19 research outputs found

    The bHLH transcription factor SPATULA enables cytokinin signaling, and both activate auxin biosynthesis and transport genes at the medial domain of the gynoecium

    Get PDF
    [EN] Fruits and seeds are the major food source on earth. Both derive from the gynoecium and, therefore, it is crucial to understand the mechanisms that guide the development of this organ of angiosperm species. In Arabidopsis, the gynoecium is composed of two congenitally fused carpels, where two domains: medial and lateral, can be distinguished. The medial domain includes the carpel margin meristem (CMM) that is key for the production of the internal tissues involved in fertilization, such as septum, ovules, and transmitting tract. Interestingly, the medial domain shows a high cytokinin signaling output, in contrast to the lateral domain, where it is hardly detected. While it is known that cytokinin provides meristematic properties, understanding on the mechanisms that underlie the cytokinin signaling pattern in the young gynoecium is lacking. Moreover, in other tissues, the cytokinin pathway is often connected to the auxin pathway, but we also lack knowledge about these connections in the young gynoecium. Our results reveal that cytokinin signaling, that can provide meristematic properties required for CMM activity and growth, is enabled by the transcription factor SPATULA (SPT) in the medial domain. Meanwhile, cytokinin signaling is confined to the medial domain by the cytokinin response repressor ARABIDOPSIS HISTIDINE PHOSPHOTRANSFERASE 6 (AHP6), and perhaps by ARR16 (a type-A ARR) as well, both present in the lateral domains (presumptive valves) of the developing gynoecia. Moreover, SPT and cytokinin, probably together, promote the expression of the auxin biosynthetic gene TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) and the gene encoding the auxin efflux transporter PIN-FORMED 3 (PIN3), likely creating auxin drainage important for gynoecium growth. This study provides novel insights in the spatiotemporal determination of the cytokinin signaling pattern and its connection to the auxin pathway in the young gynoecium.IRO, VMZM, HHU and PLS were supported by the Mexican National Council of Science and Technology (CONACyT) with a PhD fellowship (210085, 210100, 243380 and 219883, respectively). Work in the SDF laboratory was financed by the CONACyT grants CB-2012-177739, FC-2015-2/1061, and INFR-2015-253504, and NMM by the CONACyT grant CB-2011-165986. SDF, CF and LC acknowledge the support of the European Union FP7-PEOPLE-2009-IRSES project EVOCODE (grant no. 247587) and H2020-MSCARISE-2015 project ExpoSEED (grant no. 691109). SDF also acknowledges the Marine Biological Laboratory (MBL) in Woods Hole for a scholarship for the Gene Regulatory Networks for Development Course 2015 (GERN2015). IE acknowledges the International European Fellowship-METMADS project and the Universita degli Studi di Milano (RTD-A; 2016). Research in the laboratory of MFY was funded by NSF (grant IOS-1121055), NIH (grant 1R01GM112976-01A1) and the Paul D. Saltman Endowed Chair in Science Education (MFY). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Reyes Olalde, J.; Zuñiga, V.; Serwatowska, J.; Chávez Montes, R.; Lozano-Sotomayor, P.; Herrera-Ubaldo, H.; Gonzalez Aguilera, K.... (2017). The bHLH transcription factor SPATULA enables cytokinin signaling, and both activate auxin biosynthesis and transport genes at the medial domain of the gynoecium. PLoS Genetics. 13(4):1-31. https://doi.org/10.1371/journal.pgen.1006726S131134Reyes-Olalde, J. I., Zuñiga-Mayo, V. M., Chávez Montes, R. A., Marsch-Martínez, N., & de Folter, S. (2013). Inside the gynoecium: at the carpel margin. Trends in Plant Science, 18(11), 644-655. doi:10.1016/j.tplants.2013.08.002Alvarez-Buylla, E. R., Benítez, M., Corvera-Poiré, A., Chaos Cador, Á., de Folter, S., Gamboa de Buen, A., … Sánchez-Corrales, Y. E. (2010). Flower Development. The Arabidopsis Book, 8, e0127. doi:10.1199/tab.0127Bowman, J. L., Baum, S. F., Eshed, Y., Putterill, J., & Alvarez, J. (1999). 4 Molecular Genetics of Gynoecium Development in Arabidopsis. Current Topics in Developmental Biology Volume 45, 155-205. doi:10.1016/s0070-2153(08)60316-6Chávez Montes, R. A., Herrera-Ubaldo, H., Serwatowska, J., & de Folter, S. (2015). Towards a comprehensive and dynamic gynoecium gene regulatory network. Current Plant Biology, 3-4, 3-12. doi:10.1016/j.cpb.2015.08.002Marsch-Martínez, N., & de Folter, S. (2016). Hormonal control of the development of the gynoecium. Current Opinion in Plant Biology, 29, 104-114. doi:10.1016/j.pbi.2015.12.006Marsch-Martínez, N., Ramos-Cruz, D., Irepan Reyes-Olalde, J., Lozano-Sotomayor, P., Zúñiga-Mayo, V. M., & de Folter, S. (2012). The role of cytokinin during Arabidopsis gynoecia and fruit morphogenesis and patterning. The Plant Journal, 72(2), 222-234. doi:10.1111/j.1365-313x.2012.05062.xZhao, Z., Andersen, S. U., Ljung, K., Dolezal, K., Miotk, A., Schultheiss, S. J., & Lohmann, J. U. (2010). Hormonal control of the shoot stem-cell niche. Nature, 465(7301), 1089-1092. doi:10.1038/nature09126Ashikari, M. (2005). Cytokinin Oxidase Regulates Rice Grain Production. Science, 309(5735), 741-745. doi:10.1126/science.1113373Bartrina, I., Otto, E., Strnad, M., Werner, T., & Schmülling, T. (2011). Cytokinin Regulates the Activity of Reproductive Meristems, Flower Organ Size, Ovule Formation, and Thus Seed Yield in Arabidopsis thaliana. The Plant Cell, 23(1), 69-80. doi:10.1105/tpc.110.079079Hwang, I., Sheen, J., & Müller, B. (2012). Cytokinin Signaling Networks. Annual Review of Plant Biology, 63(1), 353-380. doi:10.1146/annurev-arplant-042811-105503Schaller, G. E., Bishopp, A., & Kieber, J. J. (2015). The Yin-Yang of Hormones: Cytokinin and Auxin Interactions in Plant Development. The Plant Cell, 27(1), 44-63. doi:10.1105/tpc.114.133595Kieber, J. J., & Schaller, G. E. (2010). The Perception of Cytokinin: A Story 50 Years in the Making: Figure 1. Plant Physiology, 154(2), 487-492. doi:10.1104/pp.110.161596Long, J. A., Moan, E. I., Medford, J. I., & Barton, M. K. (1996). A member of the KNOTTED class of homeodomain proteins encoded by the STM gene of Arabidopsis. Nature, 379(6560), 66-69. doi:10.1038/379066a0Jasinski, S., Piazza, P., Craft, J., Hay, A., Woolley, L., Rieu, I., … Tsiantis, M. (2005). KNOX Action in Arabidopsis Is Mediated by Coordinate Regulation of Cytokinin and Gibberellin Activities. Current Biology, 15(17), 1560-1565. doi:10.1016/j.cub.2005.07.023Yanai, O., Shani, E., Dolezal, K., Tarkowski, P., Sablowski, R., Sandberg, G., … Ori, N. (2005). Arabidopsis KNOXI Proteins Activate Cytokinin Biosynthesis. Current Biology, 15(17), 1566-1571. doi:10.1016/j.cub.2005.07.060Scofield, S., Dewitte, W., Nieuwland, J., & Murray, J. A. H. (2013). The Arabidopsis homeobox gene SHOOT MERISTEMLESS has cellular and meristem-organisational roles with differential requirements for cytokinin and CYCD3 activity. The Plant Journal, 75(1), 53-66. doi:10.1111/tpj.12198Gordon, S. P., Chickarmane, V. S., Ohno, C., & Meyerowitz, E. M. (2009). Multiple feedback loops through cytokinin signaling control stem cell number within the Arabidopsis shoot meristem. Proceedings of the National Academy of Sciences, 106(38), 16529-16534. doi:10.1073/pnas.0908122106Chickarmane, V. S., Gordon, S. P., Tarr, P. T., Heisler, M. G., & Meyerowitz, E. M. (2012). Cytokinin signaling as a positional cue for patterning the apical-basal axis of the growing Arabidopsis shoot meristem. Proceedings of the National Academy of Sciences, 109(10), 4002-4007. doi:10.1073/pnas.1200636109Leibfried, A., To, J. P. C., Busch, W., Stehling, S., Kehle, A., Demar, M., … Lohmann, J. U. (2005). WUSCHEL controls meristem function by direct regulation of cytokinin-inducible response regulators. Nature, 438(7071), 1172-1175. doi:10.1038/nature04270Werner, T., Motyka, V., Laucou, V., Smets, R., Van Onckelen, H., & Schmülling, T. (2003). Cytokinin-Deficient Transgenic Arabidopsis Plants Show Multiple Developmental Alterations Indicating Opposite Functions of Cytokinins in the Regulation of Shoot and Root Meristem Activity. The Plant Cell, 15(11), 2532-2550. doi:10.1105/tpc.014928Larsson, E., Franks, R. G., & Sundberg, E. (2013). Auxin and the Arabidopsis thaliana gynoecium. Journal of Experimental Botany, 64(9), 2619-2627. doi:10.1093/jxb/ert099Weijers, D., & Wagner, D. (2016). Transcriptional Responses to the Auxin Hormone. Annual Review of Plant Biology, 67(1), 539-574. doi:10.1146/annurev-arplant-043015-112122Robert, H. S., Crhak Khaitova, L., Mroue, S., & Benková, E. (2015). The importance of localized auxin production for morphogenesis of reproductive organs and embryos inArabidopsis. Journal of Experimental Botany, 66(16), 5029-5042. doi:10.1093/jxb/erv256Kuusk, S., Sohlberg, J. J., Magnus Eklund, D., & Sundberg, E. (2006). Functionally redundantSHIfamily genes regulate Arabidopsis gynoecium development in a dose-dependent manner. The Plant Journal, 47(1), 99-111. doi:10.1111/j.1365-313x.2006.02774.xSohlberg, J. J., Myrenås, M., Kuusk, S., Lagercrantz, U., Kowalczyk, M., Sandberg, G., & Sundberg, E. (2006). STY1regulates auxin homeostasis and affects apical-basal patterning of the Arabidopsis gynoecium. The Plant Journal, 47(1), 112-123. doi:10.1111/j.1365-313x.2006.02775.xStåldal, V., Sohlberg, J. J., Eklund, D. M., Ljung, K., & Sundberg, E. (2008). Auxin can act independently ofCRC,LUG,SEU,SPTandSTY1in style development but not apical-basal patterning of theArabidopsisgynoecium. New Phytologist, 180(4), 798-808. doi:10.1111/j.1469-8137.2008.02625.xVan Gelderen, K., van Rongen, M., Liu, A., Otten, A., & Offringa, R. (2016). An INDEHISCENT-Controlled Auxin Response Specifies the Separation Layer in Early Arabidopsis Fruit. Molecular Plant, 9(6), 857-869. doi:10.1016/j.molp.2016.03.005José Ripoll, J., Bailey, L. J., Mai, Q.-A., Wu, S. L., Hon, C. T., Chapman, E. J., … Yanofsky, M. F. (2015). microRNA regulation of fruit growth. Nature Plants, 1(4). doi:10.1038/nplants.2015.36Larsson, E., Roberts, C. J., Claes, A. R., Franks, R. G., & Sundberg, E. (2014). Polar Auxin Transport Is Essential for Medial versus Lateral Tissue Specification and Vascular-Mediated Valve Outgrowth in Arabidopsis Gynoecia. Plant Physiology, 166(4), 1998-2012. doi:10.1104/pp.114.245951Nole-Wilson, S., Azhakanandam, S., & Franks, R. G. (2010). Polar auxin transport together with AINTEGUMENTA and REVOLUTA coordinate early Arabidopsis gynoecium development. Developmental Biology, 346(2), 181-195. doi:10.1016/j.ydbio.2010.07.016De Folter, S. (2016). Auxin Is Required for Valve Margin Patterning in Arabidopsis After All. Molecular Plant, 9(6), 768-770. doi:10.1016/j.molp.2016.05.005Moubayidin, L., & Østergaard, L. (2014). Dynamic Control of Auxin Distribution Imposes a Bilateral-to-Radial Symmetry Switch during Gynoecium Development. Current Biology, 24(22), 2743-2748. doi:10.1016/j.cub.2014.09.080Girin, T., Paicu, T., Stephenson, P., Fuentes, S., Körner, E., O’Brien, M., … Østergaard, L. (2011). INDEHISCENT and SPATULA Interact to Specify Carpel and Valve Margin Tissue and Thus Promote Seed Dispersal in Arabidopsis. The Plant Cell, 23(10), 3641-3653. doi:10.1105/tpc.111.090944Ioio, R. D., Nakamura, K., Moubayidin, L., Perilli, S., Taniguchi, M., Morita, M. T., … Sabatini, S. (2008). A Genetic Framework for the Control of Cell Division and Differentiation in the Root Meristem. Science, 322(5906), 1380-1384. doi:10.1126/science.1164147Bishopp, A., Help, H., El-Showk, S., Weijers, D., Scheres, B., Friml, J., … Helariutta, Y. (2011). A Mutually Inhibitory Interaction between Auxin and Cytokinin Specifies Vascular Pattern in Roots. Current Biology, 21(11), 917-926. doi:10.1016/j.cub.2011.04.017De Rybel, B., Adibi, M., Breda, A. S., Wendrich, J. R., Smit, M. E., Novák, O., … Weijers, D. (2014). Integration of growth and patterning during vascular tissue formation in Arabidopsis. Science, 345(6197), 1255215. doi:10.1126/science.1255215Pernisova, M., Klima, P., Horak, J., Valkova, M., Malbeck, J., Soucek, P., … Hejatko, J. (2009). Cytokinins modulate auxin-induced organogenesis in plants via regulation of the auxin efflux. Proceedings of the National Academy of Sciences, 106(9), 3609-3614. doi:10.1073/pnas.0811539106Cheng, Z. J., Wang, L., Sun, W., Zhang, Y., Zhou, C., Su, Y. H., … Zhang, X. S. (2012). Pattern of Auxin and Cytokinin Responses for Shoot Meristem Induction Results from the Regulation of Cytokinin Biosynthesis by AUXIN RESPONSE FACTOR3. Plant Physiology, 161(1), 240-251. doi:10.1104/pp.112.203166Alvarez, J., & Smyth, D. R. (2002). CRABS CLAWandSPATULAGenes Regulate Growth and Pattern Formation during Gynoecium Development inArabidopsis thaliana. International Journal of Plant Sciences, 163(1), 17-41. doi:10.1086/324178Groszmann, M., Bylstra, Y., Lampugnani, E. R., & Smyth, D. R. (2010). Regulation of tissue-specific expression of SPATULA, a bHLH gene involved in carpel development, seedling germination, and lateral organ growth in Arabidopsis. Journal of Experimental Botany, 61(5), 1495-1508. doi:10.1093/jxb/erq015Smyth, D. R., Bowman, J. L., & Meyerowitz, E. M. (1990). Early flower development in Arabidopsis. The Plant Cell, 2(8), 755-767. doi:10.1105/tpc.2.8.755Müller, B., & Sheen, J. (2008). Cytokinin and auxin interaction in root stem-cell specification during early embryogenesis. Nature, 453(7198), 1094-1097. doi:10.1038/nature06943Argyros, R. D., Mathews, D. E., Chiang, Y.-H., Palmer, C. M., Thibault, D. M., Etheridge, N., … Schaller, G. E. (2008). Type B Response Regulators of Arabidopsis Play Key Roles in Cytokinin Signaling and Plant Development. The Plant Cell, 20(8), 2102-2116. doi:10.1105/tpc.108.059584Mason, M. G., Mathews, D. E., Argyros, D. A., Maxwell, B. B., Kieber, J. J., Alonso, J. M., … Schaller, G. E. (2005). Multiple Type-B Response Regulators Mediate Cytokinin Signal Transduction in Arabidopsis. The Plant Cell, 17(11), 3007-3018. doi:10.1105/tpc.105.035451Ishida, K., Yamashino, T., Yokoyama, A., & Mizuno, T. (2008). Three Type-B Response Regulators, ARR1, ARR10 and ARR12, Play Essential but Redundant Roles in Cytokinin Signal Transduction Throughout the Life Cycle of Arabidopsis thaliana. Plant and Cell Physiology, 49(1), 47-57. doi:10.1093/pcp/pcm165Yokoyama, A., Yamashino, T., Amano, Y.-I., Tajima, Y., Imamura, A., Sakakibara, H., & Mizuno, T. (2006). Type-B ARR Transcription Factors, ARR10 and ARR12, are Implicated in Cytokinin-Mediated Regulation of Protoxylem Differentiation in Roots of Arabidopsis thaliana. Plant and Cell Physiology, 48(1), 84-96. doi:10.1093/pcp/pcl040Schuster, C., Gaillochet, C., & Lohmann, J. U. (2015). Arabidopsis HECATE genes function in phytohormone control during gynoecium development. Development, 142(19), 3343-3350. doi:10.1242/dev.120444Toledo-Ortiz, G., Huq, E., & Quail, P. H. (2003). The Arabidopsis Basic/Helix-Loop-Helix Transcription Factor Family. The Plant Cell, 15(8), 1749-1770. doi:10.1105/tpc.013839Reymond, M. C., Brunoud, G., Chauvet, A., Martínez-Garcia, J. F., Martin-Magniette, M.-L., Monéger, F., & Scutt, C. P. (2012). A Light-Regulated Genetic Module Was Recruited to Carpel Development in Arabidopsis following a Structural Change to SPATULA. The Plant Cell, 24(7), 2812-2825. doi:10.1105/tpc.112.097915Ballester, P., Navarrete-Gómez, M., Carbonero, P., Oñate-Sánchez, L., & Ferrándiz, C. (2015). Leaf expansion in Arabidopsis is controlled by a TCP-NGA regulatory module likely conserved in distantly related species. Physiologia Plantarum, 155(1), 21-32. doi:10.1111/ppl.12327Hellens, R., Allan, A., Friel, E., Bolitho, K., Grafton, K., Templeton, M., … Laing, W. (2005). Plant Methods, 1(1), 13. doi:10.1186/1746-4811-1-13Makkena, S., & Lamb, R. S. (2013). The bHLH transcription factor SPATULA regulates root growth by controlling the size of the root meristem. BMC Plant Biology, 13(1), 1. doi:10.1186/1471-2229-13-1Stepanova, A. N., Robertson-Hoyt, J., Yun, J., Benavente, L. M., Xie, D.-Y., Doležal, K., … Alonso, J. M. (2008). TAA1-Mediated Auxin Biosynthesis Is Essential for Hormone Crosstalk and Plant Development. Cell, 133(1), 177-191. doi:10.1016/j.cell.2008.01.047Bhargava, A., Clabaugh, I., To, J. P., Maxwell, B. B., Chiang, Y.-H., Schaller, G. E., … Kieber, J. J. (2013). Identification of Cytokinin-Responsive Genes Using Microarray Meta-Analysis and RNA-Seq in Arabidopsis. Plant Physiology, 162(1), 272-294. doi:10.1104/pp.113.217026Sakai, H., Aoyama, T., & Oka, A. (2000). Arabidopsis ARR1 and ARR2 response regulators operate as transcriptional activators. The Plant Journal, 24(6), 703-711. doi:10.1046/j.1365-313x.2000.00909.xSakai, H. (2001). ARR1, a Transcription Factor for Genes Immediately Responsive to Cytokinins. Science, 294(5546), 1519-1521. doi:10.1126/science.1065201Moubayidin, L., Di Mambro, R., Sozzani, R., Pacifici, E., Salvi, E., Terpstra, I., … Sabatini, S. (2013). Spatial Coordination between Stem Cell Activity and Cell Differentiation in the Root Meristem. Developmental Cell, 26(4), 405-415. doi:10.1016/j.devcel.2013.06.025Benková, E., Michniewicz, M., Sauer, M., Teichmann, T., Seifertová, D., Jürgens, G., & Friml, J. (2003). Local, Efflux-Dependent Auxin Gradients as a Common Module for Plant Organ Formation. Cell, 115(5), 591-602. doi:10.1016/s0092-8674(03)00924-3Okada, K., Ueda, J., Komaki, M. K., Bell, C. J., & Shimura, Y. (1991). Requirement of the Auxin Polar Transport System in Early Stages of Arabidopsis Floral Bud Formation. The Plant Cell, 677-684. doi:10.1105/tpc.3.7.677Blilou, I., Xu, J., Wildwater, M., Willemsen, V., Paponov, I., Friml, J., … Scheres, B. (2005). The PIN auxin efflux facilitator network controls growth and patterning in Arabidopsis roots. Nature, 433(7021), 39-44. doi:10.1038/nature03184Mahonen, A. P. (2006). Cytokinin Signaling and Its Inhibitor AHP6 Regulate Cell Fate During Vascular Development. Science, 311(5757), 94-98. doi:10.1126/science.1118875Besnard, F., Refahi, Y., Morin, V., Marteaux, B., Brunoud, G., Chambrier, P., … Vernoux, T. (2013). Cytokinin signalling inhibitory fields provide robustness to phyllotaxis. Nature, 505(7483), 417-421. doi:10.1038/nature12791Longabaugh, W. J. R., Davidson, E. H., & Bolouri, H. (2005). Computational representation of developmental genetic regulatory networks. Developmental Biology, 283(1), 1-16. doi:10.1016/j.ydbio.2005.04.023Faure, E., Peter, I. S., & Davidson, E. H. (2013). A New Software Package for Predictive Gene Regulatory Network Modeling and Redesign. Journal of Computational Biology, 20(6), 419-423. doi:10.1089/cmb.2012.0297Mangan, S., & Alon, U. (2003). Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences, 100(21), 11980-11985. doi:10.1073/pnas.2133841100Chen, Q., Liu, Y., Maere, S., Lee, E., Van Isterdael, G., Xie, Z., … Vanneste, S. (2015). A coherent transcriptional feed-forward motif model for mediating auxin-sensitive PIN3 expression during lateral root development. Nature Communications, 6(1). doi:10.1038/ncomms9821Qiu, K., Li, Z., Yang, Z., Chen, J., Wu, S., Zhu, X., … Zhou, X. (2015). EIN3 and ORE1 Accelerate Degreening during Ethylene-Mediated Leaf Senescence by Directly Activating Chlorophyll Catabolic Genes in Arabidopsis. PLOS Genetics, 11(7), e1005399. doi:10.1371/journal.pgen.1005399Seaton, D. D., Smith, R. W., Song, Y. H., MacGregor, D. R., Stewart, K., Steel, G., … Halliday, K. J. (2015). Linked circadian outputs control elongation growth and flowering in response to photoperiod and temperature. Molecular Systems Biology, 11(1), 776. doi:10.15252/msb.20145766Roeder, A. H. K., & Yanofsky, M. F. (2006). Fruit Development in Arabidopsis. The Arabidopsis Book, 4, e0075. doi:10.1199/tab.0075Marsch-Martínez, N., Reyes-Olalde, J. I., Ramos-Cruz, D., Lozano-Sotomayor, P., Zúñiga-Mayo, V. M., & de Folter, S. (2012). Hormones talking. Plant Signaling & Behavior, 7(12), 1698-1701. doi:10.4161/psb.22422Balanza, V., Navarrete, M., Trigueros, M., & Ferrandiz, C. (2006). Patterning the female side of Arabidopsis: the importance of hormones. Journal of Experimental Botany, 57(13), 3457-3469. doi:10.1093/jxb/erl188Kamiuchi, Y., Yamamoto, K., Furutani, M., Tasaka, M., & Aida, M. (2014). The CUC1 and CUC2 genes promote carpel margin meristem formation during Arabidopsis gynoecium development. Frontiers in Plant Science, 5. doi:10.3389/fpls.2014.00165Scofield, S., Dewitte, W., & Murray, J. A. H. (2007). The KNOX gene SHOOT MERISTEMLESS is required for the development of reproductive meristematic tissues in Arabidopsis. The Plant Journal, 50(5), 767-781. doi:10.1111/j.1365-313x.2007.03095.xLi, K., Yu, R., Fan, L.-M., Wei, N., Chen, H., & Deng, X. W. (2016). DELLA-mediated PIF degradation contributes to coordination of light and gibberellin signalling in Arabidopsis. Nature Communications, 7(1). doi:10.1038/ncomms11868Oh, E., Zhu, J.-Y., & Wang, Z.-Y. (2012). Interaction between BZR1 and PIF4 integrates brassinosteroid and environmental responses. Nature Cell Biology, 14(8), 802-809. doi:10.1038/ncb2545Sharma, N., Xin, R., Kim, D.-H., Sung, S., Lange, T., & Huq, E. (2016). NO FLOWERING IN SHORT DAY (NFL) is a bHLH transcription factor that promotes flowering specifically under short-day conditions inArabidopsis. Development, 143(4), 682-690. doi:10.1242/dev.128595Varaud, E., Brioudes, F., Szécsi, J., Leroux, J., Brown, S., Perrot-Rechenmann, C., & Bendahmane, M. (2011). AUXIN RESPONSE FACTOR8 Regulates Arabidopsis Petal Growth by Interacting with the bHLH Transcription Factor BIGPETALp. The Plant Cell, 23(3), 973-983. doi:10.1105/tpc.110.081653Savaldi-Goldstein, S., & Chory, J. (2008). Growth coordination and the shoot epidermis. Current Opinion in Plant Biology, 11(1), 42-48. doi:10.1016/j.pbi.2007.10.009Schuster, C., Gaillochet, C., Medzihradszky, A., Busch, W., Daum, G., Krebs, M., … Lohmann, J. U. (2014). A Regulatory Framework for Shoot Stem Cell Co

    Documenting the Recovery of Vascular Services in European Centres Following the Initial COVID-19 Pandemic Peak: Results from a Multicentre Collaborative Study

    Get PDF
    Objective: To document the recovery of vascular services in Europe following the first COVID-19 pandemic peak. Methods: An online structured vascular service survey with repeated data entry between 23 March and 9 August 2020 was carried out. Unit level data were collected using repeated questionnaires addressing modifications to vascular services during the first peak (March – May 2020, “period 1”), and then again between May and June (“period 2”) and June and July 2020 (“period 3”). The duration of each period was similar. From 2 June, as reductions in cases began to be reported, centres were first asked if they were in a region still affected by rising cases, or if they had passed the peak of the first wave. These centres were asked additional questions about adaptations made to their standard pathways to permit elective surgery to resume. Results: The impact of the pandemic continued to be felt well after countries’ first peak was thought to have passed in 2020. Aneurysm screening had not returned to normal in 21.7% of centres. Carotid surgery was still offered on a case by case basis in 33.8% of centres, and only 52.9% of centres had returned to their normal aneurysm threshold for surgery. Half of centres (49.4%) believed their management of lower limb ischaemia continued to be negatively affected by the pandemic. Reduced operating theatre capacity continued in 45.5% of centres. Twenty per cent of responding centres documented a backlog of at least 20 aortic repairs. At least one negative swab and 14 days of isolation were the most common strategies used for permitting safe elective surgery to recommence. Conclusion: Centres reported a broad return of services approaching pre-pandemic “normal” by July 2020. Many introduced protocols to manage peri-operative COVID-19 risk. Backlogs in cases were reported for all major vascular surgeries

    Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

    Get PDF
    Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

    Single-dose administration and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine: a pooled analysis of four randomised trials.

    Get PDF
    BACKGROUND: The ChAdOx1 nCoV-19 (AZD1222) vaccine has been approved for emergency use by the UK regulatory authority, Medicines and Healthcare products Regulatory Agency, with a regimen of two standard doses given with an interval of 4-12 weeks. The planned roll-out in the UK will involve vaccinating people in high-risk categories with their first dose immediately, and delivering the second dose 12 weeks later. Here, we provide both a further prespecified pooled analysis of trials of ChAdOx1 nCoV-19 and exploratory analyses of the impact on immunogenicity and efficacy of extending the interval between priming and booster doses. In addition, we show the immunogenicity and protection afforded by the first dose, before a booster dose has been offered. METHODS: We present data from three single-blind randomised controlled trials-one phase 1/2 study in the UK (COV001), one phase 2/3 study in the UK (COV002), and a phase 3 study in Brazil (COV003)-and one double-blind phase 1/2 study in South Africa (COV005). As previously described, individuals 18 years and older were randomly assigned 1:1 to receive two standard doses of ChAdOx1 nCoV-19 (5 × 1010 viral particles) or a control vaccine or saline placebo. In the UK trial, a subset of participants received a lower dose (2·2 × 1010 viral particles) of the ChAdOx1 nCoV-19 for the first dose. The primary outcome was virologically confirmed symptomatic COVID-19 disease, defined as a nucleic acid amplification test (NAAT)-positive swab combined with at least one qualifying symptom (fever ≥37·8°C, cough, shortness of breath, or anosmia or ageusia) more than 14 days after the second dose. Secondary efficacy analyses included cases occuring at least 22 days after the first dose. Antibody responses measured by immunoassay and by pseudovirus neutralisation were exploratory outcomes. All cases of COVID-19 with a NAAT-positive swab were adjudicated for inclusion in the analysis by a masked independent endpoint review committee. The primary analysis included all participants who were SARS-CoV-2 N protein seronegative at baseline, had had at least 14 days of follow-up after the second dose, and had no evidence of previous SARS-CoV-2 infection from NAAT swabs. Safety was assessed in all participants who received at least one dose. The four trials are registered at ISRCTN89951424 (COV003) and ClinicalTrials.gov, NCT04324606 (COV001), NCT04400838 (COV002), and NCT04444674 (COV005). FINDINGS: Between April 23 and Dec 6, 2020, 24 422 participants were recruited and vaccinated across the four studies, of whom 17 178 were included in the primary analysis (8597 receiving ChAdOx1 nCoV-19 and 8581 receiving control vaccine). The data cutoff for these analyses was Dec 7, 2020. 332 NAAT-positive infections met the primary endpoint of symptomatic infection more than 14 days after the second dose. Overall vaccine efficacy more than 14 days after the second dose was 66·7% (95% CI 57·4-74·0), with 84 (1·0%) cases in the 8597 participants in the ChAdOx1 nCoV-19 group and 248 (2·9%) in the 8581 participants in the control group. There were no hospital admissions for COVID-19 in the ChAdOx1 nCoV-19 group after the initial 21-day exclusion period, and 15 in the control group. 108 (0·9%) of 12 282 participants in the ChAdOx1 nCoV-19 group and 127 (1·1%) of 11 962 participants in the control group had serious adverse events. There were seven deaths considered unrelated to vaccination (two in the ChAdOx1 nCov-19 group and five in the control group), including one COVID-19-related death in one participant in the control group. Exploratory analyses showed that vaccine efficacy after a single standard dose of vaccine from day 22 to day 90 after vaccination was 76·0% (59·3-85·9). Our modelling analysis indicated that protection did not wane during this initial 3-month period. Similarly, antibody levels were maintained during this period with minimal waning by day 90 (geometric mean ratio [GMR] 0·66 [95% CI 0·59-0·74]). In the participants who received two standard doses, after the second dose, efficacy was higher in those with a longer prime-boost interval (vaccine efficacy 81·3% [95% CI 60·3-91·2] at ≥12 weeks) than in those with a short interval (vaccine efficacy 55·1% [33·0-69·9] at <6 weeks). These observations are supported by immunogenicity data that showed binding antibody responses more than two-fold higher after an interval of 12 or more weeks compared with an interval of less than 6 weeks in those who were aged 18-55 years (GMR 2·32 [2·01-2·68]). INTERPRETATION: The results of this primary analysis of two doses of ChAdOx1 nCoV-19 were consistent with those seen in the interim analysis of the trials and confirm that the vaccine is efficacious, with results varying by dose interval in exploratory analyses. A 3-month dose interval might have advantages over a programme with a short dose interval for roll-out of a pandemic vaccine to protect the largest number of individuals in the population as early as possible when supplies are scarce, while also improving protection after receiving a second dose. FUNDING: UK Research and Innovation, National Institutes of Health Research (NIHR), The Coalition for Epidemic Preparedness Innovations, the Bill & Melinda Gates Foundation, the Lemann Foundation, Rede D'Or, the Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

    Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK.

    Get PDF
    BACKGROUND: A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. METHODS: This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. FINDINGS: Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0-75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4-97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8-80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3-4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. INTERPRETATION: ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. FUNDING: UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D'Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

    Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

    Get PDF
    Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials

    Malaria: Paving the way to developing peptide-based vaccines against invasion in infectious diseases.

    No full text
    Malaria remains a large-scale public health problem, killing more than 400,000 people and infecting up to 230 million worldwide, every year. Unfortunately, despite numerous efforts and research concerning vaccine development, results to date have been low and/or strain-specific. This work describes a strategy involving Plasmodium falciparum Duffy binding-like (DBL) and reticulocyte-binding protein homologue (RH) family-derived minimum functional peptides, netMHCIIpan3.2 parental and modified peptides' in silico binding prediction and modeling some Aotus major histocompatibility class II (MHCII) molecules based on known human molecules' structure to understand their differences. These are used to explain peptides' immunological behaviour when used as vaccine components in the Aotus model. Despite the great similarity between human and Aotus immune system molecules, around 50% of Aotus allele molecules lack a counterpart in the human immune system which could lead to an Aotus-specific vaccine. It was also confirmed that functional Plasmodium falciparum' conserved proteins are immunologically silent (in both the animal model and in-silico prediction); they must therefore be modified to elicit an appropriate immune response. Some peptides studied here had the desired behaviour and can thus be considered components of a fully-protective antimalarial vaccine

    Safety and immunogenicity of ChAdOx1 nCoV-19 vaccine administered in a prime-boost regimen in young and old adults (COV002): a single-blind, randomised, controlled, phase 2/3 trial

    Get PDF
    Background Older adults (aged ≥70 years) are at increased risk of severe disease and death if they develop COVID-19 and are therefore a priority for immunisation should an efficacious vaccine be developed. Immunogenicity of vaccines is often worse in older adults as a result of immunosenescence. We have reported the immunogenicity of a novel chimpanzee adenovirus-vectored vaccine, ChAdOx1 nCoV-19 (AZD1222), in young adults, and now describe the safety and immunogenicity of this vaccine in a wider range of participants, including adults aged 70 years and older. Methods In this report of the phase 2 component of a single-blind, randomised, controlled, phase 2/3 trial (COV002), healthy adults aged 18 years and older were enrolled at two UK clinical research facilities, in an age-escalation manner, into 18–55 years, 56–69 years, and 70 years and older immunogenicity subgroups. Participants were eligible if they did not have severe or uncontrolled medical comorbidities or a high frailty score (if aged ≥65 years). First, participants were recruited to a low-dose cohort, and within each age group, participants were randomly assigned to receive either intramuscular ChAdOx1 nCoV-19 (2·2 × 1010 virus particles) or a control vaccine, MenACWY, using block randomisation and stratified by age and dose group and study site, using the following ratios: in the 18–55 years group, 1:1 to either two doses of ChAdOx1 nCoV-19 or two doses of MenACWY; in the 56–69 years group, 3:1:3:1 to one dose of ChAdOx1 nCoV-19, one dose of MenACWY, two doses of ChAdOx1 nCoV-19, or two doses of MenACWY; and in the 70 years and older, 5:1:5:1 to one dose of ChAdOx1 nCoV-19, one dose of MenACWY, two doses of ChAdOx1 nCoV-19, or two doses of MenACWY. Prime-booster regimens were given 28 days apart. Participants were then recruited to the standard-dose cohort (3·5–6·5 × 1010 virus particles of ChAdOx1 nCoV-19) and the same randomisation procedures were followed, except the 18–55 years group was assigned in a 5:1 ratio to two doses of ChAdOx1 nCoV-19 or two doses of MenACWY. Participants and investigators, but not staff administering the vaccine, were masked to vaccine allocation. The specific objectives of this report were to assess the safety and humoral and cellular immunogenicity of a single-dose and two-dose schedule in adults older than 55 years. Humoral responses at baseline and after each vaccination until 1 year after the booster were assessed using an in-house standardised ELISA, a multiplex immunoassay, and a live severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) microneutralisation assay (MNA80). Cellular responses were assessed using an ex-vivo IFN-γ enzyme-linked immunospot assay. The coprimary outcomes of the trial were efficacy, as measured by the number of cases of symptomatic, virologically confirmed COVID-19, and safety, as measured by the occurrence of serious adverse events. Analyses were by group allocation in participants who received the vaccine. Here, we report the preliminary findings on safety, reactogenicity, and cellular and humoral immune responses. This study is ongoing and is registered with ClinicalTrials.gov, NCT04400838, and ISRCTN, 15281137. Findings Between May 30 and Aug 8, 2020, 560 participants were enrolled: 160 aged 18–55 years (100 assigned to ChAdOx1 nCoV-19, 60 assigned to MenACWY), 160 aged 56–69 years (120 assigned to ChAdOx1 nCoV-19: 40 assigned to MenACWY), and 240 aged 70 years and older (200 assigned to ChAdOx1 nCoV-19: 40 assigned to MenACWY). Seven participants did not receive the boost dose of their assigned two-dose regimen, one participant received the incorrect vaccine, and three were excluded from immunogenicity analyses due to incorrectly labelled samples. 280 (50%) of 552 analysable participants were female. Local and systemic reactions were more common in participants given ChAdOx1 nCoV-19 than in those given the control vaccine, and similar in nature to those previously reported (injection-site pain, feeling feverish, muscle ache, headache), but were less common in older adults (aged ≥56 years) than younger adults. In those receiving two standard doses of ChAdOx1 nCoV-19, after the prime vaccination local reactions were reported in 43 (88%) of 49 participants in the 18–55 years group, 22 (73%) of 30 in the 56–69 years group, and 30 (61%) of 49 in the 70 years and older group, and systemic reactions in 42 (86%) participants in the 18–55 years group, 23 (77%) in the 56–69 years group, and 32 (65%) in the 70 years and older group. As of Oct 26, 2020, 13 serious adverse events occurred during the study period, none of which were considered to be related to either study vaccine. In participants who received two doses of vaccine, median anti-spike SARS-CoV-2 IgG responses 28 days after the boost dose were similar across the three age cohorts (standard-dose groups: 18–55 years, 20 713 arbitrary units [AU]/mL [IQR 13 898–33 550], n=39; 56–69 years, 16 170 AU/mL [10 233–40 353], n=26; and ≥70 years 17 561 AU/mL [9705–37 796], n=47; p=0·68). Neutralising antibody titres after a boost dose were similar across all age groups (median MNA80 at day 42 in the standard-dose groups: 18–55 years, 193 [IQR 113–238], n=39; 56–69 years, 144 [119–347], n=20; and ≥70 years, 161 [73–323], n=47; p=0·40). By 14 days after the boost dose, 208 (>99%) of 209 boosted participants had neutralising antibody responses. T-cell responses peaked at day 14 after a single standard dose of ChAdOx1 nCoV-19 (18–55 years: median 1187 spot-forming cells [SFCs] per million peripheral blood mononuclear cells [IQR 841–2428], n=24; 56–69 years: 797 SFCs [383–1817], n=29; and ≥70 years: 977 SFCs [458–1914], n=48). Interpretation ChAdOx1 nCoV-19 appears to be better tolerated in older adults than in younger adults and has similar immunogenicity across all age groups after a boost dose. Further assessment of the efficacy of this vaccine is warranted in all age groups and individuals with comorbidities. Funding UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midlands NIHR Clinical Research Network, and AstraZeneca
    corecore