Barcoding cells using cell-surface programmable DNA-binding domains

We develop here a novel approach to barcode large numbers of cells through cell-surface expression of programmable zinc-finger DNA-binding domains (sZFs). We show sZFs enable double-stranded DNA to sequence-specifically label living cells, and also develop a sequential tagging approach to in situ image >3 cell types using just 3 fluorophores. Finally we demonstrate their broad versatility through ability to serve as surrogate reporters and facilitate selective cell capture and targeting

Первый директор БЕН РАН А. Г. Захаров. К 100-летию со дня рождения

The article is dedicated to the memory of the first director of the Library of Natural Sciences of the Russian Academy of Sciences (before 1991, the USSR Academy of Sciences). The Library for Natural Sciences was established in 1973 on the basis of the Sector for Special Libraries (in charge of collection development of Moscow research institutes and of their union catalog maintenance). The Library for Natural Sciences was conceived as an information library center focused on science and research information support based on modern technologies. Alexander Grigorievich Zakharov, newly-retired military professional, Lieutenant General, headed the library. In the shortest time possible, Alexander Zakharov built the centralized library system headed by the Library for Natural Sciences and meeting the demands of the time. For many years the Library’s Centralized Library System has been the largest and most developed network; the Library has been the leader in library automation based on the newest computer and network technologies. The authors have been working for the Library for over 40 years, and over 30 years under the leadership of Alexander G. Zakharov. They review the main stages of Zakharov’s career: the Great Patriotic War (he went through the war from beginning to end), his service at cosmodrome of Baikonur (launch operations, including support of Yury Gagarin’s flight), his work in the Library for Natural Sciences.Статья посвящена памяти первого директора Библиотеки по естественным наукам (БЕН) Российской академии наук (до 1991 г. – БЕН АН СССР). БЕН была образована в 1973 г. на базе Сектора сети специальных библиотек (занимался комплектованием библиотек академических институтов Москвы и ведением сводного каталога их фондов). БЕН создавалась как информационно-библиотечный центр, основная задача которого – информационное обеспечение учёных на основе современных технологий. Директором БЕН был назначен Александр Григорьевич Захаров – профессиональный военный, незадолго до назначения вышедший в отставку в звании генерал-лейтенанта. В кратчайшие сроки он создал централизованную библиотечную систему (ЦБС) во главе с БЕН, отвечающую самым строгим современным требованиям. На протяжении многих лет ЦБС БЕН оставалась наиболее крупной и развитой сетью библиотек страны, а БЕН – одной из ведущих библиотек в области автоматизации информационно-библиотечных процессов на основе новейших компьютерных и сетевых технологий. Авторы проработали в БЕН более 40 лет, из них – более 30 под руководством А. Г. Захарова. В статье рассмотрены основные этапы жизненного пути Александра Григорьевича: Великая Отечественная война (прошёл её от начала до конца), служба на космодроме Байконур (подготовка запуска космических кораблей, в том числе полёта Ю. А. Гагарина), работа в БЕН

Effective selection of informative SNPs and classification on the HapMap genotype data

<p>Abstract</p> <p>Background</p> <p>Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to identify the correct source population of an individual. For efficient population identification with the HapMap genotype data, as few informative SNPs as possible are required from the original 4 million SNPs. Recently, Park <it>et al.</it> (2006) adopted the nearest shrunken centroid method to classify the three populations, i.e., Utah residents with ancestry from Northern and Western Europe (CEU), Yoruba in Ibadan, Nigeria in West Africa (YRI), and Han Chinese in Beijing together with Japanese in Tokyo (CHB+JPT), from which 100,736 SNPs were obtained and the top 82 SNPs could completely classify the three populations.</p> <p>Results</p> <p>In this paper, we propose to first rank each feature (SNP) using a ranking measure, i.e., a modified t-test or F-statistics. Then from the ranking list, we form different feature subsets by sequentially choosing different numbers of features (e.g., 1, 2, 3, ..., 100.) with top ranking values, train and test them by a classifier, e.g., the support vector machine (SVM), thereby finding one subset which has the highest classification accuracy. Compared to the classification method of Park <it>et al.</it>, we obtain a better result, i.e., good classification of the 3 populations using on average 64 SNPs.</p> <p>Conclusion</p> <p>Experimental results show that the both of the modified t-test and F-statistics method are very effective in ranking SNPs about their classification capabilities. Combined with the SVM classifier, a desirable feature subset (with the minimum size and most informativeness) can be quickly found in the greedy manner after ranking all SNPs. Our method is able to identify a very small number of important SNPs that can determine the populations of individuals.</p

Barcoding cells using cell-surface programmable DNA-binding domains

We report an approach to barcode cells through cell-surface expression of programmable zinc-finger DNA-binding domains (surface zinc fingers, sZFs). We show that sZFs enable sequence-specific labeling of living cells by dsDNA, and we develop a sequential labeling approach to image more than three cell types in mixed populations using three fluorophores. We demonstrate the versatility of sZFs through applications in which they serve as surrogate reporters, function as selective cell capture reagents and facilitate targeted cellular delivery of viruses

De novo assembly of a transcriptome from the eggs and early embryos of Astropecten aranciacus

Starfish have been instrumental in many fields of biological and ecological research. Oocytes of Astropecten aranciacus, a common species native to the Mediterranean Sea and the East Atlantic, have long been used as an experimental model to study meiotic maturation, fertilization, intracellular Ca2+ signaling, and cell cycle controls. However, investigation of the underlying molecular mechanisms has often been hampered by the overall lack of DNA or protein sequences for the species. In this study, we have assembled a transcriptome for this species from the oocytes, eggs, zygotes, and early embryos, which are known to have the highest RNA sequence complexity. Annotation of the transcriptome identified over 32,000 transcripts including the ones that encode 13 distinct cyclins and as many cyclin-dependent kinases (CDK), as well as the expected components of intracellular Ca2+ signaling toolkit. Although the mRNAs of cyclin and CDK families did not undergo significant abundance changes through the stages from oocyte to early embryo, as judged by real-time PCR, the transcript encoding Mos, a negative regulator of mitotic cell cycle, was drastically reduced during the period of rapid cleavages. Molecular phylogenetic analysis using the homologous amino acid sequences of cytochrome oxidase subunit I from A. aranciacus and 30 other starfish species indicated that Paxillosida, to which A. aranciacus belongs, is not likely to be the most basal order in Asteroidea. Taken together, the first transcriptome we assembled in this species is expected to enable us to perform comparative studies and to design gene-specific molecular tools with which to tackle long-standing biological questions