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The Rise and Fall of the Bovine Corpus Luteum
University of Nebraska Medical Center DigitalCommons@UNMC Theses & Dissertations Graduate Studies Spring 5-6-2017 The Rise and Fall of the Bovine Corpus Luteum Heather Talbott University of Nebraska Medical Center Follow this and additional works at: https://digitalcommons.unmc.edu/etd Part of the Biochemistry Commons, Molecular Biology Commons, and the Obstetrics and Gynecology Commons Recommended Citation Talbott, Heather, "The Rise and Fall of the Bovine Corpus Luteum" (2017). Theses & Dissertations. 207. https://digitalcommons.unmc.edu/etd/207 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@UNMC. It has been accepted for inclusion in Theses & Dissertations by an authorized administrator of DigitalCommons@UNMC. For more information, please contact [email protected]. THE RISE AND FALL OF THE BOVINE CORPUS LUTEUM by Heather Talbott A DISSERTATION Presented to the Faculty of the University of Nebraska Graduate College in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Biochemistry and Molecular Biology Graduate Program Under the Supervision of Professor John S. Davis University of Nebraska Medical Center Omaha, Nebraska May, 2017 Supervisory Committee: Carol A. Casey, Ph.D. Andrea S. Cupp, Ph.D. Parmender P. Mehta, Ph.D. Justin L. Mott, Ph.D. i ACKNOWLEDGEMENTS This dissertation was supported by the Agriculture and Food Research Initiative from the USDA National Institute of Food and Agriculture (NIFA) Pre-doctoral award; University of Nebraska Medical Center Graduate Student Assistantship; University of Nebraska Medical Center Exceptional Incoming Graduate Student Award; the VA Nebraska-Western Iowa Health Care System Department of Veterans Affairs; and The Olson Center for Women’s Health, Department of Obstetrics and Gynecology, Nebraska Medical Center. -
Table 2. Functional Classification of Genes Differentially Regulated After HOXB4 Inactivation in HSC/Hpcs
Table 2. Functional classification of genes differentially regulated after HOXB4 inactivation in HSC/HPCs Symbol Gene description Fold-change (mean ± SD) Signal transduction Adam8 A disintegrin and metalloprotease domain 8 1.91 ± 0.51 Arl4 ADP-ribosylation factor-like 4 - 1.80 ± 0.40 Dusp6 Dual specificity phosphatase 6 (Mkp3) - 2.30 ± 0.46 Ksr1 Kinase suppressor of ras 1 1.92 ± 0.42 Lyst Lysosomal trafficking regulator 1.89 ± 0.34 Mapk1ip1 Mitogen activated protein kinase 1 interacting protein 1 1.84 ± 0.22 Narf* Nuclear prelamin A recognition factor 2.12 ± 0.04 Plekha2 Pleckstrin homology domain-containing. family A. (phosphoinosite 2.15 ± 0.22 binding specific) member 2 Ptp4a2 Protein tyrosine phosphatase 4a2 - 2.04 ± 0.94 Rasa2* RAS p21 activator protein 2 - 2.80 ± 0.13 Rassf4 RAS association (RalGDS/AF-6) domain family 4 3.44 ± 2.56 Rgs18 Regulator of G-protein signaling - 1.93 ± 0.57 Rrad Ras-related associated with diabetes 1.81 ± 0.73 Sh3kbp1 SH3 domain kinase bindings protein 1 - 2.19 ± 0.53 Senp2 SUMO/sentrin specific protease 2 - 1.97 ± 0.49 Socs2 Suppressor of cytokine signaling 2 - 2.82 ± 0.85 Socs5 Suppressor of cytokine signaling 5 2.13 ± 0.08 Socs6 Suppressor of cytokine signaling 6 - 2.18 ± 0.38 Spry1 Sprouty 1 - 2.69 ± 0.19 Sos1 Son of sevenless homolog 1 (Drosophila) 2.16 ± 0.71 Ywhag 3-monooxygenase/tryptophan 5- monooxygenase activation protein. - 2.37 ± 1.42 gamma polypeptide Zfyve21 Zinc finger. FYVE domain containing 21 1.93 ± 0.57 Ligands and receptors Bambi BMP and activin membrane-bound inhibitor - 2.94 ± 0.62 -
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. -
0.5) in Stat3∆/∆ Compared with Stat3flox/Flox
Supplemental Table 2 Genes down-regulated (<0.5) in Stat3∆/∆ compared with Stat3flox/flox Probe ID Gene Symbol Gene Description Entrez gene ID 1460599_at Ermp1 endoplasmic reticulum metallopeptidase 1 226090 1460463_at H60c histocompatibility 60c 670558 1460431_at Gcnt1 glucosaminyl (N-acetyl) transferase 1, core 2 14537 1459979_x_at Zfp68 zinc finger protein 68 24135 1459747_at --- --- --- 1459608_at --- --- --- 1459168_at --- --- --- 1458718_at --- --- --- 1458618_at --- --- --- 1458466_at Ctsa cathepsin A 19025 1458345_s_at Colec11 collectin sub-family member 11 71693 1458046_at --- --- --- 1457769_at H60a histocompatibility 60a 15101 1457680_a_at Tmem69 transmembrane protein 69 230657 1457644_s_at Cxcl1 chemokine (C-X-C motif) ligand 1 14825 1457639_at Atp6v1h ATPase, H+ transporting, lysosomal V1 subunit H 108664 1457260_at 5730409E04Rik RIKEN cDNA 5730409E04Rik gene 230757 1457070_at --- --- --- 1456893_at --- --- --- 1456823_at Gm70 predicted gene 70 210762 1456671_at Tbrg3 transforming growth factor beta regulated gene 3 21378 1456211_at Nlrp10 NLR family, pyrin domain containing 10 244202 1455881_at Ier5l immediate early response 5-like 72500 1455576_at Rinl Ras and Rab interactor-like 320435 1455304_at Unc13c unc-13 homolog C (C. elegans) 208898 1455241_at BC037703 cDNA sequence BC037703 242125 1454866_s_at Clic6 chloride intracellular channel 6 209195 1453906_at Med13l mediator complex subunit 13-like 76199 1453522_at 6530401N04Rik RIKEN cDNA 6530401N04 gene 328092 1453354_at Gm11602 predicted gene 11602 100380944 1453234_at -
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). -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells. -
Systems-Epigenomics Inference of Transcription Factor Activity
Chen et al. Genome Biology (2017) 18:236 DOI 10.1186/s13059-017-1366-0 RESEARCH Open Access Systems-epigenomics inference of transcription factor activity implicates aryl- hydrocarbon-receptor inactivation as a key event in lung cancer development Yuting Chen1†, Martin Widschwendter2 and Andrew E. Teschendorff1,2,3*† Abstract Background: Diverse molecular alterations associated with smoking in normal and precursor lung cancer cells have been reported, yet their role in lung cancer etiology remains unclear. A prominent example is hypomethylation of the aryl hydrocarbon-receptor repressor (AHRR) locus, which is observed in blood and squamous epithelial cells of smokers, but not in lung cancer. Results: Using a novel systems-epigenomics algorithm, called SEPIRA, which leverages the power of a large RNA- sequencing expression compendium to infer regulatory activity from messenger RNA expression or DNA methylation (DNAm) profiles, we infer the landscape of binding activity of lung-specific transcription factors (TFs) in lung carcinogenesis. We show that lung-specific TFs become preferentially inactivated in lung cancer and precursor lung cancer lesions and further demonstrate that these results can be derived using only DNAm data. We identify subsets of TFs which become inactivated in precursor cells. Among these regulatory factors, we identify AHR, the aryl hydrocarbon-receptor which controls a healthy immune response in the lung epithelium and whose repressor, AHRR, has recently been implicated in smoking-mediated lung cancer. In addition, we identify FOXJ1, a TF which promotes growth of airway cilia and effective clearance of the lung airway epithelium from carcinogens. Conclusions: We identify TFs, such as AHR, which become inactivated in the earliest stages of lung cancer and which, unlike AHRR hypomethylation, are also inactivated in lung cancer itself. -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
SLC46A3 As a Potential Predictive Biomarker for Antibody–Drug
Published OnlineFirst August 21, 2018; DOI: 10.1158/1078-0432.CCR-18-1300 Cancer Therapy: Preclinical Clinical Cancer Research SLC46A3 as a Potential Predictive Biomarker for Antibody–Drug Conjugates Bearing Noncleavable Linked Maytansinoid and Pyrrolobenzodiazepine Warheads Krista Kinneer1, John Meekin1, Arnaud C. Tiberghien2, Yu-Tzu Tai3, Sandrina Phipps4, Christine Mione Kiefer4, Marlon C. Rebelatto5, Nazzareno Dimasi4, Alyssa Moriarty6, Kyriakos P. Papadopoulos6, Sriram Sridhar5, Stephen J. Gregson2, Michael J. Wick6, Luke Masterson2, Kenneth C. Anderson3, Ronald Herbst1, Philip W. Howard2, and David A. Tice1 Abstract Purpose: Antibody–drug conjugates (ADC) utilizing non- also examined in patient-derived xenograft and in vitro cleavable linker drugs have been approved for clinical use, and models of acquired T-DM1 resistance and multiple myeloma several are in development targeting solid and hematologic bone marrow samples by RT-PCR. malignancies including multiple myeloma. Currently, there Results: Loss of SLC46A3 expressionwasfoundtobea are no reliable biomarkers of activity for these ADCs other than mechanismofinnateandacquiredresistancetoADCs presence of the targeted antigen. We observed that certain cell bearing DM1 and SG3376. Sensitivity was restored in refrac- lines are innately resistant to such ADCs, and sought to tory lines upon introduction of SLC46A3, suggesting that uncover the underlying mechanism of resistance. expression of SLC46A3 maybemorepredictiveofactivity Experimental Design: The expression of 43 lysosomal than target antigen levels alone. Interrogation of primary membrane target genes was evaluated in cell lines resistant multiple myeloma samples indicated a range of SLC46A3 to ADCs bearing the noncleavable linker, pyrrolobenzodiaze- expression, including samples with undetectable levels like pine payload SG3376, in vitro. The functional relevance of multiple myeloma cell lines resistant to BCMA-targeting SLC46A3, a lysosomal transporter of noncleavable ADC DM1andSG3376ADCs. -
UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The
UNIVERSITY OF CALIFORNIA RIVERSIDE Investigations into the Role of TAF1-mediated Phosphorylation in Gene Regulation A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Cell, Molecular and Developmental Biology by Brian James Gadd December 2012 Dissertation Committee: Dr. Xuan Liu, Chairperson Dr. Frank Sauer Dr. Frances M. Sladek Copyright by Brian James Gadd 2012 The Dissertation of Brian James Gadd is approved Committee Chairperson University of California, Riverside Acknowledgments I am thankful to Dr. Liu for her patience and support over the last eight years. I am deeply indebted to my committee members, Dr. Frank Sauer and Dr. Frances Sladek for the insightful comments on my research and this dissertation. Thanks goes out to CMDB, especially Dr. Bachant, Dr. Springer and Kathy Redd for their support. Thanks to all the members of the Liu lab both past and present. A very special thanks to the members of the Sauer lab, including Silvia, Stephane, David, Matt, Stephen, Ninuo, Toby, Josh, Alice, Alex and Flora. You have made all the years here fly by and made them so enjoyable. From the Sladek lab I want to thank Eugene, John, Linh and Karthi. Special thanks go out to all the friends I’ve made over the years here. Chris, Amber, Stephane and David, thank you so much for feeding me, encouraging me and keeping me sane. Thanks to the brothers for all your encouragement and prayers. To any I haven’t mentioned by name, I promise I haven’t forgotten all you’ve done for me during my graduate years. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Core Circadian Clock Transcription Factor BMAL1 Regulates Mammary Epithelial Cell
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.23.432439; this version posted February 23, 2021. 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. 1 Title: Core circadian clock transcription factor BMAL1 regulates mammary epithelial cell 2 growth, differentiation, and milk component synthesis. 3 Authors: Theresa Casey1ǂ, Aridany Suarez-Trujillo1, Shelby Cummings1, Katelyn Huff1, 4 Jennifer Crodian1, Ketaki Bhide2, Clare Aduwari1, Kelsey Teeple1, Avi Shamay3, Sameer J. 5 Mabjeesh4, Phillip San Miguel5, Jyothi Thimmapuram2, and Karen Plaut1 6 Affiliations: 1. Department of Animal Science, Purdue University, West Lafayette, IN, USA; 2. 7 Bioinformatics Core, Purdue University; 3. Animal Science Institute, Agriculture Research 8 Origination, The Volcani Center, Rishon Letsiyon, Israel. 4. Department of Animal Sciences, 9 The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of 10 Jerusalem, Rehovot, Israel. 5. Genomics Core, Purdue University 11 Grant support: Binational Agricultural Research Development (BARD) Research Project US- 12 4715-14; Photoperiod effects on milk production in goats: Are they mediated by the molecular 13 clock in the mammary gland? 14 ǂAddress for correspondence. 15 Theresa M. Casey 16 BCHM Room 326 17 175 South University St. 18 West Lafayette, IN 47907 19 Email: [email protected] 20 Phone: 802-373-1319 21 22 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.23.432439; this version posted February 23, 2021. 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.