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- Nat Biotechnol 29(9):vii-viii (2011)
Nature Biotechnology | In This Issue In this issue Journal name:Nature BiotechnologyVolume: 29,Pages:vii–viiiYear published:(2011)DOI:doi:10.1038/nbt.1979Published online08 September 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Modeling ALS across the board Amyotrophic lateral sclerosis (ALS; Lou Gehrig's disease) is an incurable, adult-onset, paralytic, neurodegenerative disease. Although a small percentage of cases are inherited in a dominant fashion (familial ALS), for >90% of patients, there is no family history of the disease (sporadic ALS). Rodent models of familial ALS, based on the overexpression of dominant mutations in the superoxide dismutase 1 (SOD1) gene found in <2% of all ALS cases, have demonstrated that ALS astrocytes can kill neighboring wild-type motor neurons in vitro. However, it has never been shown that this toxicity is observed when expressing mutant SOD1 at normal levels in nontransgenic cells and when the astrocytes are derived from patients with sporadic ALS, potentially drawing into question the value of models of familial ALS for the majority of ALS patients. Kaspar and colleagues show that human astrocytes from neural progenitor cells obtained from the cadaveric spinal cords of individuals with eit! her sporadic or familial ALS (red) are toxic to motor neurons derived from mouse embryonic stem cells (green), suggesting a shared pathogenic mechanism(s). The finding that SOD1 knockdown substantially attenuates the toxicity of astrocytes from patients with sporadic ALS bolsters the notion that SOD1 may be a valuable therapeutic target for sporadic, as well as familial, ALS. PH Safer ES cell therapies In principle, human embryonic stem cells (hESCs) differentiated into appropriate lineages could provide an unlimited source of cells for any form of cell therapy. Drukker and colleagues set out to address a much-discussed safety concern associated with such therapies: the possibility that residual undifferentiated cells in transplanted cell populations will give rise to teratomas in patients. To find cell-surface markers that could be used to identify and discard rare teratoma-forming cells, they screen a large number of antibodies in search of antigens that are expressed on hESCs and rapidly downregulated upon differentiation. These experiments reveal a novel H type-1 glycan, which the authors name stage-specific embryonic antigen (SSEA)-5. Removal of SSEA-5–positive cells by flow cytometry from preparations of differentiated hESCs greatly reduces the chances that the cells will generate teratomas, and complete depletion of teratoma-forming cells is achieved by sorting wi! th SSEA-5 and two other hESC surface markers. [] KA Imaging protein diffusion Measuring protein mobility and concentrations in vivo is important for developing quantitative models of cellular functions. The method of choice for quantitatively studying molecular mobility in living cells is fluorescence correlation spectroscopy (FCS), but current methods have been limited to measurements at single points or along lines. Knop and colleagues describe a microscope that can perform FCS measurements at each pixel of a microscopic image. The microscope uses light sheet illumination to excite fluorescence in a diffraction-limited pad of light. The emission light is recorded by a high-speed camera, and spatially resolved mobility maps are created by analyzing the fluorescent intensity fluctuations at each pixel. The authors measure diffusion coefficients in cultured cells and Drosophila wing disc tissue. Two-dimensional maps of the diffusion coefficient of GFP-labeled heterochromatin protein 1α (HP1α) lead to the discovery of areas of low mobility of HP1α ou! tside classical heterochromatin domains. [] ME Specificity of zinc-finger nucleases Zinc-finger nucleases (ZFNs) cleave the genome at loci chosen by the investigator, enabling precise genome editing, but they may also cleave at off-target sites, with potentially toxic effects on the cell. Although the risk is academic in a research setting, it becomes more worrisome as ZFN-modified cells are considered for clinical applications. Detecting off-target cleavage sites comprehensively is no easy task. Naldini, von Kalle and colleagues show that integrase-defective lentiviral vectors integrate into the genome during repair of double-strand breaks, and then use this vector to tag ZFN cleavage sites in human cells. The approach allows off-target sites to be identified experimentally on a genome-wide scale without the biases introduced by in vitro DNA-binding studies or bioinformatic methods. The authors find that all off-target sites are very similar in sequence to the target site but are not accurately predicted computationally. Comparison of a ZFN pair containing! wild-type Fok1 nuclease domains with the corresponding 'obligate heterodimer' shows that the latter has lower off-target activity. As the obligate heterodimer cleaves only at heterodimeric and not at homodimeric binding sites, the findings confirm earlier in vitro data suggesting that both of the DNA-binding domains of a ZFN dimer must interact with the DNA for cleavage to occur. KA ES cell library of microRNA knockouts Prosser and colleagues describe a comprehensive resource for studying the function of microRNAs in mice. Using a high-throughput pipeline for generating targeting vectors and genetically modified embryonic stem (ES) cells, they have produced knockouts for 392 microRNA genes. The targeting vector contains a selectable marker flanked by recombinase sites, which can be used to introduce alternative allelic variants, such as a fluorescent reporter or a conditional allele. Knockout ES cell clones will be made available for distribution from public repositories and are cataloged in the International Knockout Mouse Consortium database. [] CM Patent roundup Myriad Genetics's patent claims on breast cancer genes were upheld by the US Court of Appeals for the Federal Circuit's decision in July reversing a controversial 2010 court ruling that DNA is not patentable. [] LM US Congress is poised to introduce sweeping changes to US patent law, switching from a first-to-invent to a first-to-file system. [] LM Although traditional patent licensing models have treated the value of a patent as a constant, in reality, patent value changes during a patent's life cycle. Wu and Wu propose a stochastic simulation model of pharmaceutical patent value that bridges the gap between traditional patent evaluation approaches and real-world patent features. [] MF Recent patent applications in breast cancer diagnostics.[] MF Next month in Nature Biotechnology * De novo genome assembly from single cells * Photoswitchable fluorescent protein for super-resolution imaging * Highly myelogenic oligodendrocyte progenitor cells * Comparing exome-sequencing methods * Comparative genomics of thermophilic biomass-degrading fungi * Genome sequences of nonhuman primates * Tracking single HSCs in vivo * Making sense of mass cytometry data Additional data - Outbreak genomics
- Nat Biotechnol 29(9):769 (2011)
Nature Biotechnology | Editorial Outbreak genomics Journal name:Nature BiotechnologyVolume: 29,Page:769Year published:(2011)DOI:doi:10.1038/nbt.1978Published online08 September 2011 Whole-genome sequencing and crowdsourced analyses proved a powerful adjunct to traditional typing in the recent Escherichia coli outbreak. View full text Additional data - Myriad decision reassures biotechs but diagnostics still murky
- Nat Biotechnol 29(9):771-772 (2011)
Article preview View full access options Nature Biotechnology | News Myriad decision reassures biotechs but diagnostics still murky * Malorye Allison1Journal name:Nature BiotechnologyVolume: 29,Pages:771–772Year published:(2011)DOI:doi:10.1038/nbt0911-771Published online08 September 2011 BSIP/NewscomBS The majority of tumors (shown) in familial breast cancer are due to mutations in the BRCA1 and BRCA2 genes, which are the subject of controversial patents owned by Myriad. In late July, the US Court of Appeals for the Federal Circuit (CAFC) announced its long-awaited decision in the lawsuit brought against Myriad Genetics and the United States Patent and Trademark Office (USPTO) by a group of more than 20 plaintiffs. The CAFC ruled that isolated DNA sequences are patentable because such molecules do not exist in nature. Biotech companies, whose livelihoods depend on patents to protect their business, cheered the court's decision. But the aspect of the ruling relating to diagnostics, which involves methods and "transformative" steps, is less clear and is likely to be challenged. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * Acton, Massachusetts * Malorye Allison Author Details * Malorye Allison Search for this author in: * NPG journals * PubMed * Google Scholar - GM grass eludes outmoded USDA oversight
- Nat Biotechnol 29(9):772-773 (2011)
Article preview View full access options Nature Biotechnology | News GM grass eludes outmoded USDA oversight * Emily Waltz1Journal name:Nature BiotechnologyVolume: 29,Pages:772–773Year published:(2011)DOI:doi:10.1038/nbt0911-772Published online08 September 2011 Bill Grove/istockphoto The USDA has determined it will not regulate Scott's herbicide-tolerant lawn grass, exposing a loophole. In July, the US Department of Agriculture (USDA) said an herbicide-tolerant variety of lawn grass fell outside its regulatory authority. The case represents the first time a large company has purposely and successfully taken advantage of a critical weakness in the regulation of genetically modified (GM) plants. Although the grass maker, Scotts Miracle-Gro of Marysville, Ohio, has no intention of commercializing the product, the route to market for its GM Kentucky bluegrass is now the same as any variety produced by conventional methods, which are not required to follow the agency's approval route—a process that typically requires years of expensive field trials and environmental testing. "The bluegrass decision is a major landmark, as it sets a huge loophole to circumvent [USDA] regulations," says Alan McHughen, a biotechnologist at University of California, Riverside. The regulatory gap has been known to the industry for years and "now Scotts has shown it can be don! e," he says. As Scotts blazes a regulatory trail, other companies, particularly small developers, may be encouraged to follow. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * Nashville, Tennessee * Emily Waltz Author Details * Emily Waltz Search for this author in: * NPG journals * PubMed * Google Scholar - New models emerge for commercializing university assets
- Nat Biotechnol 29(9):774-775 (2011)
Article preview View full access options Nature Biotechnology | News New models emerge for commercializing university assets * Nuala Moran1Journal name:Nature BiotechnologyVolume: 29,Pages:774–775Year published:(2011)DOI:doi:10.1038/nbt0911-774Published online08 September 2011 Daniella Zalcman/istockphoto Columbia University is one of BioPontis' partners. Faced with a dwindling supply of traditional venture capital (VC) and fewer funds focusing on early-stage research, universities are partnering with commercial entities that offer investor knowledge, industry contacts and R&D capacity in return for academic intellectual property (IP). One of these entities, BioPontis Alliance, headquartered in Research Triangle Park, Raleigh-Durham, North Carolina, is rapidly building a network of university partners from which it can cherry pick IP assets. A similar IP commercialization model has been pioneered in the UK by London-based IP Group, which spins out companies from IP screened from long-term partnerships with universities. Rather than simply spinning out companies, the BioPontis model uses an R&D network of contract research organizations to develop exclusively licensed assets. What's more, the company has completed partnership agreements with three big pharma companies, which have the option to acquire assets once BioPontis has! developed them to human proof of concept. An agreement signed by BioPontis in July with Horsham, Pennsylvania–based Janssen Biotech (wholly owned by Johnson & Johnson) follows on from recent pacts with Pfizer of New York and Merck of New Jersey. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * London * Nuala Moran Author Details * Nuala Moran Search for this author in: * NPG journals * PubMed * Google Scholar - Around the world in a month
- Nat Biotechnol 29(9):775 (2011)
Article preview View full access options Nature Biotechnology | News Around the world in a month Journal name:Nature BiotechnologyVolume: 29,Page:775Year published:(2011)DOI:doi:10.1038/nbt0911-775Published online08 September 2011 Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data - BIO marches to Congress with growth package in hand
- Nat Biotechnol 29(9):776-777 (2011)
Article preview View full access options Nature Biotechnology | News BIO marches to Congress with growth package in hand * Karen Carey1Journal name:Nature BiotechnologyVolume: 29,Pages:776–777Year published:(2011)DOI:doi:10.1038/nbt0911-776Published online08 September 2011 Dwight Nadig/istockphoto BIO has presented to Congress a long list of suggested ways to improve the environment for biotechs. On July 7, members of the Biotechnology Industry Organization (BIO)'s board of directors were invited to Capitol Hill to testify at a hearing on Prescription Drug User Fee Authorization (PDUFA) V. BIO attended the hearing, summoned by the House Energy and Commerce Subcommittee on Health, to help lay the groundwork for revising PDUFA IV (due to expire September 2012) and also to present ideas on what should be done to jump-start the drug innovation engine. BIO hopes its policy proposals (http://www.bio.org/sites/default/files/PromiseofBiotech.pdf) will be incorporated into new legislation, as Congress redraws PDUFA. But beyond regulatory reform, the industry association also highlighted strategies aimed at making more money available for early-stage innovator companies and to introduce rewards to US-based companies to keep innovation on American soil. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * York, Pennsylvania, with additional reporting by Laura DeFrancesco * Karen Carey Author Details * Karen Carey Search for this author in: * NPG journals * PubMed * Google Scholar - 13,000-biomarker deal
- Nat Biotechnol 29(9):777 (2011)
Article preview View full access options Nature Biotechnology | News 13,000-biomarker deal * Killugudi JayaramanJournal name:Nature BiotechnologyVolume: 29,Page:777Year published:(2011)DOI:doi:10.1038/nbt0911-777Published online08 September 2011 A Hyderabad-based firm entered an agreement in June to make its 13,000-biomarker database available to US researchers. Indian contract research organization GVK Biosciences signed a deal in June with Indianapolis-based Indiana Clinical and Translational Sciences Institute (CTSI), and a similar pact was signed with the Biomarker Qualification Group of the US Food and Drug Administration (FDA) in April. The GVK Clinical Biomarker Database called GOBIOM "is probably the first comprehensive biomarker-oriented database," says Lang Li, head of bioinformatics at CTSI. It is a repository of biochemical, genomic, imaging, metabolite, cellular, physiological and clinical scoring-scale information gathered from clinical trial reports, scientific conferences and public literature. The data include preclinical, exploratory and clinically evaluated compounds—but not validated biomarkers—for 16 different therapeutic areas across 528 indications. GVK Biosciences said its collaborati! ons with the genomics group of the FDA "helped us in developing a tetrahedral data model linking the biomarker to the disease, drug and target," as a discovery tool for basic scientists developing new compounds, as well as clinicians designing phase 0, 1 or 2 trials, he said. GOBIOM is available to CTSI investigators, and scientists at Indiana, Purdue and Notre Dame Universities and affiliated organizations. "We have plans to develop a series of clinically relevant biomarkers for personalized medicine as well as conducting new discoveries," says Anantha Shekhar, director of the Indiana CTSI. Financial details of the deal were not disclosed. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Killugudi Jayaraman Search for this author in: * NPG journals * PubMed * Google Scholar - Patent reform on the brink
- Nat Biotechnol 29(9):778 (2011)
Article preview View full access options Nature Biotechnology | News Patent reform on the brink * Jeffrey L FoxJournal name:Nature BiotechnologyVolume: 29,Page:778Year published:(2011)DOI:doi:10.1038/nbt0911-778aPublished online08 September 2011 stuartbur/istockphoto Patent reform on the brink! Congress stands poised to introduce dramatic changes to US patent law, switching from a first-to-invent to a first-to-file system. Late in June the House of Representatives passed its version of the American Invents Act (H.R. 1249), following similar actions of the Senate, which passed its patent reform bill last March. Despite this momentum, the two bills are sufficiently different to require negotiation and reconciliation—raising a whiff of doubt about the ultimate success of these reform efforts. One promising sign is that US Senate Majority Leader Harry Reid of Nevada announced that the Senate will take up patent reform on the first day back from its August recess. He urges the Senate to adopt the House bill, a procedural step that aims at simplifying reconciliation of their differences, but which also risks obstructionism. One key attraction of the House bill is that it incorporates a political compromise permitting the US Patent and Trademark Office (USPTO) to fund i! ts activities in part through revenues from fees that it collects. Those provisions are "necessary to prevent user fees collected from patent and trademark applications from being redirected to other non-USPTO purposes," according to the Biotechnology Industry Organization (BIO) in Washington, DC. More generally, both versions of this reform legislation would move the US patent system into a first-to-file system, thus aligning it with Europe and many other industrialized nations. BIO, the Pharmaceutical Research and Manufacturers of America of Washington, DC, and other industrial groups generally back these patent reform efforts, saying they will streamline patent reviews and will help to reduce costly litigation over patents and patent applications. However, critics of the new legislation argue that some of these provisions will weaken the hand of inventors at universities and startup companies. For example, Carl E. Gulbrandsen, who is managing director of the Wisconsi! n Alumni Research Foundation in Madison, Wisconsin, asserts th! at the reforms, if implemented, would "decrease the value of patents, make it more difficult to license and increase the cost of enforcement, which impacts innovators disproportionately more than large companies." He also questions whether the new law is compatible with the US Constitution. "Times are hard enough as it is to start a company," he says. "The last thing investors want is uncertainty, which is exactly what will happen if this proposed legislation becomes law." Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Jeffrey L Fox Search for this author in: * NPG journals * PubMed * Google Scholar - Drugmakers use real-world patient data to calibrate product development
- Nat Biotechnol 29(9):778-779 (2011)
Article preview View full access options Nature Biotechnology | News Drugmakers use real-world patient data to calibrate product development * Cormac Sheridan1Journal name:Nature BiotechnologyVolume: 29,Pages:778–779Year published:(2011)DOI:doi:10.1038/nbt0911-778bPublished online08 September 2011 Dean Mitchell/istockphoto As healthcare systems around the world cope with burgeoning populations of aging patients, health resources are being stretched and companies are increasingly having to consider reimbursement in decision making. On June 22, Paris-based Sanofi announced a partnership with pharmacy benefits manager Medco Health Solutions, of Wilmington, Delaware, to feed real-world evidence into its early-stage product development efforts. The companies did not disclose financial terms, but the agreement entitles the French drug maker to use data from Medco's wholly owned subsidiary, United BioSource Corporation (UBC), to determine patient populations who are in need of new treatments, identify patients suited to particular drugs, compare new drugs to current treatments and ensure treatments are used in the most effective way. Another recent collaboration to integrate real-world treatment information into product development came on 2 February, when London-based AstraZeneca unveiled an alliance with HealthCore, the health outcomes research arm of Indianapolis-based health insurer WellPoint. Other large pharma firms are lining up similar initiatives, says Rich Gliklich, CEO of Outcome Sciences, a Cambr! idge, Massachusetts–based outcomes research consultancy—a sign that the drug industry is moving to a world in which randomized clinical trials will still be necessary but no longer sufficient to ensure the commercial viability of its products. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * Dublin * Cormac Sheridan Author Details * Cormac Sheridan Search for this author in: * NPG journals * PubMed * Google Scholar - Money pot for SMEs
- Nat Biotechnol 29(9):779 (2011)
Article preview View full access options Nature Biotechnology | News Money pot for SMEs * Gunjan SinhaJournal name:Nature BiotechnologyVolume: 29,Page:779Year published:(2011)DOI:doi:10.1038/nbt0911-779aPublished online08 September 2011 The European Commission (EC) has allocated 654 ($941) million to fund 38 health-related topics, and this time small- and medium-sized enterprises (SMEs) are encouraged to apply. The EC's 6th call for health research proposals, funded by the 7th Framework Programme for 2012, was launched in July and contains several changes that should be of clear benefit to SMEs. "I've never seen such a quick turnaround from feedback into action," comments Nathalie Moll, secretary general at EuropaBio in Belgium. One change, applicable to 14 of those topics, requires participating SMEs to receive anywhere between 15% and 50% of total EC funding for a project. Another change is a two-stage application that allows firms to present a short proposal first to get a sense of its success before expending resources on a detailed proposal that might fail. The EC has also cut the minimum number of obligatory participants from five to three, which will help small companies take the helm in managing! projects. "It's potentially a huge pot of money," says Tom Saylor, CEO of Cambridge, UK–based Arecor. "EC money could help companies carry their research to higher stages of value without depending on private markets." The turnaround time between application and funding, which can take up to a year, is a cause for concern, and the complexity of the paperwork often puts people off, Moll adds. "It would be nice if there were a help hotline for SMEs." Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Gunjan Sinha Search for this author in: * NPG journals * PubMed * Google Scholar - China's $300 billion goal
- Nat Biotechnol 29(9):779 (2011)
Article preview View full access options Nature Biotechnology | News China's $300 billion goal * Heiko YangJournal name:Nature BiotechnologyVolume: 29,Page:779Year published:(2011)DOI:doi:10.1038/nbt0911-779bPublished online08 September 2011 China's central government will spend 10 billion yuan ($1.6 billion) and raise an additional 30 billion yuan ($4.8 billion) from provincial governments to gain a leading position in global biopharma. This strategic investment is part of its Five-Year Plan, aimed at shedding the nation's reputation as a cheap producer of low-quality products. Of the seven industries selected for investment, biotech is one of them. "The government is pouring money to really support innovative work," says Dan Zhang, CEO of Fountain Medical Development in Beijing, who is reviewing grant proposals for the Ministry of Science and Technology (MOST). "Almost all of the grant money will go to preclinical and clinical studies of truly innovative projects." MOST vice-chairman Liu Yanhua announced at a bioeconomy meeting in Tianjin in June that the government hopes biotech revenue will exceed 2 trillion yuan ($311 billion) by 2020. Many Western biotechs view China's commitment to innovation as a! boon for both sides, as analysts predict that partnerships between China and the West will flourish over the next decade. Whether China's expectations for a meteoric rise will threaten the West's biotech leadership is uncertain. Ingrid Yin, senior analyst for Oppenheimer in New York, believes China must first expand its research infrastructure and attract a talent base before it can develop into a world power in biotech. "It will be a gradual process," she says. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Author Details * Heiko Yang Search for this author in: * NPG journals * PubMed * Google Scholar - Biotech on pace for record year
- Nat Biotechnol 29(9):780 (2011)
Article preview View full access options Nature Biotechnology | News | Data Page Biotech on pace for record year * Walter Yang1Journal name:Nature BiotechnologyVolume: 29,Page:780Year published:(2011)DOI:doi:10.1038/nbt.1970Published online08 September 2011 The biotech industry is on track to raise $44 billion in 2011—the most ever, including the genomics bubble of 2000. Biotech indexes performed well and the private biotech sector was also up, raising $2.9 billion. Excluding partnership monies, biotechs pulled in $22.1 billion during the first six months; debt deals accounted for more than two-thirds of the total. Initial public offerings remained sluggish, with only 11 companies raising $514.2 million altogether. Stock market performance Box 1: Stock market performance Full box Global biotech initial public offerings Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Walter Yang is Research Director at BioCentury Author Details * Walter Yang Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Trends in biotech literature 2009–2010
- Nat Biotechnol 29(9):781 (2011)
Article preview View full access options Nature Biotechnology | News | Data Page Trends in biotech literature 2009–2010 * Wayne Peng1Journal name:Nature BiotechnologyVolume: 29,Page:781Year published:(2011)DOI:doi:10.1038/nbt.1971Published online08 September 2011 The emergence of large-scale, high-throughput technologies for analyzing epigenetic modifications and RNAs has fueled growth in these fields. Seminal publications appeared describing DNA nanotechnology, characterizing the gut microbiome and disclosing new platforms for DNA/RNA sequencing. China continues its march in terms of numbers of papers, but US institutions still accrue the most citations. Historic trends in biotech fields Box 1: Historic trends in biotech fields Full box Top 25 institutions publishing in biotech in 2009 Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Wayne Peng is Emerging Technology Analyst, Nature Publishing Group Author Details * Wayne Peng Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - More than insulin
- Nat Biotechnol 29(9):782-785 (2011)
Nature Biotechnology | News Feature More than insulin * Michael Eisenstein1Journal name:Nature BiotechnologyVolume: 29,Pages:782–785Year published:(2011)DOI:doi:10.1038/nbt.1967Published online08 September 2011 For a century, insulin has been the only drug available to type 1 diabetics. Now a raft of novel drugs are coming through the pipeline. Michael Eisenstein reports. View full text Additional data Affiliations * Philadelphia * Michael Eisenstein Author Details * Michael Eisenstein Search for this author in: * NPG journals * PubMed * Google Scholar - The Isis manifesto
- Nat Biotechnol 29(9):786-788 (2011)
- Shaping the future of safer innovative drugs in Europe
- Nat Biotechnol 29(9):789-790 (2011)
Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Shaping the future of safer innovative drugs in Europe * Jordi Mestres1 * Sharon D Bryant2 * Ismael Zamora3 * Johann Gasteiger4 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:789–790Year published:(2011)DOI:doi:10.1038/nbt.1973Published online08 September 2011 To the Editor: An Editorial entitled "Members need only apply" published in the July issue1 expressed concerns about the input of small- to medium-sized enterprises (SMEs) into the agenda of the Innovative Medicine Initiative (IMI) Joint Undertaking. The editorial argued that the SMEs currently participating in IMI projects do not represent the whole spectrum of companies that make up the innovative biotech space in Europe. We would like to address these criticisms in the context of the eTOX consortium, one of the projects funded following the IMI's first call for proposals in 2008 and specifically singled out for comment in the Editorial. The eTOX consortium comprises 11 European pharmaceutical companies, 8 academic and not-for-profit organizations and 4 SMEs that bring data, methodologies, experience and expertise into a common framework that aims to integrate bioinformatics and chemoinformatics approaches to develop expert computational systems for predictive toxicology. The four SMEs within the eTOX project provide specific informatics solutions to realize a vision of an integrated computational system for predictive toxicology that exploit a repository of proprietary safety-relevant data (Fig. 1)2, 3, 4, 5. Molecular Networks (Erlangen, Germany) has an established reputation for providing chemoinformatics solutions6, including the calculation of molecular descriptors7, and it is actively involved in all aspects related to toxicity data informatics and development of the eTOX system; Lead Molecular Design (Sant Cugat del Vallès, Spain) develops some widely used tools in absorption, distribution, metabolis! m excretion and toxicity modeling, allowing the detection of sites of metabolism8 and the subsequent prediction of metabolites9 from chemical structures; Inte:Ligand (Enzersdorf, Austria) contributes by providing well-established pharmacophore perception, virtual screening and activity profiling methods implemented in their LigandScout10 and Pharmacophore Database software11; and Chemotargets (Barcelona, Spain) offers a platform for the affinity profiling of small molecules across almost 5,000 protein targets12 that can be applied to anticipating adverse drug events linked to off-target pharmacology13. Together, these SMEs represent an expert ensemble of innovative biochemoinformatics companies and thus offer an optimal complement to the rest of the eTOX consortium that will ensure that novel approaches to predictive toxicology are developed and implemented in an efficient integrated system. Figure 1: Innovative SME contributions to the integrative in silico toxicology approach currently under development within eTOX, an IMI EU project. * Full size image (181 KB) From our perspective as successful participants in the eTOX consortium, we concur with the Editorial's call that SMEs should have an even more prominent role in future IMI calls. However, we strongly object to the Editorial's suggestion that the eTOX project somehow lacks industrial expertise because none of the SMEs happen to be venture-backed biotech firms and that these companies were discouraged to apply to IMI simply because of intellectual property (IP) issues. It would have been instructive perhaps if the Editorial had highlighted venture-backed companies that Nature Biotechnology thought should be participating in eTOX, but are not. In any case, we regard the singling out of the eTOX consortium as an unfair basis for an argument concerning the types of SMEs involved across IMI as a whole. To make such a point, the Editorial should at least have provided supporting data from a detailed and thorough analysis of the current SME composition of all 23 active IMI projects ! relative to the set of potential European biotech actors that could have contributed to each of them. What your readers got instead was subjective opinion based on one or two projects. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Chemotargets, IMIM-Hospital del Mar, and University Pompeu Fabra, Barcelona, Catalonia, Spain. * Jordi Mestres * Inte:Ligand, Vienna, Austria. * Sharon D Bryant * Lead Molecular Design, Sant Cugat del Vallès, Spain. * Ismael Zamora * Molecular Networks, Erlangen, Germany. * Johann Gasteiger Competing financial interests J.M. is the president of Chemotargets, S.D.B. is the CEO of Inte:Ligand, I.E. is the CEO of Lead Molecular Design and J.G. is the president of Molecular Networks. Corresponding author Correspondence to: * Jordi Mestres Author Details * Jordi Mestres Contact Jordi Mestres Search for this author in: * NPG journals * PubMed * Google Scholar * Sharon D Bryant Search for this author in: * NPG journals * PubMed * Google Scholar * Ismael Zamora Search for this author in: * NPG journals * PubMed * Google Scholar * Johann Gasteiger Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Clarity and claims in variation/mutation databasing
- Nat Biotechnol 29(9):790-792 (2011)
Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Clarity and claims in variation/mutation databasing * Raymond Dalgleish1 * William S Oetting2 * Arleen D Auerbach3 * Jacques S Beckmann4 * Anne Cambon-Thomsen5, 6 * Andrew Devereau7 * Marc S Greenblatt8 * George P Patrinos9 * Graham R Taylor10 * Mauno Vihinen11 * Anthony J Brookes1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:790–792Year published:(2011)DOI:doi:10.1038/nbt.1961Published online08 September 2011 To the Editor: In response to the paper "MutaDATABASE: a centralized and standardized DNA variation database" by Patrick Willems and colleagues1, we agree that there is a need to collect, analyze and create database resources for DNA variation associated with genetic disease. We are also broadly optimistic that many and various ventures, such as MutaDATABASE, can make a positive contribution if appropriately conducted. However, certain aspects of the MutaDATABASE initiative could give some cause for concern—in as much as they are properly addressed neither in the published correspondence nor on the MutaDATABASE website. In particular, we seek clarification on three key claims presented by the authors: first, "many DNA variation classifications in the current literature are incorrect as a result of the lack of standards and nomenclature for classifying variants..."; second, unpublished variants detected in research and diagnostic laboratories are not being submitted to existing pu! blic databases because "data entry is tedious and laborious with the current platforms" and there are associated intellectual property and patient confidentiality issues; and third, the MutaDATABASE system will be open and free, and it will address the shortcomings of existing tools to enable a fully integrated "closed-loop" system, which will include community-group discussions of issues relating to particular genes (through "MutaCIRCLES"). To preface our thoughts on these points, we would like to first comment that there is a substantial amount of overlap between aspects of the MutaDATABASE proposal and other initiatives already being run or facilitated by the Human Variome Project (http://www.humanvariomeproject.org/), the Human Genome Variation Society (HGVS; http://www.hgvs.org/) and the GEN2PHEN project (http://www.gen2phen.org/). In making this observation, we express a hope that far greater synergy of planning and construction will emerge between these major collaborating initiatives and the MutaDATABASE endeavor. In terms of the authors' first claim about classifying variants, it is difficult to understand why any objective observer would conclude that there is a lack of standards and nomenclature in this field. The point could perhaps be better stated as a "lack of consensus regarding standards and nomenclature" for classifying variants. Two major consortia and many other smaller groups have worked intensely to develop and promote standards related to human genome variation; for example, the Human Variome Project was launched in 2006 and the GEN2PHEN consortium was initiated in 2008. Examples of tools from these and other initiatives include the following: the HGVS variant nomenclature system2, which has its origins nearly 20 years ago and is well established and widely used in the literature; the Leiden Open Variation Database (LOVD) system3 that, under the auspices of GEN2PHEN, has now been developed to provide a standardized database for every disease gene in Online Mendelian! Inheritance in Man; the assignment of a unique gene symbol and name for every human gene by the Human Genome Organization Gene Nomenclature Committee4; the GEN2PHEN, the National Center for Biotechnology Information (Bethesda, MD, USA) and the European Bioinformatics Institute (EBI; Hinxton, UK) innovation of the Locus Reference Genomic DNA reference standard for variant reporting5; creation of the Mutalyzer tool for sequence-variant description validation6; and development of the GEN2PHEN WAVe tool for variome data integration7. Furthermore, many teams globally joined forces to devise a robust overarching data structure (PaGE-OM) for information relating to DNA variation8, just as many are working together on the Human Phenotype Ontology9. The International Agency for Research on Cancer convened a Working Group on Unclassified Genetic Variants, which has reviewed the current status, directions and needs of the field. Analyses and conclusions from their 2008 meeting were published, including a new classification system for variants based on the integration of multiple lines of data, with databases playing a key role in the dissemination of consensus classifications10. The cancer genetics community has begun using this system in publications and databases11. These are examples of major core components that any project as seemingly ambitious as MutaDATABASE should really be aware of, and fully acknowledge. The authors' second claim that the flow of data from the diagnostic laboratories is less than many would hope is widely acknowledged. At present, most variation data are being reported by research laboratories through publications, and we can expect a far greater quantity of disease gene–specific variation observations to be produced as molecular diagnostic teams increasingly adopt high-throughput sequencing platforms. Some claim the paucity of genetic variant data entering repositories is due to the cumbersome and time-consuming process of data submission, but in our experience there are issues around data 'ownership' that are equally problematic. Partly this involves legitimate concerns with respect to how the data might be repurposed by others once released (that is, control and rights issues), as well as uncertainties regarding legal ownership and responsibilities concerning the totality of genotype and phenotype data on any patient, given the complexities surrounding ! patient confidentiality and informed consent12. Experience in the UK with the Diagnostic Mutation Database project has shown that collection of variant data from a supportive diagnostic laboratory community entails a major and proactive curational effort and clear understanding of data ownership and governance, and this will be harder in the clinical community. Given the backdrop of this challenging landscape, the MutaDATABASE model requires and expects data to flow into its system under terms that explicitly state that submitters will relinquish all rights to their data under a Creative Commons Universal (CC0 1.0) Public Domain Dedication. In our view, however, concerns remain about subsequent data ownership and the control by the MutaDATABASE foundation, about which there is little information other than that it is "a non-profit organization," over the release and archiving of the data. We suggest that this may not be a workable strategy and so would urge Willems and colleagues to reconsider. For example, European Union law grants copyright to databases and this copyright should be sufficient—as is demonstrated by the standard 'copyright and disclaimer statement' displayed by the LOVD database system. Quite simply, there is no contradiction between collating data for further dissemination and allowing the originators of the! data to retain copyright and intellectual property rights on that information. A closely related social and cultural dimension that comes into play is encouraging engagement and building trust and mutual respect among variation database initiatives, the data generators and data curators. We suggest that substantial progress on this front could be made by implementing robust and highly transparent recognition and accreditation for those submitting and improving the quality of the data. Indeed, this concept is now under active development by several groups, with the benefits of micro-attribution13 now having been demonstrated in the context of variation databases14. Perhaps this is a further area in which MutaDATABASE might want to revisit its overall strategy. As an illustration of a very different model that could provide some useful lessons, the GEN2PHEN project has developed a data 'depot' through which users can discover data from many disparate sources (including diagnostic laboratories) and collect or view them using automated procedures that transparently put all the sharing decisions (from fully open to tightly regulated) in the hands of the data originators. This project, Cafe Variome (http://www.cafevariome.org/), employs a community-defined and standards-based data-exchange format, leaves data ownership with the person or organization that generated the information and is now engaged with diagnostic centers in Europe and North America to pilot the system. Time will tell whether projects like this, which are designed to be inclusive, respectful, secure and federated, ultimately work better than the fully centralized and acquisitive model of MutaDATABASE. The last claim of Willems and colleagues is that their platform is "open and free." A key software component of MutaDATABASE is MutaREPORTER, which enables graphical displays of variant information. What perhaps needs to be further clarified is that free (that is, zero cost) access to MutaDATABASE data pertains only to a limited feature set within MutaREPORTER unless a software license is purchased. A purchased license grants access to features, including tools to analyze the significance of sequence variants as well as improved tools for data submission to MutaDATABASE. Similarly, without a license, printing and export of data appears to be limited at present to summary-level information only (that is, lists of variants but no details of instances of variants in patients), though this may be a consequence of a current lack of such data in MutaDATABASE. In addition, there is no evidence that any web services are provided for programmatic access to the data. Perhaps most ! crucially of all, the ability to print MutaREPORTS and participate in MutaCIRCLES discussion forums both also require the purchase of a license to MutaREPORTER. A single license costs 2,000 [$2,846] plus a 700 [$996] yearly user fee plus tax (VAT), though prices do drop with larger numbers of licenses. This would seem to dilute the concept of "freely available" access and appears to be entirely contradictory to the claim in the MutaDATABASE charter that there will be "no usage fees." Creating an ambitious variant database with long-term viability requires sustainable funding, which is a problem that other such projects have had to address, so clarity is needed from the authors with respect to the funding model for this enterprise. With providers of some variant databases and analysis tools starting to charge subscription fees, small laboratories, those in developing countries and various other stakeholders, not least private citizens and their clinicians, need to be! clear about the costs and benefits of any system to be able t! o justify access charges such as those currently proposed. Restricted access to MutaCIRCLES for licensing reasons is likely to stifle the discussion that is necessary to make sense of rare variants. The increasing use of ultra-high throughput exome or genome sequencing applied to rare diseases will result in a flurry of potentially pathogenic variants. It will be difficult to assemble sufficient incriminating evidence for pathogenicity without an adequate forum or database where the data and corresponding phenotypes are entered and made visible to the entire medical genetics community. This is how new genomic disorders are constantly defined and identified, as exemplified by 17q21.31 syndrome15. A similar paradigm also needs to be implemented now for point mutations, but that will not happen with MutaDATABASE. On balance we are concerned that the proposals for MutaDATABASE do not optimally recognize or build upon the efforts and progress already made by other organizations in the field, and we hope this letter may encourage this oversight to be corrected. Ideally, we would like to see interoperability between all resources and analytical tools developed in this space, managed through an open-source center (or centers), which would be funded by multiple agencies that might include a combination of government, academic, philanthropic and commercial interests, without any single governmental or commercial agency exerting control. As DNA analysis technologies advance and related healthcare opportunities consequently grow, it becomes ever more essential that we move toward unified global efforts to fairly collect, optimally store and appropriately exploit this valuable information. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Department of Genetics, University of Leicester, Leicester, UK. * Raymond Dalgleish & * Anthony J Brookes * Department of Experimental and Clinical Pharmacology, School of Pharmacy, University of Minnesota, Minneapolis, Minnesota, USA. * William S Oetting * Program in Human Genetics and Hematology, The Rockefeller University, New York, New York, USA. * Arleen D Auerbach * Department of Medical Genetics, University of Lausanne, and Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland. * Jacques S Beckmann * Inserm, UMR1027, Epidemiology and Analyses in Public Health, Toulouse, France. * Anne Cambon-Thomsen * University of Toulouse, Paul Sabatier, UMR1027, Faculty of Medicine, Toulouse, France. * Anne Cambon-Thomsen * NGRL Manchester, Genetic Medicine, St. Mary's Hospital, Manchester, UK. * Andrew Devereau * Department of Medicine, University of Vermont College of Medicine, Burlington, Vermont, USA. * Marc S Greenblatt * Department of Pharmacy, School of Health Sciences, University of Patras, Patras, Greece. * George P Patrinos * University of Leeds Institute of Molecular Medicine, Leeds, UK. * Graham R Taylor * Institute of Biomedical Technology, University of Tampere, Tampere, Finland. * Mauno Vihinen Competing financial interests A.D. manages DmuDB, which will soon become a noncommerical subscription service. Corresponding author Correspondence to: * Raymond Dalgleish Author Details * Raymond Dalgleish Contact Raymond Dalgleish Search for this author in: * NPG journals * PubMed * Google Scholar * William S Oetting Search for this author in: * NPG journals * PubMed * Google Scholar * Arleen D Auerbach Search for this author in: * NPG journals * PubMed * Google Scholar * Jacques S Beckmann Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Cambon-Thomsen Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew Devereau Search for this author in: * NPG journals * PubMed * Google Scholar * Marc S Greenblatt Search for this author in: * NPG journals * PubMed * Google Scholar * George P Patrinos Search for this author in: * NPG journals * PubMed * Google Scholar * Graham R Taylor Search for this author in: * NPG journals * PubMed * Google Scholar * Mauno Vihinen Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony J Brookes Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Reply to Clarity and claims in variation/mutation databasing
- Nat Biotechnol 29(9):792-794 (2011)
Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Reply to Clarity and claims in variation/mutation databasing * Sherri Bale1 * Heidi L Rehm2 * Robert Nussbaum3 * Madhuri Hegde4 * Johan T den Dunnen5 * Patrick Willems6 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:792–794Year published:(2011)DOI:doi:10.1038/nbt.1962Published online08 September 2011 Willems and colleagues reply: We thank the authors for their public expression of optimism that MutaDATABASE can make a positive contribution to the existing need to collect, analyze and create database resources for DNA variation associated with genetic disease. The original goal of our correspondence on the aims and objectives of MutaDATABASE and the MutaREPORTER software was not to comment on other existing databasing initiatives, but we are pleased that the authors have given us an opportunity to do so. We respond here to each of the three points highlighted by Dalgleish et al. With regard to their comments about standards and nomenclature, it is true that many DNA variants have been incorrectly classified, both in the literature and in existing variation/ mutation databases. The classification and nomenclature we referred to in our Correspondence is the classification of "pathogenicity" (e.g., pathogenic versus benign) and the nomenclature used to describe variants (e.g., mutations, single nucleotide polymorphisms (SNPs) and polymorphisms). Dalgleish et al. appear to be mainly discussing "gene or variant nomenclature" and other issues not really relevant to "pathogenicity classification." Nomenclature used to refer to genes as established by the Human Genome Organization (HUGO) Gene Nomenclature Committee, and nomenclature used to refer to DNA variants as established by the Human Genome Variation Society and den Dunnen et al.1, a co-author of our Correspondence, are now widely accepted and used and thus not a real issue anymore. We can! also reassure Dalgleish et al. that the MutaDATABASE principal investigators, some of whom are responsible for large diagnostic laboratories, the scientific advisory board of 80 renowned geneticists, and the hundreds of clinical and molecular geneticists involved in this project are fully aware of the pioneering work that Dalgleish et al. have already performed, and which is elegantly reviewed in their comments. That said, there remains a lack of a consensus on a nomenclature and pathogenicity classification system for DNA variants. Many papers and databases still contain ill-defined and inappropriate variant descriptions, such as SNPs, polymorphisms, functional polymorphisms and mutations. Furthermore, no consensus exists among geneticists as to how to score the effect of the variants in terms of pathogenicity, which is after all the most important objective and critical aspect in genetic diagnosis. This results in a myriad of pathogenicity classification systems, with each laboratory having its own private in-house classification system. The statement from Dalgleish et al. that "the cancer genetics community has begun using this [The International Agency for Research on Cancer] (IARC) system" described by Plon et al.2 is more hope than hype as most diagnostic laboratories simply do not use this classification. Nevertheless, the IARC classification, together with the American C! ollege of Medical Genetics Laboratory Quality Assurance Committee Working Group on Standards for Interpretation of Sequence Variations Revisions 2007 (ref. 3), the recommendations proposed by the Clinical Molecular Genetics Society (http://cmgsweb.shared.hosting.zen.co.uk/BPGs/Best_Practice_Guidelines.htm) and the recommendations and evaluation from a substantial number of the large diagnostic laboratories have resulted in a pathogenicity classification guide, which is now posted on the MutaDATABASE website (http://www.mutadatabase.org/). We recognize that ongoing efforts will be needed to continue to develop and refine this classification system, and most importantly to engage with all laboratories to ensure universal adoption of a common classification system. We hope to move the community toward objective scoring approaches and away from subjective methods that lead to inconsistent assessment of the DNA variants. Apart from the fact that there is no consensus on pathogenicity classification, more importantly many DNA variants have proven to have been incorrectly classified, both in the literature and in existing databases4. Such misclassification, where benign variants are referred to as pathogenic and vice versa, is partly the consequence of the above-described absence of any consensus for pathogenicity classification. More difficulties arise owing to the absence of data-driven analytical systems to suggest pathogenicity classification (such as now provided by the MutaREPORTER software), and the absence of a real mathematical model for variant assessment and insufficient curation in databases. In terms of the issue of data sharing, Dalgleish et al. raise two different points. First, they suggest that issues around data "ownership" might be the bottleneck in submission of molecular and clinical information into public databases by diagnostic laboratories. This turns out to be a misconception as it is only the rare exception where a clinical diagnostic laboratory makes intellectual property or ownership claims on molecular data. The MutaDATABASE website now lists >100 diagnostic laboratories that are willing to release their data into the public domain through MutaDATABASE, with only two nonparticipating laboratories. All laboratories participating in the MutaDATABASE project adhere to the MutaDATABASE charter (http://www.mutadatabase.org/index.php?option=com_content&view=article&id=51&Itemid=50) that states that DNA variants are "res publica" (public property) and do not belong to any single entity, such as the diagnostic laboratory identifying the variant,! the patient from which it came or the doctor diagnosing the disease. The MutaDATABASE charter does not state that the submitters must relinquish all rights to the submitted data to MutaDATABASE; it simply states that the submitted data become publicly available and "open access" with "no restrictions and no usage fees." It is ironic that Dalgleish et al. raise questions over public access to MutaDATABASE data and claim there are "issues around data 'ownership'" while at the same time defending the "copyright and disclaimer statement" of other databases they seem to support. Second, Dalgleish et al. seem to underestimate the real bottleneck in submission of DNA variants into the public domain, namely the time and effort required for submission and pathogenicity evaluation. Many of the large diagnostic laboratories participating in MutaDATABASE have vast numbers of variants that have been clinically evaluated for pathogenicity, likely greater than what is present in the combined literature and public databases taken together. The fact that these variants have not been published in the literature or submitted to databases is mostly a matter of the time and effort required to place these data in the public domain. Manual submission easily takes up several minutes per variant, even when portals are used such as that provided by Dalgleish et al., which they refer to as "Cafe Variome." One way to encourage diagnostic laboratories to submit all their variants is by enabling automated submission using the same software that these laboratories use to do the daily work of variant annotation. For this purpose, the specific software program MutaREPORTER was developed, which couples variant assessment to variant submission. All laboratories using MutaREPORTER to do their day-to-day variant assessment can query MutaDATABASE to receive information about known variants, and they can also automatically submit this information into MutaDATABASE. The MutaREPORTER software is also made available at no charge to all curators in MutaDATABASE. Although licensing is currently required from some users to provide the financial support necessary for development of the software, we are seeking other sources of funding so that licensing fees can be kept to a minimum. In terms of their third point, Dalgleish et al. appear to suggest that a license to the MutaREPORTER is necessary to obtain the information in MutaDATABASE. As stated on the MutaDATABASE charter, all information in MutaDATABASE is "freely available" and there are "no usage fees." The license for MutaREPORTER is only applicable to those laboratories that want to use the software to perform variant assessment, in very much the same way as they might use other commercial software. Furthermore, the MutaREPORTER software is freely available for all curators of MutaDATABASE. The free access to MutaDATABASE is by no means different from other variant databases advocated by Dalgleish et al. In fact, the real difference between MutaDATABASE and other variant databases is that the majority of existing variant databases are in the hands of private curators, universities or companies that without exception have personal rights to the data, and therefore are not really "public.! " MutaDATABASE, to the contrary, is truly res publica, and belongs to the public as all submitters and curators form the nonprofit foundation that currently holds the database. It should be mentioned that the MutaDATABASE group is now working with other organizations involved in variant curation, including the Human Genome Mutation Database, the Human Variome Project, the Leiden Open Variation Database and ClinVar, as we believe the only way to achieve community consensus is through broad collaborations. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * GENEDX, Gaithersburg, Maryland, USA. * Sherri Bale * Harvard Medical School, Boston, Massachusetts, USA. * Heidi L Rehm * Institute of Human Genetics, University of California San Francisco, San Francisco, California, USA. * Robert Nussbaum * Department of Human Genetics, Emory University, Atlanta, Georgia, USA. * Madhuri Hegde * Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands. * Johan T den Dunnen * GENDIA, Antwerp, Belgium. * Patrick Willems Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Patrick Willems Author Details * Sherri Bale Search for this author in: * NPG journals * PubMed * Google Scholar * Heidi L Rehm Search for this author in: * NPG journals * PubMed * Google Scholar * Robert Nussbaum Search for this author in: * NPG journals * PubMed * Google Scholar * Madhuri Hegde Search for this author in: * NPG journals * PubMed * Google Scholar * Johan T den Dunnen Search for this author in: * NPG journals * PubMed * Google Scholar * Patrick Willems Contact Patrick Willems Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Why an abbreviated FDA pathway for biosimilars is overhyped
- Nat Biotechnol 29(9):794-795 (2011)
Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Why an abbreviated FDA pathway for biosimilars is overhyped * Henry I Miller1Journal name:Nature BiotechnologyVolume: 29,Pages:794–795Year published:(2011)DOI:doi:10.1038/nbt.1960Published online08 September 2011 To the Editor: This journal has highlighted the debate about the likelihood that the US Food and Drug Administration (FDA) will require clinical data for its proposed pathway for biosimilars, or biogenerics—copies of innovator biologics. The head of FDA's drug center, Janet Woodcock, has acknowledged in congressional testimony (http://www.fda.gov/NewsEvents/Testimony/ucm154070.htm) the scientific and technical challenges posed by biosimilars. She said that in asking for new data, the agency "will be influenced by the extent to which the follow-on product can be demonstrated to be sufficiently similar (structurally, functionally, and clinically) to an approved protein product to permit some degree of reliance on the findings of safety and effectiveness for the approved product." That demonstration will certainly involve sophisticated analytical chemistry and possibly animal studies. And she emphasized the importance of possible immunogenicity—the ability to stimulate an immune respo! nse—of a follow-on version of a biological drug. Woodcock observed that "The ability to predict immunogenicity of a protein product, particularly the more complex proteins, is extremely limited," and concluded that "Therefore, some degree of clinical assessment of a new product's immunogenic potential will ordinarily be needed." Additional indications of the FDA's view of biosimilars are provided in two publications, one of them from last month. In the Federal Register last October1, the agency acknowledged that the Biologics Price Competition and Innovation Act of 2009 is intended to align with "appropriate reliance on what is already known about a drug, thereby saving time and resources and avoiding unnecessary duplication of human or animal testing." But it also acknowledges that "The implementation of an abbreviated approval pathway for biological products can present challenges given the scientific and technical complexities that may be associated with the larger and often more complex structure of biological products...." The detail in the FDA's statement is revealing. It describes two levels of similarity. To meet the lower, more lenient standard, a product would be considered biosimilar to the reference product if it "is highly similar to the reference product notwithstanding minor differences in clinically inactive components, and if there are no clinically meaningful differences between the biological product and the reference product in terms of safety, purity, and potency" [emphasis added]. This finding, when accepted by the FDA, would substitute for a demonstration of the subject product's efficacy, which would have been established by the reference product. It is hard to imagine how one could demonstrate the absence of "clinically meaningful differences between the biological product and the reference product in terms of safety, purity, and potency of the product" without new clinical data. The report goes on to say that "To meet the higher standard of interchangeability, a product must demonstrate that it can be expected to produce the same clinical result as the reference product in any given patient and, if the biological product is administered more than once to an individual, the risk in terms of safety or diminished efficacy of alternating or switching between the use of the biological product and the reference product is not greater than the risk of using the reference product without such alternation or switch." The second publication, in the New England Journal of Medicine by four senior FDA officials2, provides additional confirmation of the earlier statements: First, "Generally, therapeutic proteins must have a specific set of structural features (e.g., amino acid sequence, glycosylation, protein folding) essential to their intended effect, and slight modifications can affect their performance in humans"; second, "inadvertent chemical modifications can affect their immunogenicity"; third, "additional animal and clinical studies will generally be needed for protein biosimilars for the foreseeable future"; fourth, before regulators can even advise on required animal and human studies, "the FDA should already have completed an in-depth review of comparative analytic characterization and in vitro data"; and fifth, "[t]he FDA process for biosimilars must include product-specific safety monitoring" because "pharmaceutical companies will make manufacturing-related ! changes to biologics periodically throughout their lifecycles, and even small changes could affect safety or efficacy." Thus, it seems a foregone conclusion that clinical trials—possibly large ones to achieve sufficient statistical power—will be required to demonstrate the efficacy and, especially, the safety of 'biosimilars' before the FDA approves them. The higher standard for interchangeability will be extremely difficult to meet. If any further insight into the FDA's mindset is needed in addition to the clear statements by the agency's top drug regulator and the October 2010 Federal Register notice, there are the agency's approvals over many years of a small number of 'follow-on biologics'—biosimilars or generic biologicals by another name—all of which required a substantial amount of laboratory and clinical testing. This history and the agency's rationale for those approvals is summarized in a 2007 article by FDA officials3. Depending on where their self-interest lies, various interested parties, including insurance companies, healthcare providers, pharmaceutical companies and members of Congress have aggressively lobbied FDA to make policy toward biosimilars in a way that favors the developer of either the original drug or the follow-on version—most often turning on how the agency defines terms like 'exclusivity' and 'bioequivalence'. The high costs involved in planning, conducting and analyzing the results of clinical trials will prevent a stampede to make biosimilars; in fact, several major drug companies are pursuing the development of biosimilars as though they were completely new and distinct from the original products and have expressed their intention to submit a new Biologics License Application to obtain marketing approval. Thus, the savings to federal entitlement programs, insurers and patients will surely be far less than some of the hyperbolic predictions made by politicians and others. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * The Hoover Institution, Stanford University, Stanford, California, USA. * Henry I Miller Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Henry I Miller Author Details * Henry I Miller Contact Henry I Miller Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Stem cell funding in the Midwest
- Nat Biotechnol 29(9):795 (2011)
Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Stem cell funding in the Midwest * Jonathan M W Slack1 * Dan S Kaufman1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Page:795Year published:(2011)DOI:doi:10.1038/nbt.1959Published online08 September 2011 To the Editor: We noticed that the news story "Stem cell funding resumes" by Laura DeFrancesco (Nat. Biotechnol.29, 468, 2011) contained the final sentence "...efforts continue in at least two states, Minnesota and Oklahoma, to prohibit hESC [human embryonic stem cell] research." This does not accurately describe the status of hESC research in Minnesota today. There were unsuccessful legislative efforts in Minnesota this past session to prohibit and restrict funding for somatic cell nuclear transfer (SCNT) procedures for making new hESC lines. There were no efforts to restrict hESC research generally. This research is permissible under Minnesota law and continues to be performed at the University of Minnesota. The SCNT legislation passed by the legislature was opposed by patient advocacy groups, the business community and both the University of Minnesota and the Mayo Clinic. Governor Dayton vetoed the legislation in a strongly worded statement. However, even if the legislation had been enacted, it would not have limited hESC research generally. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Stem Cell Institute, University of Minnesota, McGuire Translational Research Facility, Minneapolis, Minnesota, USA. * Jonathan M W Slack & * Dan S Kaufman Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jonathan M W Slack Author Details * Jonathan M W Slack Contact Jonathan M W Slack Search for this author in: * NPG journals * PubMed * Google Scholar * Dan S Kaufman Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Comprehensive catalog of European biobanks
- Nat Biotechnol 29(9):795-797 (2011)
Nature Biotechnology | Opinion and Comment | Correspondence Comprehensive catalog of European biobanks * H-Erich Wichmann1, 2, 29 * Klaus A Kuhn3, 29 * Melanie Waldenberger1, 2 * Dominik Schmelcher3 * Simone Schuffenhauer4 * Thomas Meitinger4, 5 * Sebastian H R Wurst3 * Gregor Lamla3 * Isabel Fortier6, 7 * Paul R Burton6, 8 * Leena Peltonen9, 10, 11, 12, 28 * Markus Perola13 * Andres Metspalu14 * Peter Riegman15 * Ulf Landegren16 * Michael J Taussig17 * Jan-Eric Litton18 * Martin N Fransson18 * Johann Eder19 * Anne Cambon-Thomsen20, 21 * Jasper Bovenberg22 * Georges Dagher23 * Gert-Jan van Ommen24 * Michael Griffith25 * Martin Yuille26 * Kurt Zatloukal27 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:795–797Year published:(2011)DOI:doi:10.1038/nbt.1958Published online08 September 2011 To the Editor: Biobanks are well-organized resources comprising biological samples and associated information that are accessible to scientific investigation1, 2. They have become a key element for research involving human genetic or genomic and proteomic information in conjunction with other personal or health data. There is consensus in the scientific community that progress in understanding disease will depend on the establishment, harmonization and broad use of this information3, 4, 5, 6, 7.The large spectrum of existing biobanks has been considered as a specific strength of European research4, 6. Their optimal use, however, is constrained by fragmentation, a lack of harmonization, incompleteness and a lack of overview of existing resources1, 3. 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 Primary authors * These authors contributed equally to this work. * H-Erich Wichmann & * Klaus A Kuhn Affiliations * Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. * H-Erich Wichmann & * Melanie Waldenberger * Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany. * H-Erich Wichmann & * Melanie Waldenberger * Institute of Medical Statistics and Epidemiology, Technische Universität München, Munich, Germany. * Klaus A Kuhn, * Dominik Schmelcher, * Sebastian H R Wurst & * Gregor Lamla * Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. * Simone Schuffenhauer & * Thomas Meitinger * Institute of Human Genetics, Technical University, Munich, Germany. * Thomas Meitinger * Public Population Project in Genomics (P3G), University of Montreal, Montreal, Canada. * Isabel Fortier & * Paul R Burton * Département de Médecine Sociale et Préventive, University of Montreal, Montreal, Canada. * Isabel Fortier * Departments of Health Sciences and Genetics, University of Leicester, Leicester, UK. * Paul R Burton * Institute for Molecular Medicine Finland FIMM, Helsinki, Finland. * Leena Peltonen * Department of Medical Genetics, University of Helsinki, Helsinki, Finland. * Leena Peltonen * Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland. * Leena Peltonen * The Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA. * Leena Peltonen * National Public Health Institute, Helsinki, Finland. * Markus Perola * Estonian Genome Center of University of Tartu, Tartu, Estonia. * Andres Metspalu * Department of Pathology, Josephine Nefkens Institute, Erasmus Medical Center, Rotterdam, The Netherlands. * Peter Riegman * Department of Genetics and Pathology, University of Uppsala, Uppsala, Sweden. * Ulf Landegren * Babraham Bioscience Technologies, Cambridge, UK. * Michael J Taussig * Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden. * Jan-Eric Litton & * Martin N Fransson * Alps Adria University Klagenfurt, Institute for Informatics-Systems, Klagenfurt, Austria. * Johann Eder * Inserm, Département of Epidemiology, Health Economics and Public Health, University Paul Sabatier, Toulouse, France. * Anne Cambon-Thomsen * Genotoul, Genetics and Society Platform, Toulouse Midi-Pyrénées Genopole, Castanet-Tolosan, France. * Anne Cambon-Thomsen * Legal Pathways Institute for Health and Biolaw, Aerdenhout, The Netherlands. * Jasper Bovenberg * Inserm, Public Health Institute, Paris, France. * Georges Dagher * Department of Human Genetics, Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands. * Gert-Jan van Ommen * Trinity College Dublin, Dublin, Ireland. * Michael Griffith * The University of Manchester, Centre for Integrated Genomic Medical Research, Manchester, UK. * Martin Yuille * Institute of Pathology, Medical University of Graz, Graz, Austria. * Kurt Zatloukal * Deceased. * Leena Peltonen Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * H-Erich Wichmann Author Details * H-Erich Wichmann Contact H-Erich Wichmann Search for this author in: * NPG journals * PubMed * Google Scholar * Klaus A Kuhn Search for this author in: * NPG journals * PubMed * Google Scholar * Melanie Waldenberger Search for this author in: * NPG journals * PubMed * Google Scholar * Dominik Schmelcher Search for this author in: * NPG journals * PubMed * Google Scholar * Simone Schuffenhauer Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Meitinger Search for this author in: * NPG journals * PubMed * Google Scholar * Sebastian H R Wurst Search for this author in: * NPG journals * PubMed * Google Scholar * Gregor Lamla Search for this author in: * NPG journals * PubMed * Google Scholar * Isabel Fortier Search for this author in: * NPG journals * PubMed * Google Scholar * Paul R Burton Search for this author in: * NPG journals * PubMed * Google Scholar * Leena Peltonen Search for this author in: * NPG journals * PubMed * Google Scholar * Markus Perola Search for this author in: * NPG journals * PubMed * Google Scholar * Andres Metspalu Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Riegman Search for this author in: * NPG journals * PubMed * Google Scholar * Ulf Landegren Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Taussig Search for this author in: * NPG journals * PubMed * Google Scholar * Jan-Eric Litton Search for this author in: * NPG journals * PubMed * Google Scholar * Martin N Fransson Search for this author in: * NPG journals * PubMed * Google Scholar * Johann Eder Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Cambon-Thomsen Search for this author in: * NPG journals * PubMed * Google Scholar * Jasper Bovenberg Search for this author in: * NPG journals * PubMed * Google Scholar * Georges Dagher Search for this author in: * NPG journals * PubMed * Google Scholar * Gert-Jan van Ommen Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Griffith Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Yuille Search for this author in: * NPG journals * PubMed * Google Scholar * Kurt Zatloukal Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (397K) Supplementary Figures 1–5 and Supplementary Tables 1–3 Additional data - Pharmaceutical patent evaluation and licensing using a stochastic model and Monte Carlo simulations
- Nat Biotechnol 29(9):798-801 (2011)
Nature Biotechnology | Feature | Patents Pharmaceutical patent evaluation and licensing using a stochastic model and Monte Carlo simulations * Liangchuan Wu1 * Lianghong Wu2 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:798–801Year published:(2011)DOI:doi:10.1038/nbt.1963Published online08 September 2011 The long-neglected patent value pattern must be considered when evaluating patents. View full text Figures at a glance * Figure 1: The S-shape curve life cycle of patent value. Successful pharmaceutical R&D in each phase increases the potential value of a patent. In the early stages of patent licensing, the patent's value is low because of the risks and uncertainties involved. However, in the later stages, such as phases 1–3, the value of a pharmaceutical patent grows at an accelerated pace as the potentially huge market revenues protected by the patent are realized. Data source: Ministry of Economic Affairs16. * Figure 2: The patent value obtained by 2,000 Monte Carlo simulations represents the life cycle as well as value uncertainty over a 20-year period. () The union of the 2,000 patent value paths under conditions of uncertainty; () and () are taken from the union of the 2,000 simulations, and illustrate two possible scenarios of patent value under uncertainty. * Figure 3: Life cycle uncertainty, market sales uncertainty and upper/lower bounds of possible patent value. () Base scenario (reversion rate: 2%, volatility: 8%, drift rate:10%). () Patent value (reversion rate decreases from 2% to 1%). () Patent value (volatility increases from 8% to 20%). () Patent value (drift rate increases from 10% to 30%). 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 * Liangchuan Wu is at National Chung Hsing University, Taichung, Taiwan * Lianghong Wu is at National Central University, ChungLi, Taiwan. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Lianghong Wu Author Details * Liangchuan Wu Search for this author in: * NPG journals * PubMed * Google Scholar * Lianghong Wu Contact Lianghong Wu Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (344K) Supplementary Methods and Supplementary Table 1 Additional data - Recent patent applications in breast cancer diagnostics
- Nat Biotechnol 29(9):802 (2011)
Article preview View full access options Nature Biotechnology | Feature | Patents Recent patent applications in breast cancer diagnostics Journal name:Nature BiotechnologyVolume: 29,Page:802Year published:(2011)DOI:doi:10.1038/nbt.1980Published online08 September 2011 Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. - Toward safer regenerative medicine
- Nat Biotechnol 29(9):803-805 (2011)
Article preview View full access options Nature Biotechnology | News and Views Toward safer regenerative medicine * Peter W Andrews1Journal name:Nature BiotechnologyVolume: 29,Pages:803–805Year published:(2011)DOI:doi:10.1038/nbt.1974Published online08 September 2011 A newly identified surface marker on human embryonic stem cells allows rare tumor-forming cells to be removed from preparations of differentiated cells. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Peter W. Andrews is at the Centre for Stem Cell Biology, University of Sheffield, Sheffield, UK. Competing financial interests I receive payment from the Wistar Institute for a proportion of royalty payments that Wistar receives form the sale of TRA antibodies. Corresponding author Correspondence to: * Peter W Andrews Author Details * Peter W Andrews Contact Peter W Andrews Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Semiconductors charge into sequencing
- Nat Biotechnol 29(9):805-807 (2011)
Article preview View full access options Nature Biotechnology | News and Views Semiconductors charge into sequencing * Keith Robison1Journal name:Nature BiotechnologyVolume: 29,Pages:805–807Year published:(2011)DOI:doi:10.1038/nbt.1965Published online08 September 2011 The convergence of semiconductor chips and DNA sequencing begets a strong contender in the race to build the best sequencers. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Keith Robison is at Infinity Pharmaceuticals, Cambridge, Massachusetts, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Keith Robison Author Details * Keith Robison Contact Keith Robison Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Genome remodeling
- Nat Biotechnol 29(9):807-808 (2011)
Article preview View full access options Nature Biotechnology | News and Views Genome remodeling * Yizhi Cai1 * Jef D Boeke1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:807–808Year published:(2011)DOI:doi:10.1038/nbt.1964Published online08 September 2011 Alteration of a stop codon across an entire bacterial genome opens the way to exploring the biotech potential of synthetic genetic codes. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * 日本語要約 * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Yizhi Cai and Jef D. Boeke are in the Department of Molecular Biology and Genetics and the High Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jef D Boeke Author Details * Yizhi Cai Search for this author in: * NPG journals * PubMed * Google Scholar * Jef D Boeke Contact Jef D Boeke Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - Verification of systems biology research in the age of collaborative competition
- Nat Biotechnol 29(9):811-815 (2011)
Nature Biotechnology | Computational Biology | Commentary Verification of systems biology research in the age of collaborative competition * Pablo Meyer1 * Leonidas G Alexopoulos2 * Thomas Bonk3 * Andrea Califano4 * Carolyn R Cho5 * Alberto de la Fuente6 * David de Graaf7 * Alexander J Hartemink8 * Julia Hoeng3 * Nikolai V Ivanov3 * Heinz Koeppl9 * Rune Linding10 * Daniel Marbach11 * Raquel Norel1 * Manuel C Peitsch3 * J Jeremy Rice1 * Ajay Royyuru1 * Frank Schacherer12 * Joerg Sprengel13 * Katrin Stolle3 * Dennis Vitkup4 * Gustavo Stolovitzky1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:811–815Year published:(2011)DOI:doi:10.1038/nbt.1968Published online08 September 2011 Collaborative competitions in which communities of researchers compete to solve challenges may facilitate more rigorous scrutiny of scientific results. View full text Figures at a glance * Figure 1: Current approaches to systems biology verification. Different paths for reaching systems biology verification are represented, both for academia (blue) and for industry (red). Black represents pathways common to industry and academia. The color of the rectangles represent the grounds on which the assessment of systems biology results are based: mostly on innovation (green), mostly robustness (orange) and both innovation and robustness (yellow). The thickness of the arrows represents the current predominant pathway. * Figure 2: Example application of IMPROVER for verification of a plausible research workflow. 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 * IBM Computational Biology Center, Yorktown Heights, New York, USA. * Pablo Meyer, * Raquel Norel, * J Jeremy Rice, * Ajay Royyuru & * Gustavo Stolovitzky * National Technical University of Athens, Athens, Greece. * Leonidas G Alexopoulos * Philip Morris International R&D, Neuchâtel, Switzerland. * Thomas Bonk, * Julia Hoeng, * Nikolai V Ivanov, * Manuel C Peitsch & * Katrin Stolle * Center for Computational Biology and Bioinformatics, Department of Biomedical Informatics, Columbia University, New York, USA. * Andrea Califano & * Dennis Vitkup * Modeling and Simulation, Merck & Co., Rahway, New Jersey, USA. * Carolyn R Cho * Center for Advanced Studies, Research and Development in Sardinia (CRS4), Laboratorio di Bioinformatica, Parco tecnologico della Sardegna, Pula, Italy. * Alberto de la Fuente * Selventa, Cambridge, Massachusetts, USA. * David de Graaf * Duke University, Durham, North Carolina, USA. * Alexander J Hartemink * ETH Zurich, Zurich, Switzerland. * Heinz Koeppl * Cellular Signal Integration Group (C-SIG), Center for Biological Sequence Analysis (CBS), Department of Systems Biology, Technical University of Denmark (DTU), Copenhagen, Denmark. * Rune Linding * Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT) and Broad Institute of MIT and Harvard, Cambridge, USA. * Daniel Marbach * Biobase GmbH, Wolfenbuettel, Germany. * Frank Schacherer * IBM Life Sciences Division, Zurich, Switzerland. * Joerg Sprengel Competing financial interests IBM and PMI authors performed this work under a joint research collaboration funded by PMI. Corresponding author Correspondence to: * Gustavo Stolovitzky Author Details * Pablo Meyer Search for this author in: * NPG journals * PubMed * Google Scholar * Leonidas G Alexopoulos Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Bonk Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Califano Search for this author in: * NPG journals * PubMed * Google Scholar * Carolyn R Cho Search for this author in: * NPG journals * PubMed * Google Scholar * Alberto de la Fuente Search for this author in: * NPG journals * PubMed * Google Scholar * David de Graaf Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander J Hartemink Search for this author in: * NPG journals * PubMed * Google Scholar * Julia Hoeng Search for this author in: * NPG journals * PubMed * Google Scholar * Nikolai V Ivanov Search for this author in: * NPG journals * PubMed * Google Scholar * Heinz Koeppl Search for this author in: * NPG journals * PubMed * Google Scholar * Rune Linding Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Marbach Search for this author in: * NPG journals * PubMed * Google Scholar * Raquel Norel Search for this author in: * NPG journals * PubMed * Google Scholar * Manuel C Peitsch Search for this author in: * NPG journals * PubMed * Google Scholar * J Jeremy Rice Search for this author in: * NPG journals * PubMed * Google Scholar * Ajay Royyuru Search for this author in: * NPG journals * PubMed * Google Scholar * Frank Schacherer Search for this author in: * NPG journals * PubMed * Google Scholar * Joerg Sprengel Search for this author in: * NPG journals * PubMed * Google Scholar * Katrin Stolle Search for this author in: * NPG journals * PubMed * Google Scholar * Dennis Vitkup Search for this author in: * NPG journals * PubMed * Google Scholar * Gustavo Stolovitzky Contact Gustavo Stolovitzky Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - An unbiased genome-wide analysis of zinc-finger nuclease specificity
- Nat Biotechnol 29(9):816-823 (2011)
Nature Biotechnology | Research | Article An unbiased genome-wide analysis of zinc-finger nuclease specificity * Richard Gabriel1, 4 * Angelo Lombardo2, 4 * Anne Arens1 * Jeffrey C Miller3 * Pietro Genovese2 * Christine Kaeppel1 * Ali Nowrouzi1 * Cynthia C Bartholomae1 * Jianbin Wang3 * Geoffrey Friedman3 * Michael C Holmes3 * Philip D Gregory3 * Hanno Glimm1 * Manfred Schmidt1, 4 * Luigi Naldini2, 4 * Christof von Kalle1, 4 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:816–823Year published:(2011)DOI:doi:10.1038/nbt.1948Received12 May 2011Accepted19 July 2011Published online07 August 2011 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 Zinc-finger nucleases (ZFNs) allow gene editing in live cells by inducing a targeted DNA double-strand break (DSB) at a specific genomic locus. However, strategies for characterizing the genome-wide specificity of ZFNs remain limited. We show that nonhomologous end-joining captures integrase-defective lentiviral vectors at DSBs, tagging these transient events. Genome-wide integration site analysis mapped the actual in vivo cleavage activity of four ZFN pairs targeting CCR5 or IL2RG. Ranking loci with repeatedly detectable nuclease activity by deep-sequencing allowed us to monitor the degree of ZFN specificity in vivo at these positions. Cleavage required binding of ZFNs in specific spatial arrangements on DNA bearing high homology to the intended target site and only tolerated mismatches at individual positions of the ZFN binding sites. Whereas the consensus binding sequence derived in vivo closely matched that obtained in biochemical experiments, the ranking of in vivo clea! vage sites could not be predicted in silico. Comprehensive mapping of ZFN activity in vivo will facilitate the broad application of these reagents in translational research. View full text Figures at a glance * Figure 1: Trapping of IDLVs into ZFN-induced DNA DSBs. () Upon their transient expression, ZFNs bind to the intended DNA sequence and to off-target sites and introduce a DSB. During NHEJ repair of these DSBs (which often results in insertion or deletion of sequences), a full copy of the IDLV can be introduced into the ZFN target site but also at off-target ZFN-induced DSBs, thereby stably marking the transient DSB. () IDLV-GFP transduced A549 cells were photon-irradiated with different doses 24 h after transduction and GFP-positive cells were measured by flow-cytometry analysis (FACSCalibur). At the last time point analyzed, the fractions of GFP-expressing cells were: 0 Gy: 4.73 ± 3.56% (dark blue line); 2 Gy: 31.80 ± 5.82% (light green line); 5 Gy: 59.40 ± 7.93% (dark green line). () Same as in panel in K562 cells. 0 Gy: 2.3 ± 0.2% (dark blue line); 2 Gy: 8.5 ± 1.1% (light green line); 5 Gy: 10.8 ± 1.4% (dark green line). () Representative FACS analysis of IDLV-transduced K562 cells either without ZFNs or together with CC! R5wt or CCR5muF ZFNs analyzed after 4 weeks. Percentages of GFP-positive cells were: CCR5wt/IDLV: 6.5 ± 0.1%; CCR5muF/IDLV: 6.06 ± 0.3%; IDLV 2.6 ± 0.15%; mean ± s.d., n = 3. () Insertion sites located in a ± 60-bp window surrounding the ZFN binding site in exon 3 of the CCR5 gene. Blue bars: integration site from wild-type ZFN (CCR5wt/IDLV); green bars: integration site from ZFN with obligate heterodimeric FokI domain (CCR5muF/IDLV). () Insertion sites (IS) located in a ± 60-bp window surrounding the ZFN binding site in exon 5 of IL2RG. Blue bars: IL2RG1/IDLV; green bars: IL2RG2/IDLV. * Figure 2: Gene targeting using ZFNs and a homologous donor vector. () Co-delivery of a donor template DNA, which contains homology regions to the target site, additionally allows targeted integration of solely an exogenous expression cassette. Therefore, treatment of cells with ZFN and the cognate homologous donor IDLV can result in three different ways of on-target integration: (i) integration of a single expression cassette (without residual vector sequence; left drawing) or of head-to-tail concatemers (with intervening viral sequences) by HDR at the target locus; (ii) integration by a combined mechanism of HDR and NHEJ, thereby joining vector sequence to the target locus (middle left drawing); and (iii) pure NHEJ-mediated IDLV integration (middle right drawing). Also by using a homology- containing donor vector off-target integration by NHEJ can occur (right drawing). () Meta-analysis of 258 integration sites retrieved from 212 GFP-positive cell clones derived from the homology-containing donor IDLVs plus ZFN- treated cells. 89.9% of the! integrations occurred by HDR at the intended ZFN site. A further 3.9% of the integrations occurred at the intended target site by a combined mechanism of HDR and NHEJ. 6.2% of the IDLV integrations were into unidentified off-target genomic locations. () Representative FACS analysis (n = 3) of K562 cells treated with a GFP-expressing IDLV containing homologous sequences to the CCR5 target site either alone (without ZFNs) or together with CCR5wt ZFNs or CCR5muF ZFNs. The frequency of GFP-positive cells is indicated for each sample. Note that the presence of homology dramatically increased the number of GFP+ cells. * Figure 3: CLIS at genomic loci in ZFN-treated cells. () Genomic regions with ≥3 integration sites in CCR5-ZFN–treated samples. Blue line: identity to the ZFN target site; dark-blue bars: CCR5wt/IDLV; light-blue bars: CCR5wt/IDLVhc; dark-green bars: CCR5muF/IDLV; light-green bars: CCR5muF/IDLVhc. X axis: nearest RefSeq gene and percentage of identity to the ZFN target site. IS, insertion site. () Enrichment of CCR5-ZFN binding sites at CLIS loci. The curves show the average identity of the 24-bp ZFN-dimer binding site (separated by a 5-bp spacer) to the CCR5 target site in close vicinity to different IDLV integration site data sets. The x axis shows the location of the dimer binding site relative to the appropriate integration site data set. Blue: CLIS loci described in panel ; green: 188 single integration site loci from the CCR5muF/IDLV samples; black: 98 integration site loci retrieved from no ZFN samples (IDLV). () Genomic regions with ≥3 integration site in IL2RG-ZFN–treated cells. Brown line: identity to the ZFN t! arget site; brown bars: IL2RG1/IDLV; orange bars: IL2RG1/IDLVhi; red bars: IL2RG2/IDLV. () Enrichment of IL2RG ZFN binding sites at CLIS loci. Similar to , but brown: IL2RG CLIS loci from ; red: 170 single integration-site loci from IL2RG1/IDLV sample; black: 98 integration-site loci retrieved from no ZFN samples (IDLV). * Figure 4: Validation of (nr)LAM-PCR identified off-target CLIS loci. Cel1 analysis of the CCR5, ABLIM2, PGC, KRR1, PKN2, FBXL11, ZCCHC14, C3orf59, SOS1 and ACSM5 loci in K562 cells mock transfected (Con) or transfected with plasmid DNA encoding CCR5wt or CCR5muF. Arrows denote the Cel1 cleavage bands, and the percentage of modified alleles determined by the assay is indicated below each lane. * Figure 5: Comparative analysis of zinc-finger sequence specificity in vivo. The sequences of the most frequently hit off-target binding sites for the CCR5 ZFNs that were found by DSB trapping can be considered as consensus sequences for the true binding affinity of each zinc-finger combination. Mapping of ZFN-induced DSB for each vector precisely delineates which zinc finger in which particular nucleotide position of its target sequence contributes to off-target DNA binding. The target site sequence itself is indicated under the sequence logos. () The binding sites near the CLIS loci CCR5, ABLIM2, CCR2, PGC, KRR1, FBXL11, ZCCHC14, PKN2, C3orf59, PTGS2, SOS1, ACSM5 and VEZT have been aligned and weighted by the number of integration sites derived from (nr)LAM-PCR experiments to create the consensus binding sequence for CCR5wt ZFN. The SELEX-derived consensus sequence, done as described8, for the left and right CCR5 ZFNs aligned to the intended genomic target, is shown at the bottom. () The binding sites near the CLIS loci IL2RG, SCARB1, SLC31A1, SEC1! 6A, STAG1, RRS1 and FAM133B have been aligned and weighted by the number of integration sites derived from (nr)LAM-PCR to create the consensus binding sequence for IL2RG1 ZFN. ) Accordingly, the binding sites near the CLIS loci IL2RG, A2BP1, SLC31A1, SEC16A, KIAA0528, SF3B1, KCTD8, NARG1L and FAM133B have been aligned and weighted by the number of integration sites derived from (nr)LAM-PCR to create the consensus binding sequence for IL2RG2 ZFN. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Richard Gabriel, * Angelo Lombardo, * Manfred Schmidt, * Luigi Naldini & * Christof von Kalle Affiliations * Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), Heidelberg, Germany. * Richard Gabriel, * Anne Arens, * Christine Kaeppel, * Ali Nowrouzi, * Cynthia C Bartholomae, * Hanno Glimm, * Manfred Schmidt & * Christof von Kalle * San Raffaele Telethon Institute for Gene Therapy (HSR-TIGET), Vita Salute San Raffaele University, Milan, Italy. * Angelo Lombardo, * Pietro Genovese & * Luigi Naldini * Sangamo BioSciences, Inc., Richmond, California, USA. * Jeffrey C Miller, * Jianbin Wang, * Geoffrey Friedman, * Michael C Holmes & * Philip D Gregory Contributions R.G., A.L., H.G., M.S., J.C.M., P.D.G., M.C.H., L.N. and C.v.K. conceived the project, designed experiments and interpreted data. R.G., A.L., P.G., C.K., A.N., J.W., G.F. and C.C.B. performed experiments. R.G., A.A. and J.C.M. conducted bioinformatics analysis. M.C.H. and P.D.G. provided ZFN. R.G., A.L., A.A., J.C.M., M.C.H., P.D.G., M.S., L.N. and C.v.K. prepared and wrote the manuscript. Competing financial interests J.C.M., J.W., G.F., M.C.H. and P.D.G. are full-time employees of Sangamo BioSciences. Corresponding authors Correspondence to: * Luigi Naldini or * Christof von Kalle Author Details * Richard Gabriel Search for this author in: * NPG journals * PubMed * Google Scholar * Angelo Lombardo Search for this author in: * NPG journals * PubMed * Google Scholar * Anne Arens Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey C Miller Search for this author in: * NPG journals * PubMed * Google Scholar * Pietro Genovese Search for this author in: * NPG journals * PubMed * Google Scholar * Christine Kaeppel Search for this author in: * NPG journals * PubMed * Google Scholar * Ali Nowrouzi Search for this author in: * NPG journals * PubMed * Google Scholar * Cynthia C Bartholomae Search for this author in: * NPG journals * PubMed * Google Scholar * Jianbin Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Geoffrey Friedman Search for this author in: * NPG journals * PubMed * Google Scholar * Michael C Holmes Search for this author in: * NPG journals * PubMed * Google Scholar * Philip D Gregory Search for this author in: * NPG journals * PubMed * Google Scholar * Hanno Glimm Search for this author in: * NPG journals * PubMed * Google Scholar * Manfred Schmidt Search for this author in: * NPG journals * PubMed * Google Scholar * Luigi Naldini Contact Luigi Naldini Search for this author in: * NPG journals * PubMed * Google Scholar * Christof von Kalle Contact Christof von Kalle Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (950K) Supplementary Tables 1,2, Supplementary Discussion, Supplementary Methods and Supplementary Figures 1–16 Additional data - Astrocytes from familial and sporadic ALS patients are toxic to motor neurons
- Nat Biotechnol 29(9):824-828 (2011)
Nature Biotechnology | Research | Letter Astrocytes from familial and sporadic ALS patients are toxic to motor neurons * Amanda M Haidet-Phillips1, 2, 7 * Mark E Hester1, 7 * Carlos J Miranda1, 7 * Kathrin Meyer1 * Lyndsey Braun1 * Ashley Frakes1, 2 * SungWon Song1, 3 * Shibi Likhite1, 3 * Matthew J Murtha1, 3 * Kevin D Foust1 * Meghan Rao1 * Amy Eagle1 * Anja Kammesheidt4 * Ashley Christensen4 * Jerry R Mendell1, 2 * Arthur H M Burghes5 * Brian K Kaspar1, 2, 3, 6 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:824–828Year published:(2011)DOI:doi:10.1038/nbt.1957Received15 July 2011Accepted26 July 2011Published online10 August 2011 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 Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease, with astrocytes implicated as contributing substantially to motor neuron death in familial (F)ALS1, 2, 3, 4, 5. However, the proposed role of astrocytes in the pathology of ALS derives in part from rodent models of FALS based upon dominant mutations within the superoxide dismutase 1 (SOD1) gene, which account for <2% of all ALS cases2, 4, 5. Their role in sporadic (S)ALS, which affects >90% of ALS patients, remains to be established. Using astrocytes generated from postmortem tissue from both FALS and SALS patients, we show that astrocytes derived from both patient groups are similarly toxic to motor neurons. We also demonstrate that SOD1 is a viable target for SALS, as its knockdown significantly attenuates astrocyte-mediated toxicity toward motor neurons. Our data highlight astrocytes as a non–cell autonomous component in SALS and provide an in vitro model system to investigate common disease mechanisms! and evaluate potential therapies for SALS and FALS. View full text Figures at a glance * Figure 1: NPCs can be differentiated into highly enriched astrocyte cultures that show a similar gene profile to spinal cord primary astrocytes. () Marker analysis of human NPC-derived astrocytes, showing specific immunoreactivity against human nuclear antigen (hNA); high expression of the astrocyte markers CD44, vimentin and GFAP; absence of the glial progenitor marker NG2; and absence of the microglia marker CD11B. Scale bars, 50 μm. () Comparison of CD11B expression levels by qRT-PCR in NPC-derived astrocyte cultures from control and ALS patients. Mesenchymal stem cells and human microglia were used as negative and positive controls, respectively. Error bars represent s.e.m. () Gene expression profile analysis of NPC-derived astrocytes. Comparisons were made to a human sample of mesenchymal stem cells, undifferentiated NPCs and primary human astrocytes derived from spinal cord. * Figure 2: Astrocytes derived from SALS and FALS patients cause motor neuron death in coculture. () Representative microscopic field showing the morphology of Hb9-GFP+ motor neurons in coculture with human astrocytes at 24 and 120 h. Scale bar, 100 μm. () Soma size and neurite length of Hb9-GFP+ motor neurons at 48 and 96 h when cocultured with astrocytes from FALS, SALS and non-ALS controls. Dashed lines represent group averages. () Counts of Hb9-GFP+ motor neurons per well after 120 h of coculture with astrocytes from FALS, SALS and non-ALS controls. *P < 0.05, **P < 0.01 and ***P < 0.001 compared to non-ALS control cell line (63358). Error bars represent s.e.m. () Representative microscopic field showing the morphology of Hb9-GFP+ motor neurons treated with astrocyte-conditioned media for 24 or 120 h. Scale bar, 100 μm. () Counts of Hb9-GFP+ motor neurons per well after 120 h of treatment with astrocyte-conditioned media. *, P < 0.05; **, P < 0.01; and ***, P < 0.001 compared to 63358 (non-ALS control). Error bars represent s.e.m. * Figure 3: Activation of inflammatory genes in FALS and SALS astrocytes. () Hierarchical clustering analysis of inflammatory cytokine and receptor genes differentially expressed in ALS astrocytes compared to non-ALS control cell line (63358). () Cluster of inflammatory genes most upregulated in ALS astrocytes compared to non-ALS control. Shades of red correspond to the magnitude of increase in gene expression, whereas the intensity of green corresponds to the magnitude of decrease in gene transcript abundance. Display range was set at a maximum of ± 15-fold. * Figure 4: Suppression of SOD1 in both FALS and SALS astrocytes is motor neuron protective. () Representative microscopic fields showing the morphology of motor neurons stained with choline acetyl transferase (ChAT) after 120 h of coculture with human astrocytes transduced with either missense or SOD1 shRNA lentivirus. Scale bar, 100 μm. () Counts of motor neurons per well after 120 h in coculture with astrocytes expressing the missense shRNA (white bars) or the SOD1 shRNA (black bars). Error bars represent s.e.m. () Quantification of SOD1 levels in astrocyte cell lysate measured by ELISA. *, P < 0.05 and **, P < 0.01 compared to 63358 (non-ALS control). Error bars represent s.e.m. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Amanda M Haidet-Phillips, * Mark E Hester & * Carlos J Miranda Affiliations * The Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA. * Amanda M Haidet-Phillips, * Mark E Hester, * Carlos J Miranda, * Kathrin Meyer, * Lyndsey Braun, * Ashley Frakes, * SungWon Song, * Shibi Likhite, * Matthew J Murtha, * Kevin D Foust, * Meghan Rao, * Amy Eagle, * Jerry R Mendell & * Brian K Kaspar * Integrated Biomedical Science Graduate Program, College of Medicine, The Ohio State University, Columbus, Ohio, USA. * Amanda M Haidet-Phillips, * Ashley Frakes, * Jerry R Mendell & * Brian K Kaspar * Molecular, Cellular & Developmental Biology Graduate Program, The Ohio State University, Columbus, Ohio, USA. * SungWon Song, * Shibi Likhite, * Matthew J Murtha & * Brian K Kaspar * Ambry Genetics, Aliso Viejo, California, USA. * Anja Kammesheidt & * Ashley Christensen * Molecular and Cellular Biochemistry, The Ohio State University, Columbus, Ohio, USA. * Arthur H M Burghes * Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA. * Brian K Kaspar Contributions Conceived and designed the experiments: M.E.H., A.M.H.-P., C.J.M., A.H.M.B., J.R.M. and B.K.K. Performed the experiments: M.E.H., A.M.H.-P., C.J.M., K.M., L.B., A.F., S.S., S.L., M.J.M., K.D.F., M.R., A.E., A.K. and A.C. Analyzed the data: B.K.K., M.E.H., A.M.H. and C.J.M. Wrote the manuscript: M.E.H., A.M.H.-P., C.J.M. and B.K.K with input from the other co-authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Brian K Kaspar Author Details * Amanda M Haidet-Phillips Search for this author in: * NPG journals * PubMed * Google Scholar * Mark E Hester Search for this author in: * NPG journals * PubMed * Google Scholar * Carlos J Miranda Search for this author in: * NPG journals * PubMed * Google Scholar * Kathrin Meyer Search for this author in: * NPG journals * PubMed * Google Scholar * Lyndsey Braun Search for this author in: * NPG journals * PubMed * Google Scholar * Ashley Frakes Search for this author in: * NPG journals * PubMed * Google Scholar * SungWon Song Search for this author in: * NPG journals * PubMed * Google Scholar * Shibi Likhite Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew J Murtha Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin D Foust Search for this author in: * NPG journals * PubMed * Google Scholar * Meghan Rao Search for this author in: * NPG journals * PubMed * Google Scholar * Amy Eagle Search for this author in: * NPG journals * PubMed * Google Scholar * Anja Kammesheidt Search for this author in: * NPG journals * PubMed * Google Scholar * Ashley Christensen Search for this author in: * NPG journals * PubMed * Google Scholar * Jerry R Mendell Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur H M Burghes Search for this author in: * NPG journals * PubMed * Google Scholar * Brian K Kaspar Contact Brian K Kaspar Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (5.5M) Supplementary Tables 1–6 and Supplementary Figures 1–11 Additional data - An antibody against SSEA-5 glycan on human pluripotent stem cells enables removal of teratoma-forming cells
- Nat Biotechnol 29(9):829-834 (2011)
Nature Biotechnology | Research | Letter An antibody against SSEA-5 glycan on human pluripotent stem cells enables removal of teratoma-forming cells * Chad Tang1 * Andrew S Lee2 * Jens-Peter Volkmer1, 3 * Debashis Sahoo1 * Divya Nag2 * Adriane R Mosley1 * Matthew A Inlay1 * Reza Ardehali1 * Shawn L Chavez1 * Renee Reijo Pera1 * Barry Behr4 * Joseph C Wu2 * Irving L Weissman1 * Micha Drukker1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:829–834Year published:(2011)DOI:doi:10.1038/nbt.1947Received05 April 2011Accepted18 July 2011Published online14 August 2011 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 An important risk in the clinical application of human pluripotent stem cells (hPSCs), including human embryonic and induced pluripotent stem cells (hESCs and hiPSCs), is teratoma formation by residual undifferentiated cells. We raised a monoclonal antibody against hESCs, designated anti–stage-specific embryonic antigen (SSEA)-5, which binds a previously unidentified antigen highly and specifically expressed on hPSCs—the H type-1 glycan. Separation based on SSEA-5 expression through fluorescence-activated cell sorting (FACS) greatly reduced teratoma-formation potential of heterogeneously differentiated cultures. To ensure complete removal of teratoma-forming cells, we identified additional pluripotency surface markers (PSMs) exhibiting a large dynamic expression range during differentiation: CD9, CD30, CD50, CD90 and CD200. Immunohistochemistry studies of human fetal tissues and bioinformatics analysis of a microarray database revealed that concurrent expression of these! markers is both common and specific to hPSCs. Immunodepletion with antibodies against SSEA-5 and two additional PSMs completely removed teratoma-formation potential from incompletely differentiated hESC cultures. View full text Figures at a glance * Figure 1: Anti-SSEA-5 mAb is specific for hPSCs. () Representative FACS plots demonstrating high SSEA-5 expression on pluripotent hESCs (undiff), and decline of signal after 7-d treatment with FBS (green), and FBS supplemented with retinoic acid (RA; red) or BMP4 (gray). Compared with TRA-1-81, SSEA-3 and SSEA-4, SSEA-5 exhibited a greater reduction in dynamic range following hESC differentiation in retinoic acid. () Pluripotency genes OCT4, NANOG and SOX2 were enriched in the SSEA-5+ versus SSEA-5− populations sorted after 7-d retinoic acid treatment. () Immunostaining of human blastocyst-stage embryos with anti-SSEA-5 (red) overlayed on bright-field (BF) images revealed bright labeling of two ICMs (arrows) in day-6 human monozygotic twin blastocyst. () SSEA-4+ and epithelial-specific antigen (ESA)+ epithelial cells in human teratomas contained a subset of SSEA-5+ cells, amounting to ~2% of total teratoma cells (flow cytometry). () SSEA-5+, but not SSEA-5−, populations from dissociated hESC-derived teratomas reproduce! d teratomas in vivo. *, P < 0.05; **, P < 0.01. Error bars indicate s.d. () 7-month-old human fetal tissues did not exhibit SSEA-5 expression. Analysis at high magnification (http://tma.stanford.edu/cgi-bin/viewAvailableStains.pl?array_block_name=TA-326) revealed that signals observed in the skin and central nervous system were unspecific. () SSEA-5 and the hematopoietic markers CD34 and CD43 were expressed by different cell populations on hESCs differentiated toward the hematopoietic lineage. DAPI (blue) was used to stain nuclei. Scale bars, 100 μm. * Figure 2: Anti-SSEA-5 mAb enables partial removal of teratoma-initiating cells. () Schematic illustration of teratoma-formation assay using sorted fully differentiated hESCs produced through 14-d retinoic acid treatment (red) spiked with undifferentiated hESCs (blue) at a 100:1 ratio. Flow cytometry analyses with anti-SSEA-5 mAb confirmed binding to undifferentiated cells but not to cells from retinoic acid treated cultures (insets). Sorting gates indicate the viability-sorted (dashed square sector) and SSEA-5–depleted (pink-shaded sector) populations sorted from spiked mixtures and transplanted under the kidney capsule of immunodeficient mice. () Time series luciferase signal from implants derived from hESCs following 14-d retinoic acid treatment (blue), spiked hESCs/fully differentiated cells mixtures sorted for viability (purple) and SSEA-5-high depleted mixtures (red). Right panels show representative luciferase imaging of transplanted mice and explanted kidneys. Error bars indicate standard deviation. () Schematic illustration of teratoma-formati! on assay using SSEA-5-high and SSEA-5-low populations sorted (gated as shown on right, blue and red sectors, respectively) from heterogeneous differentiated cultures produced by 3-d retinoic acid treatment. Flow cytometry analyses with anti-SSEA-5 mAb confirmed that the 3-d retinoic acid–treated culture consisted of mixed populations (insets). Error bars indicate standard deviation. () Time series luciferase signal from implants derived from viable, SSEA-5-high and SSEA-5-low populations sorted from hESC cultures treated with retinoic acid for 3 d. Right panels show representative H&E stained sections of explanted tissues emerging from SSEA-5-high and SSEA-5-low populations, demonstrating cartilaginous, epithelial and neural rosette structures (left to right). Scale bars, 100 μm. *, P < 0.05; **, P < 0.01. * Figure 3: Depletion of cells concurrently expressing three PSMs eliminates teratoma-initiation potential. (,) Concurrent expression of three and four PSMs is highly specific for hPSCs. () Analysis of PSM expression levels among >27,000 human tissue microarrays (light blue) highlights a distinct cluster of 120 samples representing undifferentiated hESCs/hiPSCs (red) and germ cell tumors (blue). () Representative expression analysis of three PSMs (CD9, CD30 and CD200) within the microarray database revealed concurrent high levels in undifferentiated ES/IPS cells (red) and germ cell tumors (blue) compared to all other samples (gray). Dotted box indicates those samples expressing PSMs at levels similar to hPSCs, and pie chart presents the proportions of tissue types within the dotted box. Bar graph presents the percentage of nonpluripotent samples (% of total in database) excluded from the PSM high co-expression cluster analyzed with representative combinations of 1–4 PSMs. () Gating strategy used to sort hESCs treated for 3 d with retinoic acid for SSEA-5/CD9/CD90-high and SSEA-5! /CD9/CD90-low populations. () Time series luciferase activity measurements of implants derived from SSEA-5/CD9/CD90-high (purple) and SSEA-5/CD9/CD90-low (red) sorted populations. The TRA-1-81/SSEA-4-high (green) implants were found to exhibit high luciferase activity similar to that of TRA-1-81/SSEA-4-low (orange) and SSEA-5/CD9/CD90-high populations. *, P < 0.01 compared to SSEA-5/CD9/CD90-low grafts. () Representative H&E stained sections of SSEA-5/CD9/CD90-high and SSEA-5/CD9/CD90-low implants at 9 weeks demonstrated cartilaginous, epithelial and neural rosette structures in the triple-high grafts, whereas the triple-low grafts consisted only of mesenchyme and epithelium structures. Scale bars, 100 μm. Author information * Author information * Supplementary information Affiliations * Institute of Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California, USA. * Chad Tang, * Jens-Peter Volkmer, * Debashis Sahoo, * Adriane R Mosley, * Matthew A Inlay, * Reza Ardehali, * Shawn L Chavez, * Renee Reijo Pera, * Irving L Weissman & * Micha Drukker * Departments of Radiology and Medicine (Division of Cardiology), Stanford University School of Medicine, Stanford, California, USA. * Andrew S Lee, * Divya Nag & * Joseph C Wu * Department of Urology, University of Duesseldorf, Duesseldorf, Germany. * Jens-Peter Volkmer * Department of Gynecology & Obstetrics, Stanford University School of Medicine, Stanford, California, USA. * Barry Behr Contributions C.T., J.-P.V., I.L.W. and M.D. designed the experiments and wrote the manuscript. C.T., A.S.L., J.-P.V., D.S., A.R.M., D.N., M.A.I. and M.D. performed the experiments and analyzed data. R.A., S.L.C., R.R.P., B.B. and J.C.W. provided samples and reagents. All authors endorse the full content of this work. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Micha Drukker or * Irving L Weissman Author Details * Chad Tang Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew S Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Jens-Peter Volkmer Search for this author in: * NPG journals * PubMed * Google Scholar * Debashis Sahoo Search for this author in: * NPG journals * PubMed * Google Scholar * Divya Nag Search for this author in: * NPG journals * PubMed * Google Scholar * Adriane R Mosley Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew A Inlay Search for this author in: * NPG journals * PubMed * Google Scholar * Reza Ardehali Search for this author in: * NPG journals * PubMed * Google Scholar * Shawn L Chavez Search for this author in: * NPG journals * PubMed * Google Scholar * Renee Reijo Pera Search for this author in: * NPG journals * PubMed * Google Scholar * Barry Behr Search for this author in: * NPG journals * PubMed * Google Scholar * Joseph C Wu Search for this author in: * NPG journals * PubMed * Google Scholar * Irving L Weissman Contact Irving L Weissman Search for this author in: * NPG journals * PubMed * Google Scholar * Micha Drukker Contact Micha Drukker Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Table 1 and Supplementary Figures 1–7 Additional data - Quantitative fluorescence imaging of protein diffusion and interaction in living cells
- Nat Biotechnol 29(9):835-839 (2011)
Nature Biotechnology | Research | Letter Quantitative fluorescence imaging of protein diffusion and interaction in living cells * Jérémie Capoulade1, 3 * Malte Wachsmuth1, 3 * Lars Hufnagel1 * Michael Knop1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:835–839Year published:(2011)DOI:doi:10.1038/nbt.1928Received07 March 2011Accepted27 June 2011Published online07 August 2011 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 Diffusion processes and local dynamic equilibria inside cells lead to nonuniform spatial distributions of molecules, which are essential for processes such as nuclear organization and signaling in cell division, differentiation and migration1. To understand these mechanisms, spatially resolved quantitative measurements of protein abundance, mobilities and interactions are needed, but current methods have limited capabilities to study dynamic parameters. Here we describe a microscope based on light-sheet illumination2 that allows massively parallel fluorescence correlation spectroscopy (FCS)3 measurements and use it to visualize the diffusion and interactions of proteins in mammalian cells and in isolated fly tissue. Imaging the mobility of heterochromatin protein HP1α (ref. 4) in cell nuclei we could provide high-resolution diffusion maps that reveal euchromatin areas with heterochromatin-like HP1α-chromatin interactions. We expect that FCS imaging will become a useful met! hod for the precise characterization of cellular reaction-diffusion processes. View full text Figures at a glance * Figure 1: FCS imaging using the diffraction-limited light-pad. () Front view of the main components of the light-pad microscope. The specimen is contained in a Petri dish. The first objective lens illuminates a thin slice in the specimen. Optical sectioning is performed under 45° with respect to the bottom of the Petri dish. The high aperture angle of the illumination light-sheet (74°) leads to weak illumination of cells lying outside the light-pad area (inset (i)). Fluorescence is detected at a right angle to the illumination plane by the detection lens. Spatial filters in the illumination path and the detection path confine the observed area to a rectangular array of volume elements, the light-pad (inset (ii)). An inverted microscope allows convenient positioning of the specimen. () Each individual pixel of the EM-CCD records a fluctuating fluorescence signal over time. These fluctuations are analyzed by temporal correlation analysis resulting in one ACF for each pixel. The ACF provides information about the diffusion coefficient D ! (dashed line) and the concentration C of diffusing fluorescently labeled molecules (amplitude of the curve). * Figure 2: 1D- and 2D-FCS imaging of protein diffusion in Madin-Darby canine kidney (MDCK) cells. () MDCK cells expressing a small green fluorescent protein fusion (mAG-hGem). The bright areas are nuclei where mAG-hGem is enriched. The dashed line indicates the position of the 1D-FCS recording. Scale bar, 10 μm. () Kymograph of the first 12 ms of the fluorescence signal acquired along the line in . () Autocorrelation functions (ACFs) calculated from pixels outside the cells (region 1 in ). () ACFs calculated from pixels within a cell (region 2 in ). () Profiles of intensities, concentrations and apparent diffusion coefficients of mAG-hGem obtained from fitting the ACFs to a one-component model for anomalous diffusion. The intensity profile (gray line) represents the averaged intensity of the first 500 ms of the acquired data. () mAG-hGem MDCK cell selected for 2D-FCS recording. The dashed rectangle indicates the area of the 2D-FCS recording corresponding to the light-pad. Scale bar, 10 μm. () First five frames of the recorded data. () ACFs calculated for the nuclear re! gion highlighted in with a dashed rectangle. () Intensity map of the area used for 2D-FCS imaging (averaged over the first 500 ms of the acquired data). The dashed rectangle highlights the same region as in where the ACFs shown in were extracted. Scale bar, 2.5 μm. () Map of the concentrations of mAG-hGem obtained from fitting the ACFs to a one-component model for anomalous diffusion. () Map of the apparent diffusion coefficients of mAG-hGem obtained from the same model fitting. Time resolution, 70 μs (1D-FCS) and 700 μs (2D-FCS). * Figure 3: 2D-FCS imaging of protein diffusion in Drosophila wing imaginal discs. () Optical sections of a wing imaginal disc from a Drosophila larva expressing GFP-NLS (single section stitched from four adjacent images) imaged with the light-pad microscope. To obtain these images, the numerical aperture of the illumination was reduced to increase the focal depth of the light-sheet. Two sections at a distance of 45 μm are shown (a 3D reconstruction of the full stack is provided with Supplementary Video 5); scale bar, 10 μm. () Intensity map of an area of a wing disc used for 2D-FCS imaging (averaged over the first 500 ms of the acquired data). Scale bar, 5 μm. () Autocorrelation functions (ACFs) calculated for the region delimited by dashed lines in . (,) Maps of the concentrations () and of the apparent diffusion coefficients () of GFP-NLS, obtained from fitting the ACFs to a one-component model for anomalous diffusion. 2D-FCS time resolution, 700 μs. * Figure 4: Spatially resolved HP1α mobility in 3T3 cells investigated by 2D-FCS imaging. () 3T3 cell expressing HP1α-EGFP. The arrowheads mark the positions (gray, cytoplasm; purple, euchromatin; green, heterochromatin) where the autocorrelation functions (ACFs) from confocal FCS measurements shown in were acquired. Euc.: euchromatin; Heteroc.: heterochromatin. Scale bar, 10 μm. () Scatter plots of the diffusion coefficient D of HP1α in heterochromatin and euchromatin (slow component), resulting from confocal FCS measurements in six cells. The gray band highlights the overlap of the diffusion coefficient of eu- and heterochromatin. () Light-pad intensity image of the part of a 3T3 cell expressing HP1α-EGFP used for FCS imaging (overview image shown in Supplementary Fig. 8a). The light-pad crosses nuclear (bright area) and cytoplasmic regions (very dim areas around the nucleus) for this cell. () Map of apparent diffusion coefficients of HP1α-EGFP (slow component) obtained from fitting the ACFs to a two-component anomalous diffusion model. () The color-coded ! diffusion coefficient map () was intensity weighted with the inverted intensity image () to emphasize the distribution of D in euchromatin. () Classification map of nuclear regions. Segmentation based on intensity thresholds (Supplementary Fig. 8b,c) was used to delimitate euchromatin (red and blue regions), heterochromatin (green) and cytoplasm (gray). Additional segmentation based on a diffusion coefficient threshold at D = 0.36 μm2 s−1 (mean + 1 s.d. of the distribution of diffusion coefficients in heterochromatin) was applied to to visualize regions in euchromatin with a mean apparent diffusion coefficient of HP1α similar to the one in heterochromatin (blue regions). Scale bar, 1 μm. () ACFs calculated and averaged for the four different regions highlighted in the segmentation map (). For ACF calculation in the cytoplasm, the area of the dashed rectangle in was used. 2D-FCS time resolution, 700 μs. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jérémie Capoulade & * Malte Wachsmuth Affiliations * Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany. * Jérémie Capoulade, * Malte Wachsmuth, * Lars Hufnagel & * Michael Knop * Present address: Zentrum für Molekulare Biologie der Universität Heidelberg (ZMBH), DKFZ-ZMBH Allianz, Universität Heidelberg, Germany. * Michael Knop Contributions M.K. and M.W. conceived the research. J.C. implemented the light-pad microscope. J.C. and M.W. conducted the yeast and mammalian work. J.C., M.W. and L.H. conducted the Drosophila wing disc work. J.C., M.W. and M.K. analyzed the data and wrote the manuscript. All authors commented on the manuscript. Competing financial interests J.C., M.K. and M.W. are named inventors on a patent application on technologies described in this manuscript. Corresponding authors Correspondence to: * Malte Wachsmuth or * Michael Knop Author Details * Jérémie Capoulade Search for this author in: * NPG journals * PubMed * Google Scholar * Malte Wachsmuth Contact Malte Wachsmuth Search for this author in: * NPG journals * PubMed * Google Scholar * Lars Hufnagel Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Knop Contact Michael Knop Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information Movies * Supplementary Video S1 (788K) z-stack of images of yeast cells expressing Pma1-GFP acquired with the light-pad microscope * Supplementary Video S2 (5M) 1D-FCS recording of 20 nm fluorescent beads diffusing in water * Supplementary Video S3 (1M) 2D-FCS recording of 20 nm fluorescent beads diffusing in water * Supplementary Video S4 (2M) 20 nm fluorescent beads diffusing in water recorded with the imaging camera showing Brownian motion and convective flow * Supplementary Video S5 (2M) 3D reconstruction of a Drosophila larva wing imaginal disc expressing GFP-NLS acquired with the light-pad microscope PDF files * Supplementary Text and Figures (3M) Supplementary Table 1, Supplementary Results and Supplementary Figures 1–8 Additional data - A resource of vectors and ES cells for targeted deletion of microRNAs in mice
- Nat Biotechnol 29(9):840-845 (2011)
Nature Biotechnology | Research | Resources A resource of vectors and ES cells for targeted deletion of microRNAs in mice * Haydn M Prosser1 * Hiroko Koike-Yusa1 * James D Cooper1 * Frances C Law1 * Allan Bradley1 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:840–845Year published:(2011)DOI:doi:10.1038/nbt.1929Received20 April 2011Accepted05 July 2011Published online07 August 2011 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 The 21–23 nucleotide, single-stranded RNAs classified as microRNAs (miRNA) perform fundamental roles in diverse cellular and developmental processes. In contrast to the situation for protein-coding genes, no public resource of miRNA mouse mutant alleles exists. Here we describe a collection of 428 miRNA targeting vectors covering 476 of the miRNA genes annotated in the miRBase registry. Using these vectors, we generated a library of highly germline-transmissible C57BL/6N mouse embryonic stem (ES) cell clones harboring targeted deletions for 392 miRNA genes. For most of these targeted clones, chimerism and germline transmission can be scored through a coat color marker. The targeted alleles have been designed to be adaptable research tools that can be efficiently altered by recombinase-mediated cassette exchange to create reporter, conditional and other allelic variants. This miRNA knockout (mirKO) resource can be searched electronically and is available from ES cell reposi! tories for distribution to the scientific community. View full text Figures at a glance * Figure 1: Schematic illustration of targeting vector construction. The kanamycin-resistance recombineering cassette was PCR amplified from the pHPmK3 vector and recombineered into bacterial artificial chromosomes (BACs) in E. coli, deleting the miRNA gene. The homology arms and kanamycin selection cassette were retrieved by recombineering a PCR-amplified pPL611 vector backbone to create a PGK-Neo targeting vector (Neo-TV). The kanamycin/neomycin selection cassette of the targeting vector was switched to PuroΔtk by using a PGK-EM7-PuroΔtk-bpA restriction fragment for recombineering to generate the puromycin version of the targeting vector (Puro-TV). * Figure 2: Targeting and reporter modification of the mir-290~295 cluster. () Targeting of the intergenic miRNA cluster mir-290~295 replaces 2,255 bp of genomic sequence with the PGK-PuroΔtk cassette. The PGK-PuroΔtk deletion was by Cre recombinase transfection and FIAU selection. Alternatively, RMCE by FLPo recombinase transfection was used to integrate a neomycin resistance (NeoR) plasmid (e.g., pMA_F3RoxNeoRoxTd-tomatoLoxPFRT). The PGK-NeoR deletion was by Dre recombinase transfection. The predicted sizes of PCR products generated by PCR across the mir-290~295 cluster or modified alleles are indicated in brackets. () Ethidium bromide–stained agarose gel showing products for long-range PCR between primers specific for the selection cassette and the region external to the 5′ and 3′ homologous arms of the targeting vector. () Ethidium bromide–stained agarose gel showing products for PCR between primers specific for flanking sequences of mir-290~295 locus and the allelic variants. () Brightfield and corresponding fluorescent images of the ! same mir-290~295Td-tomato/+ ES cell colony (top left), mir-290~295PuroΔtk/+ control ES cell colony (top right), embryoid bodies at d5 and d8 into the differentiation regime for mir-290~295Td-tomato/+ (middle and bottom left) and mir-290~295PuroΔtk/+ (middle and bottom right). Scale bars, 100 μm. * Figure 3: Targeting and reporter modification of the mir-21 gene. () The mir-21 gene was removed as a 141-bp deletion using the PuroΔtk cassette, which could then be a substrate for either deletion or RMCE using a reporter construct. The predicted sizes of PCR products generated by PCR across the mir-21 locus or modified alleles are indicated in parentheses. () Products for long-range PCR between primers specific for the selection cassette and the area external to the 5′ and 3′ homologous arms of the targeting vector. () Ethidium bromide–stained agarose gel showing products for PCR across the targeted and modified mir-21 locus. Note that the mir-21− allele yields a PCR product that migrates as a doublet with the wild-type allele/JM8.A3 PCR product. () Brightfield and fluorescent images of the same mir-21Td-tomato/+ undifferentiated ES cell colonies (top left) mir-21PuroΔtk/+ control ES cell colonies (top right), embryoid bodies at d5, d16 and d19 of differentiation for mir-21Td-tomato/+ and mir-21PuroΔtk/+ as indicated. The bott! om image shows a close-up of a d16 differentiation mir-21Td-tomato/+ embryoid body. Scale bars, 100 μm. * Figure 4: Targeting and conditional modification of the mir-106a~363 cluster. () The mir-106a~363 cluster was removed as a 931-bp deletion using the PuroΔtk cassette. The predicted sizes of PCR products generated by PCR (internal to the targeting vector) across the mir-106a-363 cluster or modified alleles are indicated in brackets. An RMCE cassette containing a cloned genomic sequence for the wild-type mir-106a~363 cluster (pMA_F3RoxNeoRox_miR106a~363_LoxPFRT) was inserted into the targeted locus by co-transfected with PGK-FLPo followed by FIAU and G418 selection. The PGK-NeoR deletion was by Dre recombinase transfection. Cre deletion successfully deleted the conditional allele, although the mir-106a~363− clone analyzed in this figure was derived by Cre deletion of the mir-106a~363PuroΔtk clone. () Ethidium bromide–stained agarose gel showing products for long-range PCR between primers specific for the selection cassette and the region external to the 5′ and 3′ homologous arms of the targeting vector. () Ethidium bromide–stained agarose ge! l showing products for PCR between primers (internal to the targeting vector) specific for flanking sequences of mir-106a~363 locus and the allelic variants. () Comparative quantitative PCR for miRNAs within the mir-106a~363 cluster and miR-294 as a control. The TaqMan MicroRNA assays used are color coded and are either for mouse (mmu) miRNAs or human (hsa) miRNAs but can also detect the mouse ortholog. n = 3; error bars show s.d. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * JN195814 * JN195815 * JN195816 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. * Haydn M Prosser, * Hiroko Koike-Yusa, * James D Cooper, * Frances C Law & * Allan Bradley Contributions H.M.P. planned and managed the project, constructed novel plasmid reagents and performed high-throughput vector construction, ES cell targeting experiments, post-targeting modifications, collated data and wrote the paper. H.K.-Y. performed high-throughput vector construction, planned and performed the ES cell targeting experiments, ES cell genotyping and collated data. J.D.C. performed high-throughput vector construction, ES cell targeting and genotyping. F.C.L. performed ES cell targeting experiments. A.B. initiated and supervised the project and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Haydn M Prosser Author Details * Haydn M Prosser Contact Haydn M Prosser Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroko Koike-Yusa Search for this author in: * NPG journals * PubMed * Google Scholar * James D Cooper Search for this author in: * NPG journals * PubMed * Google Scholar * Frances C Law Search for this author in: * NPG journals * PubMed * Google Scholar * Allan Bradley Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information Excel files * Supplementary Table 1 (147K) Current status of individual mirKO targeting projects. PDF files * Supplementary Text and Figures (1M) Supplementary Table 2 and Supplementary Figures 1–4 Additional data - Second-quarter biotech job picture
- Nat Biotechnol 29(9):846 (2011)
Article preview View full access options Nature Biotechnology | Careers and Recruitment Second-quarter biotech job picture * Michael Francisco1Journal name:Nature BiotechnologyVolume: 29,Page:846Year published:(2011)DOI:doi:10.1038/nbt.1969Published online08 September 2011 Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Michael Francisco is a Senior Editor at Nature Biotechnology. Author Details * Michael Francisco Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - People
- Nat Biotechnol 29(9):848 (2011)
Article preview View full access options Nature Biotechnology | Careers and Recruitment | People People Journal name:Nature BiotechnologyVolume: 29,Page:848Year published:(2011)DOI:doi:10.1038/nbt.1981Published online08 September 2011 Astrid Magenau for ComBio2007 (right), a noted expert in xenotransplantation, died of cardiac arrest on August 14 in his home in Manchester-by-the-Sea, Massachusetts. Bach was born in Vienna in 1934 and attended Harvard College and Harvard Medical School. His research took him to the University of Wisconsin, Madison, the University of Minnesota, Minneapolis, and Harvard Medical School. Among his achievements was describing the mixed leukocyte culture test for matching donors and recipients for transplantation, which led to his contributing to the description of the major histocompatibility complex in humans. He also headed the team that performed the first successful matched bone marrow transplant. Recently, he researched ways to transplant pig organs to humans as a way to alleviate the chronic shortage of organ donors, though he advised caution in proceeding, and urged that the public—not just experts—be involved in making policy decisions. Prana Biotechnology (Melbourne) has elected to the company's board of directors. Gozlan is the founder and chief investment officer of Scientia Capital. Previously, he was responsible for the largest biotech investment portfolio in Australia as the institutional biotech analyst at the Queensland Investment Corporation. Numira Biosciences (Salt Lake City) has announced the appointment of to its board of directors. He currently serves as CEO of VIDA Sciences and previously held a number of senior management positions at MPI Research, including president and COO. Tengion (E. Norriton, PA, USA) has named , currently senior vice president, clinical development and chief medical officer at Endo Pharmaceuticals, to its board of directors. Tengion also announced that , managing partner at Quaker BioVentures, is stepping down from the Tengion board after five years of service. has been appointed CSO of 3-V Biosciences (Menlo Park, CA, USA). Before joining the company, he served as senior vice president of R&D and head of research at MedImmune. Creabilis (Luxembourg) has announced the expansion of its senior management team. joins the company as vice president, head of finance and operations, joins as senior vice president, head of development, and has been named senior vice president for chemistry manufacturing and controls. Leech was most recently head of operations at Solace Pharmaceuticals, and he was previously at Pfizer. Sandy has over 25 years of pharma development R&D experience, most recently as development team leader of Pfizer's gastrointestinal portfolio. Spargo was most recently a senior vice president at Novexel. CorMedix (Bridgewater, NJ, USA) has named to the company's board of directors. Lefkowitz is currently president and founder of Wade Capital and holds board positions in both publicly traded and privately held companies. has been appointed to the board of directors of specialty pharma Tonix Pharmaceuticals (New York). Mather is currently a managing director in the investment banking group at Janney Capital Markets, and co-heads the equity capital markets group. Planet Biopharmaceuticals (Liberty, MO, USA) has announced the appointment of as executive chairman and CEO. He replaces , who has joined MediMedia USA as CEO. Goldberg will remain on Planet's board of directors as an independent director. Odlaug was most recently president and CEO of CyDex Pharmaceuticals. Akrimax Pharmaceuticals (Cranford, NJ, USA) has named as president. Olsen has over 30 years of pharma industry experience, most recently as executive vice president at Cempra Pharmaceuticals. Before that he was at the Johnson & Johnson Pharmaceuticals Group. has been appointed vice president and head of research at Verastem (Boston). He previously served as head of cancer biology at OSI Pharmaceuticals. has joined Human Genome Sciences (Rockville, MD, USA) as senior vice president, strategy and corporate development. He was most recently CEO and co-founder of Vega Therapeutics, and before that was senior vice president of corporate development and finance and CFO of Proteolix, which was acquired by Onyx Pharmaceuticals in 2009. has been named president, CEO and a member of the board of directors of Cangene (Toronto). Michael Graham, who had been serving as interim president and CEO during the search process, will continue in his regular role as CFO. Sedor most recently served as president, CEO and a director of CPEX Pharmaceuticals. Avanir Pharmaceuticals (Aliso Viejo, CA, USA) has named to the position of senior vice president of R&D, a newly created role. Siffert previously served as vice president and chief medical officer at Ceregene. Auxilium Pharmaceuticals (Malvern, PA, USA) has promoted to the position of chief medical officer. Tursi joined Auxilium in March 2009. Previously he served as a medical director at Procter & Gamble Pharmaceuticals and was responsible for medical affairs at GlaxoSmithKline Biologicals' cancer vaccines unit. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Biotechnology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * Rent this article from DeepDyve * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data
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