After transduction, GFP+ cells were sorted for assays. In vitro liquid culture 1000 transduced cells (with or control; GFP+) were sorted into 16 wells of a 96-well plate per group, cultured in SFEM medium. (PNG 73?kb) 12918_2017_467_MOESM2_ESM.png (74K) GUID:?36BA1C7F-4C6A-45F2-BDDA-BB73065E26E9 Additional file 3: Figure S3: Simualtion results with additional regulation Maff Cdk2 (:Cyclin E) with respect to at high (upper) and low (lower) expression-levels. In each panel, steady-state Mouse monoclonal to ISL1 molecular quantities of Cyclin D-Cdk4/6 (left), Cyclin E-Cdk2 (middle) and CD235 E2F (right) are shown. The correct bistability with respect to is usually qualitatively reproduced with the additional molecular action. (PNG 31?kb) 12918_2017_467_MOESM3_ESM.png (32K) GUID:?86AA15FF-22EE-4E4D-A7D5-8200A55518E3 Additional file 4: Figure S4: Outcomes produced by other regulatory sturctures. Apparently false dynamics resulted by other hypotheses of regulations. Basically, all the other network structures than the one in Fig. ?Fig.5/Additional5/Additional file 1: Figure S1 produce qualitatively false results on (at least) one of Cdk4/6:CyclinD, Cdk2:CyclinE, and E2F. Here we show the most typically false results, combinations of regulatory relations are randomly assigned. Upper panel: unrealistic dynamic levels of Cdk2:CyclinE and E2F with respect to transcription under low expression, which is usually dictated by a randomly assigned network structure (regulatory code 1212); middle panel: results of Cdk2:CyclinE and E2F dictated by another network structure (regulatory code 2133); results of Cdk4/6:CyclinD and E2F dictated by a third different network structure (regulatory code 3321). Refer to Additional file 7: Table S1 for depiction of the regulatory codes. (PNG 52?kb) 12918_2017_467_MOESM4_ESM.png (53K) GUID:?4A236A54-D642-472E-976F-0F705CECBBA1 Additional file 5: Figure S5: Binding motif of Maff is also discovered within 2?kb upstream of gene. The Maff binding motif for transcriptional activation occurs at a location 1?kb upstream the transcription start site (TSS) of Pf4, which is potentially within the promoter region of the gene. The observation indicated that Maff might positively regulate Pf4, which is a regulator of platelet formation. (PDF 5?kb) 12918_2017_467_MOESM5_ESM.pdf (5.9K) GUID:?EB096B62-2F55-49D4-9DAE-494EC761796D Additional file 6: Formulations of the mathematical model. Descriptions for the ODEs and the modeling process are enclosed here. (DOC 128?kb) 12918_2017_467_MOESM6_ESM.doc (128K) GUID:?57C10617-5ECC-4AA5-95BF-2E34A5AD5649 Additional file 7: Table S1: Table for the combinatorial numerical tests. Qualitative results of the numerical assessments on combinations of possible regulatory relations are documented here, with all 81 combinations exhausted. The first four columns represent the regulatory code, 1 C inhibitory, 2 C none, and 3 C activatory effects, respectively. Molecular actions are indicated by the column headers. The last two columns show the agreement or discrepancy with input experimental data, 0 qualitative discrepancy, 1 qualitative agreement. The input experimental data for model training are the cell-cycle status after transduction of and qRT-PCR results for cell-cycle genes. (XLSX 13?kb) 12918_2017_467_MOESM7_ESM.xlsx (13K) GUID:?D73C2AA0-C401-464E-83D7-A35731A381C0 Additional file 8: Table S2: Model parameters. Symbols, definitions, values, units and references for all model parameters are listed in the table here. (XLS 28?kb) 12918_2017_467_MOESM8_ESM.xls (28K) GUID:?951C5A53-5876-4C70-85A1-97BAB9900639 Data Availability StatementAll data supporting the results and conclusion of this work were presented in the supplemental files (refer to section Additional files). Raw experimental data were provided in Ref [7, CD235 8]. Abstract Background Molecular mechanisms of the functional alteration of hematopoietic stem cells (HSCs) in leukemic environment attract intensive research interests. As known in previous researches, and are two important genes having opposite functions on cell cycle; however, they are both highly expressed in HSCs under leukemia. Hence, exploring the molecular mechanisms of how the genes act on cell cycle will help revealing the functional alteration of HSCs. Results We herein utilize the bioinformatic resources to computationally model the acting mechanisms of and on cell cycle. Using the data of functional experiments as reference, molecular acting mechanisms are optimally enumerated through model selection. The results are consolidated by evidences from gene sequence analysis, thus having enhanced the confidence of our pilot findings, which suggest that HSCs possibly undergo a adaptation – suppression process in response to the CD235 malignant environment of leukemia. Conclusion As a pilot research, our results may provide valuable insights for further experimental studies. Meanwhile, our research method combining computational modeling and data from functional experiments can be worthwhile for knowledge discovery; and it can be generalized and extended to other biological/biomedical studies. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0467-4) contains supplementary material, which is available to authorized users. and and are two important regulatory factors in hematopoiesis development. Previous studies showed that was mainly responsible for the transcription regulation of megakaryote differentiation (towards platelet) [1C3]; and less was known for the functions of in cell cycle [4]. Both Maff and Egr3 are able to recognize certain DNA elements, thus enhancing the transcriptions of their target genes [5, 6]. We had.
After transduction, GFP+ cells were sorted for assays
