Latest Articles Include:
- What health reform means for innovation
- Nature Biotechnology 28(4):293 (2010)
Nature Biotechnology | Editorial What health reform means for innovation Journal name:Nature BiotechnologyVolume:28,Page:293Year published:(2010)DOI:doi:10.1038/nbt0410-293 Healthcare reform will not only boost biotech investment by massively expanding the US drug market, but also change the dynamics of biotech innovation in the longer term. View full text Additional data - Safety signal dampens reception for mipomersen antisense
- Nature Biotechnology 28(4):295-297 (2010)
In February, Isis announced its cholesterol-lowering antisense therapy, mipomersen, had met its endpoints in a phase 3 trial of 124 patients with heterozygous familial hypercholesterolemia (FH) and coronary artery disease. The news ought to have sent share prices soaring, as mipomersen, if approved, could rival blockbuster statin drugs. - Bt brinjal splits Indian cabinet
- Nature Biotechnology 28(4):296 (2010)
India's prime minister, Manmohan Singh, has intervened in the political wrangle that erupted over a genetically modified (GM) eggplant strain due for commercial release. Approval of the locally developed Bacillus thuringiensis (Bt) variety appeared imminent, but on February 9, the minister of environment and forests, Jairam Ramesh, responded to public opposition by declaring an indefinite moratorium on the approval of Bt brinjal, as it is known locally, on the grounds of insufficient data to confirm that it is safe to eat. - Orphans on the rise
- Nature Biotechnology 28(4):297 (2010)
The number of drug approvals for orphan indications has doubled in recent years, according to a report from the Tufts Center for the Study of Drug Development. The independent, nonprofit research group at Tufts University in Boston, found that between 2000 and 2002 the US Food and Drug Administration (FDA) approved 208 orphan drugs, and the number climbed to 425 between 2006 and 2008. - Pharma's Asian syndicate
- Nature Biotechnology 28(4):297 (2010)
Three big pharmas—Pfizer, Merck, and Eli Lilly—are pooling their resources to set up an independent nonprofit company to spur research into innovative treatments for cancers common in Asian populations. The new Asian Cancer Research Group (ACRG) will build an open-access pharmacogenomic cancer database, which will be made publicly available to researchers in the field. - Roche plans for more convenient-to-use Herceptin and Rituxan
- Nature Biotechnology 28(4):298 (2010)
In January, the Swiss drug manufacturer Roche announced a 190 million ($175 million) investment to manufacture a device that enables the subcutaneous injection of biologics, notably its blockbuster antibody cancer drug Herceptin (trastuzumab), by combining it with an enzyme that opens up channels in the extracellular matrix. San Diego–based Halozyme Therapeutics is supplying the enzyme, a recombinant hyaluronidase it has developed. - US pharmacies broaden access to pharmacogenetic tests
- Nature Biotechnology 28(4):299-300 (2010)
Medco Health Solutions, the pharmacy services manager, bolstered its commitment to personalized medicine in February, with the acquisition of DNA Direct, a San Francisco–based genomic medicine company. The terms of the deal were not disclosed, but Medco of Franklin Lakes, New Jersey, has now incorporated more than 2,000 genetic and molecular tests into its books. - RNAi patent jolt
- Nature Biotechnology 28(4):300 (2010)
The US Patent and Trademark Office has issued a patent for detection of RNA-mediated gene silencing to Sir David Baulcombe, University of Cambridge, and Andrew Hamilton, University of Glasgow, over a decade after their gene silencing findings in plants were first reported (Science 286, 950–952, 1999). "The new patent has implications beyond plants," says Jan Chojecki, CEO of Plant Bioscience Limited (PBL), of Norwich, the tech transfer company that owns the patents. - Court voids HGS gene patent
- Nature Biotechnology 28(4):300 (2010)
In the first British case to deal with the validity of a gene sequence patent, a UK Court of Appeal struck down a patent held by Rockville, Maryland–based Human Genome Sciences (HGS) for lack of industrial application. The dispute in Eli Lilly & Company v Human Genome Sciences, Inc. - Public companies get creative in raising finance
- Nature Biotechnology 28(4):301-302 (2010)
The beginning of March saw that rarest of events, a substantial secondary public offering of stock from a European biotech company. Ablynx, of Ghent, Belgium, raised 50 million to fund a range of new and continuing clinical programs of its single-domain antibody fragment (or 'nanobody') products. - Erythropoietins locked into risk management program
- Nature Biotechnology 28(4):303 (2010)
The US Food and Drug Administration (FDA) and the makers of erythropoietin stimulating agents (ESAs) have agreed on a formal strategy to reduce the risks associated with these drugs. Starting in March, drug makers will operate under a risk evaluation and mitigation strategy (REMS) requiring healthcare providers who prescribe the drugs for cancer patients to register with the drug makers and enroll in a training program on their use. - Stem cells to order
- Nature Biotechnology 28(4):303 (2010)
The UK Stem Cell Bank (UKSCB) is relocating to a new building, a move that should boost its growing partnership with the private sector. The Potters Bar–based facility keeps quality-controlled, standardized stocks of stem cell lines that it ships to accredited researchers worldwide together with advice on how to use them. - ReNeuron first in stroke
- Nature Biotechnology 28(4):303 (2010)
ReNeuron will be treating the first stroke patients with stem cells later this year in the UK after overcoming a string of regulatory holdups abroad. In February, the Surrey-based company received the go-ahead to start a phase 1 trial from the UK's Gene Therapy Advisory Committee (GTAC) for ReN001, a genetically engineered neural stem cell line originally derived from fetal brain tissue. - EPA releases land-use rule for biofuels to mixed reception
- Nature Biotechnology 28(4):304 (2010)
The US Environmental Protection Agency (EPA) has issued long-awaited regulations governing renewable fuel standards, but the reception in political circles has been frosty. Part of the backlash, from both Republican and Democratic politicians, relates to bipartisan opposition to US climate change legislation of any kind. - Shell's billions to convert Brazilian biomass into fuel
- Nature Biotechnology 28(4):305 (2010)
Oil giant Royal Dutch Shell in February announced a $12 billion joint venture with Brazilian sugarcane-to-ethanol producer Cosan. In a deal that could lead to large-scale production of advanced biofuels, Shell will contribute its Brazilian fuel distribution network and $1. - 2nd-generation GM traits progress
- Nature Biotechnology 28(4):306 (2010)
With 5.6 million new hectares (35%) of transgenic crops, Brazil supplanted Argentina to become the 2nd largest cultivator. - Fresh from the biologic pipeline—2009
- Nature Biotechnology 28(4):307-310 (2010)
Nature Biotechnology | News | News Feature Fresh from the biologic pipeline—2009 * Cormac Sheridan1 Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature BiotechnologyVolume:28,Pages:307–310Year published:(2010)DOI:doi:10.1038/nbt0410-307 Human antibodies take center stage, as they pile up in the list of approved biologics in 2009. Cormac Sheridan reports. View full text Figures at a glance * Figure 1: FDA approvals 1996–2009. * Figure 2: FDA new molecular entities and biologics license applications since 2004 according to therapeutic indication. Tallied numbers may be in more than one indication. Source: Biocentury, BCIQ. Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg PDF files * Supplementary Text and Figures (88K) Supplementary Table 1 Additional data Affiliations * Dublin * Cormac Sheridan - Biotech in a blink
- Nature Biotechnology 28(4):311-314 (2010)
Nature Biotechnology | News | News Feature Biotech in a blink * Ken Garber1 Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature BiotechnologyVolume:28,Pages:311–314Year published:(2010)DOI:doi:10.1038/nbt0410-311 The eye, and particularly the retina, has become a favored testing ground for new biologic drugs. How well novel nucleic acid and cellular therapies work in retinal disease could determine their expansion to other indications. Ken Garber reports. View full text Additional data Affiliations * Ann Arbor, Michigan * Ken Garber - Selling out
- Nature Biotechnology 28(4):315-317 (2010)
- Making the most of GM potatoes
- Nature Biotechnology 28(4):318 (2010)
The recent approval of the Amflora potato by the European Union (EU)—the EU's first registration of a genetically modified (GM) potato in 12 years—has garnered considerable media attention and public controversy. Amflora (EH92-527-1) is a GM potato produced by BASF (Ludwigshafen, Germany) that lacks amylose and instead contains amylopectin (>98%) as the predominant starch1, 2. - Peer-reviewed surveys indicate positive impact of commercialized GM crops
- Nature Biotechnology 28(4):319-321 (2010)
Nature Biotechnology | Opinion and Comment | Correspondence Peer-reviewed surveys indicate positive impact of commercialized GM crops * Janet E Carpenter1 Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature BiotechnologyVolume:28,Pages:319–321Year published:(2010)DOI:doi:10.1038/nbt0410-319 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To the Editor: The benefits of genetically modified (GM) crops continue to be disputed, despite rapid and widespread adoption since their commercial introduction in the United States and Canada in 1995. Last year, 14 million farmers in 25 countries grew GM crops commercially, over 90% of them small farmers in developing countries1. Farmer surveys are a valuable measure of the impact of GM crops. These surveys estimate the technology's performance as it is incorporated into farmer practices, given constraints on time, access to information, differing levels of risk aversion and other factors. This analysis summarizes results from 49 peer-reviewed publications reporting on farmer surveys that compare yields and other indicators of economic performance for adopters and non-adopters of currently commercialized GM crops. The surveys cover GM insect-resistant and herbicide-tolerant crops, which account for >99% of global GM crop area1. Results from 12 countries indicate, with few exceptions, tha! t GM crops have benefitted farmers. The benefits, especially in terms of increased yields, are greatest for the mostly small farmers in developing countries, who have benefitted from the spillover of technologies originally targeted at farmers in industrialized countries. View full text Author information * Author information * Supplementary information Affiliations * PO Box 1008, Boylston, Massachusetts, USA. * Janet E Carpenter Competing financial interests This research was supported by CropLife International. Corresponding author Correspondence to: * Janet E Carpenter (janet.e.carpenter@gmail.com) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (144K) Supplementary Tables 1,2,3 Additional data - A global map of human gene expression
- Nature Biotechnology 28(4):322-324 (2010)
Nature Biotechnology | Opinion and Comment | Correspondence A global map of human gene expression * Margus Lukk1 Search for this author in: * NPG journals * PubMed * Google Scholar * Misha Kapushesky1 Search for this author in: * NPG journals * PubMed * Google Scholar * Janne Nikkilä2 Search for this author in: * NPG journals * PubMed * Google Scholar * Helen Parkinson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Angela Goncalves1 Search for this author in: * NPG journals * PubMed * Google Scholar * Wolfgang Huber1 Search for this author in: * NPG journals * PubMed * Google Scholar * Esko Ukkonen3 Search for this author in: * NPG journals * PubMed * Google Scholar * Alvis Brazma1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:322–324Year published:(2010)DOI:doi:10.1038/nbt0410-322 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To the Editor: Although there is only one human genome sequence, different genes are expressed in many different cell types and tissues, as well as in different developmental stages or diseases. The structure of this 'expression space' is still largely unknown, as most transcriptomics experiments focus on sampling small regions. We have constructed a global gene expression map by integrating microarray data from 5,372 human samples representing 369 different cell and tissue types, disease states and cell lines. These have been compiled in an online resource (http://www.ebi.ac.uk/gxa/array/U133A) that allows the user to search for a gene of interest and find the conditions in which it is over- or underexpressed, or, conversely, to find which genes are over- or underexpressed in a particular condition. An analysis of the structure of the expression space reveals that it can be described by a small number of distinct expression profile classes and that the first three principal components of ! this space have biological interpretations. The hematopoietic system, solid tissues and incompletely differentiated cell types are arranged on the first principal axis; cell lines, neoplastic samples and non-neoplastic primary tissue–derived samples are on the second principal axis; and nervous system is separated from the rest of the samples on the third axis. We also show below that most cell lines cluster together rather than with their tissues of origin. View full text Accession codes * Accession codes * Author information * Supplementary information Referenced accessions ArrayExpress * E-MTAB-62 Author information * Accession codes * Author information * Supplementary information Affiliations * European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. * Margus Lukk, * Misha Kapushesky, * Helen Parkinson, * Angela Goncalves, * Wolfgang Huber & * Alvis Brazma * Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland * Janne Nikkilä * Department of Computer Science, University of Helsinki, Helsinki, Finland. * Esko Ukkonen Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Alvis Brazma (brazma@ebi.ac.uk) Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (16M) Supplementary Figs. 1–6 and Supplementary Methods Additional data - Empirical analysis of major stem cell patent cases: the role of universities
- Nature Biotechnology 28(4):325-328 (2010)
Nature Biotechnology | Opinion and Comment | Patents Empirical analysis of major stem cell patent cases: the role of universities * Ann E Mills1 Search for this author in: * NPG journals * PubMed * Google Scholar * Patti M Tereskerz1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:325–328Year published:(2010)DOI:doi:10.1038/nbt0410-325 A study of stem cell patent litigation sheds light on the current patent reform debate. View full text Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Ann E. Mills and Patti M. Tereskerz are at the University of Virginia Center for Biomedical Ethics and Humanities, Program in Ethics and Policy in Health Systems, Charlottesville, Virginia, USA. Competing financial interests A.E.M. and P.T. have been consultants for the Biotechnology Industry Organization on the issue that is the subject of this article. Corresponding author Correspondence to: * Ann E Mills (amh2r@virginia.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (144K) Supplementary Tables 1–7 Additional data - Recent patent applications in high-throughput drug screening
- Nature Biotechnology 28(4):329 (2010)
Table 1 - Broad-spectrum defense against plant pathogens
- Nature Biotechnology 28(4):330-331 (2010)
Transfer of a pattern-recognition immune receptor to a crop confers resistance to several bacterial pathogens. - Antagonizing metastasis
- Nature Biotechnology 28(4):331-332 (2010)
Therapeutic inhibition of a microRNA reduces metastasis formation in a mouse model of breast cancer. - Stem cell biologists sure play a mean pinball
- Nature Biotechnology 28(4):333-335 (2010)
Mouse fibroblasts are reprogrammed to functional neurons by expression of a few transcription factors. - RNA interference in three humans
- Nature Biotechnology 28(4):335 (2010)
Many animal studies have shown the therapeutic potential of using small interfering RNAs (siRNAs) to reduce expression of target genes. Although clinical trials with siRNA are underway for a range of diseases1, it has not yet been demonstrated that delivery of siRNA can trigger RNA interference (RNAi) in humans. - Research highlights
- Nature Biotechnology 28(4):336 (2010)
- Analyzing 'omics data using hierarchical models
- Nature Biotechnology 28(4):337-340 (2010)
Nature Biotechnology | Computational Biology | Primer Analyzing 'omics data using hierarchical models * Hongkai Ji1 Search for this author in: * NPG journals * PubMed * Google Scholar * X Shirley Liu2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume:28,Pages:337–340Year published:(2010)DOI:doi:10.1038/nbt.1619 Hierarchical models provide reliable statistical estimates for data sets from high-throughput experiments where measurements vastly outnumber experimental samples. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Hongkai Ji is in the Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA * X. Shirley Liu is in the Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, Massachusetts, USA. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Hongkai Ji (hji@jhsph.edu) or * X Shirley Liu (xsliu@jimmy.harvard.edu) Additional data - Therapeutic silencing of miR-10b inhibits metastasis in a mouse mammary tumor model
Ma L Reinhardt F Pan E Soutschek J Bhat B Marcusson EG Teruya-Feldstein J Bell GW Weinberg RA - Nature Biotechnology 28(4):341-347 (2010)
Nature Biotechnology | Research | Article Therapeutic silencing of miR-10b inhibits metastasis in a mouse mammary tumor model * Li Ma1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Ferenc Reinhardt1 Search for this author in: * NPG journals * PubMed * Google Scholar * Elizabeth Pan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Jürgen Soutschek3 Search for this author in: * NPG journals * PubMed * Google Scholar * Balkrishen Bhat3 Search for this author in: * NPG journals * PubMed * Google Scholar * Eric G Marcusson3 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie Teruya-Feldstein4 Search for this author in: * NPG journals * PubMed * Google Scholar * George W Bell1 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert A Weinberg1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:341–347Year published:(2010)DOI:doi:10.1038/nbt.1618Received11 January 2010Accepted01 March 2010Published online28 March 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg MicroRNAs (miRNAs) are increasingly implicated in the regulation of metastasis. Despite their potential as targets for anti-metastatic therapy, miRNAs have only been silenced in normal tissues of rodents and nonhuman primates. Therefore, the development of effective approaches for sequence-specific inhibition of miRNAs in tumors remains a scientific and clinical challenge. Here we show that systemic treatment of tumor-bearing mice with miR-10b antagomirs—a class of chemically modified anti-miRNA oligonucleotide—suppresses breast cancer metastasis. Both in vitro and in vivo, silencing of miR-10b with antagomirs significantly decreases miR-10b levels and increases the levels of a functionally important miR-10b target, Hoxd10. Administration of miR-10b antagomirs to mice bearing highly metastatic cells does not reduce primary mammary tumor growth but markedly suppresses formation of lung metastases in a sequence-specific manner. The miR-10b antagomir, which is well tolerate! d by normal animals, appears to be a promising candidate for the development of new anti-metastasis agents. View full text Figures at a glance * Figure 1: Antagomir-10b can be directly delivered to tumor cells in vitro and can inhibit cell motility and invasiveness. () Real-time RT-PCR of miR-10b in cultured 4T1 cells treated with PBS or antagomir-10b. () Immunoblotting of Hoxd10 in 4T1 cells treated with PBS or antagomir-10b. Full-length blots and molecular weight markers are presented in Supplementary Figure 6. () Transwell migration assay and Matrigel invasion assay of 4T1 cells treated with PBS or antagomir-10b. () Growth curves of 4T1 cells treated with PBS or antagomir-10b. () Real-time RT-PCR of Hoxd10 in cultured 4T1 cells transfected with Hoxd10 siRNA or control oligonucleotides. () Transwell migration assay and Matrigel invasion assay of control siRNA- or Hoxd10 siRNA-transfected 4T1 cells that are treated with either antagomir-10b or the vehicle (PBS). A representative experiment is shown in triplicate along with s.e.m. in , and –. * Figure 2: The metastasis-suppressing effect of antagomir-10b is sequence-specific. () Real-time RT-PCR of miR-10b in primary breast tumors (left panel) and livers (right panel) of 4T1 tumor-bearing mice treated with antagomir-10b or antagomir-10b_mm. Data are presented as mean ± s.e.m. (n = 6 mice in each group; each data point represents the mean expression value of triplicates of the sample from one mouse). () Immunoblotting of Hoxd10 in primary breast tumors of 4T1 tumor-bearing mice treated with antagomir-10b or antagomir-10b_mm. SE: short exposure; LE: long exposure. Full-length blots and molecular weight markers are presented in Supplementary Figure 6. () Primary tumor weight of 4T1 tumor-bearing mice treated with antagomir-10b or antagomir-10b_mm, at 4 weeks after orthotopic implantation. (,) Brightfield imaging (, scale bars, 800 μm) and H&E staining (, scale bars, 200 μm) of the lungs from 4T1 tumor-bearing mice treated with antagomir-10b or antagomir-10b_mm, at 4 weeks after orthotopic implantation. Arrows indicate lung metastases. (,) Number ! of visible lung metastases () and metastasis index ( = metastasis number divided by primary tumor weight, ) in 4T1 tumor-bearing mice treated with antagomir-10b or antagomir-10b_mm, at 4 weeks after orthotopic implantation. Data in , and are presented as mean ± s.e.m. (n = 9 mice per group). * Figure 3: 'Sponge'-mediated silencing of miR-10b in tumor cells is sufficient to inhibit metastasis. () Real-time RT-PCR of miR-10b in 4T1 cells infected with the miR-10b sponge or control sponge. A representative experiment is shown in triplicate along with s.e.m. () Weight of primary mouse mammary tumors formed by 4T1 cells infected with the miR-10b sponge or control sponge. (,) Brightfield imaging and H&E staining of the lungs () and number of visible lung metastases () in mice bearing 4T1 cells infected with the miR-10b sponge or control sponge, at 4 weeks after orthotopic implantation. Arrows indicate lung metastases. Scale bars, 800 μm for brightfield imaging; 200 μm for H&E staining. Data in and are presented as mean ± s.e.m. (n = 5 mice in each group). * Figure 4: Antagomir-10b treatment does not affect late stages of the metastatic process. () Schematic representation of the antagomir administration schedule for mice with tail vein injection of 4T1 cells. () Real-time RT-PCR of miR-10b in livers of mice with tail vein injection of 4T1 cells and subsequent treatment with PBS or antagomir-10b. Data are presented as mean ± s.e.m. (n = 6 mice in each group; each data point represents the mean expression value of triplicates of the sample from one mouse). (,) Brightfield imaging and H&E staining of the lungs () and number of visible lung metastases () in PBS- or antagomir-10b–treated mice at day 19 after tail vein injection of 4T1 cells. Scale bars, 800 μm for brightfield imaging; 200 μm for H&E staining. Data in are presented as mean ± s.e.m (n = 6 mice in each group). * Figure 5: Toxicity assessment following intravenous delivery of antagomir-10b in normal mice. () Real-time RT-PCR of miR-10b in normal BALB/c mice after treatment with PBS or six doses of 50 mg/kg antagomir-10b or antagomir-10b_mm. Data are presented as mean ± s.e.m. (n = 6 mice in each group; each data point represents the mean expression value of triplicates of the sample from one mouse). () Total body weight was measured twice a week during the study. () H&E-stained sections of liver samples. Arrows indicate Kupffer cell macrophages. The circle indicates occasional lobular lymphocytes. Scale bars, 30 μm. (,) White blood cell () and lymphocyte () count. Data in , and are presented as mean ± s.e.m. (n = 5 mice in each group). Author information * Abstract * Author information * Supplementary information Affiliations * Whitehead Institute for Biomedical Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Li Ma, * Ferenc Reinhardt, * Elizabeth Pan, * George W Bell & * Robert A Weinberg * MIT Ludwig Center for Molecular Oncology, Cambridge, Massachusetts, USA. * Li Ma & * Robert A Weinberg * Regulus Therapeutics, Carlsbad, California, USA. * Jürgen Soutschek, * Balkrishen Bhat & * Eric G Marcusson * Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Julie Teruya-Feldstein Contributions R.A.W. supervised research. L.M., J.S. and E.G.M. designed experiments. J.S., B.B. and E.G.M. provided antagomirs and conditions. L.M., F.R. and E.P. performed most of the experiments. E.G.M. led toxicity assessment at Regulus. J.T.-F. performed pathological analysis. G.W.B. contributed to graphics and statistical analysis. L.M. and R.A.W. wrote the manuscript. Competing financial interests J.S., B.B. and E.M. are employees of Regulus Therapeutics. Corresponding author Correspondence to: * Robert A Weinberg (weinberg@wi.mit.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figs. 1–6 Additional data - V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets
Peng H Ruan Z Long F Simpson JH Myers EW - Nature Biotechnology 28(4):348-353 (2010)
Nature Biotechnology | Research | Article V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets * Hanchuan Peng1 Search for this author in: * NPG journals * PubMed * Google Scholar * Zongcai Ruan1 Search for this author in: * NPG journals * PubMed * Google Scholar * Fuhui Long1 Search for this author in: * NPG journals * PubMed * Google Scholar * Julie H Simpson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Eugene W Myers1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:348–353Year published:(2010)DOI:doi:10.1038/nbt.1612Received30 November 2009Accepted08 February 2010Published online14 March 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The V3D system provides three-dimensional (3D) visualization of gigabyte-sized microscopy image stacks in real time on current laptops and desktops. V3D streamlines the online analysis, measurement and proofreading of complicated image patterns by combining ergonomic functions for selecting a location in an image directly in 3D space and for displaying biological measurements, such as from fluorescent probes, using the overlaid surface objects. V3D runs on all major computer platforms and can be enhanced by software plug-ins to address specific biological problems. To demonstrate this extensibility, we built a V3D-based application, V3D-Neuron, to reconstruct complex 3D neuronal structures from high-resolution brain images. V3D-Neuron can precisely digitize the morphology of a single neuron in a fruitfly brain in minutes, with about a 17-fold improvement in reliability and tenfold savings in time compared with other neuron reconstruction tools. Using V3D-Neuron, we demonstra! te the feasibility of building a 3D digital atlas of neurite tracts in the fruitfly brain. View full text Figures at a glance * Figure 1: V3D visualization. () Use of V3D in visualizing a digital model of a fruitfly brain. Magenta voxels: the 3D volumetric image of a fruitfly brain; green voxels: a 3D GAL4 neurite pattern; colored surface objects of irregular shapes: digital models of various brain compartments; colored tree-like surface objects: 3D reconstructed neurons. () Volumetric image rendering speed of V3D visualization engine under synchronous and asynchronous modes. For each image size, both the peak speed (green and yellow bars) and the respective s.d. (black line-ranges) of at least ten speed-test trials are shown. The tests were done on a 64-bit Redhat Linux machine with a GTX280 graphics card. () V3D hierarchical visualization and analysis. Local 3D viewers of different brain regions can be initialized from the global viewer. Local viewers can have their own color maps and surface objects independent of the global viewer. They can also be used to analyze sub-volumes of an image separately. * Figure 2: 3D pinpointing methods of V3D. () 3D pinpointing using two mouse-clicks. The color image is a 3D confocal image of neurons, fluorescently tagged for three different transcriptional factors at the same time, in a fruitfly embryo. A and B: non-parallel rays generated at two viewing angles, corresponding to two mouse-clicks; p: the estimated 3D intersection location that is closest to both A and B. () 3D pinpointing using one mouse-click. p1 to pN: the progressively estimated centers of mass; R1 to RN: the progressively smaller intervals to estimate p1 to pN. * Figure 3: Quantitative measurement of the 3D gene expression level in a C. elegans confocal image. Green voxels: myo3: green fluorescent protein (GFP)-tagged body wall muscle cells; blue voxels: DAPI (4,6-diamidino-2-phenylindole)-tagged nuclei for the entire animal; colored spheres: pinpointed markers; colored line-segments: the line-indicator for measuring along different directions and with different starting and ending locations; line profile graph: the channel-by-channel display of the voxel intensity along a line segment. * Figure 4: V3D-Neuron tracing. () Pinpointing terminals of a fruitfly neuron. 3D image: a GFP-tagged neuron produced via twin-spot MARCM; colored spheres: markers defined for the tips of this neuron. () Reconstructed neuron produced by V3D-Neuron. Colored segments: the automatically reconstructed neurite structures. () Skeleton view of the reconstructed neuron. * Figure 5: Accuracy of V3D-Neuron reconstructions compared with manual reconstructions. () Inconsistency of independent trials of reconstructions. e1, e2, e3, e4: examples of the obvious inconsistent parts in manual reconstructions; e5: an example of the inconsistent region in V3D-Neuron reconstructions. () Spatial divergence of reconstructed neurons using different methods, each with two independent runs. Also shown in the legend are the average and the s.d. of the spatial divergence (Online Methods) of all neurons. () Percent of the neuron structure that noticeably varies in independent reconstructions. Also shown in the legend are the average and the s.d. of this score over all neurons. SSD: substantial spatial distance. * Figure 6: An atlas of stereotyped neurite tracts in a fruitfly brain. () Statistical models of the 3D reconstructed neurite tracts. Grayscale image: the 'typical' fruitfly brain which was used as the target in 3D alignment; each colored tubular structure: the average of multiple neurite tracts reconstructed from images of the same GAL4 line. The width of each tract equals twice the spatial variation of the respective group of reconstructions. () Distribution of the spatial variation of all neurite tracts. Author information * Abstract * Author information * Supplementary information Affiliations * Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. * Hanchuan Peng, * Zongcai Ruan, * Fuhui Long, * Julie H Simpson & * Eugene W Myers Contributions H.P. designed this research and developed the algorithms and systems, did the experiments and wrote the manuscript. Z.R. and F.L. helped develop the systems. J.H.S. provided raw images for building the neurite atlas. E.W.M. supported the initial proposal of a fast 3D volumetric image renderer. E.W.M., F.L. and J.H.S. helped write the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Hanchuan Peng (pengh@janelia.hhmi.org) Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Video 1 (8M) 3D visualization of a digital model of a fruit fly brain. Magenta voxels: the 3D volumetric image of a fruit fly brain; green voxels: a 3D GAL4 neurite pattern; colored surface objects of irregular shapes: digital models of various brain compartments; colored tree-like surface objects: two 3D reconstructed neurons. * Supplementary Video 2a (6M) Hierarchical visualization of a fruit fly brain: The global 3D viewer. * Supplementary Video 2b (6M) Hierarchical visualization of a fruit fly brain: Local 3D viewer for region A of Fig. 1c. * Supplementary Video 2c (6M) Hierarchical visualization of a fruit fly brain: The local 3D viewer for region B in Fig. 1c is used for tracing neurite and proofreading the reconstruction in 3D. * Supplementary Video 3a (3M) 3D pinpointing methods in V3D: Pinpointing using 2-clicks. * Supplementary Video 3b (3M) 3D pinpointing methods in V3D: Pinpointing using 1-click. * Supplementary Video 4 (7M) 3D counting of neurons in the arcuate nucleus of the hypothalamus of a mouse brain. For better visibility, only a small trunk of data is displayed. Red: AgrP neurons infected with FLEX-AAV-ChR2-td-tomato virus; blue: DAPI staining indicating the cell bodies of neurons; green spheres: markers indicating the locations of neurons. * Supplementary Video 5 (4M) 5D volumetric image visualization and quantitative measuring for C. elegans neurons. A series of SPIM images (Supplementary Figure 3) were used. The neuron centers 1~8 were directly pinpointed. 3D line segments were defined between them for profiling both voxel intensity and distance between the moving neurons. * Supplementary Video 6 (6M) The use of V3D-Neuron in visualization, reconstruction, and proofreading of the 3D morphology of a fruit fly neuron. * Supplementary Video 7 (7M) A 3D atlas of 111 stereotyped neurite tracts in a fruit fly brain. The width of a tract indicates the spatial variation of its location. * Supplementary Video 8 (6M) V3D-Neuron can display a neuron in multiple ways (see Methods). * Supplementary Video 9 (3M) Editing a neuron using V3D-Neuron (see Methods). * Supplementary Video 10 (7M) Display of multiple neurons in V3D-Neuron. The first half shows how to display the atlas of fruit fly neurite tracts in Figure 6. The second half shows how to display multiple mouse brain neurons. Zip files * Supplementary Software (2M) * Supplementary Data (9M) PDF files * Supplementary Text and Figures (1M) Supplementary Figs. 1–3 and Supplementary Note Additional data - Derivation, propagation and controlled differentiation of human embryonic stem cells in suspension
Steiner D Khaner H Cohen M Even-Ram S Gil Y Itsykson P Turetsky T Idelson M Aizenman E Ram R Berman-Zaken Y Reubinoff B - Nature Biotechnology 28(4):361-364 (2010)
Nature Biotechnology | Research | Letter Derivation, propagation and controlled differentiation of human embryonic stem cells in suspension * Debora Steiner1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hanita Khaner1 Search for this author in: * NPG journals * PubMed * Google Scholar * Malkiel Cohen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sharona Even-Ram1 Search for this author in: * NPG journals * PubMed * Google Scholar * Yaniv Gil1 Search for this author in: * NPG journals * PubMed * Google Scholar * Pavel Itsykson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tikva Turetsky1 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Idelson1 Search for this author in: * NPG journals * PubMed * Google Scholar * Einat Aizenman2 Search for this author in: * NPG journals * PubMed * Google Scholar * Rita Ram3 Search for this author in: * NPG journals * PubMed * Google Scholar * Yael Berman-Zaken1 Search for this author in: * NPG journals * PubMed * Google Scholar * Benjamin Reubinoff1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:361–364Year published:(2010)DOI:doi:10.1038/nbt.1616Received24 July 2009Accepted16 February 2010Published online28 March 2010 Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Undifferentiated human embryonic stem cells (hESCs) are currently propagated on a relatively small scale as monolayer colonies1, 2, 3, 4, 5, 6, 7. Culture of hESCs as floating aggregates is widely used for induction of differentiation into embryoid bodies8. Here we show that hESC lines can be derived from floating inner cell masses in suspension culture conditions that do not involve feeder cells or microcarriers. This culture system supports prolonged propagation of the pluripotent stem cells as floating clusters without their differentiation into embryoid bodies. HESCs cultivated as aggregates in suspension maintain the expression of pluripotency markers and can differentiate into progeny of the three germ layers both in vitro and in vivo. We further show the controlled differentiation of hESC clusters in suspension into neural spheres. These results pave the way for large-scale expansion and controlled differentiation of hESCs in suspension, which would be valuable in bas! ic and applied research. View full text Figures at a glance * Figure 1: Human ESCs remain pluripotent after 10 weeks propagation in suspension. () FACS analysis of HES1 cells after cultivation in suspension and on feeders showing that in both culture conditions >90% of the cells express markers of pluripotent stem cells, whereas <2% express PSA-NCAM, which is a marker of early neural differentiation (n = 3). Data are presented as mean ± s.d. () RT-PCR analysis of free-floating clusters of hESCs confirming the expression of transcripts of markers of pluripotency, whereas the expression of the primitive ectoderm marker FGF5 is not detected. () Immunostaining of cells dissociated from the clusters and plated for 24 h, demonstrating that the majority of cells express OCT-4. () Darkfield micrograph of the clusters of hESCs in suspension. () Alkaline phosphatase activity within the hESC aggregates is demonstrated (fluorescence image). (,) After plating of the clusters on feeders, they give rise to colonies with morphological characteristics of colonies of undifferentiated hESCs (, phase contrast image), which are compris! ed of cells harboring alkaline phosphatase activity (, fluorescence image). () Proliferation curve showing the fold increase in the number of cells cultivated in suspension or as colonies on feeders. Cell number was monitored each week and the cumulative fold increase in cell number from the starting population was calculated in three independent experiments. (–) Histological analysis of H&E-stained sections of teratoma tumors that developed after inoculation of the hESC-clusters under the testes capsule of NOD/SCID mice showing differentiated tissues representing the three germ layers (low magnitude image (), cartilage (), neural rosette () and glandular structure ()). (–) Immunostaining of in vitro–differentiated progeny, representing the three embryonic germ layers, within the outgrowth of plated embryoid bodies (human muscle actin (), and SOX-17, ()) and neural spheres (β-III Tubulin, ()). () G-banding analysis showing a normal karyotype. Nuclei are counterstaine! d by DAPI in () and (–). Scale bars, 20 μm (,,–); 50 μm ! (,,,); 100 μm (,); 500 μm (). * Figure 2: Derivation of hESCs in suspension. (,) Darkfield micrograph of an inner cell mass after transfer to suspension culture conditions (), and of the clusters of cells that were derived from the inner cell mass after 10 weeks of cultivation (). () Fluorescence image showing alkaline phosphatase activity within a cluster. (–) After plating on feeders, the clusters gave rise to colonies with morphological characteristics of colonies of undifferentiated hESCs (, phase contrast image), which were comprised of cells immunoreactive with anti-SSEA-4 (), SSEA-3 (), TRA-1-60 () and TRA-1-81 () (fluorescence images). (–) Immunostaining of in vitro–differentiated progeny, representing the three embryonic germ layers, within the outgrowth of plated embryoid bodies (β-III tubulin, (); SOX-17, (); human muscle actin, ()). () G-banding analysis showing a normal karyotype after 10 weeks of cultivation in suspension. Nuclei are counterstained by DAPI in –. Scale bars, 20 μm (, –); 50 μm (); 100 μm (,). HAD17 hESC lin! e. * Figure 3: Controlled conversion of the hESC clusters in suspension into neural precursor spheres. Clusters of H7 cells, cultivated in suspension for 7 weeks, were transferred and further cultured 4 weeks in a chemically defined medium supplemented with noggin and FGF2. () FACS analysis of one representative experiment showing that 91% of the cells expressed PSA-NCAM, whereas 1.2% expressed TRA-1-81. (–) After plating and culturing for 1 week on laminin, indirect immunofluorescence staining showed cells within rosettes expressing markers of neural precursors such as nestin and Pax6 (), the neural stem/radial glial cell marker 3CB2 (), subtypes of neurons expressing β-III tubulin and tyrosine hydroxylase (TH) (), GABA () and glutamate (), as well as cells expressing the astrocyte marker GFAP () and the marker of oligodendroglial progenitors NG2 (). Nuclei are counterstained by DAPI. Scale bars, 20 μm. Author information * Author information * Supplementary information Affiliations * The Hadassah Human Embryonic Stem Cell Research Center, The Goldyne Savad Institute of Gene Therapy. * Debora Steiner, * Hanita Khaner, * Malkiel Cohen, * Sharona Even-Ram, * Yaniv Gil, * Pavel Itsykson, * Tikva Turetsky, * Maria Idelson, * Yael Berman-Zaken & * Benjamin Reubinoff * Department of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. * Einat Aizenman * Department of Genetics, Hadassah-Hebrew University Medical Center, Jerusalem, Israel. * Rita Ram Contributions D.S. designed and performed the experiments, analyzed the data and wrote the manuscript; H.K. and M.C. performed the neural differentiation study; S.E.-R. conducted immunostainings and confocal analysis; Y.G. performed the teratoma studies; P.I. contributed to developing the concept of suspension culture; T.T. contributed to the experiments; M.I. performed PCR analysis; E.A. contributed to embryo recruitment, culture and isolation of inner cell masses; R.R. and Y.B.-Z. conducted karyotype analysis. B.R. conceived the study and wrote the paper. Competing financial interests B.R. is the CSO and holds shares in CellCure Neurosciences Ltd. However, the project was not funded by CellCure Neurosciences Ltd. and the company has no rights in its results. Corresponding author Correspondence to: * Benjamin Reubinoff (benjaminr@ekmd.huji.ac.il) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (772K) Supplementary Figs. 1–10 Additional data - Self-sufficient control of urate homeostasis in mice by a synthetic circuit
Kemmer C Gitzinger M Daoud-El Baba M Djonov V Stelling J Fussenegger M - Nature Biotechnology 28(4):355-360 (2010)
Nature Biotechnology | Research | Letter Self-sufficient control of urate homeostasis in mice by a synthetic circuit * Christian Kemmer1 Search for this author in: * NPG journals * PubMed * Google Scholar * Marc Gitzinger1 Search for this author in: * NPG journals * PubMed * Google Scholar * Marie Daoud-El Baba2 Search for this author in: * NPG journals * PubMed * Google Scholar * Valentin Djonov3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jörg Stelling1, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Fussenegger1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume:28,Pages:355–360Year published:(2010)DOI:doi:10.1038/nbt.1617Received01 February 2010Accepted19 February 2010Published online28 March 2010 Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Synthetic biology has shown that the metabolic behavior of mammalian cells can be altered by genetic devices such as epigenetic and hysteretic switches1, 2, timers and oscillators3, 4, biocomputers5, hormone systems6 and heterologous metabolic shunts7. To explore the potential of such devices for therapeutic strategies, we designed a synthetic mammalian circuit to maintain uric acid homeostasis in the bloodstream, disturbance of which is associated with tumor lysis syndrome and gout8, 9. This synthetic device consists of a modified Deinococcus radiodurans-derived protein that senses uric acids levels and triggers dose-dependent derepression of a secretion-engineered Aspergillus flavus urate oxidase that eliminates uric acid. In urate oxidase–deficient mice, which develop acute hyperuricemia, the synthetic circuit decreased blood urate concentration to stable sub-pathologic levels in a dose-dependent manner and reduced uric acid crystal deposits in the kidney. Synthetic gen! e-network devices providing self-sufficient control of pathologic metabolites represent molecular prostheses, which may foster advances in future gene- and cell-based therapies. View full text Figures at a glance * Figure 1: Synthetic uric acid–responsive mammalian sensor circuit. () Expression vectors for uric acid–responsive transgene expression (UREX) (Supplementary Table 1 for abbreviations). () Diagram of UREX in action. In the absence of uric acid (−UA), mUTS (KRAB-HucR) binds to hucO8 and represses SEAP production. In the presence of uric acid (+UA), mUTS is released from hucO8, which derepresses PUREX8 and results in PSV40-driven SEAP expression. () mUTS-mediated repression of PUREX8 in different human cell lines. HeLa, HEK-293 and HT-1080 were transfected with pCK9 (PUREX8-SEAP-pA; -mUTS) alone or together with pCK25 (PhEF1α-mUTS-pA; +mUTS) and cultivated for 48 h before quantification of SEAP expression. (–) Uric acid–dependent dose-response characteristics of UREX in the presence or absence of the human urate transporter (URAT1) or the human organic anion transporter 2 (OAT2), which is not related to urate transport. 3 × 105 HeLa (), HEK-293 () or HT-1080 () were co-transfected with the UREX sensor plasmids pCK9 and pCK25 (Fig. 1a! ) and either pURAT1 (PhCMV-URAT1-pA), pOAT2 (PhCMV-OAT2-pA) or the isogenic control vector pcDNA3.1. The transfected populations were cultivated in medium supplemented with different uric acid concentrations and resulting SEAP levels were profiled after 48 h. * Figure 2: Validation of UREX-controlled SEAP expression in transgenic HEK-293 and urate oxidase–deficient mice. () Uric acid–based dose response profile of the triple-transgenic HEK-293UREX15 cell line stably engineered for UREX-controlled SEAP and constitutive URAT1 expression. 5 × 104 HEK-293UREX15 cells were cultivated in the presence of different uric acid concentrations and SEAP levels were quantified in the culture supernatant after 72 h. () Reversibility of the UREX-based uric acid sensor circuit. 2 × 105 HEK-293UREX15 cells were cultivated for 10 d while uric acid concentrations were alternated from 0–5 mM every 72 h (arrows). () HeLaURAT1 cells engineered for UREX-controlled SEAP expression were microencapsulated in coherent alginate-poly-l-lysine-alginate microcapsules and intraperitoneally injected (2 × 106 cells per mouse, 200 cells/capsule) into uox−/− mice that had received 150 μg/ml (wt/vol) of the hyperuricemia therapeutic allopurinol (+allopurinol) in their drinking water to reduce urate levels (UREX) or untreated uox−/− mice exhibiting pathologic urat! e levels (−allopurinol). Control implants contained cells transgenic for constitutive SEAP expression (control). SEAP levels were profiled in the serum of the animals 72 h after cell implantation. * Figure 3: Functional characterization of an engineered mammalian A. flavus–derived urate oxidase. () Profiling of urate reduction mediated by constitutive or UREX-controlled expression of an intracellular (mUox) or secretion-engineered (smUox) urate oxidase variant. 2 × 105 HeLaURAT1 cells were co-transfected with either pCK65 and isogenic control vector pcDNA3.1, pCK65 and pCK25, pCK67 and pcDNA3.1, or pCK67 and pCK25. The cells were cultivated for 72 h with 0.5 mM uric acid before uric acid levels were determined in the culture supernatant. () Uric acid degradation profiles of UREX-controlled smUox expression. 2 × 105 HeLaURAT1 cells engineered for UREX-controlled smUox expression (solid lines) were cultivated in medium containing starting uric acid concentrations of either 0.1, 0.2, 0.5 or 1 mM and uric acid reduction kinetics were profiled for 120 h. Control experiments show 2 × 105 HeLaURAT1 engineered for constitutive smUox or mUTS expression (dashed lines). The upper panel shows smUox and GAPDH (control) transcript levels profiled 24 h after induction. () Uric ! acid homeostasis. 2 × 105 HeLaURAT1 cells engineered for UREX-controlled smUox expression were cultivated in medium containing starting concentrations of 0, 0.1 or 0.5 mM uric acid. After 72 h the cultures received a second dose of uric acid (0.1, 0.3, 0.5 mM) after which the UREX-based control device again adjusted uric acid concentrations to the homeostasis level (dashed red line, 0.5 mM uric acid profile of Fig. 3b). (,) Model predictions for uric acid homeostasis using a physiological model. Steady-state values of uric acid concentration obtained by simulating the interplay of UREX circuit in HeLaURAT1 cells and of body cells connected by a fluid flow (Supplementary Results). Contour plots of steady-state extracellular urate concentration as a function of relative mUTS expression and of relative PUREX promoter strength (), and as a function of relative URAT1 expression and of maximal uric acid export rate (), respectively. Colors indicate concentrations according to th! e color bar in ; see also labels, values in mM. * Figure 4: UREX-controlled smUox-mediated reduction of pathologic urate levels in mice. Microencapsulated HeLaURAT1 cells engineered for UREX-controlled smUox expression were intraperitoneally implanted (2 × 106 cells per mouse) into untreated uox−/− mice exhibiting pathologic urate levels or into uox−/− mice having received 150 μg/ml (wt/vol) of the hyperuricemia therapeutic allopurinol in their drinking water (UREX-smUox) (control). Control implants contained parental HeLaURAT1. (,) Urate levels were profiled in serum () and urine (collected for 24 h) () of the animals 3 and 7 d after cell implantation. (–) Tissue sections showing anisotropic uric acid crystals (arrow) in the kidneys of uox−/− mice receiving 150 μg/ml (wt/vol) allopurinol (positive control) (), phosphate-buffered saline (negative control) (), implants with HeLaURAT1 engineered for UREX-controlled smUox expression () and implants with HeLaURAT1 engineered for constitutive smUox expression (). Quantitative morphometric analysis revealed 3.3% ± 2.9 (s.d.)/1.5% ± 0.8 (s.d.) (),! 109.1% ± 27.3 (s.d.)/26.9% ± 5.6 (s.d.) (), 10.4% ± 4.6(s.d.)/3.7% ± 1.5 (s.d.) () and 0.4% ± 0.5 (s.d.)/0.6% ± 0.7 (s.d.) (), percent crystals/percent relative area of crystalline deposits per tubulus and/or tubulus lumen profile of the respective treatment group. Scale bars, 100 μm. Author information * Author information * Supplementary information Affiliations * Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. * Christian Kemmer, * Marc Gitzinger, * Jörg Stelling & * Martin Fussenegger * Institut Universitaire de Technologie, IUTA, Département Génie Biologique, Villeurbanne Cedex, France. * Marie Daoud-El Baba * Département de Médecine, Université de Fribourg, Fribourg, Switzerland. * Valentin Djonov * Swiss Institute of Bioinformatics, ETH Zurich, Zurich, Switzerland. * Jörg Stelling Contributions C.K., J.S. and M.F. designed the project, analyzed results and wrote the manuscript. C.K., M.G., M.D.-E.B. and V.D. performed the experimental work. J.S. designed the mathematical model and performed simulations. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Martin Fussenegger (fussenegger@bsse.ethz.ch) or * Jörg Stelling (joerg.stelling@bsse.ethz.ch) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (844K) Supplementary Figs. 1–13 and Supplementary Tables 1–6 and Supplementary Results Additional data - Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance
Lacombe S Rougon-Cardoso A Sherwood E Peeters N Dahlbeck D van Esse HP Smoker M Rallapalli G Thomma BP Staskawicz B Jones JD Zipfel C - Nature Biotechnology 28(4):365-369 (2010)
Nature Biotechnology | Research | Letter Interfamily transfer of a plant pattern-recognition receptor confers broad-spectrum bacterial resistance * Séverine Lacombe1, 5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Alejandra Rougon-Cardoso1, 5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Emma Sherwood1, 5, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Nemo Peeters2 Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas Dahlbeck3 Search for this author in: * NPG journals * PubMed * Google Scholar * H Peter van Esse4 Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew Smoker1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ghanasyam Rallapalli1 Search for this author in: * NPG journals * PubMed * Google Scholar * Bart P H J Thomma4 Search for this author in: * NPG journals * PubMed * Google Scholar * Brian Staskawicz3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan D G Jones1 Search for this author in: * NPG journals * PubMed * Google Scholar * Cyril Zipfel1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume:28,Pages:365–369Year published:(2010)DOI:doi:10.1038/nbt.1613Received09 December 2009Accepted09 February 2010Published online14 March 2010 Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Plant diseases cause massive losses in agriculture. Increasing the natural defenses of plants may reduce the impact of phytopathogens on agricultural productivity. Pattern-recognition receptors (PRRs) detect microbes by recognizing conserved pathogen-associated molecular patterns (PAMPs)1, 2, 3. Although the overall importance of PAMP-triggered immunity for plant defense is established2, 3, it has not been used to confer disease resistance in crops. We report that activity of a PRR is retained after its transfer between two plant families. Expression of EFR (ref. 4), a PRR from the cruciferous plant Arabidopsis thaliana, confers responsiveness to bacterial elongation factor Tu in the solanaceous plants Nicotiana benthamiana and tomato (Solanum lycopersicum), making them more resistant to a range of phytopathogenic bacteria from different genera. Our results in controlled laboratory conditions suggest that heterologous expression of PAMP recognition systems could be used to e! ngineer broad-spectrum disease resistance to important bacterial pathogens, potentially enabling more durable and sustainable resistance in the field. View full text Figures at a glance * Figure 1: Eliciting activities of elf18 peptides and EF-Tu from selected phytopathogenic bacteria in A. thaliana. () Alignment of elf18 regions from selected bacteria. Capital letters on the right indicate the subgroups of elf18 peptides. Accession numbers are from UniProtKB. XANAC, X. axonopodis pv. citri 306; XANCM, X. campestris pv. musacearum 4381; XANOR, X. oryzae pv. oryzae KXO85; XANOM, X. oryzae pv. oryzae MAFF 311018; XANC5, X. campestris pv. vesicatoria 85-10; XANC8, X. campestris pv. campestris 8004; XANCB, X. campestris pv. campestris B100; AGRT5, A. tumefaciens C58; AGRTU, A. tumefaciens; AGRRK, Agrobacterium radiobacter K84; AGRVS, Agrobacterium vitis S4; ERWCT, E. carotovora ssp. atroseptica/P. atrosepticum SCRI1043; DIDIA, Dickeya dianthicola/E. chrysanthemi SCRI3534; ECOLI, E. coli K12; RALSO, R. solanacearum GMI1000; PSE14, P. syringae pv. phaseolicola 1448A/Race 6; PSEU2, Pss B728a; PSEPF, Pseudomonas fluorescens Pf0-1; PSESM, Pto DC3000. () WebLogo representation of the elf18 consensus sequence. () Oxidative burst triggered by elf18 peptides from different subgroups ! as defined in . We calculated the eliciting activity as the amount of relative light units (RLU) produced in response to 1 μM elf18 peptide minus the amount of ROS produced in response to water in wild-type (Col-0 ecotype) A. thaliana leaf discs. Results are averages ± s.e.m. (n = 12). () Oxidative burst triggered by 10 μl bacterial extracts from P. carotovorum 193, P. atrosepticum 1043 and D. dianthicola 3534 in A. thaliana leaf discs from wild-type (Col-0; black), efr (light gray), fls2 (gray) and fls2 efr (white) plants, measured as RLU. Results are averages ± s.e.m. (n = 12). We repeated all experiments at least three times with similar results. * Figure 2: Transgenic expression of EFR in N. benthamiana and tomato confers elf18 responsiveness. () Four-week-old wild-type (left) and transgenic EFR (right) N. benthamiana plants. () Oxidative burst triggered by 100 nM elf18Ecoli or flg22 in wild-type (white) or transgenic EFR (black) N. benthamiana leaf discs measured as RLU. Results are averages ± s.e.m. (n = 12). () Gene expression of marker genes determined by reverse transcriptase PCR. We treated wild-type and transgenic EFR N. benthamiana seedlings grown in axenic conditions with 100 nM elf18Ecoli or flg22 for the times indicated. EF-1α is a housekeeping gene used a loading control. () Four-week-old wild-type (variety Moneymaker; left) and EFR-expressing transgenic tomato (right) plants. () Oxidative burst triggered by 100 nM elf18Ecoli or flg22 in wild-type (variety Moneymaker; white) or transgenic EFR (black) tomato leaf discs measured as RLU. Results are averages ± s.e.m. (n = 12). *, P < 0.05 using Student's t-test. We repeated all experiments at least three times with similar results. * Figure 3: Transgenic expression of EFR in N. benthamiana confers broad-spectrum bacterial resistance. (,) Infection with Pss B728a () and Pta 11528 (). We sprayed 4-week-old N. benthamiana plants with 108 colony-forming units (CFU) of bacteria per milliliter supplemented with 0.06% (vol/vol) Silwet-L77 and photographed them 6 days post-inoculation (dpi). Results are averages ± s.e.m. (n = 4). () Infection with A. tumefaciens A281. We stab-inoculated stems of 4-week-old N. benthamiana plants with bacteria that had been cultured on a plate for 2 d. We took pictures (left) and tumor fresh-weight measurements (right) at 3 weeks post-inoculation. Results are averages ± s.e.m. (n = 16). *, P < 0.05 using Student's t test. We repeated all experiments at least three times with similar results. * Figure 4: Transgenic expression of EFR in tomato confers broad-spectrum bacterial resistance. () Wild-type (variety Moneymaker; left) and transgenic EFR (right) tomato plants infected with R. solanacearum GMI1000. We drench-inoculated 4-week-old plants with 108 CFU ml−1 bacteria and photographed them 6 d after inoculation. () Disease scoring after infection with R. solanacearum GMI1000 in wild-type Moneymaker (blue) and transgenic EFR (red) tomato plants. Results are averages ± s.e.m. (n = 24). () Wild-type Moneymaker (MM) or VF36 and transgenic EFR- or Bs2-expressing tomato plants infected with X. perforans T4-4B. We dipped 6-week-old tomato plants in bacterial suspension (107 CFU ml−1 supplemented with 0.008% (vol/vol) Silwet-L77) and counted bacteria 14 d after inoculation. Results are averages ± s.e.m. (n = 3). *, P < 0.05 using Student's t-test. We repeated all experiments at least twice with similar results. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Séverine Lacombe, * Alejandra Rougon-Cardoso & * Emma Sherwood Affiliations * The Sainsbury Laboratory, Norwich Research Park, Norwich, UK. * Séverine Lacombe, * Alejandra Rougon-Cardoso, * Emma Sherwood, * Matthew Smoker, * Ghanasyam Rallapalli, * Jonathan D G Jones & * Cyril Zipfel * Centre National de la Recherche Scientifique-Institut National de la Recherche Agronomique, Unité Mixte de Recherche, Laboratoire des Interactions Plantes Microorganismes, Castanet-Tolosan, France. * Nemo Peeters * Department of Plant and Microbial Biology, University of California, Berkeley, California, USA. * Douglas Dahlbeck & * Brian Staskawicz * Laboratory of Phytopathology, Wageningen University, Wageningen, The Netherlands. * H Peter van Esse & * Bart P H J Thomma * Present addresses: Institut National de la Recherche Agronomique, Unité de Recherche, Génétique et Amélioration des Fruits et Légumes, Montfavet, France (S.L.), Laboratorio Nacional de Genómica para la Biodiversidad, CINVESTAV Irapuato, Irapuato, Mexico (A.R.-C.) and Department of Molecular Microbiology, John Innes Centre, Norwich, UK (E.S.). * Séverine Lacombe, * Alejandra Rougon-Cardoso & * Emma Sherwood Contributions S.L., A.R.-C., E.S., N.P., D.D., H.P.E. and G.R. performed experiments and analyzed data. M.S. generated the transgenic plants. B.S. and B.P.H.J.T. contributed ideas, conceived experiments and analyzed data. J.D.G.J. initiated the project and contributed ideas. C.Z. initiated the project, conceived, designed and performed experiments, analyzed data, obtained funding, and wrote the manuscript. All authors commented on the manuscript prior to submission. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Cyril Zipfel (cyril.zipfel@tsl.ac.uk) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–5 Additional data - High-resolution DNA analysis of human embryonic stem cell lines reveals culture-induced copy number changes and loss of heterozygosity
Närvä E Autio R Rahkonen N Kong L Harrison N Kitsberg D Borghese L Itskovitz-Eldor J Rasool O Dvorak P Hovatta O Otonkoski T Tuuri T Cui W Brüstle O Baker D Maltby E Moore HD Benvenisty N Andrews PW Yli-Harja O Lahesmaa R - Nature Biotechnology 28(4):371-377 (2010)
Nature Biotechnology | Research | Resources High-resolution DNA analysis of human embryonic stem cell lines reveals culture-induced copy number changes and loss of heterozygosity * Elisa Närvä1 Search for this author in: * NPG journals * PubMed * Google Scholar * Reija Autio1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Nelly Rahkonen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Lingjia Kong2 Search for this author in: * NPG journals * PubMed * Google Scholar * Neil Harrison3 Search for this author in: * NPG journals * PubMed * Google Scholar * Danny Kitsberg4 Search for this author in: * NPG journals * PubMed * Google Scholar * Lodovica Borghese5 Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph Itskovitz-Eldor6 Search for this author in: * NPG journals * PubMed * Google Scholar * Omid Rasool1 Search for this author in: * NPG journals * PubMed * Google Scholar * Petr Dvorak7 Search for this author in: * NPG journals * PubMed * Google Scholar * Outi Hovatta8 Search for this author in: * NPG journals * PubMed * Google Scholar * Timo Otonkoski9, 10 Search for this author in: * NPG journals * PubMed * Google Scholar * Timo Tuuri9 Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Cui11 Search for this author in: * NPG journals * PubMed * Google Scholar * Oliver Brüstle5 Search for this author in: * NPG journals * PubMed * Google Scholar * Duncan Baker12 Search for this author in: * NPG journals * PubMed * Google Scholar * Edna Maltby12 Search for this author in: * NPG journals * PubMed * Google Scholar * Harry D Moore13 Search for this author in: * NPG journals * PubMed * Google Scholar * Nissim Benvenisty14 Search for this author in: * NPG journals * PubMed * Google Scholar * Peter W Andrews3 Search for this author in: * NPG journals * PubMed * Google Scholar * Olli Yli-Harja2, 15 Search for this author in: * NPG journals * PubMed * Google Scholar * Riitta Lahesmaa1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume:28,Pages:371–377Year published:(2010)DOI:doi:10.1038/nbt.1615Received24 June 2009Accepted16 February 2010Published online28 March 2010 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * 日本語要約 * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Prolonged culture of human embryonic stem cells (hESCs) can lead to adaptation and the acquisition of chromosomal abnormalities, underscoring the need for rigorous genetic analysis of these cells. Here we report the highest-resolution study of hESCs to date using an Affymetrix SNP 6.0 array containing 906,600 probes for single nucleotide polymorphisms (SNPs) and 946,000 probes for copy number variations (CNVs). Analysis of 17 different hESC lines maintained in different laboratories identified 843 CNVs of 50 kb–3 Mb in size. We identified, on average, 24% of the loss of heterozygosity (LOH) sites and 66% of the CNVs changed in culture between early and late passages of the same lines. Thirty percent of the genes detected within CNV sites had altered expression compared to samples with normal copy number states, of which >44% were functionally linked to cancer. Furthermore, LOH of the q arm of chromosome 16, which has not been observed previously in hESCs, was detected. View full text Figures at a glance * Figure 1: Amplifications contribute to majority of total genomic size affected by CNV in hESCs. (,) Average chromosomal distribution of 50 kb–3 Mb size CNVs in hESCs () and in Caucasian HapMap population (). The majority (72%) of the total genomic size affected by CNVs found in hESCs corresponded to amplifications, whereas gains and losses were equally distributed in the HapMap samples. Chromosomal distribution differences between hESCs and HapMap were most prominent in chromosomes 10, 14, 20, X and Y. * Figure 2: LOH and CNV regions change in culture. () The number of LOH, CNV and passages between sample collections in sample pairs (H9 P25/P34, CCTL-14 P38/P49, I3 P41/P55, HS293 P26/P60, H7 P30/P91). CNVs that remained stable during the culture are marked with dashed line. () The percentage of total genomic area changed plotted against the passages in culture shows clear correlation within chromosomes 1 (78%), 10 (89%), 17 (84%), 20 (90%) and X (88%) in H7 sample series, all P < 0.05. All seven samples are from the same hESC line H7 (P30, P38, P128, P132, P230 and P237). Large chromosomal changes in addition to CNVs were included in the analysis. * Figure 3: Chromosomal abnormalities detected. () The array karyotype of the sample H7 (s6) P237 shows deletions of extra abnormal chromosome 1 in 1p35 and in 1p terminus, as well as gains of 9p13–p21.2 and 10p11.2–p15, which were not seen by conventional karyotyping. () Mosaic karyotype of FES61, having an extra copy of chromosomes 3, 5, 11, 16, 17 and 20 and two extra copies of chromosome 12 in half of the cell population, was seen on the array karyoview as multiple CNVs in the chromosomes of the extra copy and total gain in the case of chromosome 12. () Summary of the large karyotype abnormalities detected. Gain, blue (↑); loss, red (↓). Each individual CNV is marked with a symbol: ▴, gain, ▾, loss. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE15097 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland. * Elisa Närvä, * Reija Autio, * Nelly Rahkonen, * Omid Rasool & * Riitta Lahesmaa * Department of Signal Processing, Tampere University of Technology, Tampere, Finland. * Reija Autio, * Lingjia Kong & * Olli Yli-Harja * Centre for Stem Cell Biology and the Department of Biomedical Science, University of Sheffield, Sheffield, UK. * Neil Harrison & * Peter W Andrews * Stem Cell Technologies Ltd., Jerusalem, Israel. * Danny Kitsberg * Institute of Reconstructive Neurobiology, Life & Brain Center, University of Bonn and Hertie Foundation, Bonn, Germany. * Lodovica Borghese & * Oliver Brüstle * Faculty of Medicine, Technion-Israel Institute of Technology and Department of Obstetrics and Gynecology, Rambam Health Care Campus, Haifa, Israel. * Joseph Itskovitz-Eldor * Department of Biology, Faculty of Medicine, Masaryk University & Department of Molecular Embryology, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Brno, Czech Republic. * Petr Dvorak * Department CLINTEC, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden. * Outi Hovatta * Program of Molecular Neurology, Biomedicum Stem Cell Center, University of Helsinki, Helsinki, Finland. * Timo Otonkoski & * Timo Tuuri * Children's Hospital, University of Helsinki, Helsinki, Finland. * Timo Otonkoski * Institute of Reproductive and Developmental Biology, Faculty of Medicine, Imperial College London, Hammersmith Campus, London, UK. * Wei Cui * Sheffield Diagnostic Genetic Services, Sheffield Children's NHS Trust, Sheffield, UK. * Duncan Baker & * Edna Maltby * Centre for Stem Cell Biology and the Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, UK. * Harry D Moore * Stem Cell Unit, Department of Genetics, The Institute of Life Sciences, The Hebrew University, Jerusalem, Israel. * Nissim Benvenisty * Institute for Systems Biology, Seattle, Washington, USA. * Olli Yli-Harja Contributions E.N., R.A., N.B., P.W.A., O.Y.-H. and R.L. designed the experiments, E.N. and R.L. were responsible for the coordination of the project and microarray experiments. R.A., E.N. and O.Y.-H. were responsible for data analysis, integration and statistical analysis. N.R. performed RNA extractions. L.K. built the gene annotation list of genes overlapping CNVs. D.B. performed conventional karyotyping. E.N. and N.R. performed copy-number state validations with RT-PCR. J.I.-E. provided I3 and I6 lines for the study. P.D., O.H., T.O., T.T., N.B., W.C., O.B., E.M., H.D.M., P.W.A., O.Y.-H. and R.L. provided the samples and coordinated the project in their groups. E.N., R.A., N.R., L.K., N.H., D.K., L.B., J.I.-E., O.R., P.D., O.H., T.O., T.T., N.B., W.C., O.B., D.B., E.M., H.D.M., P.W.A., O.Y.-H. and R.L. contributed to writing the paper. Competing financial interests D.K. is affiliated with Stem Cell Technologies, Ltd. (However, the study was not supported by the company.) Corresponding authors Correspondence to: * Riitta Lahesmaa (riitta.lahesmaa@btk.fi) or * Elisa Närvä (elisa.narva@btk.fi) Supplementary information * Abstract * Accession codes * Author information * Supplementary information Excel files * Supplementary Table 1. (92K) SNP profiles and Hapmap codes.xls * Supplementary Table 2. (956K) CNV region list * Supplementary Table 3. (2.4K) HapMap CNV region list * Supplementary Table 7. (1M) Genes affected by CNVs HapMap * Supplementary Table 8. (236K) Genes affected by CNVs * Supplementary Table 9. (60K) genes changed by adaptation * Supplementary Table 10a. (172K) integrated analysis, losses * Supplementary Table 10b. (3.9K) integrated analysis, gains * Supplementary Table 11. (20K) Culture conditions PDF files * Supplementary Text and Figures (304K) Supplementary Figs. 1–4 and Supplementary Tables 4,5,6,12 Additional data - Building a sustainable career in science
- Nature Biotechnology 28(4):378-379 (2010)
Nature Biotechnology | Careers and Recruitment Building a sustainable career in science * Aakanksha Singhvi1 Search for this author in: * NPG journals * PubMed * Google Scholar * Pallavi Sachdev1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume:28,Pages:378–379Year published:(2010)DOI:doi:10.1038/nbt0410-378 Establishing a successful academic career in the age of 'big science'. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Aakanksha Singhvi and Pallavi Sachdev are at Rockefeller University, New York, New York, USA. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Aakanksha Singhvi (asinghvi@rockefeller.edu) or * Pallavi Sachdev (sachdep@rockefeller.edu) Additional data - People
- Nature Biotechnology 28(4):380 (2010)
VaxInnate (Cranbury, NJ, USA) has named Thomas Hofstaetter (near right) as president and CEO. Alan Shaw (far right), who previously held that position, has assumed the newly created role of CSO and becomes chairman of the board.
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