Laboratoire de Biologie et Modélisation de la Cellule

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, but the diversity of their subtype sets impedes their clinical application. OBJECTIVE: To achieve an international consensus on MIBC molecular subtypes that reconciles the published classification schemes. DESIGN, SETTING, AND PARTICIPANTS: We used 1750 MIBC transcriptomic profiles from 16 published datasets and two additional cohorts. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed a network-based analysis of six independent MIBC classification systems to identify a consensus set of molecular classes. Association with survival was assessed using multivariable Cox models. RESULTS AND LIMITATIONS: We report the results of an international effort to reach a consensus on MIBC molecular subtypes. We identified a consensus set of six molecular classes: luminal papillary (24%), luminal nonspecified (8%), luminal unstable (15%), stroma-rich (15%), basal/squamous (35%), and neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics, including outcomes. We provide a single-sample classifier that assigns a consensus class label to a tumor sample's transcriptome. Limitations of the work are retrospective clinical data collection and a lack of complete information regarding patient treatment. CONCLUSIONS: This consensus system offers a robust framework that will enable testing and validation of predictive biomarkers in future prospective clinical trials. PATIENT SUMMARY: Bladder cancers are heterogeneous at the molecular level, and scientists have proposed several classifications into sets of molecular classes. While these classifications may be useful to stratify patients for prognosis or response to treatment, a consensus classification would facilitate the clinical use of molecular classes. Conducted by multidisciplinary expert teams in the field, this study proposes such a consensus and provides a tool for applying the consensus classification in the clinical setting.

The Rho signaling pathway regulates the cytoskeleton and motility and plays an important role in neuronal growth inhibition. Here we demonstrate that inactivation of Rho or its downstream target Rho-associated kinase (ROK) stimulated neurite growth in primary cells of cortical neurons plated on myelin or chondroitin sulfate proteoglycan substrates. Furthermore, treatment either with C3 transferase (C3) to inactivate Rho or with Y27632 to inhibit ROK was sufficient to stimulate axon regeneration and recovery of hindlimb function after spinal cord injury (SCI) in adult mice. Injured mice were treated with a single injection of Rho or Rho-associated kinase inhibitors delivered in a protein adhesive at the lesion site. Treated animals showed long-distance regeneration of anterogradely labeled corticospinal axons and increased levels of GAP-43 mRNA in the motor cortex. Behaviorally, inactivation of Rho pathway induced rapid recovery of locomotion and progressive recuperation of forelimb-hindlimb coordination. These findings provide evidence that the Rho signaling pathway is a potential target for therapeutic interventions after spinal cord injury.

Reverse transcription-polymerase chain reaction (RT-PCR) approaches have been used in a large proportion of transcriptome analyses published to date. The accuracy of the results obtained by this method strongly depends on accurate transcript normalization using stably expressed genes, known as references. Statistical algorithms have been developed recently to help validate reference genes, and most studies of gene expression in mammals, yeast and bacteria now include such validation. Surprisingly, this important approach is under-utilized in plant studies, where putative housekeeping genes tend to be used as references without any appropriate validation. Using quantitative RT-PCR, the expression stability of several genes commonly used as references was tested in various tissues of Arabidopsis thaliana and hybrid aspen (Populus tremula x Populus tremuloides). It was found that the expression of most of these genes was unstable, indicating that their use as references is inappropriate. The major impact of the use of such inappropriate references on the results obtained by RT-PCR is demonstrated in this study. Using aspen as a model, evidence is presented indicating that no gene can act as a universal reference, implying the need for a systematic validation of reference genes. For the first time, the extent to which the lack of a systematic validation of reference genes is a stumbling block to the reliability of results obtained by RT-PCR in plants is clearly shown.

Despite its critical sociobiological importance, the brain processing of visual sexual stimuli has not been characterized precisely in human beings. We used Positron Emission Tomography (PET) to investigate responses of regional cerebral blood flow (rCBF) in nine healthy males presented with visual sexual stimuli of graded intensity. Statistical Parametric Mapping was used to locate brain regions whose activation was associated with the presentation of the sexual stimuli and was correlated with markers of sexual arousal. The claustrum, a region whose function had been unclear, displayed one of the highest activations. Additionally, activations were recorded in paralimbic areas (anterior cingulate gyrus, orbito-frontal cortex), in the striatum (head of caudate nucleus, putamen), and in the posterior hypothalamus. By contrast, decreased rCBF was observed in several temporal areas. Based on these results, we propose a model of the brain processes mediating the cognitive, emotional, motivational, and autonomic components of human male sexual arousal.

In the yeast Saccharomyces cerevisiae, telomere elongation is negatively regulated by the telomere repeat-binding protein Rap1p, such that a narrow length distribution of telomere repeat tracts is observed. This length regulation was shown to function independently of the orientation of the telomere repeats. The number of repeats at an individual telomere was reduced when hybrid proteins containing the Rap1p carboxyl terminus were targeted there by a heterologous DNA-binding domain. The extent of this telomere tract shortening was proportional to the number of targeted molecules, consistent with a feedback mechanism of telomere length regulation that can discriminate the precise number of Rap1p molecules bound to the chromosome end.

The recent development of gene transfer methods for almost all eukaryotes has revealed that transgenes can undergo silencing after integration in the genome. Host genes can also be silenced as a consequence of the presence of a homologous transgene, thus limiting the potential application of genetic transformation. Despite this limitation, transgene-induced gene silencing events were considered originally as anecdotal phenomena. However, as more and more similarities were found between transgene-induced gene silencing and natural epigenetic phenomena, considerable interest has been devoted to this subject (for recent reviews see Depicker & Van Montagu 1997;Stam et al. 1997b ). Epigenetics is commonly defined as ‘the study of mitotically and/or meiotically heritable changes in the function of a gene that cannot be explained by changes in its DNA sequence’ ( Russo et al. 1996 ). For a long time, DNA was considered as the only target for epigenetic modifications. Epigenetic changes corresponding to changes in chromatin structure and affecting transcription have been reported in almost all eukaryotes: yeast, fungi, Drosophila, plants and mammals ( Dorer 1997;Foss & Selker 1991;Rossignol & Faugeron 1994;Ye 1996). However, recent studies have suggested that, besides DNA, other molecules can be modified in a manner that resembles epigenetic DNA changes. First, it was shown that proteins can be converted into molecules of aberrant conformation called prions in yeast and mammals ( Lacroute 1971;Prusiner 1982). More recently, the involvement of RNA was hypothesized to explain post-transcriptional silencing in plants, fungi and nematodes ( Cogoni et al. 1996 ;Fire et al. 1998 ;Napoli et al. 1990 ). This review will focus on transgene-induced silencing phenomena in plants. The number of copies of a transgene that integrate into the genome of a transformed plant and the position of the integration site cannot be predicted, regardless of whether Agrobacterium-mediated transfer or direct gene transfer are used. Therefore, one or multiple intact or rearranged copies can integrate at one or multiple unlinked loci. Cis-inactivation will be used to refer to silencing events that affect the expression of transgenes integrated at a single locus, irrespective of the copy number, while trans-inactivation will be used to define the silencing effect of one locus on another. As defined by Stam et al. (1997b) , transcriptional gene silencing will be referred to as TGS, and post-transcriptional gene silencing as PTGS. Transgenes can undergo TGS in cis when one or multiple copies integrate at a locus located in or next to silent hypermethylated genomic sequences. This case closely resembles position effect variegation (PEV) in Drosophila which occurs when a euchromatic gene is moved next to heterochromatin by chromosomal rearrangement. Heterochromatin can then spread into the gene and affect its expression in a stochastic, cell-autonomous and clonal manner, thus leading to variegation (for review see Karpen 1994). Methylation in plants may spread like heterochromatin in Drosophila from the adjacent sequences into the transgene, thus leading to silencing ( Pröls & Meyer 1992). Transgenes can also undergo TGS in cis when multiple copies become methylated although they integrate at a hypomethylated locus. This case resembles local heterochromatin formation and silencing in Drosophila induced by the extension of transgene repeats (for review see Dorer 1997). Such repeat-induced gene silencing in plants, defined as RIGS by Assaad et al. (1993) , correlates with increased methylation and increased resistance to both DNase I and microccocal nuclease in transgenic Arabidopsis plants, indicating that RIGS correlates with changes in chromatin configuration ( Ye & Signer 1996). Occasionally, transgenes inserted as single copies at a hypomethylated locus can undergo TGS ( Meyer & Heidmann 1994;Meyer et al. 1992 ). Silencing was observed when a transgene derived from a monocotyledonous plant was introduced into a dicotyledonous plant, whereas it was not observed with the corresponding dicot gene ( Elomaa et al. 1995 ), suggesting that a strong discrepancy between the DNA composition of the transgene and that of the surrounding genomic sequences can be recognized by the cellular machinery, leading to the specific methylation and silencing of foreign sequences. In this case also, TGS correlated with increased methylation and increased resistance to both DNase I and microccocal nuclease ( van Blokland et al. 1997 ), thus indicating that hypermethylation and chromatin condensation are general characteristics associated with transcriptional silencing. TGS can result from the uni-directional effect of one transgene on another. An active copy of a transgene can become silent and methylated when brought by crossing into the presence of a silenced homologous copy, and can acquire the capacity to inactivate another copies in subsequent crosses ( Meyer et al. 1993 ). This phenomenon resembles ‘paramutation’, a natural epigenetic phenomenon affecting host genes in the absence of transgenes. Paramutator (inactive) alleles inhibit the expression of paramutable (active) alleles which themselves become paramutators ( Brink 1956). Paramutation indicates that homologous chromosomes can exchange information in somatic cells. The mechanism invoked for paramutation involves DNA–DNA pairing and transmission of the chromatin structure from the silent copy to the active copy, as shown in Drosophila where PEV can be transmitted in a dominant manner from the rearranged silent chromosome to the wild-type active chromosome (for review see Karpen 1994). Active transgenes can also become silent and methylated when brought into the presence of an unlinked silenced homologous transgene ( Matzke et al. 1989 ;Vaucheret 1993). This phenomenon can be defined as ‘ectopic trans-inactivation’. It differs from paramutation because the target-silenced transgenes do not acquire the capacity to inactivate in trans other unlinked transgenes ( Park et al. 1996 ). It can affect any transgene that is expressed under the control of the same promoter, irrespective of the coding sequence being expressed ( Matzke et al. 1994 ;Vaucheret 1993). This specificity indicates that the promoter of the transgene is the target for this form of transcriptional silencing ( Thierry & Vaucheret 1996). Deletion analysis indicated that 90 bp of homology between a silencing locus and the promoter of a target transgene is sufficient for directing silencing and methylation ( Vaucheret 1993). Two silencing loci showing transcriptional silencing of unlinked promoter–homologous transgenes irrespective of their positions within the genome have been identified ( Matzke et al. 1994 ;Vaucheret 1993). These two loci consist of multiple and rearranged copies of the transgene and are each located on or near a telomere ( Park et al. 1996 ). These data suggest that the ability to trigger ectopic trans-inactivation may depend on the ability of the silencing loci to interact with any other position of the genome by direct DNA–DNA pairing. Alternatively, it could involve the production of diffusible RNA by the silencing locus that leads to heritable silencing and methylation of homologous target loci via an RNA–DNA interaction ( Park et al. 1996 ;Wassenegger & Pélissier 1998). However, since one of these two silencing loci was shown to be unable to silence the expression of extra-chromosomal copies of a target transgene ( Vaucheret 1994), the transmission of silencing is more likely to occur through DNA–DNA pairing between stably integrated homologous copies. When the silenced target transgenes are separated from a silencing locus by segregation, they reactivate more or less quickly, i.e. during a period that ranges between immediately after segregation and two or three generations following the segregation. The fact that target transgenes which remain silent in the absence of the silencing locus are still methylated ( Park et al. 1996 ;Vaucheret 1994) indicates that methylation is probably involved in the maintenance of the silent state. Target transgenes driven by a 35S promoter devoid of CG and CNG methylation acceptor sites were as susceptible to silencing in trans as those driven by a wild-type promoter, indicating that methylation at CG and CNG sites is not a prerequisite for silencing. However, using this promoter, silencing was immediately relieved in the absence of the trans-silencer, thus further supporting the hypothesis that CG/CNG methylation is essential for the maintenance of silencing ( Diéguez et al. 1998 ). Transgene silencing is defined as occurring at the post-transcriptional level when RNA does not accumulate even though transcription occurs. As opposed to TGS, which is meiotically heritable ( Assaad et al. 1993 ;Matzke et al. 1989 ;Mittelsten Scheid et al. 1998 ;Park et al. 1996 ;Vaucheret 1993), PTGS is reset (i.e. affected genes are reactivated) after meiosis ( Balandin & Castresana 1997;Dehio & Schell 1994;Dorlhac de Borne et al. 1994 ;Hart et al. 1992 ;Vaucheret et al. 1995 ). However, in affected lines, PTGS recurs every generation at some time during plant development. Up until now, post-transcriptional cis-inactivation has been observed when foreign (bacterial) transgenes (uidA, npt, rolB) were introduced under the control of the strong viral 35S promoter ( Dehio & Schell 1994;Elmayan & Vaucheret 1996;English et al. 1996 ;Ingelbrecht et al. 1994 ). In all cases, PTGS occurred more efficiently (or exclusively) in haploids and homozygous plants as compared with hemizygous plants, suggesting a transgene dose effect. PTGS was observed in a larger proportion of transformants using a 35S promoter with a double enhancer as compared to the classical 35S promoter ( Elmayan & Vaucheret 1996;English et al. 1996 ). These results initially suggested that PTGS was due to the over-production of transgene RNA above a putative threshold level that triggers the irreversible degradation of RNA ( Dehio & Schell 1994). However, the level of transgene transcription was not always found to be significantly higher in silenced lines as compared to non-silenced lines ( English et al. 1996 ), thus suggesting that some other parameters may also play a role in the triggering of PTGS. The presence of repeats at the transgene locus of the silenced lines was proposed to play such a role ( English et al. 1996 ). Multiple models of PTGS have been proposed, considering mainly the roles of RNA thresholds and DNA repeats (reviewed by Baulcombe 1996). These models may not be exclusive if we consider that only a particular subpopulation of transgene RNA is important for the triggering of PTGS. Transgene RNA could be specifically degraded if tagged by specific molecules. To account for sequence-specific RNA degradation, these tag molecules are hypothesized to be small complementary RNA (cRNA). They could be synthesized by a plant RNA dependent RNA polymerase (RdRp) using transgene RNA as template ( Dougherty & Parks 1995). Alternatively, they could be internal fragments of transgene RNA produced by pairing-cleavage cycles between aberrant poly (A)– RNA and normal transgene RNA as a result of internal sequence complementarity ( Metzlaff et al. 1997 ). These cRNA could interact with mRNA, thus forming duplexes that behave as targets for cellular enzymes like double-strand RNA-specific RNase. Not all transgenic lines undergo PTGS. Therefore, the transgene loci that trigger PTGS may have some specific characteristics. First, the presence of repeats could allow DNA–DNA interactions and subsequent changes in methylation and/or chromatin structure that impedes correct transcription and leads to the production of malformed (aberrant) RNA that are a better template for RdRp than mRNA. Second, the utilisation of a very strong promoter to drive the transgene may contribute to elevate the amount of malformed (aberrant) RNA produced spontaneously by RNA polymerase errors up to a threshold that triggers PTGS. These aberrant RNA and/or the high amount of mRNA accumulated in the cytoplasm due to the use of a strong promoter may also trigger methylation of the coding sequence of the corresponding transgene by a feedback mechanism ( Wassenegger et al. 1994 ). Feedback methylated transgenes may therefore produce aberrant RNA as might do methylated transgene repeats. Therefore, either the use of a strong promoter or the presence of transgene repeats may lead to post-transcriptional silencing as a consequence of the production of aberrant RNA and subsequently of cRNA. PTGS was originally discovered as the reciprocal and co-ordinated silencing of transgenes and homologous host genes, and is usually referred to as ‘co-suppression’ ( Napoli et al. 1990 ). Since that time, a number of transgenes encoding part or the entire transcribed sequence of a host gene have been shown to trigger co-suppression of homologous host genes (for recent reviews see Depicker & Van Montagu 1997;Stam et al. 1997b ). Co-suppression occurs more efficiently (or exclusively) in haploids and homozygous plants as compared with hemizygous plants, suggesting a transgene dose effect ( de Carvalho et al. 1992 ;Dorlhac de Borne et al. 1994 ;Hart et al. 1992 ). As shown by a large scale analysis of petunia plants transformed with a chalcone synthase transgene, the efficiency of co-suppression correlates with the strength of the promoter driving the transgene, suggesting a transgene product dose effect rather than a transgene dose effect ( Que et al. 1997 ). Co-suppression of nitrate reductase is inhibited when the transgenes homologous to the host genes are themselves silenced at the transcriptional level, thus indicating that transgene transcription is required ( Vaucheret et al. 1997 ). In addition, the efficiency of co-suppression is reduced or delayed when host genes are not expressed ( Dorlhac de Borne et al. 1994 ;Smith et al. 1990 ), or when transgenes are introduced into mutants lacking a functional host gene ( Vaucheret et al. 1997 ). These results suggest that co-suppression cannot be considered as the unidirectional silencing effect of transgenes onto host genes, but rather as a reciprocal and synergistic phenomenon where host genes and transgenes can co-operate to produce aberrant RNA and/or cRNA above the threshold level that activates the RNA degradation of the co-suppression events result from the of expressed and data PTGS of host genes by transcribed or transgenes have been reported ( van Blokland et al. 1994 ). These data can be with the aberrant hypothesis above if we consider that these transgene loci always consist of transgene repeats ( Stam et al. ). Therefore, as proposed DNA–DNA pairing could play a role in the of production of aberrant between transgene repeats or between the transgene repeats and the homologous host genes could therefore trigger changes in methylation or chromatin leading to the production of aberrant RNA either by a transcribed transgene or by the host genes only when the transgene does not a When the transgene which PTGS part of the genome of a plant RNA silenced transgenic plants become (reviewed by Baulcombe In some cases, resistance can be after a of a phenomenon called ( et al. 1993 ). In this the silent is not in the transgenic and only the by the triggers transgene silencing and It is that transgene transcription and both contribute to the level of of RNA that triggers PTGS. a transgene inserted within their genome to transgenic plants that PTGS of this transgene ( English et al. 1996 ). These results are with a in which viral RNA and transgene RNA the same sequence are tagged by the same cRNA and are subsequently degraded by the RNA degradation a transgene inserted within their genome in transgenic plants that do not PTGS of this However, the transgene may become silenced after a phenomenon called gene ( et al. 1998 ). PTGS as a ( et al. 1994 ;Hart et al. 1992 et al. 1996 ). and in the of the silencing during plant development suggest the of a silencing through the Co-suppression of nitrate reductase and host genes and transgenes in lead to particular or with the of the corresponding that can be the Co-suppression as or on one and then to the with silencing efficiency ( et al. 1994 et al. 1996 ). Since these of are found in all transgenic lines silenced for a this that a sequence-specific involved in the control of PTGS through the plant in a specific the transmission of a PTGS was in Silencing was transmitted with efficiency from silenced to target the corresponding transgene ( et al. 1997 ), indicating the of a The transmission of co-suppression also occurred when silenced and non-silenced target were separated by up to of of a wild-type These results therefore the hypothesis that a the of de post-transcriptional silencing long within the plant, a phenomenon called silencing or ( et al. 1997 ). were when PTGS was after of one of a transgenic plant a non-silenced transgene by an the same transgene ( & Baulcombe 1997). using nitrate reductase silenced and a of transgenic and revealed for the of RNA degradation, and RNA degradation occurred in both transgenic mRNA due to the presence of a transgene and host mRNA due to However, RNA degradation not occur in wild-type thus indicating that mRNA above the level of wild-type plants rather than the presence of a transgene in the is required for the RNA degradation of co-suppression ( & Vaucheret 1998). When silenced were from the silenced and onto wild-type plants, silencing was not in plants and in transgenic lines that are not to trigger co-suppression silencing was in transgenic lines that are to trigger co-suppression thus indicating that only the transgene loci that are to co-suppression can also a silent ( silencing silencing. transgene loci are to produce a that sequence-specific RNA degradation in the This to through and at long through the then triggering degradation of homologous this silencing is it is likely that it from the it is a direct product of the transgene (for an aberrant or a product (for a and whether such RNA through the plant or with a host to be The absence of maintenance of silencing in plants that undergo RNA degradation that the silencing is not of RNA degradation It also indicates that the transgene locus as a to co-suppression in each that the In the absence of a transgene locus, a production of the silencing by the silenced is required to RNA degradation in the This phenomenon could therefore be as silencing because it is not when the silenced are in a transgene locus, the could an epigenetic of the transgene locus that the of the production of both the RNA degradation and the silencing thus leading to silencing in the a silencing is involved in all PTGS events reported to be In were produced by transgenes that control As proposed by co-suppression may of plant to of This hypothesis is in with the fact that wild-type onto transgenic silenced do not undergo whereas which accumulate the host mRNA above the level of the wild-type do undergo silencing ( & Vaucheret 1998). Therefore, both a sequence-specific silencing and a high amount of target mRNA (or a high of to be required to a silent state. Dougherty et al. not the transmission of resistance in plants a viral thus suggesting that and/or is not a general However, this result be in the of recent studies showing that PTGS of et al. reported that PTGS of nitrate reductase or transgenes in of and Arabidopsis plants, suggesting that the spread of has sequence to the or may inhibit the spread of the PTGS genes are likely to be involved in both TGS and PTGS. In Drosophila, of genes PEV has the of more than loci (for review see Karpen 1994). These loci to two that PEV and that of the corresponding genes have been of the are involved in the formation of heterochromatin while genes of the transcription in which PTGS is have been in These called (for define three genetic loci ( Cogoni & 1997). in the control of TGS have been in Arabidopsis and are called mutants (for These mutants which are to reactivate a silent transgene ( Scheid et al. 1998 ). These mutants also a in the methylation of sequences of the as do methylation mutants called in DNA ( et al. 1993 ). is to The function by the gene is It is that it a because the plants a normal plants lacking were using an transgene the gene TGS was not in such plants ( Scheid et al. 1998 ). Therefore, these results that in the between TGS and affected in PTGS have also been in Arabidopsis These mutants to two The to mutants called (for enhancer of gene in which PTGS of a transgene is These are and define two genetic loci ( Dehio & Schell 1994). The to mutants called (for of gene which PTGS of a transgene as as post-transcriptional co-suppression of nitrate reductase host genes and transgenes. These are and define two genetic loci ( Elmayan et al. 1998 ), which probably to loci in and are not to reactivate a silent transgene, and do not trigger a in the methylation of sequences of the genome. Therefore, genes are to specifically control PTGS. The of and genes will the of the of TGS and PTGS. gene silencing in plants can occur at the transcriptional or post-transcriptional TGS occurs mainly when multiple repeats of a transgene are inserted in the genome of transgenic plants. It correlates with condensation of chromatin and with The transfer of methylation and silencing from one locus to another indicates that of the genome and exchange This transfer may occur through direct DNA–DNA pairing. Alternatively, it could involve the production of diffusible RNA by one locus, leading to of homologous targets via an RNA–DNA interaction ( Park et al. 1996 ;Wassenegger & Pélissier 1998). Epigenetic of sequences may be an important because it might or between transgene repeats may be for the between induced methylated and DNA molecules may not be thus This hypothesis may not only to the genome of transformants transgene but also to wild-type plants in which an in the number of can the of the genome if they can with each Such a to in other In the fungi and DNA that the are very silenced and In addition, in methylation of is by a very high of in a phenomenon called repeat-induced or ( et al. 1989 ). Such methylation and are proposed to also occur in to the homology between repeats and to efficiently ( et al. 1992 ). In plants, for such a has been observed ( Scheid et al. 1994 ), suggesting that may be sufficient to the genome transgene-induced PTGS occurs mainly when transgene RNA is produced at high under the control of the 35S promoter of the it has been shown that and initially when by from which they by of This phenomenon correlates with the absence of of and 35S RNA although their of transcription remain ( et al. 1998 et al. 1997 ). plants spontaneously from by the ( et al. 1997 ). These results suggest that plants can in a post-transcriptional Therefore, of the of PTGS of transgenes may result from the of high of RNA transcription and from the subsequent degradation of this RNA by the cellular involved in post-transcriptional However, since or transcribed transgenes can lead to post-transcriptional silencing of homologous host genes, some molecules (for the aberrant RNA and/or cRNA defined involved in the of events leading to RNA degradation might be produced in an manner, for by and subsequently methylated that diffusible can the plant to trigger silencing in the other ( et al. 1997 ), as aberrant RNA and/or cRNA as diffusible of silencing and whether they can or with to be The similarities between transgene-induced PTGS and in plants ( et al. 1997 ), and the between the spread of and the spread of PTGS ( et al. 1998 ), the hypothesis that transgene-induced PTGS from a natural post-transcriptional TGS and PTGS phenomena may natural of plant at the DNA or RNA level or like TGS may cellular DNA that into the while PTGS may cellular DNA that in the or RNA that in the large of transgene and/or or can be introduced in plants to their silencing and as plant mutants affected in the control of silencing become it is to further in the analysis of the and the natural roles of epigenetic control in plants. from the on Silencing for and and for of the

Recent research has demonstrated that all body fluids assessed contain substantial amounts of vesicles that range in size from 30 to 1000 nm and that are surrounded by phospholipid membranes containing different membrane microdomains such as lipid rafts and caveolae. The most prominent representatives of these so-called extracellular vesicles (EVs) are nanosized exosomes (70-150 nm), which are derivatives of the endosomal system, and microvesicles (100-1000 nm), which are produced by outward budding of the plasma membrane. Nanosized EVs are released by almost all cell types and mediate targeted intercellular communication under physiological and pathophysiological conditions. Containing cell-type-specific signatures, EVs have been proposed as biomarkers in a variety of diseases. Furthermore, according to their physical functions, EVs of selected cell types have been used as therapeutic agents in immune therapy, vaccination trials, regenerative medicine, and drug delivery. Undoubtedly, the rapidly emerging field of basic and applied EV research will significantly influence the biomedicinal landscape in the future. In this Perspective, we, a network of European scientists from clinical, academic, and industry settings collaborating through the H2020 European Cooperation in Science and Technology (COST) program European Network on Microvesicles and Exosomes in Health and Disease (ME-HAD), demonstrate the high potential of nanosized EVs for both diagnostic and therapeutic (i.e., theranostic) areas of nanomedicine.

Long non-protein coding RNAs (npcRNA) represent an emerging class of riboregulators, which either act directly in this long form or are processed to shorter miRNA and siRNA. Genome-wide bioinformatic analysis of full-length cDNA databases identified 76 Arabidopsis npcRNAs. Fourteen npcRNAs were antisense to protein-coding mRNAs, suggesting cis-regulatory roles. Numerous 24-nt siRNA matched to five different npcRNAs, suggesting that these npcRNAs are precursors of this type of siRNA. Expression analyses of the 76 npcRNAs identified a novel npcRNA that accumulates in a dcl1 mutant but does not appear to produce trans-acting siRNA or miRNA. Additionally, another npcRNA was the precursor of miR869 and shown to be up-regulated in dcl4 but not in dcl1 mutants, indicative of a young miRNA gene. Abiotic stress altered the accumulation of 22 npcRNAs among the 76, a fraction significantly higher than that observed for the RNA binding protein-coding fraction of the transcriptome. Overexpression analyses in Arabidopsis identified two npcRNAs as regulators of root growth during salt stress and leaf morphology, respectively. Hence, together with small RNAs, long npcRNAs encompass a sensitive component of the transcriptome that have diverse roles during growth and differentiation.

Podosomes, small actin-based adhesion structures, differ from focal adhesions in two aspects: their core structure and their ability to organize into large patterns in osteoclasts. To address the mechanisms underlying these features, we imaged live preosteoclasts expressing green fluorescent protein-actin during their differentiation. We observe that podosomes always form inside or close to podosome groups, which are surrounded by an actin cloud. Fluorescence recovery after photobleaching shows that actin turns over in individual podosomes in contrast to cortactin, suggesting a continuous actin polymerization in the podosome core. The observation of podosome assemblies during osteoclast differentiation reveals that they evolve from simple clusters into rings that expand by the continuous formation of new podosomes at their outer ridge and inhibition of podosome formation inside the rings. This self-organization of podosomes into dynamic rings is the mechanism that drives podosomes at the periphery of the cell in large circular patterns. We also show that an additional step of differentiation, requiring microtubule integrity, stabilizes the podosome circles at the cell periphery to form the characteristic podosome belt pattern of mature osteoclasts. These results therefore provide a mechanism for the patterning of podosomes in osteoclasts and reveal a turnover of actin inside the podosome.

Mouse embryonic stem cells were induced to differentiate in culture with retinoic acid. Putative precursors of neurons and glial cells (nestin-positive cells) were clearly identified as early as three days after the onset of differentiation. At day 6, neuron-like cells could be clearly identified, either as isolated cells or as cellular networks. Some of these cells were positive for astrocyte- or oligodendrocyte-specific antigens (GFAP or O4 antigens, respectively). Other cells were positive for neuron-specific antigens (cytoskeleton proteins MAP2, MAP5 and NF200, as well as synaptophysin). Some neuronal-like cells were also positive for acetylcholinesterase activity or glutamic acid decarboxylase expression, indicating that ES cells could differentiate into GABAergic and possibly cholinergic neurons. Electrophysiological analyses performed in voltage clamp conditions showed that cell membranes contained voltage-dependent channels. Overshooting action potentials could be triggered by current injection. Taken together, these data provide evidence that embryonic stem cells can differentiate first into neuron-glia progenitors, and later into glial cells and functional neurons, in vitro. This technique provides an unique system to study early steps of neuronal differentiation in vitro.

Teleost fishes provide the first unambiguous support for ancient whole-genome duplication in an animal lineage. Studies in yeast or plants have shown that the effects of such duplications can be mediated by a complex pattern of gene retention and changes in evolutionary pressure. To explore such patterns in fishes, we have determined by phylogenetic analysis the evolutionary origin of 675 Tetraodon duplicated genes assigned to chromosomes, using additional data from other species of actinopterygian fishes. The subset of genes, which was retained in double after the genome duplication, is enriched in development, signaling, behavior, and regulation functional categories. The evolutionary rate of duplicate fish genes appears to be determined by 3 forces: 1) fish proteins evolve faster than mammalian orthologs; 2) the genes kept in double after genome duplication represent the subset under strongest purifying selection; and 3) following duplication, there is an asymmetric acceleration of evolutionary rate in one of the paralogs. These results show that similar mechanisms are at work in fishes as in yeast or plants and provide a framework for future investigation of the consequences of duplication in fishes and other animals.

There are two estrogen receptor (ER) subtypes in fish, ERalpha and ERbeta, and increasing evidence that the ERbeta subtype has more than one form. However, there is little information on the characteristics and functional significance of these ERs in adults and during development. Here, we report the cloning and characterization of three functional ER forms, zfERalpha, zfERbeta1, and zfERbeta2, in the zebrafish. The percentages of identity between these receptors suggest the existence of three distinct genes. Each cDNA encoded a protein that specifically bound estradiol with a dissociation constant ranging from 0.4 nM (zfERbeta2) to 0.75 nM (zfERalpha and zfERbeta1). In transiently transfected cells, all three forms were able to induce, in a dose-dependent manner, the expression of a reporter gene driven by a consensus estrogen responsive element; zfERbeta2 was slightly more sensitive than zfERalpha and zfERbeta1. Tissue distribution pattern, analyzed by reverse transcription polymerase chain reaction, showed that the three zfER mRNAs largely overlap and are predominantly expressed in brain, pituitary, liver, and gonads. In situ hybridization was performed to study in more detail the distribution of the three zfER mRNAs in the brain of adult females. The zfER mRNAs exhibit distinct but partially overlapping patterns of expression in two neuroendocrine regions, the preoptic area and the mediobasal hypothalamus. The characterization of these zfERs provides a new perspective for understanding the mechanisms underlying estradiol actions in a vertebrate species commonly used for developmental studies.

Activation of naive CD8 T-cells can lead to the generation of multiple effector and memory subsets. Multiple parameters associated with activation conditions are involved in generating this diversity that is associated with heterogeneous molecular contents of activated cells. Although naive cell polarisation upon antigenic stimulation and the resulting asymmetric division are known to be a major source of heterogeneity and cell fate regulation, the consequences of stochastic uneven partitioning of molecular content upon subsequent divisions remain unclear yet. Here we aim at studying the impact of uneven partitioning on molecular-content heterogeneity and then on the immune response dynamics at the cellular level. To do so, we introduce a multiscale mathematical model of the CD8 T-cell immune response in the lymph node. In the model, cells are described as agents evolving and interacting in a 2D environment while a set of differential equations, embedded in each cell, models the regulation of intra and extracellular proteins involved in cell differentiation. Based on the analysis of \textit{in silico} data at the single cell level, we show that immune response dynamics can be explained by the molecular-content heterogeneity generated by uneven partitioning at cell division. In particular, uneven partitioning acts as a regulator of cell differentiation and induces the emergence of two coexisting sub-populations of cells exhibiting antagonistic fates. We show that the degree of unevenness of molecular partitioning, along all cell divisions, affects the outcome of the immune response and can promote the generation of memory cells.

Beta1- and beta2-adrenoceptors in heart muscle cells mediate the catecholamine-induced increase in the force and frequency of cardiac contraction. Recently, in addition, we demonstrated the functional expression of beta3-adrenoceptors in the human heart. Their stimulation, in marked contrast with that of beta1- and beta2-adrenoceptors, induces a decrease in contractility through presently unknown mechanisms. In the present study, we examined the role of a nitric oxide (NO) synthase pathway in mediating the beta3-adrenoceptor effect on the contractility of human endomyocardial biopsies. The negative inotropic effects of a beta3-adrenoceptor agonist, BRL 37344, and also of norepinephrine in the presence of alpha- and beta1-2-blockade were inhibited both by a nonspecific blocker of NO, methylene blue, and two NO synthase (NOS) inhibitors, L-N-monomethyl-arginine and L-nitroarginine-methyl ester. The effect of the NOS inhibitors was reversed by an excess of L-arginine, the natural substrate of NOS, but not by D-arginine. Moreover, the effects of the beta3-adrenoceptor agonist on contractility were associated with parallel increases in the production of NO and intracellular cGMP, which were also inhibited by NOS inhibitors. Immunohistochemical staining of human ventricular biopsies showed the expression of the endothelial constitutive (eNOS), but not the inducible (iNOS) isoform of NOS in both ventricular myocytes and endothelial cells. These results demonstrate that beta3-adrenoceptor stimulation decreases cardiac contractility through activation of an NOS pathway. Changes in the expression of this pathway may alter the balance between positive and negative inotropic effects of catecholamines on the heart potentially leading to myocardial dysfunction.

Mammalian target of rapamycin (mTOR) is a key regulator of cell growth that associates with raptor and rictor to form the mTOR complex 1 (mTORC1) and mTORC2, respectively. Raptor is required for oxidative muscle integrity, whereas rictor is dispensable. In this study, we show that muscle-specific inactivation of mTOR leads to severe myopathy, resulting in premature death. mTOR-deficient muscles display metabolic changes similar to those observed in muscles lacking raptor, including impaired oxidative metabolism, altered mitochondrial regulation, and glycogen accumulation associated with protein kinase B/Akt hyperactivation. In addition, mTOR-deficient muscles exhibit increased basal glucose uptake, whereas whole body glucose homeostasis is essentially maintained. Importantly, loss of mTOR exacerbates the myopathic features in both slow oxidative and fast glycolytic muscles. Moreover, mTOR but not raptor and rictor deficiency leads to reduced muscle dystrophin content. We provide evidence that mTOR controls dystrophin transcription in a cell-autonomous, rapamycin-resistant, and kinase-independent manner. Collectively, our results demonstrate that mTOR acts mainly via mTORC1, whereas regulation of dystrophin is raptor and rictor independent.

Post-transcriptional gene silencing (PTGS) in plants is an RNA-degradation mechanism that shows similarities to RNA interference (RNAi) in animals. Indeed, both involve double-stranded RNA (dsRNA), spread within the organism from a localised initiating area, correlate with the accumulation of small interfering RNA (siRNA) and require putative RNA-dependent RNA polymerases, RNA helicases and proteins of unknown functions containing PAZ and Piwi domains. However, some differences are evident. First, PTGS in plants requires at least two genes--SGS3 (which encodes a protein of unknown function containing a coil-coiled domain) and MET1 (which encodes a DNA-methyltransferase)--that are absent in C. elegans and thus are not required for RNAi. Second, all Arabidopsis mutants that exhibit impaired PTGS are hypersusceptible to infection by the cucumovirus CMV, indicating that PTGS participates in a mechanism for plant resistance to viruses. Interestingly, many viruses have developed strategies to counteract PTGS and successfully infect plants--for example, by potentiating endogenous suppressors of PTGS. Whether viruses can counteract RNAi in animals and whether endogenous suppressors of RNAi exist in animals is still unknown.

Vertically transmitted endosymbionts persist for millions of years in invertebrates and play an important role in animal evolution. However, the functional basis underlying the maintenance of these long-term resident bacteria is unknown. We report that the weevil coleoptericin-A (ColA) antimicrobial peptide selectively targets endosymbionts within the bacteriocytes and regulates their growth through the inhibition of cell division. Silencing the colA gene with RNA interference resulted in a decrease in size of the giant filamentous endosymbionts, which escaped from the bacteriocytes and spread into insect tissues. Although this family of peptides is commonly linked with microbe clearance, this work shows that endosymbiosis benefits from ColA, suggesting that long-term host-symbiont coevolution might have shaped immune effectors for symbiont maintenance.

We describe a modification in the sample application mode for isoelectric focusing with immobilized pH gradients. Instead of being applied at the surface of the gel in a sample cup, the sample is introduced into the gel during the immobilized pH gradient strip rehydration step. This modification implies the use of low percentage gels (below 3.5% T) and specially designed, but simple, rehydration chambers. The main advantages are a uniform resolution without side effects and the possibility of handling large sample volumes (500 microL for a standard 3 x 160 x 0.5 mm strip), allowing micropreparative work (milligram samples) with a simple experimental design.

Bilaterian animals are notably characterized by complex endocrine systems. The receptors for many steroids, retinoids, and other hormones belong to the superfamily of nuclear receptors, which are transcription factors regulating many aspects of development and homeostasis. Despite a diversity of regulatory mechanisms and physiological roles, nuclear receptors share a common protein organization. To obtain the broad picture of bilaterian nuclear hormone receptor evolution, we have characterized the complete set of nuclear receptor genes from nine animal genome sequences and analyzed it in a phylogenetic framework. In addition, expressed sequence tags from key lineages with no available genome sequence were also searched. This allows us to date the evolutionary events that led from an ancestral nuclear receptor gene, in an early metazoan, to present day diversity. We show that there were ;25 nuclear receptor genes in Urbilateria, the ancestor of bilaterians, at which point the fundamental diversity of the subfamily was already established. Surprisingly, differential gene loss played an important role in the evolution of different nuclear receptor sets in bilaterian lineages. The nuclear receptor distribution was also shaped by periods of gene duplication, essentially in vertebrates, as well as a lineage-specific duplication burst in nematodes. Our results imply that the genes for major receptors such as steroid receptors or thyroid hormone receptors were present in Urbilateria.