Transcriptional Regulation of Memory B Cell Differentiation
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Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
Activated Peripheral-Blood-Derived Mononuclear Cells
Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays. -
RNA-Binding Protein Hnrnpll Regulates Mrna Splicing and Stability During B-Cell to Plasma-Cell Differentiation
RNA-binding protein hnRNPLL regulates mRNA splicing and stability during B-cell to plasma-cell differentiation Xing Changa,b, Bin Lic, and Anjana Raoa,b,d,e,1 Divisions of aSignaling and Gene Expression and cVaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037; bSanford Consortium for Regenerative Medicine, La Jolla, CA 92037; and dDepartment of Pharmacology and eMoores Cancer Center, University of California at San Diego, La Jolla, CA 92093 Contributed by Anjana Rao, December 2, 2014 (sent for review July 20, 2014) Posttranscriptional regulation is a major mechanism to rewire the RBP-binding sites, thus validating the specificity of RBP binding transcriptomes during differentiation. Heterogeneous nuclear to coprecipitating RNAs and mapping RBP-binding sites on the RNA-binding protein LL (hnRNPLL) is specifically induced in terminally validated RNAs at close to single-nucleotide resolution (8). differentiated lymphocytes, including effector T cells and plasma Heterogeneous nuclear RNA-binding proteins (hnRNPs) is cells. To study the molecular functions of hnRNPLL at a genome- the term applied to a collection of unrelated nuclear RBPs. wide level, we identified hnRNPLL RNA targets and binding sites in hnRNPLL was identified through a targeted lentiviral shRNA plasma cells through integrated Photoactivatable-Ribonucleoside- screen for regulators of CD45RA to CD45RO switching during Enhanced Cross-Linking and Immunoprecipitation (PAR-CLIP) and memory T-cell development (9) and independently through RNA sequencing. hnRNPLL preferentially recognizes CA dinucleo- two separate screens performed by different groups for exclusion tide-containing sequences in introns and 3′ untranslated regions of CD45 exon 4 in a minigene context (10) and for altered CD44 (UTRs), promotes exon inclusion or exclusion in a context-dependent and CD45R expression on T cells in N-ethyl-N-nitrosourea manner, and stabilizes mRNA when associated with 3′ UTRs. -
Prospective Isolation of NKX2-1–Expressing Human Lung Progenitors Derived from Pluripotent Stem Cells
The Journal of Clinical Investigation RESEARCH ARTICLE Prospective isolation of NKX2-1–expressing human lung progenitors derived from pluripotent stem cells Finn Hawkins,1,2 Philipp Kramer,3 Anjali Jacob,1,2 Ian Driver,4 Dylan C. Thomas,1 Katherine B. McCauley,1,2 Nicholas Skvir,1 Ana M. Crane,3 Anita A. Kurmann,1,5 Anthony N. Hollenberg,5 Sinead Nguyen,1 Brandon G. Wong,6 Ahmad S. Khalil,6,7 Sarah X.L. Huang,3,8 Susan Guttentag,9 Jason R. Rock,4 John M. Shannon,10 Brian R. Davis,3 and Darrell N. Kotton1,2 2 1Center for Regenerative Medicine, and The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA. 3Center for Stem Cell and Regenerative Medicine, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas, USA. 4Department of Anatomy, UCSF, San Francisco, California, USA. 5Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. 6Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, Massachusetts, USA. 7Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA. 8Columbia Center for Translational Immunology & Columbia Center for Human Development, Columbia University Medical Center, New York, New York, USA. 9Department of Pediatrics, Monroe Carell Jr. Children’s Hospital, Vanderbilt University, Nashville, Tennessee, USA. 10Division of Pulmonary Biology, Cincinnati Children’s Hospital, Cincinnati, Ohio, USA. It has been postulated that during human fetal development, all cells of the lung epithelium derive from embryonic, endodermal, NK2 homeobox 1–expressing (NKX2-1+) precursor cells. -
Examination of the Transcription Factors Acting in Bone Marrow
THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY (PHD) Examination of the transcription factors acting in bone marrow derived macrophages by Gergely Nagy Supervisor: Dr. Endre Barta UNIVERSITY OF DEBRECEN DOCTORAL SCHOOL OF MOLECULAR CELL AND IMMUNE BIOLOGY DEBRECEN, 2016 Table of contents Table of contents ........................................................................................................................ 2 1. Introduction ............................................................................................................................ 5 1.1. Transcriptional regulation ................................................................................................... 5 1.1.1. Transcriptional initiation .................................................................................................. 5 1.1.2. Co-regulators and histone modifications .......................................................................... 8 1.2. Promoter and enhancer sequences guiding transcription factors ...................................... 11 1.2.1. General transcription factors .......................................................................................... 11 1.2.2. The ETS superfamily ..................................................................................................... 17 1.2.3. The AP-1 and CREB proteins ........................................................................................ 20 1.2.4. Other promoter specific transcription factor families ................................................... -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Clinical Utility of Recently Identified Diagnostic, Prognostic, And
Modern Pathology (2017) 30, 1338–1366 1338 © 2017 USCAP, Inc All rights reserved 0893-3952/17 $32.00 Clinical utility of recently identified diagnostic, prognostic, and predictive molecular biomarkers in mature B-cell neoplasms Arantza Onaindia1, L Jeffrey Medeiros2 and Keyur P Patel2 1Instituto de Investigacion Marques de Valdecilla (IDIVAL)/Hospital Universitario Marques de Valdecilla, Santander, Spain and 2Department of Hematopathology, MD Anderson Cancer Center, Houston, TX, USA Genomic profiling studies have provided new insights into the pathogenesis of mature B-cell neoplasms and have identified markers with prognostic impact. Recurrent mutations in tumor-suppressor genes (TP53, BIRC3, ATM), and common signaling pathways, such as the B-cell receptor (CD79A, CD79B, CARD11, TCF3, ID3), Toll- like receptor (MYD88), NOTCH (NOTCH1/2), nuclear factor-κB, and mitogen activated kinase signaling, have been identified in B-cell neoplasms. Chronic lymphocytic leukemia/small lymphocytic lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, Burkitt lymphoma, Waldenström macroglobulinemia, hairy cell leukemia, and marginal zone lymphomas of splenic, nodal, and extranodal types represent examples of B-cell neoplasms in which novel molecular biomarkers have been discovered in recent years. In addition, ongoing retrospective correlative and prospective outcome studies have resulted in an enhanced understanding of the clinical utility of novel biomarkers. This progress is reflected in the 2016 update of the World Health Organization classification of lymphoid neoplasms, which lists as many as 41 mature B-cell neoplasms (including provisional categories). Consequently, molecular genetic studies are increasingly being applied for the clinical workup of many of these neoplasms. In this review, we focus on the diagnostic, prognostic, and/or therapeutic utility of molecular biomarkers in mature B-cell neoplasms. -
The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells. -
Thyroid Gland Development and Function in the Zebrafish Model P
THYROID GLAND DEVELOPMENT AND FUNCTION IN THE ZEBRAFISH MODEL P. Porazzi, D. Calebiro, F. Benato, N. Tiso, L. Persani To cite this version: P. Porazzi, D. Calebiro, F. Benato, N. Tiso, L. Persani. THYROID GLAND DEVELOPMENT AND FUNCTION IN THE ZEBRAFISH MODEL. Molecular and Cellular Endocrinology, Elsevier, 2009, 312 (1-2), pp.14. 10.1016/j.mce.2009.05.011. hal-00521550 HAL Id: hal-00521550 https://hal.archives-ouvertes.fr/hal-00521550 Submitted on 28 Sep 2010 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Accepted Manuscript Title: THYROID GLAND DEVELOPMENT AND FUNCTION IN THE ZEBRAFISH MODEL Authors: P. Porazzi, D. Calebiro, F. Benato, N. Tiso, L. Persani PII: S0303-7207(09)00277-9 DOI: doi:10.1016/j.mce.2009.05.011 Reference: MCE 7224 To appear in: Molecular and Cellular Endocrinology Received date: 6-3-2009 Revised date: 20-5-2009 Accepted date: 20-5-2009 Please cite this article as: Porazzi, P., Calebiro, D., Benato, F., Tiso, N., Persani, L., THYROID GLAND DEVELOPMENT AND FUNCTION IN THE ZEBRAFISH MODEL, Molecular and Cellular Endocrinology (2008), doi:10.1016/j.mce.2009.05.011 This is a PDF file of an unedited manuscript that has been accepted for publication. -
Hepatitis C Virus As a Unique Human Model Disease to Define
viruses Review Hepatitis C Virus as a Unique Human Model Disease to Define Differences in the Transcriptional Landscape of T Cells in Acute versus Chronic Infection David Wolski and Georg M. Lauer * Liver Center at the Gastrointestinal Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA * Correspondence: [email protected]; Tel.: +1-617-724-7515 Received: 27 June 2019; Accepted: 23 July 2019; Published: 26 July 2019 Abstract: The hepatitis C virus is unique among chronic viral infections in that an acute outcome with complete viral elimination is observed in a minority of infected patients. This unique feature allows direct comparison of successful immune responses with those that fail in the setting of the same human infection. Here we review how this scenario can be used to achieve better understanding of transcriptional regulation of T-cell differentiation. Specifically, we discuss results from a study comparing transcriptional profiles of hepatitis C virus (HCV)-specific CD8 T-cells during early HCV infection between patients that do and do not control and eliminate HCV. Identification of early gene expression differences in key T-cell differentiation molecules as well as clearly distinct transcriptional networks related to cell metabolism and nucleosomal regulation reveal novel insights into the development of exhausted and memory T-cells. With additional transcriptional studies of HCV-specific CD4 and CD8 T-cells in different stages of infection currently underway, we expect HCV infection to become a valuable model disease to study human immunity to viruses. Keywords: viral hepatitis; hepatitis C virus; T cells; transcriptional regulation; transcription factors; metabolism; nucleosome 1. -
Applying Expression Profile Similarity for Discovery of Patient-Specific
bioRxiv preprint doi: https://doi.org/10.1101/172015; this version posted September 17, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Applying expression profile similarity for discovery of patient-specific functional mutations Guofeng Meng Partner Institute of Computational Biology, Yueyang 333, Shanghai, China email: [email protected] Abstract The progress of cancer genome sequencing projects yields unprecedented information of mutations for numerous patients. However, the complexity of mutation profiles of patients hinders the further understanding of mechanisms of oncogenesis. One basic question is how to uncover mutations with functional impacts. In this work, we introduce a computational method to predict functional somatic mutations for each of patient by integrating mutation recurrence with similarity of expression profiles of patients. With this method, the functional mutations are determined by checking the mutation enrichment among a group of patients with similar expression profiles. We applied this method to three cancer types and identified the functional mutations. Comparison of the predictions for three cancer types suggested that most of the functional mutations were cancer-type-specific with one exception to p53. By checking prediction results, we found that our method effectively filtered non-functional mutations resulting from large protein sizes. In addition, this methods can also perform functional annotation to each patient to describe their association with signalling pathways or biological processes. In breast cancer, we predicted "cell adhesion" and other mutated gene associated terms to be significantly enriched among patients.