-pSPYCE; PbeNAC1-pSPYNE and PbeDREB2A-pSPYCE, or with vectors of the positive control . Whereas there was no green fluorescent in the cells transformed with vectors of the negative control . Both the Y2H and BiFC assays indicated that PbeNAC1 could interact with PbeDREB1 or PbeDREB2A.A BiFC assay was further performed to verify the Y2H analysis. Green fluorescence was observed in P. betulifolia, will advance our understanding on the diverse roles of NACs. Here, we demonstrated that PbeNAC1 of P. betulifolia plays a positive role in drought or cold tolerance by interacting with PbeDREBs and activating the expression of stress-responsive genes.NACs, representing a large TF family specific to plants, are composed of various members in different plants. NAC proteins form an integral part of signaling web exerting crucial roles in regulating arrays of physiological or biochemical processes. However, so far, only a limited number of NACs have been characterized in a few plants, predominantly in the model plants, while functional roles and underlying mechanisms of a large number of NACs remain elusive, particularly in the perennial fruit trees. Therefore, elucidation of the functions of NACs in perennial fruit trees, such as PbeNAC1 may be clustered into the typical NAC group because it has a highly conserved NAC domain, consisting of 125 amino acids at the N-terminus. Sequence characteristics in this region have been widely observed in typical NAC proteins from other plant species, suggesting that they may share common biological features in terms of DNA binding. However, the C-terminal sequences were extensively distinct from each other, which may account for the distinct functions of different proteins derived from various clades.The defining feature of NACs is the presence of a highly conserved N-terminal DNA-binding domain composed of a NAC signature and a diversified C-terminal domain. Multiple sequence alignment suggests that PbeNAC1 mRNA levels was caused by cold, dehydration, and salt. These abiotic stresses-induced expression pattern of PbeNAC1 was supported by the earlier studies, such as rice , enzymes for biosynthesis of proline (NtP5CS) or ABA (NtNCED1), or enzymes involved in ROS scavenging , Previous study reported most of these genes or these homologs have been responsive to abiotic stresses. QPCR analysis showed that the expression level of these genes were higher in the transgenic plants compared with those of WT under either freezing or drought stress, consistent with earlier reports in which overexpression of a transcription activator may have an ability to activate a series of target genes that functions in encounters and adaptations to abiotic stresses , which were assumed to be involved in counteracting cellular drought  related to ROS scavenging, were stronger in the PbeNAC1-overexpressing lines than in the WT before and after either freezing or drought stress. It is noticeable that the expression levels of these three genes were positively correlated with the higher activities of antioxidant enzymes  relative to WT under the freezing and drought stresses. These data suggest that the PbeNAC1 could improve drought/cold tolerance by, partially, the more efficient ROS-scavenging systems in the transgenic lines.To cope with unfavorable environmental constraints plants modulate the expression of a large number of stress-responsive genes, constituting an important molecular basis for the response and adaptation of plants to stresses . To gainstresses . Accumulstresses . In this drought . In thisfindings . It is iPbeNAC1 functioned in mediating cold and drought tolerance by interacting with PbeDREBs (PbeDREB1 and PbeDREB2A). Establishment of the NAC1-DREBs network provides valuable understanding of molecular basis of NAC1 and widens our understanding of the complex cold signaling network.We demonstrate here that over-expression of PbeNAC1 in tobacco result in clear increase of drought and cold tolerance, which also acts as a positive regulator of some stress-responsive genes expression from tobacco. It is known that NAC proteins can regulate gene expression by recognizing and binding to a DNA sequence with a core 4-mer motif, CACG, that allows them to regulate downstream genes . In thisPbeNAC1 significantly modified drought and cold tolerance, but in the future, more work is required to experimentally unravel other components related to PbeNAC1 so as to gain a clear-cut silhouette of the major hub in the network.The present work demonstrate that overexpression of NtRD29A (TC115477 in DFCI database), NtRD17 (XP_016502582.1), NtLEA14 (XP_009621630), NtERD1 (Gu144573), NtERD10A (AB049335), NtERD10B (AB049336), NtERD10C (AB049337), NtERD10D (AB049338), NtERF5 (AY655738), NtLEA5 (AF053076), NtP5CS (HM854026), NtNCED1 (HM068892), NtAPX (U15933.1), NtCAT (U93244.1), NtSOD (AB093097).GenBank accession numbers for the genes which were monitored transcriptional levels are as follows: XH designed the research. XH and CJ performed the experiments. SZ, KL, XX, HC, JH, YC, YW, and HZ proofread this manuscript. XH and CJ wrote the manuscript. All authors read and approved the final manuscript.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.