Institute of Molecular Biotechnology

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,

A novel infectious disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was detected in Wuhan, China, in December 2019. The disease (COVID-19) spread rapidly, reaching epidemic proportions in China, and has been found in 27 other countries. As of February 27, 2020, over 82,000 cases of COVID-19 were reported, with > 2800 deaths. No specific therapeutics are available, and current management includes travel restrictions, patient isolation, and supportive medical care. There are a number of pharmaceuticals already being tested [1, 2], but a better understanding of the underlying pathobiology is required. In this context, this article will briefly review the rationale for angiotensin-converting enzyme 2 (ACE2) receptor as a specific target.

Classical experiments performed half a century ago demonstrated the immense self-organizing capacity of vertebrate cells. Even after complete dissociation, cells can reaggregate and reconstruct the original architecture of an organ. More recently, this outstanding feature was used to rebuild organ parts or even complete organs from tissue or embryonic stem cells. Such stem cell-derived three-dimensional cultures are called organoids. Because organoids can be grown from human stem cells and from patient-derived induced pluripotent stem cells, they have the potential to model human development and disease. Furthermore, they have potential for drug testing and even future organ replacement strategies. Here, we summarize this rapidly evolving field and outline the potential of organoid technology for future biomedical research.

A novel coronavirus has been identified as the causative agent of severe acute respiratory syndrome (SARS). The viral main proteinase (Mpro, also called 3CLpro), which controls the activities of the coronavirus replication complex, is an attractive target for therapy. We determined crystal structures for human coronavirus (strain 229E) Mpro and for an inhibitor complex of porcine coronavirus [transmissible gastroenteritis virus (TGEV)] Mpro, and we constructed a homology model for SARS coronavirus (SARS-CoV) Mpro. The structures reveal a remarkable degree of conservation of the substrate-binding sites, which is further supported by recombinant SARS-CoV Mpro-mediated cleavage of a TGEV Mpro substrate. Molecular modeling suggests that available rhinovirus 3Cpro inhibitors may be modified to make them useful for treating SARS.

Autophagy is a core molecular pathway for the preservation of cellular and organismal homeostasis. Pharmacological and genetic interventions impairing autophagy responses promote or aggravate disease in a plethora of experimental models. Consistently, mutations in autophagy-related processes cause severe human pathologies. Here, we review and discuss preclinical data linking autophagy dysfunction to the pathogenesis of major human disorders including cancer as well as cardiovascular, neurodegenerative, metabolic, pulmonary, renal, infectious, musculoskeletal, and ocular disorders.

Cerebral organoids-3D cultures of human cerebral tissue derived from pluripotent stem cells-have emerged as models of human cortical development. However, the extent to which in vitro organoid systems recapitulate neural progenitor cell proliferation and neuronal differentiation programs observed in vivo remains unclear. Here we use single-cell RNA sequencing (scRNA-seq) to dissect and compare cell composition and progenitor-to-neuron lineage relationships in human cerebral organoids and fetal neocortex. Covariation network analysis using the fetal neocortex data reveals known and previously unidentified interactions among genes central to neural progenitor proliferation and neuronal differentiation. In the organoid, we detect diverse progenitors and differentiated cell types of neuronal and mesenchymal lineages and identify cells that derived from regions resembling the fetal neocortex. We find that these organoid cortical cells use gene expression programs remarkably similar to those of the fetal tissue to organize into cerebral cortex-like regions. Our comparison of in vivo and in vitro cortical single-cell transcriptomes illuminates the genetic features underlying human cortical development that can be studied in organoid cultures.

Sclerotinia sclerotiorum and Botrytis cinerea are closely related necrotrophic plant pathogenic fungi notable for their wide host ranges and environmental persistence. These attributes have made these species models for understanding the complexity of necrotrophic, broad host-range pathogenicity. Despite their similarities, the two species differ in mating behaviour and the ability to produce asexual spores. We have sequenced the genomes of one strain of S. sclerotiorum and two strains of B. cinerea. The comparative analysis of these genomes relative to one another and to other sequenced fungal genomes is provided here. Their 38-39 Mb genomes include 11,860-14,270 predicted genes, which share 83% amino acid identity on average between the two species. We have mapped the S. sclerotiorum assembly to 16 chromosomes and found large-scale co-linearity with the B. cinerea genomes. Seven percent of the S. sclerotiorum genome comprises transposable elements compared to <1% of B. cinerea. The arsenal of genes associated with necrotrophic processes is similar between the species, including genes involved in plant cell wall degradation and oxalic acid production. Analysis of secondary metabolism gene clusters revealed an expansion in number and diversity of B. cinerea-specific secondary metabolites relative to S. sclerotiorum. The potential diversity in secondary metabolism might be involved in adaptation to specific ecological niches. Comparative genome analysis revealed the basis of differing sexual mating compatibility systems between S. sclerotiorum and B. cinerea. The organization of the mating-type loci differs, and their structures provide evidence for the evolution of heterothallism from homothallism. These data shed light on the evolutionary and mechanistic bases of the genetically complex traits of necrotrophic pathogenicity and sexual mating. This resource should facilitate the functional studies designed to better understand what makes these fungi such successful and persistent pathogens of agronomic crops.

Pichia pastoris is an established protein expression host mainly applied for the production of biopharmaceuticals and industrial enzymes. This methylotrophic yeast is a distinguished production system for its growth to very high cell densities, for the available strong and tightly regulated promoters, and for the options to produce gram amounts of recombinant protein per litre of culture both intracellularly and in secretory fashion. However, not every protein of interest is produced in or secreted by P. pastoris to such high titres. Frequently, protein yields are clearly lower, particularly if complex proteins are expressed that are hetero-oligomers, membrane-attached or prone to proteolytic degradation. The last few years have been particularly fruitful because of numerous activities in improving the expression of such complex proteins with a focus on either protein engineering or on engineering the protein expression host P. pastoris. This review refers to established tools in protein expression in P. pastoris and highlights novel developments in the areas of expression vector design, host strain engineering and screening for high-level expression strains. Breakthroughs in membrane protein expression are discussed alongside numerous commercial applications of P. pastoris derived proteins.

An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.

Activation of the innate immune system in obesity is a risk factor for the development of type 2 diabetes. The aim of the current study was to investigate the notion that increased numbers of macrophages exist in the islets of type 2 diabetes patients and that this may be explained by a dysregulation of islet-derived inflammatory factors. Increased islet-associated immune cells were observed in human type 2 diabetic patients, high-fat-fed C57BL/6J mice, the GK rat, and the db/db mouse. When cultured islets were exposed to a type 2 diabetic milieu or when islets were isolated from high-fat-fed mice, increased islet-derived inflammatory factors were produced and released, including interleukin (IL)-6, IL-8, chemokine KC, granulocyte colony-stimulating factor, and macrophage inflammatory protein 1alpha. The specificity of this response was investigated by direct comparison to nonislet pancreatic tissue and beta-cell lines and was not mimicked by the induction of islet cell death. Further, this inflammatory response was found to be biologically functional, as conditioned medium from human islets exposed to a type 2 diabetic milieu could induce increased migration of monocytes and neutrophils. This migration was blocked by IL-8 neutralization, and IL-8 was localized to the human pancreatic alpha-cell. Therefore, islet-derived inflammatory factors are regulated by a type 2 diabetic milieu and may contribute to the macrophage infiltration of pancreatic islets that we observe in type 2 diabetes.

GABA A (γ-aminobutyric acid A)-benzodiazepine receptors expressed in mammalian cells and assembled from one of three different α subunit variants (α 1 , α 2 , or α 3 ) in combination with a β 1 and a γ 2 subunit display the pharmacological properties of either type I or type II receptor subtypes. These receptors contain high-affinity binding sites for benzodiazepines. However, CL 218 872, 2-oxoquazepam, and methyl β-carboline-3-carboxylate (β-CCM) show a temperature-modulated selectivity for α 1 subunit-containing receptors. There were no significant differences in the binding of clonazepam, diazepam, Ro 15-1788, or dimethoxy-4-ethyl-β-carboline-3-carboxylate (DMCM) to all three recombinant receptors. Receptors containing the α 3 subunit show greater GABA potentiation of benzodiazepine binding than receptors containing the α 1 or α 2 subunit, indicating that there are subtypes within the type II class. Thus, diversity in benzodiazepine pharmacology is generated by heterogeneity of the α subunit of the GABA A receptor.

The presence of beta-sheets in the core of amyloid fibrils raised questions as to whether or not beta-sheet-containing proteins, such as transthyretin, are predisposed to form such fibrils. However, we show here that the molecular structure of amyloid fibrils differs more generally from the beta-sheets in native proteins. This difference is evident from the amide I region of the infrared spectrum and relates to the distribution of the phi/psi dihedral angles within the Ramachandran plot, the average number of strands per sheet, and possibly, the beta-sheet twist. These data imply that amyloid fibril formation from native beta-sheet proteins can involve a substantial structural reorganization.

Tissue regeneration is a multi-step process mediated by diverse cellular hierarchies and states that are also implicated in tissue dysfunction and pathogenesis. Here we leveraged single-cell RNA sequencing in combination with in vivo lineage tracing and organoid models to finely map the trajectories of alveolar-lineage cells during injury repair and lung regeneration. We identified a distinct AT2-lineage population, damage-associated transient progenitors (DATPs), that arises during alveolar regeneration. We found that interstitial macrophage-derived IL-1β primes a subset of AT2 cells expressing Il1r1 for conversion into DATPs via a HIF1α-mediated glycolysis pathway, which is required for mature AT1 cell differentiation. Importantly, chronic inflammation mediated by IL-1β prevents AT1 differentiation, leading to aberrant accumulation of DATPs and impaired alveolar regeneration. Together, this stepwise mapping to cell fate transitions shows how an inflammatory niche controls alveolar regeneration by controlling stem cell fate and behavior.

Mammalian imprinted genes often cluster with long noncoding (lnc) RNAs. Three lncRNAs that induce parental-specific silencing show hallmarks indicating that their transcription is more important than their product. To test whether Airn transcription or product silences the Igf2r gene, we shortened the endogenous lncRNA to different lengths. The results excluded a role for spliced and unspliced Airn lncRNA products and for Airn nuclear size and location in silencing Igf2r. Instead, silencing only required Airn transcriptional overlap of the Igf2r promoter, which interferes with RNA polymerase II recruitment in the absence of repressive chromatin. Such a repressor function for lncRNA transcriptional overlap reveals a gene silencing mechanism that may be widespread in the mammalian genome, given the abundance of lncRNA transcripts.

One of the most exciting developments in the field of bacterial pathogenesis in recent years is the discovery that many pathogens utilize complex nanomachines to deliver bacterially encoded effector proteins into target eukaryotic cells. These effector proteins modulate a variety of cellular functions for the pathogen's benefit. One of these protein-delivery machines is the type III secretion system (T3SS). T3SSs are widespread in nature and are encoded not only by bacteria pathogenic to vertebrates or plants but also by bacteria that are symbiotic to plants or insects. A central component of T3SSs is the needle complex, a supramolecular structure that mediates the passage of the secreted proteins across the bacterial envelope. Working in conjunction with several cytoplasmic components, the needle complex engages specific substrates in sequential order, moves them across the bacterial envelope, and ultimately delivers them into eukaryotic cells. The central role of T3SSs in pathogenesis makes them great targets for novel antimicrobial strategies.

Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda , is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform.

Although steroid hormone receptors are known to activate gene expression by binding to specific hormone-dependent enhancers, the mechanisms by which steroids inhibit the transcription of specific genes are unknown. It is shown here by gene transfer studies that the same glucocorticoid receptor that activates gene expression can negatively regulate expression of the human glycoprotein hormone alpha-subunit gene. Glucocorticoid inhibition was conferred by a 52-nucleotide region that also contains elements crucial both for adenosine 3',5'-monophosphate (cAMP) responsiveness and for placental-specific expression of this gene and was observed only under conditions in which these elements were functioning as enhancers. Purified glucocorticoid receptor was found to bind to DNA that overlap the cAMP responsive elements sites in this region. It is hypothesized that steroid receptors negatively regulate gene expression by interfering with the activity or binding of other important transcription factors.

Drosophila neuroblasts, the stem cells of the developing fly brain, have emerged as a key model system for neural stem cell biology and have provided key insights into the mechanisms underlying asymmetric cell division and tumor formation. More recently, they have also been used to understand how neural progenitors can generate different neuronal subtypes over time, how their cell cycle entry and exit are coordinated with development, and how proliferation in the brain is spared from the growth restrictions that occur in other organs upon starvation. In this Primer, we describe the biology of Drosophila neuroblasts and highlight the most recent advances made using neuroblasts as a model system.

Sprouting of developing blood vessels is mediated by specialized motile endothelial cells localized at the tips of growing capillaries. Following behind the tip cells, endothelial stalk cells form the capillary lumen and proliferate. Expression of the Notch ligand Delta-like-4 (Dll4) in tip cells suppresses tip cell fate in neighboring stalk cells via Notch signaling. In DLL4(+/-) mouse mutants, most retinal endothelial cells display morphologic features of tip cells. We hypothesized that these mouse mutants could be used to isolate tip cells and so to determine their genetic repertoire. Using transcriptome analysis of retinal endothelial cells isolated from DLL4(+/-) and wild-type mice, we identified 3 clusters of tip cell-enriched genes, encoding extracellular matrix degrading enzymes, basement membrane components, and secreted molecules. Secreted molecules endothelial-specific molecule 1, angiopoietin 2, and apelin bind to cognate receptors on endothelial stalk cells. Knockout mice and zebrafish morpholino knockdown of apelin showed delayed angiogenesis and reduced proliferation of stalk cells expressing the apelin receptor APJ. Thus, tip cells may regulate angiogenesis via matrix remodeling, production of basement membrane, and release of secreted molecules, some of which regulate stalk cell behavior.

Aire-expressing medullary thymic epithelial cells (mTECs) play a key role in preventing autoimmunity by expressing tissue-restricted antigens to help purge the emerging T cell receptor repertoire of self-reactive specificities. Here we demonstrate a novel role for a CD4(+)3(-) inducer cell population, previously linked to development of organized secondary lymphoid structures and maintenance of T cell memory in the functional regulation of Aire-mediated promiscuous gene expression in the thymus. CD4(+)3(-) cells are closely associated with mTECs in adult thymus, and in fetal thymus their appearance is temporally linked with the appearance of Aire(+) mTECs. We show that RANKL signals from this cell promote the maturation of RANK-expressing CD80(-)Aire(-) mTEC progenitors into CD80(+)Aire(+) mTECs, and that transplantation of RANK-deficient thymic stroma into immunodeficient hosts induces autoimmunity. Collectively, our data reveal cellular and molecular mechanisms leading to the generation of Aire(+) mTECs and highlight a previously unrecognized role for CD4(+)3(-)RANKL(+) inducer cells in intrathymic self-tolerance.