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ZNF652, a Novel Zinc Finger Protein, Interacts with the Putative Breast Tumor Suppressor CBFA2T3 to Repress Transcription
ZNF652, A Novel Zinc Finger Protein, Interacts with the Putative Breast Tumor Suppressor CBFA2T3 to Repress Transcription Raman Kumar,1 Jantina Manning,1 Hayley E. Spendlove,3 Gabriel Kremmidiotis,4 Ross McKirdy,1 Jaclyn Lee,1 David N. Millband,1 Kelly M. Cheney,1 Martha R. Stampfer,5 Prem P. Dwivedi,2 Howard A. Morris,2 and David F. Callen1 1Breast Cancer Genetics Group, Dame Roma Mitchell Cancer Research Laboratories, Department of Medicine, University of Adelaide and Hanson Institute; 2Endocrine Bone Laboratory, Hanson Institute, Adelaide, South Australia, Australia; 3Department of Laboratory Genetics, Women’s and Children’s Hospital, North Adelaide, South Australia, Australia; 4Bionomics, Ltd., Thebarton, South Australia, Australia; and 5Lawrence Berkeley National Laboratory, Berkeley, California Abstract gene effector zinc finger proteins may specifically The transcriptional repressor CBFA2T3is a putative interact with one or more of the ETO proteins to generate breast tumor suppressor. To define the role of CBFA2T3, a defined range of transcriptional repressor complexes. we used a segment of this protein as bait in a yeast (Mol Cancer Res 2006;4(9):655–65) two-hybrid screen and identified a novel uncharacterized protein, ZNF652. In general, primary tumors and cancer Introduction cell lines showed lower expression of ZNF652 than Tumor growth, characterized by unchecked cell division, normal tissues. Together with the location of this gene results from both the overexpression of growth-promoting on the long arm of chromosome 17q, a region of frequent oncogenes and the reduced expression of growth-inhibiting loss of heterozygosity in cancer, these results suggest tumor suppressor genes. These genes often encode proteins that In silico a possible role of ZNF652 in tumorigenesis. -
Genetic Variability in the Italian Heavy Draught Horse from Pedigree Data and Genomic Information
Supplementary material for manuscript: Genetic variability in the Italian Heavy Draught Horse from pedigree data and genomic information. Enrico Mancin†, Michela Ablondi†, Roberto Mantovani*, Giuseppe Pigozzi, Alberto Sabbioni and Cristina Sartori ** Correspondence: [email protected] † These two Authors equally contributed to the work Supplementary Figure S1. Mares and foal of Italian Heavy Draught Horse (IHDH; courtesy of Cinzia Stoppa) Supplementary Figure S2. Number of Equivalent Generations (EqGen; above) and pedigree completeness (PC; below) over years in Italian Heavy Draught Horse population. Supplementary Table S1. Descriptive statistics of homozygosity (observed: Ho_obs; expected: Ho_exp; total: Ho_tot) in 267 genotyped individuals of Italian Heavy Draught Horse based on the number of homozygous genotypes. Parameter Mean SD Min Max Ho_obs 35,630.3 500.7 34,291 38,013 Ho_exp 35,707.8 64.0 35,010 35,740 Ho_tot 50,674.5 93.8 49,638 50,714 1 Definitions of the methods for inbreeding are in the text. Supplementary Figure S3. Values of BIC obtained by analyzing values of K from 1 to 10, corresponding on the same amount of clusters defining the proportion of ancestry in the 267 genotyped individuals. Supplementary Table S2. Estimation of genomic effective population size (Ne) traced back to 18 generations ago (Gen. ago). The linkage disequilibrium estimation, adjusted for sampling bias was also included (LD_r2), as well as the relative standard deviation (SD(LD_r2)). Gen. ago Ne LD_r2 SD(LD_r2) 1 100 0.009 0.014 2 108 0.011 0.018 3 118 0.015 0.024 4 126 0.017 0.028 5 134 0.019 0.031 6 143 0.021 0.034 7 156 0.023 0.038 9 173 0.026 0.041 11 189 0.029 0.046 14 213 0.032 0.052 18 241 0.036 0.058 Supplementary Table S3. -
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. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
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. -
TF Activation Profiling Plate Array II Signosis, Inc
Signosis, Inc. Innovative Plate Assay Solutions TF Activation Profiling Plate Array II Catalog Number: FA-1002 (For Research Use Only) Introduction Materials Provided with the Kit Transcription factors (TFs) are a group of cellular proteins that play essential roles in regulating gene Component Qty Store at expression. They act as sensors to monitor cellular 96-Well Plates (with 2 RT changes and convert signals into gene expression. aluminum adhesive seal) Often, a specific cellular signal pathway can activate Isolation Columns 2 RT multiple TFs. The expression of a specific gene can Elution Buffer 400µL RT also be under the control of multiple TFs. Thus, TF Plate Hybridization Buffer 20mL RT monitoring the activation of multiple TFs 5X Plate Hybridization Wash 60mL RT simultaneously is critical to understanding the Buffer molecular mechanism of cellular regulation underlying 5X Detection Wash Buffer 60mL RT cell signaling and gene expression. Signosis, Inc.’s TF Blocking Buffer 60mL RT Activation Profiling Plate Array II is used for Filter Wash Buffer 5mL 4°C monitoring 96 different TFs simultaneously from one Filter Binding Buffer 1mL 4°C sample. Substrate A 2mL 4°C Substrate B 2mL 4°C Principle of the assay Streptavidin-HRP Conjugate 40µL 4°C Substrate Dilution Buffer 16mL 4°C Signosis, Inc.’s TF Activation Profiling Plate Array II TF Binding Buffer Mix 60µL -20°C is used for monitoring the activation of multiple TFs TF Probe Mix II 20µL -20°C simultaneously. With this technology a series of biotin-labeled probes are made based on the consensus sequences of TF DNA-binding sites. -
UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii -
Tbx3 Controls the Sinoatrial Node Gene Program and Imposes Pacemaker Function on the Atria
Downloaded from genesdev.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Tbx3 controls the sinoatrial node gene program and imposes pacemaker function on the atria Willem M.H. Hoogaars,1,3 Angela Engel,2,3 Janynke F. Brons,1,3 Arie O. Verkerk,2 Frederik J. de Lange,1 L.Y. Elaine Wong,1 Martijn L. Bakker,1 Danielle E. Clout,1 Vincent Wakker,1 Phil Barnett,1 Jan Hindrik Ravesloot,2 Antoon F.M. Moorman,1 E. Etienne Verheijck,2 and Vincent M. Christoffels1,4 1Department of Anatomy and Embryology, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; 2Department of Physiology, Heart Failure Research Center, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands The sinoatrial node initiates the heartbeat and controls the rate and rhythm of contraction, thus serving as the pacemaker of the heart. Despite the crucial role of the sinoatrial node in heart function, the mechanisms that underlie its specification and formation are not known. Tbx3, a transcriptional repressor required for development of vertebrates, is expressed in the developing conduction system. Here we show that Tbx3 expression delineates the sinoatrial node region, which runs a gene expression program that is distinct from that of the bordering atrial cells. We found lineage segregation of Tbx3-negative atrial and Tbx3-positive sinoatrial node precursor cells as soon as cardiac cells turn on the atrial gene expression program. Tbx3 deficiency resulted in expansion of expression of the atrial gene program into the sinoatrial node domain, and partial loss of sinoatrial node-specific gene expression. -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
The Cyclin-Dependent Kinase 8 Module Sterically Blocks Mediator Interactions with RNA Polymerase II
The cyclin-dependent kinase 8 module sterically blocks Mediator interactions with RNA polymerase II Hans Elmlund*†, Vera Baraznenok‡, Martin Lindahl†, Camilla O. Samuelsen§, Philip J. B. Koeck*¶, Steen Holmberg§, Hans Hebert*ʈ, and Claes M. Gustafsson‡ʈ *Department of Biosciences and Nutrition, Karolinska Institutet and School of Technology and Health, Royal Institute of Technology, Novum, SE-141 87 Huddinge, Sweden; †Department of Molecular Biophysics, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; ‡Division of Metabolic Diseases, Karolinska Institutet, Novum, SE-141 86 Huddinge, Sweden; §Department of Genetics, Institute of Molecular Biology, Oester Farimagsgade 2A, DK-1353 Copenhagen K, Denmark; and ¶University College of Southern Stockholm, SE-141 57 Huddinge, Sweden Communicated by Roger D. Kornberg, Stanford University School of Medicine, Stanford, CA, August 28, 2006 (received for review February 21, 2006) CDK8 (cyclin-dependent kinase 8), along with CycC, Med12, and Here, we use the S. pombe system to investigate the molecular Med13, form a repressive module (the Cdk8 module) that prevents basis for the distinct functional properties of S and L Mediator. RNA polymerase II (pol II) interactions with Mediator. Here, we We find that the Cdk8 module binds to the pol II-binding cleft report that the ability of the Cdk8 module to prevent pol II of Mediator, where it sterically blocks interactions with the interactions is independent of the Cdk8-dependent kinase activity. polymerase. In contrast to earlier assumptions, the Cdk8 kinase We use electron microscopy and single-particle reconstruction to activity is dispensable for negative regulation of pol II interac- demonstrate that the Cdk8 module forms a distinct structural tions with Mediator. -
TBX3 Acts As Tissue-Specific Component of the Wnt/Β
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.053561; this version posted April 22, 2020. 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-NC 4.0 International license. TBX3 acts as tissue-specific component of the Wnt/b-catenin enhanceosome Dario Zimmerli1,6#, Costanza Borrelli2#, Amaia Jauregi-Miguel3,4#, Simon Söderholm3,4, Salome Brütsch1, Nikolaos Doumpas1, Jan Reichmuth1, Fabienne Murphy-Seiler5, Michel Aguet5, Konrad Basler1*, Andreas E. Moor2*, Claudio Cantù3,4* 1 Department of Molecular Life Sciences, University of Zurich, Zürich, Switzerland, CH-8057 2 Institute of Molecular Cancer Research, University of Zurich, Zürich, Switzerland, CH-8057 3 Wallenberg Centre for Molecular Medicine, Linköping University 4 Department of Biomedical and Clinical Sciences, Faculty of Health Science, SE-581 83 Linköping, Sweden 5Swiss Institute for Experimental Cancer Research (ISREC), Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Life Sciences, CH-1015 Lausanne, Switzerland 6 Current address: Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands # These authors contributed equally to this work * For correspondence: [email protected] [email protected] [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.053561; this version posted April 22, 2020. 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-NC 4.0 International license. -
Functional Diversification of the Nleg Effector Family in Enterohemorrhagic Escherichia Coli
Functional diversification of the NleG effector family in enterohemorrhagic Escherichia coli Dylan Valleaua, Dustin J. Littleb, Dominika Borekc,d, Tatiana Skarinaa, Andrew T. Quailea, Rosa Di Leoa, Scott Houlistone,f, Alexander Lemake,f, Cheryl H. Arrowsmithe,f, Brian K. Coombesb, and Alexei Savchenkoa,g,1 aDepartment of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S 3E5, Canada; bDepartment of Biochemistry and Biomedical Sciences, Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada; cDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390; dDepartment of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX 75390; ePrincess Margaret Cancer Centre, University of Toronto, Toronto, ON M5G 2M9, Canada; fDepartment of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada; and gDepartment of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, AB T2N 4N1, Canada Edited by Ralph R. Isberg, Howard Hughes Medical Institute and Tufts University School of Medicine, Boston, MA, and approved August 15, 2018 (receivedfor review November 6, 2017) The pathogenic strategy of Escherichia coli and many other gram- chains. Depending on the length and nature of the polyubiquitin negative pathogens relies on the translocation of a specific set of chain, it posttranslationally regulates the target protein’s locali- proteins, called effectors, into the eukaryotic host cell during in- zation, activation, or degradation. Ubiquitination is a multistep fection. These effectors act in concert to modulate host cell pro- process which begins with the ubiquitin-activating enzyme (E1) cesses in favor of the invading pathogen. Injected by the type III using ATP to “charge” ubiquitin, covalently binding the ubiquitin secretion system (T3SS), the effector arsenal of enterohemorrhagic C terminus by a thioester linkage.