Babraham Institute

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,

SUMMARY: A combination of bisulfite treatment of DNA and high-throughput sequencing (BS-Seq) can capture a snapshot of a cell's epigenomic state by revealing its genome-wide cytosine methylation at single base resolution. Bismark is a flexible tool for the time-efficient analysis of BS-Seq data which performs both read mapping and methylation calling in a single convenient step. Its output discriminates between cytosines in CpG, CHG and CHH context and enables bench scientists to visualize and interpret their methylation data soon after the sequencing run is completed. AVAILABILITY AND IMPLEMENTATION: Bismark is released under the GNU GPLv3+ licence. The source code is freely available from www.bioinformatics.bbsrc.ac.uk/projects/bismark/.

The synergistic action of cytosolic Ca2+ and inositol 1,4,5-trisphosphate (InsP3) in releasing intracellular Ca2+ stores has been suggested to be responsible for the complex intracellular Ca2 signals observed during hormonal stimulation of many cell types. However, the ability of cytosolic Ca2+ to potentiate Ca2+ release has recently been questioned because of the observed inhibitory effects of Ca2+ chelators used in previous studies. In the present study, EGTA and BAPTA [1,2-bis-(2-amino-phenoxy)ethane- NNN'N'-tetra-acetic acid] poorly inhibited InsP3-induced Ca2+ release from permeabilized A7r5 smooth-muscle cells. Additionally, stimulatory effects of cytosolic and luminal Ca2+ were observed either in the complete absence of Ca2+ chelator or at constant Ca(2+)-free chelator concentration. These data suggest that potentiation of InsP3-induced Ca2+ release by Ca2+ in A7r5 cells reflects an interaction between Ca2+ and InsP3 receptors, rather than a decrease in chelator-dependent inhibition. The EC50 for activation of InsP3-induced Ca2+ release by cytosolic Ca2+ was unaffected by ATP, or by changing InsP3 concentration, although InsP3-induced Ca2+ release became less sensitive to the inhibitory effects of cytosolic Ca2+ as the InsP3 concentration was elevated. Increasing H+ or Mg2+ concentration shifted the Ca(2+)-activation curve towards higher Ca2+ concentrations. These data suggest that, in addition to the InsP3-binding site, the affinity of the Ca(2+)-binding site(s) on InsP3 receptors can be modulated by intracellular cations.

We have previously shown correction of X-linked severe combined immunodeficiency [SCID-X1, also known as gamma chain (gamma(c)) deficiency] in 9 out of 10 patients by retrovirus-mediated gamma(c) gene transfer into autologous CD34 bone marrow cells. However, almost 3 years after gene therapy, uncontrolled exponential clonal proliferation of mature T cells (with gammadelta+ or alphabeta+ T cell receptors) has occurred in the two youngest patients. Both patients' clones showed retrovirus vector integration in proximity to the LMO2 proto-oncogene promoter, leading to aberrant transcription and expression of LMO2. Thus, retrovirus vector insertion can trigger deregulated premalignant cell proliferation with unexpected frequency, most likely driven by retrovirus enhancer activity on the LMO2 gene promoter.

DNA methylation is a major epigenetic modification of the genome that regulates crucial aspects of its function. Genomic methylation patterns in somatic differentiated cells are generally stable and heritable. However, in mammals there are at least two developmental periods-in germ cells and in preimplantation embryos-in which methylation patterns are reprogrammed genome wide, generating cells with a broad developmental potential. Epigenetic reprogramming in germ cells is critical for imprinting; reprogramming in early embryos also affects imprinting. Reprogramming is likely to have a crucial role in establishing nuclear totipotency in normal development and in cloned animals, and in the erasure of acquired epigenetic information. A role of reprogramming in stem cell differentiation is also envisaged. DNA methylation is one of the best-studied epigenetic modifications of DNA in all unicellular and multicellular organisms. In mammals and other vertebrates, methylation occurs predominantly at the symmetrical dinucleotide CpG (1-4). Symmetrical methylation and the discovery of a DNA methyltransferase that prefers a hemimethylated substrate, Dnmt1 (4), suggested a mechanism by which specific patterns of methylation in the genome could be maintained. Patterns imposed on the genome at defined developmental time points in precursor cells could be maintained by Dnmt1, and would lead to predetermined programs of gene expression during development in descendants of the precursor cells (5, 6). This provided a means to explain how patterns of differentiation could be maintained by populations of cells. In addition, specific demethylation events in differentiated tissues could then lead to further changes in gene expression as needed. Neat and convincing as this model is, it is still largely unsubstantiated. While effects of methylation on expression of specific genes, particularly imprinted ones (7) and some retrotransposons (8), have been demonstrated in vivo, it is still unclear whether or not methylation is involved in the control of gene expression during normal development (9-13). Although enzymes have been identified that can methylate DNA de novo (Dnmt3a and Dnmt3b) (14), it is unknown how specific patterns of methylation are established in the genome. Mechanisms for active demethylation have been suggested, but no enzymes have been identified that carry out this function in vivo (15-17). Genomewide alterations in methylation-brought about, for example, by knockouts of the methylase genes-result in embryo lethality or developmental defects, but the basis for abnormal development still remains to be discovered (7, 14). What is clear, however, is that in mammals there are developmental periods of genomewide reprogramming of methylation patterns in vivo. Typically, a substantial part of the genome is demethylated, and after some time remethylated, in a cell- or tissue-specific pattern. The developmental dynamics of these reprogramming events, as well as some of the enzymatic mechanisms involved and the biological purposes, are beginning to be understood. Here we look at what is known about reprogramming in mammals and discuss how it might relate to developmental potency and imprinting.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

The formation of inositol phosphates in response to agonists was studied in brain slices, parotid gland fragments and in the insect salivary gland. The tissues were first incubated with [3H]inositol, which was incorporated into the phosphoinositides. All the tissues were found to contain glycerophosphoinositol, inositol 1-phosphate, inositol 1,4-bisphosphate and inositol 1,4,5-trisphosphate, which were identified by using anion-exchange and high-resolution anion-exchange chromatography, high-voltage paper ionophoresis and paper chromatography. There was no evidence for the existence of inositol 1:2-cyclic phosphate. A simple anion-exchange chromatographic method was developed for separating these inositol phosphates for quantitative analysis. Stimulation caused no change in the levels of glycerophosphoinositol in any of the tissues. The most prominent change concerned inositol 1,4-bisphosphate, which increased enormously in the insect salivary gland and parotid gland after stimulation with 5-hydroxytryptamine and carbachol respectively. Carbachol also induced a large increase in the level of inositol 1,4,5-trisphosphate in the parotid. Stimulation of brain slices with carbachol induced modest increase in the bis- and tris-phosphate. In all the tissues studied, there was a significant agonist-dependent increase in the level of inositol 1-phosphate. The latter may be derived from inositol 1,4-bisphosphate, because homogenates of the insect salivary gland contain a bisphosphatase in addition to a trisphosphatase. These results suggest that the earliest event in the stimulus-response pathway is the hydrolysis of polyphosphoinositides by a phosphodiesterase to yield inositol 1,4,5-trisphosphate and inositol 1,4-bisphosphate, which are subsequently hydrolysed to inositol 1-phosphate and inositol. The absence of inositol 1:2-cyclic phosphate could indicate that, at very short times after stimulation, phosphatidylinositol is not catabolized by its specific phosphodiesterase, or that any cyclic derivative liberated is rapidly hydrolysed by inositol 1:2-cyclic phosphate 2-phosphohydrolase.

MicroRNAs are a class of small RNAs that are increasingly being recognized as important regulators of gene expression. Although hundreds of microRNAs are present in the mammalian genome, genetic studies addressing their physiological roles are at an early stage. We have shown that mice deficient for bic/microRNA-155 are immunodeficient and display increased lung airway remodeling. We demonstrate a requirement of bic/microRNA-155 for the function of B and T lymphocytes and dendritic cells. Transcriptome analysis of bic/microRNA-155-deficient CD4+ T cells identified a wide spectrum of microRNA-155-regulated genes, including cytokines, chemokines, and transcription factors. Our work suggests that bic/microRNA-155 plays a key role in the homeostasis and function of the immune system.

Autophagy is the engulfment of cytosol and organelles by double-membrane vesicles termed autophagosomes. Autophagosome formation is known to require phosphatidylinositol 3-phosphate (PI(3)P) and occurs near the endoplasmic reticulum (ER), but the exact mechanisms are unknown. We show that double FYVE domain-containing protein 1, a PI(3)P-binding protein with unusual localization on ER and Golgi membranes, translocates in response to amino acid starvation to a punctate compartment partially colocalized with autophagosomal proteins. Translocation is dependent on Vps34 and beclin function. Other PI(3)P-binding probes targeted to the ER show the same starvation-induced translocation that is dependent on PI(3)P formation and recognition. Live imaging experiments show that this punctate compartment forms near Vps34-containing vesicles, is in dynamic equilibrium with the ER, and provides a membrane platform for accumulation of autophagosomal proteins, expansion of autophagosomal membranes, and emergence of fully formed autophagosomes. This PI(3)P-enriched compartment may be involved in autophagosome biogenesis. Its dynamic relationship with the ER is consistent with the idea that the ER may provide important components for autophagosome formation.

<ns3:p>DNA sequencing analysis typically involves mapping reads to just one reference genome. Mapping against multiple genomes is necessary, however, when the genome of origin requires confirmation. Mapping against multiple genomes is also advisable for detecting contamination or for identifying sample swaps which, if left undetected, may lead to incorrect experimental conclusions. Consequently, we present FastQ Screen, a tool to validate the origin of DNA samples by quantifying the proportion of reads that map to a panel of reference genomes. FastQ Screen is intended to be used routinely as a quality control measure and for analysing samples in which the origin of the DNA is uncertain or has multiple sources.</ns3:p>

In 2005, the International Lipid Classification and Nomenclature Committee under the sponsorship of the LIPID MAPS Consortium developed and established a “Comprehensive Classification System for Lipids” based on well-defined chemical and biochemical principles and using an ontology that is extensible, flexible, and scalable. This classification system, which is compatible with contemporary databasing and informatics needs, has now been accepted internationally and widely adopted. In response to considerable attention and requests from lipid researchers from around the globe and in a variety of fields, the comprehensive classification system has undergone significant revisions over the last few years to more fully represent lipid structures from a wider variety of sources and to provide additional levels of detail as necessary. The details of this classification system are reviewed and updated and are presented here, along with revisions to its suggested nomenclature and structure-drawing recommendations for lipids. In 2005, the International Lipid Classification and Nomenclature Committee under the sponsorship of the LIPID MAPS Consortium developed and established a “Comprehensive Classification System for Lipids” based on well-defined chemical and biochemical principles and using an ontology that is extensible, flexible, and scalable. This classification system, which is compatible with contemporary databasing and informatics needs, has now been accepted internationally and widely adopted. In response to considerable attention and requests from lipid researchers from around the globe and in a variety of fields, the comprehensive classification system has undergone significant revisions over the last few years to more fully represent lipid structures from a wider variety of sources and to provide additional levels of detail as necessary. The details of this classification system are reviewed and updated and are presented here, along with revisions to its suggested nomenclature and structure-drawing recommendations for lipids. In an effort to support the growing field of lipidomics and establish the importance of lipids as a major class of biomolecules, the International Lipid Classification and Nomenclature Committee (ILCNC) developed a “Comprehensive Classification System for Lipids” that was published in 2005 (1Fahy E. Subramaniam S. Brown H.A. Glass C.K. Merrill Jr., A.H. Murphy R.C. Raetz C.R. Russell D.W. Seyama Y. Shaw W. al et A comprehensive classification system for lipids.J. Lipid Res. 2005; 46: 839-862Abstract Full Text Full Text PDF PubMed Scopus (1141) Google Scholar). For the purpose of classification, we define lipids as hydrophobic or amphipathic small molecules that may originate entirely or in part by carbanion-based condensations of thioesters (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, saccharolipids, and polyketides) and/or by carbocation-based condensations of isoprene units (prenol lipids and sterol lipids). The comprehensive classification system organizes lipids into these eight well-defined categories (Table 1) that cover eukaryotic and prokaryotic sources. It has been adopted internationally and widely accepted by the lipidomics community. The system is also available online on the LIPID MAPS (2Schmelzer K. Fahy E. Subramaniam S. Dennis E.A. The lipid maps initiative in lipidomics.Methods Enzymol. 2007; 432: 171-183Crossref PubMed Scopus (115) Google Scholar) website (http://www.lipidmaps.org). The comprehensive classification system has been under the guidance of the ILCNC, 3The ILCNC currently consists of Dr. Edward A. Dennis, Chair, (US), Dr. Robert C. Murphy (US), Dr. Masahiro Nishijima (Japan), Dr. Christian R. H. Raetz (US), Dr. Takao Shimizu (Japan), Dr. Friedrich Spener (Austria), Dr. Gerrit van Meer (The Netherlands), and Dr. Michael Wakelam (UK). Dr. Shankar Subramaniam serves as Informatics Advisor, and Dr. Eoin Fahy serves as Director. Meetings were held May 7, 2006 and May 4, 2008 in La Jolla, CA. which meets periodically to propose changes and updates to classification, nomenclature, and structural representation.TABLE 1Lipid categories of the comprehensive classification system and the number of structures in the LIPID MAPS databaseCategoryAbbreviationStructures in DatabaseFatty acylsFA2678GlycerolipidsGL3009GlycerophospholipidsGP1970SphingolipidsSP620Sterol LipidsST1744Prenol LipidsPR610SaccharolipidsSL11PolyketidesPK132 Open table in a new tab The initial version of the comprehensive classification system was more heavily focused on mammalian lipids, reflecting a bias toward the experimental interests of the LIPID MAPS Consortium (2Schmelzer K. Fahy E. Subramaniam S. Dennis E.A. The lipid maps initiative in lipidomics.Methods Enzymol. 2007; 432: 171-183Crossref PubMed Scopus (115) Google Scholar). However, due to considerable attention and requests from lipid researchers in a variety of fields, the classification system has now been extended to more fully represent lipid structures from nonmammalian sources, such as plants, bacteria, and fungi. For example, two new main classes (Glycosyldiradylglycerols and Glycosylmonoradylglycerols) have been added to the Glycerolipids category to accommodate key plant structural lipids, such as the sulfoquinovosyldiacylglycerols (3Norman H.A. Mischke C.F. Allen B. Vincent J.S. Semi-preparative isolation of plant sulfoquinovosyldiacylglycerols by solid phase extraction and HPLC procedures.J. Lipid Res. 1996; 37: 1372-1376Abstract Full Text PDF PubMed Google Scholar) found in chloroplasts. Also, the list of subclasses under the Sterols main class has been expanded to include a set of 15 different core structures (Ergosterols, Gorgosterols, Furostanols, etc.), which provide a structure-based classification of these molecules that span multiple phyla. Another key development has been the adoption of existing hierarchies (4Buckingham J. Dictionary of Natural Products on CD-ROM, Version 6.1. Chapman & Hall, London1998Crossref Google Scholar) for the Polyketide category and Prenol Lipids/Isoprenoids subclasses where the majority of these molecules are derived from natural product sources and have been studied intensively from a pharmaceutical and ecological standpoint. This in turn has necessitated the expansion of the number of existing classification levels (category, main class, and subclass) to accommodate an additional level of stratification in the case of the C10 to C30 isoprenoid subclasses that now contain entries at a fourth level of detail. The “LM_ID” identifier, whose format provides a systematic means of assigning a unique identification to each lipid molecule, has accordingly been expanded in length in these particular cases, with an additional two characters being used to describe the fourth level. A detailed overview of the changes and updates to the comprehensive classification system is presented below. As a consequence of adding an extra level of classification detail, the length of the LM_ID identifier was lengthened from 12 characters to 14 in cases where a lipid defined with four levels of classification is being described (Table 2). In this case, characters 9 and 10 specify the level-4 class. It should be emphasized that all lipids that do not require a fourth level of detail (i.e., the vast majority of them) still use a 12-digit LM_ID identifier.TABLE 2Format of LIPID MAPS identifier (LM_ID) in the comprehensive classification systemCharactersDescriptionExampleComments1–2Fixed “LM” designationLMAlways LM3–4Two-letter category codePROne of eight categories5–6Two-digit class code01—7–8Two-digit subclass code03“00” when no subclass9–10Two-digit fourth level code06Only used for lipids with four levelsLast four digitsUnique four-character identifier within subclass or within fourth level0002First two of the last four digits are letters in the case of the Glycosphingolipid subclasses Open table in a new tab In keeping with the theme of having a classification system dictated by molecular structure and function, the sterol lipid subclasses Phytosterols, Marine sterols, and Fungal sterols were retired because these refer to the lipid source (marine) or biological kingdom (plants and fungi). It is possible to identify a particular sterol in more than one of these three sources. These subclasses have been replaced by a new set of subclasses based on the carbon skeleton of the sterol core structure (Ergosterols, Gorgosterols, Furostanols, etc.). The details are outlined under the Sterol Lipids section below, and the complete description of this category can be found on the LIPID MAPS website 4Supplementary tables that provide the complete list of the classes, subclasses, and fourth class level (where applicable) of each of the eight categories of lipids are available on the LIPID MAPS website at http://www.lipidmaps.org. (http://www.lipidmaps.org). The natural products chemistry and medicinal chemistry literature describes tens of thousands of molecules that fall under the scope of lipids, based on their biosynthetic origin. In particular, isoprenoids and polyketides from diverse sources, such as plant, fungi, algae, bacteria, and marine invertebrates, are well documented and have been reviewed and classified in detail. The Dictionary of Natural Products (4Buckingham J. Dictionary of Natural Products on CD-ROM, Version 6.1. Chapman & Hall, London1998Crossref Google Scholar), a database available from Chapman and Hall/CRC (http://dnp.chemnetbase.com), has a classification hierarchy that covers polyketides and isoprenoids in depth. The LIPID MAPS comprehensive classification system has now incorporated some of these hierarchies relevant to natural products, with a view to covering both mammalian and nonmammalian lipids comprehensively. 3The ILCNC currently consists of Dr. Edward A. Dennis, Chair, (US), Dr. Robert C. Murphy (US), Dr. Masahiro Nishijima (Japan), Dr. Christian R. H. Raetz (US), Dr. Takao Shimizu (Japan), Dr. Friedrich Spener (Austria), Dr. Gerrit van Meer (The Netherlands), and Dr. Michael Wakelam (UK). Dr. Shankar Subramaniam serves as Informatics Advisor, and Dr. Eoin Fahy serves as Director. Meetings were held May 7, 2006 and May 4, 2008 in La Jolla, CA. It was recognized that additional levels of stratification were required to classify certain types of lipids and that the current three-level system of category/main class/subclass needed to be expanded. For example, in the Prenol Lipids category, 3The ILCNC currently consists of Dr. Edward A. Dennis, Chair, (US), Dr. Robert C. Murphy (US), Dr. Masahiro Nishijima (Japan), Dr. Christian R. H. Raetz (US), Dr. Takao Shimizu (Japan), Dr. Friedrich Spener (Austria), Dr. Gerrit van Meer (The Netherlands), and Dr. Michael Wakelam (UK). Dr. Shankar Subramaniam serves as Informatics Advisor, and Dr. Eoin Fahy serves as Director. Meetings were held May 7, 2006 and May 4, 2008 in La Jolla, CA. the Sesquiterpene C15 subclass contains ∼90 known variants based on their carbon skeletons (Bisabolanes, Germacranes, etc.). A fourth level of detail has been added to the LIPID MAPS comprehensive classification system to handle cases such as these. In response to worldwide interest in the comprehensive classification system for lipids, the scope has been expanded to cover lipids from nonmammalian sources, such as plants, bacteria, fungi, algae, and marine organisms. To accomplish this, several new lipid classes have been added, such as fatty acyl glycosides, glycosyldiradylglycerols, and various sterol skeletons. The Polyketide category has also been revised comprehensively. 3The ILCNC currently consists of Dr. Edward A. Dennis, Chair, (US), Dr. Robert C. Murphy (US), Dr. Masahiro Nishijima (Japan), Dr. Christian R. H. Raetz (US), Dr. Takao Shimizu (Japan), Dr. Friedrich Spener (Austria), Dr. Gerrit van Meer (The Netherlands), and Dr. Michael Wakelam (UK). Dr. Shankar Subramaniam serves as Informatics Advisor, and Dr. Eoin Fahy serves as Director. Meetings were held May 7, 2006 and May 4, 2008 in La Jolla, CA. The nomenclature of lipids falls into two main categories: systematic names and common or trivial names. The latter includes abbreviations that are a convenient way to define acyl/alkyl chains in acylglycerols, sphingolipids, and glycerophospholipids and synonyms such as “phosphatidyl” for “glycerophospho.” The generally accepted guidelines for lipid systematic names have been defined by the International Union of Pure and Applied Chemists and the International Union of Biochemistry and Molecular Biology (IUPAC-IUBMB) Commission on Biochemical Nomenclature (http://www.chem.qmul.ac.uk/iupac/) (5IUPAC-IUB Commission on Biochemical Nomenclature (CBN). The nomenclature of lipids (Recommendations 1976). 1977. Eur. J. Biochem. 79: 11–21; 1977. Hoppe-Seylers Z. Physiol. Chem. 358: 617–631; 1977. Lipids 12: 455–468; 1977. Mol. Cell. Biochem. 17: 157–171; 1978. Chem. Phys. Lipids 21: 159–173; 1978. J. Lipid Res. 19: 114–128; 1978. Biochem. J. 171: 21–35. (http://www.chem.qmul.ac.uk/iupac/lipid/).Google Scholar, 6I. U. P. A. C-I. U. B. Joint Commission on Biochemical Nomenclature (JCBN). Nomenclature of glycolipids. (Recommendations 1997) 2000. Adv. Carbohydr. Chem. Biochem. 55: 311–326; 1988. Carbohydr. Res. 312: 167–175; 1998. Eur. J. Biochem. 257: 293–298; 1999. Glycoconjugate J. 16:1–6; 1999. J. Mol. Biol. 286: 963–970; 1997. Pure Appl. Chem. 69: 2475–2487. (http://www.chem.qmul.ac.uk/iupac/misc/glylp.html)Google Scholar, 7I. U. P. A. C-I. U. B. Joint Commission on Biochemical Nomenclature (JCBN). Nomenclature of prenols. (Recommendations 1987) 1987. Eur. J. Biochem. 167: 181–184. (http://www.chem.qmul.ac.uk/iupac/misc/prenol.html)Google Scholar, 8I. U. P. A. C-I. U. B. Joint Commission on Biochemical Nomenclature (JCBN). Nomenclature of steroids (Recommendations 1989) 1989. Eur. J. Biochem. 186: 429–458. (http://www.chem.qmul.ac.uk/iupac/steroid/).Google Scholar). In response to several requests from knowledgeable lipid experts, abbreviations for Glycerophospholipid classes (see http://www.lipidmaps.org for GP category 3The ILCNC currently consists of Dr. Edward A. Dennis, Chair, (US), Dr. Robert C. Murphy (US), Dr. Masahiro Nishijima (Japan), Dr. Christian R. H. Raetz (US), Dr. Takao Shimizu (Japan), Dr. Friedrich Spener (Austria), Dr. Gerrit van Meer (The Netherlands), and Dr. Michael Wakelam (UK). Dr. Shankar Subramaniam serves as Informatics Advisor, and Dr. Eoin Fahy serves as Director. Meetings were held May 7, 2006 and May 4, 2008 in La Jolla, CA.) have been changed now in the comprehensive classification system to the more universally used two-letter “PC/PE/PS/PA/PI” format. Consequently, glycerophospholipids in the LIPID MAPS structure database and LIPID MAPS standards database as well as all the Glycerophospholipids drawing tools and mass spectrometry prediction tools have been updated to conform to this new abbreviation format (Table 3).TABLE 3Changes in abbreviations for Glycerophospholipids in the comprehensive classification systemClassSynonymOldNewGlycerophosphocholinesPhosphatidylcholinesGPChoPCaFor abbreviations of monoradyglycerophospholipids (lysophospholipids), LPX may be used, for example, LPC, LPE, LPA, etc.GlycerophosphoethanolaminesPhosphatidylethanolaminesGPEtnPEGlycerophosphoserinesPhosphatidylserinesGPSerPSGlycerophosphoglycerolsPhosphatidylglycerolsGPGroPGGlycerophosphoglycerophosphatesPhosphatidylglycerol phosphatesGPGroPPGPGlycerophosphoinositolsPhosphatidylinositolsGPInsPIGlycerophosphoinositol monophosphatesPhosphatidylinositol phosphatesGPInsPPIPGlycerophosphoinositol bis-phosphatesPhosphatidylinositol bis-phosphatesGPInsP2PIP2Glycerophosphoinositol For abbreviations of monoradyglycerophospholipids (lysophospholipids), LPX may be used, for example, LPC, LPE, LPA, Open table in a new tab The LIPID MAPS Consortium has considerable effort to establish guidelines for drawing lipid structures in a and and lipids are to which to the use of unique that more than the lipid community. the structure-drawing is the in molecular of lipids. However, classes of lipids well as for structure-drawing due to their A of structure-drawing tools has been developed and that of systematic and abbreviations E. Subramaniam S. LIPID MAPS online tools for lipid Res. 2007; PubMed Scopus Google Scholar). The structures may be and in a variety of of the structure-drawing tools for fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterols are available in the section of the LIPID MAPS website (http://www.lipidmaps.org). of the structures are in the importance of these molecules in and is to have a database of lipids with a defined ontology that is extensible, flexible, and scalable. The ontology of lipids classification, nomenclature, structure and structural of all in the have developed a available comprehensive database of lipid structures of lipid molecules from existing and from the LIPID MAPS This database Fahy E. Brown A. Dennis E.A. Glass C.K. Merrill Jr., A.H. Murphy R.C. Raetz C.R. Russell D.W. al et LIPID MAPS structure Res. 2007; PubMed Scopus Google Scholar, E. R. A. J. Y. Subramaniam S. for lipidomics.Methods Enzymol. 2007; 432: PubMed Scopus Google Scholar), in to as the to and of lipid also contains systematic classification, nomenclature, and structure of lipids along with mass where than lipid molecules are now available on the LIPID MAPS and these have been adopted by the for as well as the of and database structures have been classified and to LIPID MAPS A number of different molecular such as and the and are and nomenclature of these molecules are also The database is and the include and structure-based the category, the subclasses and have been changed to and to accommodate The names of the fatty subclasses and have been to and A new acyl main class has been added to cover the number of found in bacteria, and marine of natural of fatty and PubMed Scopus Google Scholar, and of the natural PubMed Scopus Google Scholar). subclasses include acyl of and and The Glycerolipids category was to include two new main classes (Glycosyldiradylglycerols and Glycosylmonoradylglycerols) that contain key plant structural lipids, such as the found in chloroplasts. The existing subclasses were to the that is to the of on the for and of structures in the LIPID MAPS structure database have been For with two different two different structural are for with three different different of drawing all possible structural an is used as a A along with the number of possible is to the abbreviation and and a unique LM_ID is of this format is the The structure to the LM_ID on the LIPID MAPS website to the in the and the is to all in the are also cases within the and classes where are due to by certain of both the or to and where the of the at is by the acyl from the of to the at or can an In such cases when a is can be with a for example, or the is with a for example, It should be that the two-letter abbreviation or all possible types of lipid for example, having and The is by the for example, and the by the for example, The to the classes within the Glycerophospholipids In cases where is and is abbreviations such as and may be used, where the within refer to the number of and of all the For the Glycerophospholipids category, the subclass has been replaced by the more due to the that in are the in H.A. J.S. S. in and PubMed Scopus Google Scholar). updates have been for the Glycerophospholipid The lipids class has been replaced by the class to of with than As we have changed to two-letter abbreviations to describe glycerophospholipids in are abbreviations for all molecular of their These names to and are used widely in lipid as to systematic names. This format one or two chains where the structures of the chains are within is at the carbon of and the is at the In cases of molecules with at of the and of the at the the of is to the abbreviation and the abbreviation format is for molecules with at the carbon of the the of is to the and the structure is with In cases where is and is such as may be used to of and for all and are by an or identifier, as in and In the latter case, the an at of and a at the or may be with a in the for example, The “phosphatidyl” is used to refer to classes all types of chains and not acyl as was by guidelines (5IUPAC-IUB Commission on Biochemical Nomenclature (CBN). The nomenclature of lipids (Recommendations 1976). 1977. Eur. J. Biochem. 79: 11–21; 1977. Hoppe-Seylers Z. Physiol. Chem. 358: 617–631; 1977. Lipids 12: 455–468; 1977. Mol. Cell. Biochem. 17: 157–171; 1978. Chem. Phys. Lipids 21: 159–173; 1978. J. Lipid Res. 19: 114–128; 1978. Biochem. J. 171: 21–35. (http://www.chem.qmul.ac.uk/iupac/lipid/).Google Scholar). The classification is from that in the in this (2Schmelzer K. Fahy E. Subramaniam S. Dennis E.A. The lipid maps initiative in lipidomics.Methods Enzymol. 2007; 432: 171-183Crossref PubMed Scopus (115) Google Scholar). of is that for of the Glycosphingolipid subclasses, the structure of the is known the structure of the is In these cases, the last two digits of the LIPID MAPS LM_ID identifier are as to an and the and fourth last digits are a different two-letter identifier for unique within that For example, in the subclass the structure is an LM_ID of where the digits specify the unique and the digits a the has a and is a LM_ID of The Sterol lipids subclasses Phytosterols, Marine sterols, and Fungal sterols have been and replaced with a set of subclasses (Ergosterols, sterols, Gorgosterols, Furostanols, and that in the of their sterol core structures and cover multiple A. Sterols in marine Scopus Google Scholar, Phytosterols, and their in structural and Lipid Res. PubMed Scopus Google Scholar). The class has been with the and the class now includes and The class has been to the Prenol Lipids category the of the core structure is at with the of the of the Sterol Lipids The subclass of the Prenol lipids category has been added to the class. are a of that are to A. have in of and As the C10 to C30 isoprenoid subclasses now contain entries at a fourth level of detail. The LM_ID contain an extra two digits that specify the fourth level class, for example, the is an LM_ID of The class has been to the Prenol Lipids category the Sterol Lipids For the the main class acyl has been added to cover a variety of from plants, bacteria, and fungi. is the from the plant and from the of Scopus Google Scholar). It should be that this category covers structures in which fatty acyl/alkyl are to a lipids to a are found in their The category was revised and on the classification hierarchy used by the Dictionary of Natural Products (4Buckingham J. Dictionary of Natural Products on CD-ROM, Version 6.1. Chapman & Hall, London1998Crossref Google Scholar). are from bacteria, fungi, plants, and and have been heavily studied by natural products and for The new classification format provides a of the structural within this The toward classification of lipids is the of an ontology that is extensible, flexible, and scalable. be to and represent these molecules in a that is to databasing and The ILCNC the comprehensive classification system in 2005 and has been in and on a to considerable attention and requests from lipid researchers in a variety of fields, the classification system has been extended to more fully represent lipid structures from nonmammalian sources, such as plants, bacteria, and fungi. This system has been internationally accepted and is now widely used in and for The LIPID MAPS classification system has also been adopted by where hierarchies lipids, and have been and by the in format of the In an effort to LIPID MAPS lipid structures are now available on website where have been The classification system is available online where has been with an database of lipids. This in to as the and of lipid also contains systematic classification, nomenclature, and structure of lipids along with mass where structures have been classified and to LIPID MAPS The format of the LM_ID identifier (Table provides a systematic means of the classification hierarchy and assigning a unique identification to each lipid It also for the of new classification in the The database is and the include and structure-based This database is described in detail Fahy E. Brown A. Dennis E.A. Glass C.K. Merrill Jr., A.H. Murphy R.C. Raetz C.R. Russell D.W. al et LIPID MAPS structure Res. 2007; PubMed Scopus Google Scholar, E. R. A. J. Y. Subramaniam S. for lipidomics.Methods Enzymol. 2007; 432: PubMed Scopus Google Scholar). A of lipid structure-drawing tools in the section of the LIPID MAPS has been developed to structure with LIPID MAPS These tools are also of systematic names and detailed and databasing of lipid and has been to and database and to classify and LIPID MAPS These tools be expanded and as the scope of the classification system and over the The the of lipid researchers around the have and to attention in the Classification System for which to be to new and in the lipid The are also to the LIPID MAPS Consortium for their and to Dr. at the of for to this

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.

DNA sequencing analysis typically involves mapping reads to just one reference genome. Mapping against multiple genomes is necessary, however, when the genome of origin requires confirmation. Mapping against multiple genomes is also advisable for detecting contamination or for identifying sample swaps which, if left undetected, may lead to incorrect experimental conclusions. Consequently, we present FastQ Screen, a tool to validate the origin of DNA samples by quantifying the proportion of reads that map to a panel of reference genomes. FastQ Screen is intended to be used routinely as a quality control measure and for analysing samples in which the origin of the DNA is uncertain or has multiple sources.

Epigenetic marking systems confer stability of gene expression during mammalian development. Genome-wide epigenetic reprogramming occurs at stages when developmental potency of cells changes. At fertilization, the paternal genome exchanges protamines for histones, undergoes DNA demethylation, and acquires histone modifications, whereas the maternal genome appears epigenetically more static. During preimplantation development, there is passive DNA demethylation and further reorganization of histone modifications. In blastocysts, embryonic and extraembryonic lineages first show different epigenetic marks. This epigenetic reprogramming is likely to be needed for totipotency, correct initiation of embryonic gene expression, and early lineage development in the embryo. Comparative work demonstrates reprogramming in all mammalian species analysed, but the extent and timing varies, consistent with notable differences between species during preimplantation development. Parental imprinting marks originate in sperm and oocytes and are generally protected from this genome-wide reprogramming. Early primordial germ cells possess imprinting marks similar to those of somatic cells. However, rapid DNA demethylation after midgestation erases these parental imprints, in preparation for sex-specific de novo methylation during gametogenesis. Aberrant reprogramming of somatic epigenetic marks after somatic cell nuclear transfer leads to epigenetic defects in cloned embryos and stem cells. Links between epigenetic marking systems appear to be developmentally regulated contributing to plasticity. A number of activities that confer epigenetic marks are firmly established, while for those that remove marks, particularly methylation, some interesting candidates have emerged recently which need thorough testing in vivo. A mechanistic understanding of reprogramming will be crucial for medical applications of stem cell technology.

Protein kinase B (PKB) is a proto-oncogene that is activated in signaling pathways initiated by phosphoinositide 3-kinase. Chromatographic separation of brain cytosol revealed a kinase activity that phosphorylated and activated PKB only in the presence of phosphatidylinositol-3,4,5-trisphosphate [PtdIns(3,4,5)P3]. Phosphorylation occurred exclusively on threonine-308, a residue implicated in activation of PKB in vivo. PtdIns(3,4,5)P3 was determined to have a dual role: Its binding to the pleckstrin homology domain of PKB was required to allow phosphorylation by the upstream kinase and it directly activated the upstream kinase.

Epigenetic modifications of the genome are generally stable in somatic cells of multicellular organisms. In germ cells and early embryos, however, epigenetic reprogramming occurs on a genome-wide scale, which includes demethylation of DNA and remodeling of histones and their modifications. The mechanisms of genome-wide erasure of DNA methylation, which involve modifications to 5-methylcytosine and DNA repair, are being unraveled. Epigenetic reprogramming has important roles in imprinting, the natural as well as experimental acquisition of totipotency and pluripotency, control of transposons, and epigenetic inheritance across generations. Small RNAs and the inheritance of histone marks may also contribute to epigenetic inheritance and reprogramming. Reprogramming occurs in flowering plants and in mammals, and the similarities and differences illuminate developmental and reproductive strategies.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

Although T cell help for B cells was described several decades ago, it was the identification of CXCR5 expression by B follicular helper T (Tfh) cells and the subsequent discovery of their dependence on BCL6 that led to the recognition of Tfh cells as an independent helper subset and accelerated the pace of discovery. More than 20 transcription factors, together with RNA-binding proteins and microRNAs, control the expression of chemotactic receptors and molecules important for the function and homeostasis of Tfh cells. Tfh cells prime B cells to initiate extrafollicular and germinal center antibody responses and are crucial for affinity maturation and maintenance of humoral memory. In addition to the roles that Tfh cells have in antimicrobial defense, in cancer, and as HIV reservoirs, regulation of these cells is critical to prevent autoimmunity. The realization that follicular T cells are heterogeneous, comprising helper and regulatory subsets, has raised questions regarding a possible division of labor in germinal center B cell selection and elimination.

Caloric restriction (CR) protects against aging and disease, but the mechanisms by which this affects mammalian life span are unclear. We show in mice that deletion of ribosomal S6 protein kinase 1 (S6K1), a component of the nutrient-responsive mTOR (mammalian target of rapamycin) signaling pathway, led to increased life span and resistance to age-related pathologies, such as bone, immune, and motor dysfunction and loss of insulin sensitivity. Deletion of S6K1 induced gene expression patterns similar to those seen in CR or with pharmacological activation of adenosine monophosphate (AMP)-activated protein kinase (AMPK), a conserved regulator of the metabolic response to CR. Our results demonstrate that S6K1 influences healthy mammalian life-span and suggest that therapeutic manipulation of S6K1 and AMPK might mimic CR and could provide broad protection against diseases of aging.