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  - Nat Biotechnol 29(10):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.2010Published online13 October 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Genome assembly from single cells The ability to sequence a complete genome from DNA extracted from a single cell would facilitate the study of unculturable microbes. But to have sufficient amounts of DNA for sequencing, the femtograms of DNA in a single cell must be amplified to microgram quantities, typically by a biased process that results in sequencing coverage that is highly nonuniform. Lasken and colleagues describe algorithmic techniques that are tailored to accommodate such coverage. The key idea involves the use of variable thresholds in the assembly program, instead of fixed thresholds, which results in the incorporation of sequences that would otherwise be discarded. Based on data from one lane of an Illumina GAIIx sequencer per cell, the new algorithm, called Velvet-SC, was able to recover ~91% of the genes from single Escherichia coli and Staphylococcus aureus cells, approaching the ~95% recoverable if many cells are sequenced. Lasken and colleagues apply Velvet-SC to sequence the genome from a! single cell of an uncultured marine organism. Single-cell sequencing and assembly should complement shotgun metagenomics for understanding complex microbial communities. [] CM Photoswitching with uncoupled excitation and inactivation Photoswitchable fluorescent proteins have found wide application in fluorescence microscopy, especially in various techniques that enable image resolutions beyond the diffraction limit of light. Jakobs, Hell and colleagues have now addressed a major limitation of the current generation of photoswitchable proteins by uncoupling the wavelengths that switch off the protein from those that excite fluorescence. Their new protein, Dreiklang, is the first protein that can be switched on, off and imaged at three distinct wavelengths (~365 nm, ~405 nm and ~515 nm, respectively). They elucidate the mechanism of the switching behavior by solving the crystal structure of the on- and off-states and demonstrate the utility of the new protein for the super-resolution microscopy methods PALM/STORM and RESOLFT. [] ME Single-cell tracking in vivo The closer one looks at certain cell populations, such as cancer cells and tissue stem cells, the more heterogeneity one discovers. To rigorously analyze heterogeneous cell populations in vivo, it would be necessary to monitor them at the level of single cells. Lu, Weissman and colleagues combine viral cellular labeling, DNA barcoding and next-generation sequencing for quantitative, high-throughput tracking of single hematopoietic stem cells (HSCs) in vivo. Lentiviral vectors are used to deliver unique barcodes to individual cells in an HSC population. Because the barcodes are transmitted with the genome during cell division, the progeny of each starting cell can be identified. The authors transplant ~9,000 barcoded HSCs into lethally irradiated mice and 22 weeks later recover ten types of blood cells. The barcodes in each of the ten populations are analyzed by Illumina sequencing, and identical barcodes are combined to generate a copy number for every barcode. The approach ! allows discoveries about HSC differentiation without having to know the cell-surface markers that define a particular cell type. For example, the data reveal the presence of two distinct HSC populations with different lineage biases. [] KA Genomes of two thermophilic fungi Enzymes that operate at elevated temperatures are useful as research reagents and in industrial applications, such as the degradation of biomass for biofuels. Tsang and colleagues report the first genome sequences of two thermophilic eukaryotes, the filamentous fungi Myceliophthora thermophila and Thielavia terrestris. These fungi were known to be efficient biomass degraders, and analysis of the genomes found large numbers of enzymes predicted to break down plant polysaccharides. Seven enzymes were cloned into another fungal host and shown to have optimal activity at a wide range of temperatures. The authors also performed proteomic analysis of extracellular secreted proteins and transcriptome sequencing of the fungi growing on alfalfa and barley straw. Analysis of the genomes revealed the presence of mating-type genes, suggesting that these fungi may be amenable to genetic crossing. This could facilitate strain development and the use of these organisms as thermophilic host! strains. [] CM Enhancing myelination Loss of myelin, the insulating material around axons that enables rapid electrical conduction in the nervous system, is a common feature of many diseases, including multiple sclerosis and cerebral palsy. Therapeutic myelination has been achieved in mice by transplantation of human neural cells that bind the monoclonal antibody A2B5. The A2B5+ population contains myelination-competent oligodendrocyte progenitor cells, but it also includes many unwanted cells, such as neuronal progenitors and committed astrocytic cells. To isolate a purer population of myelinating cells, Goldman and colleagues use flow cytometry to recover human fetal cells expressing the oligodendrocyte marker platelet-derived growth factor receptor alpha (PDGFRa). PDGFRa+ cells are found to be a subpopulation of A2B5+ cells that does not express neuronal or astrocytes markers and that contains all A2B5+ cells capable of myelination. In the shiverer mouse model of myelin disease, PDGFRa+ cells show more effic! ient differentiation to oligodendrocytes and more robust myelination than do A2B5+ cells. [] KA Mass cytometry data analysis Analyzing a population of cells using mass cytometry can yield measurements for over twice as many cellular markers than what's possible with conventional flow cytometry. To help interpret this wealth of data, Qiu and colleagues devised the SPADE algorithm. This approach clusters and organizes the cells based on all of the available marker data, without resorting to traditional gating analysis, which makes use of only one or two markers at a time. Notably, the authors show that SPADE can be used to identify populations of rare cells that are easily missed by gating analysis, and they show how the results of two mass cytometry experiments can be analyzed jointly to effectively increase the number of markers measured per cell even further. The computational strategies implemented in SPADE may be applicable to other problems requiring the analysis of data sets with many dimensions. [] CM Exome sequencing kits compared Sequencing specific regions of a human genome, such as the exome, can be accomplished using commercial enrichment kits that use 'bait' oligonucleotides made of either DNA or RNA and differing in length and design. Snyder and colleagues compare the performance of three commercial exome enrichment kits from Agilent (Santa Clara, CA, USA), Illumina (San Diego) and Roche/Nimblegen (Madison, WI, USA) when applied to the same human DNA sample. The comparison highlights the design tradeoffs inherent to each platform. For instance, the Nimblegen method, which is the only one to use overlapping oligonucleotide baits, captures the fewest total base pairs but does so with the greatest efficiency. The authors also compare the three exome-sequencing data sets to whole-genome sequencing data of the same sample and find variants that are discernable by exome sequencing only. The conclusions from this study support the continued utility of exome sequencing even as whole-genome sequencing co! sts fall and should also be of interest to those developing custom enrichment assays. [] CM Patent roundup China has become the fourth largest filer of patents, according to a new study from the Institute of Fiscal Studies. [] LM Gilead Sciences (Foster City, CA, USA) will allow Indian manufacturers to produce low-cost versions of the biotech firm's HIV drugs following an agreement with the Medicines Patent Pool. [] LM Evergreening is a common strategy to extend patents on products at the end of their original patent life as well as data and marketing exclusivity periods. Gaudry looks at how this practice contributes to the total incentives that justify a company's investment in a new drug. [] MF Recent patent applications in drug screening. [] MF Next month in Nature Biotechnology * siRNA silencing in inflammatory monocytes * Kinase inhibitor selectivity * Cardiomyocyte surface marker * Genome sequences of nonhuman primates * In silico feedback control of gene expression * Streamlined capture of genomic targets * Xymogen-like factor Xa variants for bleeding conditions * Modified Bt toxins foil multiple resistance mechanisms Additional data
• Enlightened engineering
  - Nat Biotechnol 29(10):849 (2011)
  Nature Biotechnology | Editorial Enlightened engineering Journal name:Nature BiotechnologyVolume: 29,Page:849Year published:(2011)DOI:doi:10.1038/nbt.2016Published online13 October 2011 Optogenetics—until now primarily a tool for asking questions in basic research—is starting to spur efforts oriented toward biomedical applications. View full text Additional data
• Seattle Genetics rare cancer drug sails through accelerated approval
  - Nat Biotechnol 29(10):851-852 (2011)
  Article preview View full access options Nature Biotechnology | News Seattle Genetics rare cancer drug sails through accelerated approval * Laura DeFrancesco1Journal name:Nature BiotechnologyVolume: 29,Pages:851–852Year published:(2011)DOI:doi:10.1038/nbt1011-851Published online13 October 2011 Songmao (Ben) Zheng Seattle Genetics' CEO Clay Siegall. The biotech has just cleared a double win for its anti-CD30 monoclonal antibody. On August 19, Seattle Genetics of Bothell, Washington, received the nod from the US Food and Drug Administration (FDA) for its immunoconjugate drug Adcetris (brentuximab vedotin) in two rare cancers, relapsing Hodgkin's lymphoma and anaplastic large cell lymphoma (ALCL). The same month, FDA gave accelerated approval to Pfizer's Xalkori (crizotinib) for ALK-positive advanced non-small cell lung cancer. In addition to being good news for underserved patient populations, these approvals serve to quell fears that the FDA has raised the bar for accelerated approval, following the circus around Avastin (bevacizumab), Basel-based Roche's blockbuster monoclonal antibody (mAb) (Nat. Biotechnol., 676, 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 Affiliations * Senior Editor * Laura DeFrancesco Author Details * Laura DeFrancesco Search for this author in: * NPG journals * PubMed * Google Scholar
• HIV drugs made in tobacco
  - Nat Biotechnol 29(10):852 (2011)
  Article preview View full access options Nature Biotechnology | News HIV drugs made in tobacco * Jeffrey L FoxJournal name:Nature BiotechnologyVolume: 29,Page:852Year published:(2011)DOI:doi:10.1038/nbt1011-852Published online13 October 2011 Fraunhofer IME The bioreactor room Europe's first clinical trial to test a human monoclonal antibody (mAb) made in genetically modified tobacco plants has been given the go-ahead by UK regulators. The Medicines and Healthcare Products Regulatory Agency approved in late June Pharma-Planta's phase-1 clinical trial to test an anti-HIV type 1 protein applied as a vaginal microbicide to stop transmission of the virus between sexual partners. Pharma-Planta, a consortium of 39 academic principal investigators and industrial partners in Europe and Africa funded by the European Commission, launched the project in 2004 as part of the Sixth Framework Program. The partners' goal was to road test the regulatory pathway in Europe by taking a candidate plant-made biotherapeutic and moving it beyond proof-of-concept studies to clinical evaluation. The mAb, designated 2G12, neutralizes HIV by binding to its gp120 surface glycoprotein. If safe, the product will be tested for effectiveness in protecting users against HIV infect! ion. While the clinical trial is conducted at the University of Surrey in the UK, 2G12 is being produced in specialized greenhouses at the Fraunhofer Institute for Molecular Biology and Applied Ecology in Aachen, Germany. The approval is a major milestone. "This is indeed a big step forward in Europe, where development was hampered because of concerns over foods and GMOs [genetically modified organisms]," says Charles Arntzen, a co-director at the Biodesign Institute of Arizona State University in Tempe and a leader in the development of plant-produced vaccines. Perhaps more importantly, Pharma-Planta's step forward could boost the entire field of plant-produced vaccines where a "lot of positive results and exciting things" are ongoing, according to Arntzen. For instance, three major US plant-based, protein production facilities are up and running, providing "abundant capacity," and presenting a challenge "to fill the pipeline with products to use that capacit! y." Prospects now are bright for meeting part of that challe! nge, with several vaccines—some for sexually transmitted diseases and others for virus-induced diarrheal diseases—moving forward. Additionally, the carrot cell–produced enzyme taliglucerase alfa for treating Gaucher disease, developed by Protalix BioTherapeutics of Carmiel, Israel, has completed phase 3 clinical trials and may soon be licensed as a "biobetter," Arntzen says. Plants are attractive bioreactors because they are inexpensive and provide a versatile expression system for recombinant protein. 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
• Engineered T-cell therapy shows efficacy in blood cancer
  - Nat Biotechnol 29(10):853-855 (2011)
  Article preview View full access options Nature Biotechnology | News Engineered T-cell therapy shows efficacy in blood cancer * Simon Frantz1Journal name:Nature BiotechnologyVolume: 29,Pages:853–855Year published:(2011)DOI:doi:10.1038/nbt1011-853Published online13 October 2011 University of Pennsylvania Magnetic beads (tiny yellow) stimulate larger T-cells to proliferate before infused into the patient. Dramatic pilot study results describing an engineered T-cell cancer treatment have given the adoptive cellular immunotherapy field a much-needed boost. In simultaneously published papers from a group at the University of Pennsylvania, two out of three patients with advanced chronic lymphocytic leukemia (CLL) are reported to show complete remission after receiving engineered T cells that contain chimeric antigen receptors (CARs) specific for the B cell–specific antigen CD19 fused to a hinge region, the costimulatory molecule 4-1BB and the T-cell receptor (TCR) CD3-ζ signaling domain. The patients remain in remission for around a year after treatment (Sci. Transl. Med., 95ra73, 2011; N. Engl. J. Med., 725, 2011). "This report is [an] exciting proof of concept of the power of the immune system to attack cancer," says John Gribben, a professor of medical oncology at St. Bartholomew's Hospital, London. But in terms of turning such cell therapies into products, the path to ! market remains unclear, particularly with concerns lingering over manufacturing, reimbursement and potential autoimmune complications arising from uncontrolled proliferation of the reintroduced cells. 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 * Simon Frantz Author Details * Simon Frantz Search for this author in: * NPG journals * PubMed * Google Scholar
• 9,000 tumors for stratified medicine
  - Nat Biotechnol 29(10):854 (2011)
  Article preview View full access options Nature Biotechnology | News 9,000 tumors for stratified medicine * Susan AldridgeJournal name:Nature BiotechnologyVolume: 29,Page:854Year published:(2011)DOI:doi:10.1038/nbt1011-854aPublished online13 October 2011 A new collaborative program to ready the UK's National Health Service (NHS) for personalized cancer care is underway. The £5.5 ($8.7) million Stratified Medicine Programme, led by the charity Cancer Research UK in partnership with the National Health Service and London-based AstraZeneca and New York-based Pfizer, aims to develop a standardized national genetic screening service to help tailor oncology treatments for patients. The initiative will store clinical data from 9,000 individuals with breast, bowel, lung, prostate, ovary and skin cancers, along with the molecular diagnosis of their tumors, to develop a multigene panel to guide personalized cancer care across the UK. Genetic stratification allows clinicians to determine which individuals will respond to which treatment, for instance, KRAS testing in bowel cancer to see if Amgen's Vectibix (panitumumab) and Imclone's Erbitux (cetuximab) is indicated. Currently, only a minority of NHS patients receive such tests. "Th! e Stratified Medicine Programme will improve genetic testing in the UK," says James Peach, director of the program. "It will also provide hypotheses about the interaction between drug and tumor, which will help companies design better cancer clinical trials." Peach noted that there has been a surge in approvals for drugs with companion diagnostics. So far, there are no other biotech companies involved in the project. 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 * Susan Aldridge Search for this author in: * NPG journals * PubMed * Google Scholar
• Chinese inventors catch up
  - Nat Biotechnol 29(10):854 (2011)
  Article preview View full access options Nature Biotechnology | News Chinese inventors catch up * Nuala MoranJournal name:Nature BiotechnologyVolume: 29,Page:854Year published:(2011)DOI:doi:10.1038/nbt1011-854bPublished online13 October 2011 In 2010 China rose to be the fourth largest filer of patents with the World Intellectual Property Organization, according to a new study published in September by the Institute for Fiscal Studies (IFS). The report from the London-based think tank (http://www.ifs.org.uk/wps/wp1115.pdf) provides evidence that a decade of hefty investments in skills, infrastructure and R&D, has indeed boosted Chinese technological advancement. In 2000 China filed 1.8% of Patent Cooperation Treaty (PCT) patents; in 2010, it filed 7.5%. The authors claim the study counters the current view that China is doing a lot of lower level, incremental R&D and instead shows that Chinese innovation is as technologically advanced as in the West. Rather than count patents as a measure of innovation, the study counted citations from patents to the scientific literature to single out innovations that draw from basic research. With this metric, they found the proportion of patents near the science base to be at ! least as high as in patents filed by Western investors. "Given what the literature says, we were surprised to find China is more involved in near-science innovation than expected," said study co-author, Helen Miller, senior research economist of the IFS. Past studies took exports or levels of foreign direct investment as an indication of innovation. "Chinese inventors display the capacity to innovate alongside US and European inventors at the technological frontier," the report concludes. Chinese innovation may be growing dramatically, but in number of patents US and European inventors are still far ahead. 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 * Nuala Moran Search for this author in: * NPG journals * PubMed * Google Scholar
• ATM cash for biotechs
  - Nat Biotechnol 29(10):856 (2011)
  Article preview View full access options Nature Biotechnology | News ATM cash for biotechs * Brian OrelliJournal name:Nature BiotechnologyVolume: 29,Page:856Year published:(2011)DOI:doi:10.1038/nbt1011-856aPublished online13 October 2011 In August, Somaxon Pharmaceuticals chose an alternative strategy to raise $30 million, and in June, BioCryst Pharmaceuticals of Research Triangle Park, North Carolina, used a similar tactic to raise $70 million. Both companies raised money through at-the-market (ATM) offerings, a financing tool that was not used at all in the biotech industry as recently as 2005. Since then, ATMs have been rapidly gaining favor. According to the New York-based investment bank Brinson Patrick Securities, which specializes in ATMs, by 2010 the number of ATM offerings had grown to 26 in the biotech sector (raising $184 million), nearly tripling the 9 that took place in 2009. This year there have been 15 so far. Biotechs typically raise capital by selling shares all at once in large tranches and at a fixed price, while relying on value-adding milestones, hoping that the cash can get them through to the next milestone. Instead, with an ATM offering, a company raises capital by selling shares in t! he open market at the prevailing price over a period of time, with the advantage that the sale of shares can be stopped or initiated at any time. Todd Wyche, founder and managing director of Brinson Patrick, thinks biotechs are shifting their approaches, using multiple financing options. "Instead of an episodic financing, relying on one or two traditional tools, we're seeing them incorporate a more strategic kind of financing strategy," said Wyche. Not only are ATM offerings more flexible, providing cash when needed, but they are also cheaper than traditional stock offerings in which warrants, underwriter spreads and discounts to the market price are taken into account. ATMs aren't the perfect solution, however. One drawback is that shares have to be dribbled into the market so large amounts of capital can't be raised quickly. But Brinson Patrick has found that issuers can sell 10–15% of the daily volume without adversely affecting the share price. The shares from an ! ATM offering also end up in the open market where investors ma! y not be interested in holding them long term. Other options, such as standby equity distribution agreements offered by Yorkville Advisors of Jersey City, New Jersey, can provide the same flexibility while getting the shares into the hands of long-term investors (Nat. Biotechnol.28, 301–302, 2010). Michael J. Nowak, managing director of Yorkville Advisors, explains that as long term–only investors, they are always interested in maintaining a strong share price for the company. "In an ATM, [bankers] do not care, since they pick up their couple of percent commission on the trade regardless of impact or price," he adds. 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 * Brian Orelli Search for this author in: * NPG journals * PubMed * Google Scholar
• Pertuzumab to bolster Roche/Genentech's breast cancer franchise?
  - Nat Biotechnol 29(10):856-858 (2011)
  Article preview View full access options Nature Biotechnology | News Pertuzumab to bolster Roche/Genentech's breast cancer franchise? * Cormac Sheridan1Journal name:Nature BiotechnologyVolume: 29,Pages:856–858Year published:(2011)DOI:doi:10.1038/nbt1011-856bPublished online13 October 2011 Pertuzumab exerts its therapeutic effects by inhibiting HER2 dimerization. The monoclonal antibody binds a different epitope on the HER2 receptor to Herceptin and blocks its activation. Adapted from Nature Reviews Drug Discovery, 507–521 (June 2006). In July, Genentech announced that its humanized monoclonal antibody (mAb) drug pertuzumab met its primary endpoint in a phase 3 trial of metastatic breast cancer patients also receiving the standard regimen of Herceptin (trastuzumab) plus Taxotere (docetaxel). The company, a subsidiary of Basel-based Roche, has so far revealed few details on the outcome of the combination trial, dubbed Cleopatra. Its terse disclosure simply stated the combination "significantly" extended progression-free survival in women with HER2-overexpressing metastatic breast cancer. The safety profile was consistent with previous studies of the two drugs, either as monotherapy or in combination. But anticipation over the drug's efficacy is mounting because, if successful, the new combination could extend the benefits of targeted therapy to HER2-positive patients, who either do not respond to or relapse on existing Herceptin-based regimens. Genentech, of S. South Francisco, California, plans to unveil the details of the 808-women trial at this year's San Antonio Breast Cancer Symposium, in San Antonio, Texas, which kicks off on December 6. The company also plans to file for approval of the combination shortly after the presentation. It is difficult to judge at this stage whether Genentech will obtain approval solely on the basis of the Cleopatra study, which had progression-free survival as its primary end point. Recently, Genentech and the US Food and Drug Administration (FDA) have locked horns over this issue in connection with the approval of Avastin (bevacizumab) in breast cancer (Nat. Biotechnol.29, 669, 2011). "I don't think it should be impossible, but the data will have to be really, really good," says Elmar Kraus, analyst at DZ Bank in Frankfurt. HER2 expression, which is associated with a poor prognosis, occurs in around 20% of invasive breast cancers (as well as in lung, ovarian, pancreatic and gastric cancers). In normal cells, the transmembrane tyrosine kinase is involved in cell survival and differentiation. Signaling events implicate four closely related HER family members. HER2 is recruited to a ligand-receptor complex comprising one of over ten neuregulin ligands and either HER1, HER3 or HER4. When aberrant expression of HER2, arising from gene amplification events, gives rise to high concentrations of HER2, this equilibrium is disrupted, leading to the protein becoming constitutively active. Thus, dimerization with other HER receptors—and subsequent signaling—can occur, even in the absence of ligand binding. "We think the oncogenic unit here is the higher order complex between HER2 and HER3," says Genentech senior staff scientist Mark Sliwkowski, who has been part of Genentech's effort in developing ! HER2-targeting therapies for some 20 years. The anti-HER2 mAb Herceptin is thought to exert its therapeutic effects through multiple mechanisms. These include the promotion of antibody-dependent cellular cytotoxicity and the disruption of HER2-associated signaling, leading ultimately to cancer cell cycle arrest (Cancer Res.70, 4481–4489, 2010). The drug initially gained approval in 1998 as a front-line treatment, in combination with chemotherapy, for HER2-positive metastatic breast cancer. In 2006, it was approved as an adjuvant therapy for women with early-stage, HER2-positive cancer, who had undergone surgery or another primary therapy. In this setting, survival rates have improved from around 65% to >85%, says Sliwkowski. "It has a big impact, but it's not a curative therapy," says Larry Norton, deputy physician-in-chief for breast cancer programs at Memorial Sloan-Kettering Cancer Center in New York, who was senior author on the paper that reported the first pivotal trial of the drug (N. Engl. J. Med.344, 783–792, 2001). Resistance to Herceptin develops within a year in a majority of patients who respond initially, and ~15% of women who receive adjuvant therapy still progress to metastatic disease (Breast Cancer Res.8, 215–222, 2006). Pertuzumab, a humanized mAb that Genentech describes as a "HER2 dimerization inhibitor," binds a different epitope on the HER2 receptor and blocks its activation. The first study combining pertuzamab, Herceptin and chemotherapy that got the company "jazzed," Sliwkowski says, was a phase 2 trial in 66 HER2-positive metastatic breast cancer patients whose disease had progressed, despite having previously undergone treatment with Herceptin plus chemotherapy. The objective response rate—which includes patients who achieved either a complete or a partial response—was 24%. Another 26% had stable disease for at least six months (J. Clin. Oncol.28, 1138–1144, 2010). "In that disease setting, that's a big signal," Sliwkowski says. A second phase 2 trial, called NeoSphere, took a completely different tack, by examining the combination in the so-called neoadjuvant setting (Table 1). It recruited 417 patients with early-stage HER2-positive breast cancer who had not undergone surgery or any other therapy. Here, too, the pertuzumab/Herceptin/chemotherapy combination was clearly differentiated from the Herceptin/chemotherapy treatment, with a complete response of 46% and 29%, respectively. "Basically you've looked at the ceiling, you've looked at the floor—you've looked at both ends of the spectrum," Sliwkowski says. The so-called NeoALLTO phase 3 study, which looked at a combination of chemotherapy, Herceptin and Tykerb (lapatinib), a dual EGFR/HER2 tyrosine kinase inhibitor marketed by London-based GlaxoSmithKline, obtained a similar outcome in the neoadjuvant setting as well. Table 1: Selected trials in HER2-positive breast cancer Full table "The NeoSphere and NeoALLTO data presented at San Antonio [last year] were very impressive in that they indicated that pathological complete response rates in the upper twenties for [Herceptin] trastuzumab and paclitaxel were increased by 20%, through dual blockade of the HER2 pathway. If this translates into the metastatic setting, the Cleopatra results to be presented at San Antonio could be extremely exciting," says Brian Leyland-Jones of Emory University, Atlanta, who was a clinical investigator on pivotal trials of Herceptin in both the metastatic and adjuvant settings. 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
• Gilead donates patents for generics
  - Nat Biotechnol 29(10):857 (2011)
  Article preview View full access options Nature Biotechnology | News Gilead donates patents for generics * Simon FrantzJournal name:Nature BiotechnologyVolume: 29,Page:857Year published:(2011)DOI:doi:10.1038/nbt1011-857aPublished online13 October 2011 Gilead Sciences and the Geneva-based Medicines Patent Pool (MPP) have entered into an agreement allowing manufacturers to produce low-cost versions of the biotech firm's HIV drugs. Gilead's Viread (tenofovir), Emtriva (emtricitabine), cobicistat and elvitegravir, along with a combination of all four called the Quad, will be produced by generics manufacturers in India in return for modest royalties. "This should become a win-win for much of the global HIV-infected community and Gilead," says John Erickson, CEO of Sequoia Pharmaceuticals of Gaithersburg, Maryland. Cobicistat and elvitegravir are in phase 3, meaning low-cost versions could be available in developing countries immediately after approval. The MPP hopes the deal struck with Gilead, of Foster City, California, will bring other companies on board, and is focused on negotiations with a drawn-up list of pharma companies. For biotechs with phase 1 and 2 products, such as Sangamo BioSciences of Richmond, California,! Tobira Therapeutics of S. San Francisco, and Chimerix of Durham, North Carolina, it appears too early to consider the patent-pool scheme; they are more likely to wait until their products are closer to market. According to Erickson, inducing early-stage deals will require a different licensing rationale to avoid devaluing companies' drug intellectual property through limiting its options prematurely. For instance, the MPP or one of its generic partners could become a fully fledged development partner that shares the risks. "Otherwise, aside from optics [public relations], it is difficult to see any benefit to MPP or biotechs for entering into licenses for early-stage drugs," says Erickson. 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 * Simon Frantz Search for this author in: * NPG journals * PubMed * Google Scholar
• South Korea's stem cell approval
  - Nat Biotechnol 29(10):857 (2011)
  Article preview View full access options Nature Biotechnology | News South Korea's stem cell approval * Heiko YangJournal name:Nature BiotechnologyVolume: 29,Page:857Year published:(2011)DOI:doi:10.1038/nbt1011-857bPublished online13 October 2011 On July 1, the Korea Food and Drug Administration approved a stem cell treatment for acute myocardial infarction developed by FCB-Pharmicell of Seongnam. Locals view the regulatory go-ahead as a world first and also a vote of confidence for the nation's scientific expertise following the cloning scandal that found stem cell scientist Woo Suk Hwang guilty of fraud (Nat. Biotechnol.24, 745–747, 2006). The treatment, Hearticellgram-AMI, is an autologous stem cell transplant of mesenchymal stem cells, cultured from a patient's own bone marrow, injected into the coronary arteries. The approval comes after six years of clinical trials; as yet, the company has not published results in a peer-reviewed journal. Another major caveat is clinical efficacy: patients showed a 6% improvement in the left ventricular ejection fraction used as measure of heart function six months after one dose of Hearticellgram-AMI. "6% is not terrible. You're getting a modest improvement, and that might! be the best they ever do" says University of Michigan cardiologist Mark Russell. For Hearticellgram-AMI, a price tag of 20-million Won ($19,000) may be overly optimistic," says Russell. 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
• Drug pipeline: Q311
  - Nat Biotechnol 29(10):859 (2011)
  Article preview View full access options Nature Biotechnology | News | Data Page Drug pipeline: Q311 * Wayne Peng1Journal name:Nature BiotechnologyVolume: 29,Page:859Year published:(2011)DOI:doi:10.1038/nbt.1999Published online13 October 2011 The US Food and Drug Administration continued to approve drugs at a faster pace than during the same time last year. Small molecules were particularly prominent, including Roche's B-RAF V600E mutation-specific Zelboraf (vemurafenib), which was approved for melanoma treatment just 99 days after filing. Seattle Genetics's antibody-drug conjugate, Adcetris (brentuximab vedotin), was also approved for lymphoma. Several biologics and novel therapeutics made progress in early stages, including AVI BioPharma's exon-skipping-inducer, eteplirsen, for muscular dystrophy, Baxter's autologous stem cell therapy for cardiovascular diseases and Novavax's influenza vaccine comprising virus-like particles. Several companies announced yet to be published late-stage results: Roche/Genentech's pertuzumab met its endpoints in breast cancer, Sanofi's alemtuzumab showed efficacy in the new indication of multiple sclerosis and Dynavax's hepatitis B virus vaccine Heplisav was protective. Regulatory ! decisions on JAK-STAT pathway inhibitor INCB 18424 (ruxolitinib) for treating myeloproliferative disorders and myelofibrosis and Bristol-Myers Squibb's dapagliflozin in insulin-independent diabetes are eagerly awaited. Notable regulatory approvals (Q3 2011) Box 1: Notable regulatory approvals (Q3 2011) Full box Notable regulatory setbacks (Q3 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 * 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
• Attacks on asthma
  - Nat Biotechnol 29(10):860-863 (2011)
  Nature Biotechnology | News Feature Attacks on asthma * Sarah Webb1Journal name:Nature BiotechnologyVolume: 29,Pages:860–863Year published:(2011)DOI:doi:10.1038/nbt.1994Published online13 October 2011 The current standard of care for asthma leaves large numbers of sufferers at risk for severe exacerbations and even death. But emerging targeted therapies that may provide better treatment options also face obstacles. Sarah Webb reports. View full text Additional data Affiliations * Brooklyn * Sarah Webb Author Details * Sarah Webb Search for this author in: * NPG journals * PubMed * Google Scholar
• Headwinds into opportunity
  - Nat Biotechnol 29(10):864-866 (2011)
  Article preview View full access options Nature Biotechnology | Bioentrepreneur | Building a business Headwinds into opportunity * Prabhavathi Fernandes1Journal name:Nature BiotechnologyVolume: 29,Pages:864–866Year published:(2011)DOI:doi:10.1038/bioe.2011.8Published online18 August 2011Corrected online22 September 2011 Numerous challenges face any emerging company developing a biopharmaceutical. How you anticipate hurdles, plan for contingencies and communicate with stakeholders will play a big part in determining your success. 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. Change history * Change history * Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Corrected online 22 September 2011In the version of this article initially published online, the author wrote, "This suggested a market potential in the billions of dollars…" The sentence should have read, "This suggested a larger market potential…" The error has been corrected for the print, PDF and HTML versions of this article. Author information * Change history * Author information Affiliations * Prabhavathi Fernandes is president and CEO at Cempra Pharmaceuticals, Chapel Hill, North Carolina, USA. Author Details * Prabhavathi Fernandes Contact Prabhavathi Fernandes Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• A methodological framework to enhance the clinical success of cancer immunotherapy
  - Nat Biotechnol 29(10):867-870 (2011)
  Nature Biotechnology | Opinion and Comment | Correspondence A methodological framework to enhance the clinical success of cancer immunotherapy * Axel Hoos1, 2 * Cedrik M Britten3, 4, 5 * Christoph Huber5, 6 * Jill O'Donnell-Tormey2, 7 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:867–870Year published:(2011)DOI:doi:10.1038/nbt.2000Published online13 October 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To the Editor: Cancer immunotherapy has a rich history spanning more than 100 years. Yet the field has struggled to integrate its knowledge into methodological advances that enable clinical success. The recent approvals of sipuleucel-T (Provenge) for hormone-refractory prostate cancer and ipilimumab (Yervoy) for unresectable and metastatic melanoma mark a notable turning point for the field. The drug approvals, both based on patient survival benefit1, 2, underscore the emergence of immunotherapy as a new treatment modality for cancer and reflect key characteristics of a new methodological framework for future progress. A notable challenge for the development of immunotherapies (defined here to span vaccination, adoptive T-cell transfer and strategies to modulate adaptive immune responses) has been the absence of such a tailored methodological framework distinct from that widely used for chemotherapy. We have started to systematically address the unique characteristics of immunotherapeutic agents in clinical trials by building a methodological framework to provide the knowledge and tools needed for successful immunotherapy development. Here, we summarize the results of two community-based associations—the Cancer Immunotherapy Consortium (CIC; formerly Cancer Vaccine Consortium, a program of the nonprofit Cancer Research Institute; New York) in the United States, and the Association for Cancer Immunotherapy (CIMT; Mainz, Germany) in Europe over the past seven years. CIC and CIMT conducted various initiatives in partnership with other groups and with the participation of major stakeholders from academia, the biotech and pharmaceutical industries and the US Food and Drug Administration (FDA). The resulting framework promises to define a better path for the development of new therapies and lay the foundation for the clinical subspecialty of immuno-oncology by informing futu! re practitioners in the field3 and enabling reproducible success in the development of cancer immunotherapies. The new framework comprises several components: (i) a new development paradigm for cancer immunotherapies4, (ii) harmonized use of methods for measuring immune response as a foundation for immune biomarker development5, 6, (iii) improved study designs4 and clinical endpoints7, (iv) immune-related antitumor response criteria8, (v) a publication framework for immune monitoring results from clinical trials9 and (vi) scientific exchange and regulatory interactions to inform guidance document development by regulatory authorities10, 11 (Table 1). Table 1: Common challenges, proposed solutions and intended outcomes in immuno-oncology clinical development Full table Despite distinct scientific differences between chemotherapies and immunotherapies, clinical development of immunotherapies has followed the established chemotherapy paradigm. Notably, chemotherapies target the cancer directly whereas immunotherapies target the immune system. This methodological discrepancy may have contributed to the failures of several immunotherapy candidates4, 7, 12. The proposed paradigm recognizes characteristics of immunotherapy development that may differ from those of chemotherapy, such as the following: first, the optimal biologic dose is often not the maximum tolerated dose; second, treatment effect is not proportionally linked to toxicity; third, conventional pharmacokinetics may not determine dose and schedule; fourth, anti-tumor response is not the sole predictor of survival; and finally, clinical effects can be delayed in time and can occur after tumor volume increase (often categorized as progression). The new paradigm divides the development! process into two phases—proof-of-principle trials and efficacy trials, where efficacy trials are recommended to be randomized (phase 2 and 3 trials). Furthermore, it offers considerations for toxicity screening in early trials, concepts for measurement of biologic activity, use of immune response assays in clinical trials, dose and schedule investigation, decision points in development, trial design, improved clinical endpoints and combination therapy. Besides providing a systematic approach to the developmental science, much of the value of this paradigm lies in the consensus between all of the main participants involved in cancer immunotherapy development, namely representatives from the academic, industrial and regulatory sectors4, 7, 12. The unique clinical effects associated with immunotherapies, as opposed to chemotherapies, need to be recognized in a revision of our established concept of clinical endpoints to improve endpoints for immunotherapy trials. Oncologists are very familiar with chemotherapy effects, which occur either soon after treatment starts or not at all. For immunotherapy, however, clinical effects may have a broader spectrum and include early response (similar to chemotherapy), delayed response (after apparent tumor burden increase or progression), or slow changes over time, usually recognized as stable disease8. These response kinetics likely reflect the interplay between the immune system and the tumor. Delayed or slowed clinical effects influence both anti-tumor response and survival as clinical trial endpoints7 and require adjusted methods to measure this biology. For anti-tumor response endpoints (complete or partial response, disease control and progression-free survival), principles for the development of immunotherapy response criteria were derived from community workshops4 and translated into applicable criteria based on clinical data from the ipilimumab (a cytotoxic T lymphocyte–associated antigen 4 (CTLA-4) targeting fully human antibody) immunotherapy program conducted by Bristol-Myers Squibb (Princeton, NJ, USA) and Medarex (Princeton) encompassing 487 patients with advanced melanoma. Four patterns of response were identified: first, immediate response; second, durable stable disease with possible slow decline in tumor burden; third, response after tumor burden increase (possible lymphocyte infiltration); and fourth, response in the presence of new lesions. The resulting immune-related response criteria are generally based on the World Health Organization (WHO; Geneva) and RECIST (response evaluation criteria in solid tumor! s) criteria, describe tumor burden as a continuous variable over time, and account for new lesions in the overall tumor burden8. Current data suggest an association of such response patterns with favorable survival, indicating that immune-related response criteria identify patients who have derived previously unrecognized benefit8. These criteria present an additional tool for investigating immunotherapies and are currently being prospectively validated. For the survival endpoint, differences between chemotherapy and immunotherapy in randomized trials can be seen in the form of a delayed separation of Kaplan-Meier curves12, which for immunotherapies may occur months after treatment start and may reduce the statistical power to differentiate the curves in their entirety7. Conventional statistical methods do not have a provision for a delayed separation of curves, but rather assume a constant hazard ratio over time (proportional hazards), where the separation of curves occurs shortly after treatment start. In immunotherapy trials, a delayed separation of curves months after treatment start is expected, and events before the separation do not contribute to the differentiation between curves. These conditions need to be compensated for to avoid loss of statistical power. Consequently, alternative statistical methods should be considered when computing the required number of events for final analysis under a delayed separation as! sumption7. Importantly, any early interim and futility analysis should be carefully considered, as a delayed separation will increase the chances of a negative result at a time when curves have not yet parted. The relevance of these observations is illustrated by the development of anti-CTLA-4 antibodies in metastatic melanoma13, 14 through two independent development programs by Pfizer (tremelimumab) and Bristol-Myers Squibb (ipilimumab). The tremelimumab program conducted an early interim analysis for survival in its phase 3 study and could not observe a survival benefit, resulting in study termination for futility as recommended by the data monitoring committee. Two years later, extended follow-up on the study population revealed a separation of survival curves14. Conversely, the scientific approach for ipilimumab development, based on the new clinical paradigm, shifted away from response-based endpoints and led to the change of the primary endpoints for its two phase 3 studies in metastatic melanoma from response rate and progression-free survival to overall survival with no interim analyses13. A mature final survival analysis of the first phase 3 study of ipilimumab in pretre! ated metastatic melanoma patients demonstrated a delayed separation of curves at four months and the first survival benefit in the history of advanced melanoma clinical investigation (hazard ratio of 0.66 or 34% risk reduction for death; ref. 2). The second phase 3 trial in untreated advanced melanoma also met its survival endpoint with the same characteristics15. Immune biomarker development depends on the effective management of data variability resulting from immune assays. Activation of the immune system is the first biologic event after treatment with immunotherapy. Consequently, measurement of the immune response (T-cell or antibody response) for biomarker development is of particular interest to describe effects of therapy before reaching clinical endpoints. Immunological biomarkers, if reliably and reproducibly measured through immune monitoring assays, may fulfill several applications, from determining whether an immune intervention achieved its biological effect to predicting clinical outcomes as surrogates for clinical benefit. Current T-cell immune response assays, such as the enzyme-linked immunosorbent spot (ELISPOT) assay, intracellular cytokine staining and human leukocyte antigen–peptide multimer staining, are scientifically sound but tend to be methodologically inconsistent if not performed by specially trained lab! oratories. Unless properly controlled, they yield highly variable data and have contributed to the field's inability to define biomarkers for the above clinical applications7. A possible solution has been outlined by a series of international proficiency panels (quality control experiments across multiple centers) conducted by CIC and CIMT with >120 participating laboratories from 14 countries, encompassing the academic, nonprofit, biotech and pharmaceutical sectors, the US Department of Defense and the German regulatory agency Paul-Ehrlich-Institute (Langen, Germany). The results demonstrate that assay harmonization can substantially reduce variability5, 6 and may help to build a framework for assay use in multicenter clinical trials similar to that of The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use-Good Clinical Practice (ICH-GCP) for clinical protocols. Harmonization supports the elimination of fac! tors that cause major variability from assay conduct through t! he adoption of standard operating procedures by all laboratories conducting the respective assay. This process does not require standardization of assay protocols. Wide implementation of the assay harmonization concept will likely increase the quality of immunological monitoring and thereby enable use of assay results to guide the clinical development of new immunotherapies and provide a better understanding of exact therapeutic mechanisms of action. Furthermore, success in managing data variability for immune monitoring assays would contribute to methodological validation and clinical qualification in biomarker development. This would allow their integration into clinical development plans and possibly create regulatory utility. Tools, such as assay harmonization, should be used judiciously so they do not stifle the scientific creativity needed for new assay development. Data reporting in publications presents another challenge for immune monitoring in clinical trials. The community has not yet created the mechanism for open and consistent reporting of results. To support reproducible biomarker development, such a mechanism is needed to present results in scientific publications in a way that allows full disclosure of relevant experimental details. On the basis of the concept championed by the Minimum Information About Biological and Biomedical Investigations initiative16, CIC and CIMT together with the Human Immune Monitoring Center at Stanford University (Stanford, CA, USA) started the Minimal Information About T-Cell Assays (MIATA) project9. MIATA aims to provide guidelines for the publication of results from T-cell assays performed in clinical trials, which are based on community consensus and find broad recognition among scientists conducting such assays. The project includes wide outreach through public consultation and is planned to b! e completed late in 2011. On the basis of the above, the first regulatory guidance was developed by the FDA. The US agency participated in several of the community workshops described, and in 2007 hosted its own workshop where the above topics were reviewed. In 2009, FDA issued a guidance document on Clinical Considerations for Therapeutic Cancer Vaccines10, including many of these topics. The guidance underwent public consultation and is currently in the process of finalization. In mid-2010, the European Medicines Agency (EMA) released a concept paper to request public feedback for revision of its guidance on "evaluation of anticancer medicinal products in man" with a specific aim to address clinical endpoints for biologics and including a section on cancer vaccines11, which received feedback from CIC and CIMT. The continued interactions between community-based associations and regulatory authorities may foster the expansion of regulatory guidance to better serve new immunotherapy development. In conclusion, an obvious weakness of the past has been the absence of a tailored methodological framework for immunotherapy development that is distinct from that widely used for chemotherapy. The framework described here offers new tools, development principles and structure and has the potential to increase the credibility of the field overall. It defines a better path for development of new therapies and creates the foundation for a clinical subspecialty of immuno-oncology. It should be noted that past failures in the clinical translation of immunotherapeutic strategies can be attributed in part to, aside from methodological limitations, incomplete scientific understanding of tumor immunology, including limited knowledge of the mechanisms that determine the interaction of the immune system with the tumor17, 18. The incorporation of novel approaches to address tumor-induced immune suppression, pathways of immune modulation, such as CTLA-4 or PD-1 (programmed death 1), the tumor microenvironment or the optimization of clinical effects through tailored combination therapies19 will also play a crucial role in the future clinical successes of immunotherapies. Although many open questions remain, the outlook for immuno-oncology has substantially improved over the past two years. The framework we describe will continue to expand with the emerging field. Using the CIC and CIMT examples, continued progress may be accelerated through wide collaboration among stakeholders. References * References * Acknowledgments * Author information * Kantoff, P.W.et al. N. Engl. J. Med.363, 411–422 (2010). * ChemPort * ISI * PubMed * Article * Hodi, F.S.et al. N. Engl. J. Med.363, 711–723 (2010). * ChemPort * ISI * PubMed * Article * Goldman, B. & DeFrancesco, L.Nat. Biotechnol.27, 129–139 (2009). * ChemPort * PubMed * Article * Hoos, A.et al. J. Immunother.30, 1–15 (2007). * ISI * PubMed * Article * Janetzki, S.et al. Cancer Immunol. Immunother.57, 303–315 (2008). * PubMed * Article * Britten, C.M.et al. Cancer Immunol. Immunother.58, 1701–1713 (2009). * ChemPort * PubMed * Article * Hoos, A.et al. J. Natl. Cancer Inst.102, 1388–1397 (2010). * ChemPort * PubMed * Article * Wolchok, J.D.et al. Clin. Cancer Res.15, 7412–7420 (2009). * ChemPort * ISI * PubMed * Article * Janetzki, S.et al. Immunity31, 527–528 (2009). * ChemPort * PubMed * Article * Guidance for industry: Clinical considerations for therapeutic cancer vaccines. (US Department of Health and Human Services, Food and Drug Administration, Center for Biologics Evaluation and Research, September 2009). http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/default.htm * European Medicines Agency. Concept paper on the need to revise the guidelines on the evaluation of anticancer medicinal products in man. 22 July 2010. EMA/CHMP/EWP/433478/2010. http://www.ema.europa.eu/ema/index.jsp?curl=search.jsp&q=22+July+2010.+EMA%2Fchmp%2Fewp%2F433478%2F2010&murl=menus%2Fregulations%2Fregulations.jsp&mid= * Finke, L.H.et al. Vaccine25, B97–B109 (2007). * ChemPort * PubMed * Article * Hoos, A.et al. Semin. Oncol.37, 533–546 (2010). * ChemPort * PubMed * Article * Marshall, M., Ribas, A. & Huang, B. Evaluation of baseline serum C-reactive protein and benefit from tremelimumab compared to chemotherapy in first-line melanoma. Abstract no. 2609, presented at the 2010 annual meeting of the American Society Clinical Oncology, Chicago, IL, June 4–8, 2010. * Robert, C.et al. N. Engl. J. Med.364, 2517–2526 (2011). * ChemPort * ISI * PubMed * Article * Taylor, C.F.et al. Nat. Biotechnol.26, 889–896 (2008). * ChemPort * ISI * PubMed * Article * Finn, O.J.N. Engl. J. Med.358, 2704–2715 (2008). * ChemPort * ISI * PubMed * Article * Schreiber, R., Old, L.J. & Smyth, M.J.Science331, 1565–1570 (2011). * ChemPort * ADS * PubMed * Article * Zitvogel, L., Kepp, O. & Kroemer, G.Nat. Rev. Clin. Oncol.8, 151–160 (2011). * ChemPort * PubMed * Article Download references Acknowledgments * References * Acknowledgments * Author information We thank all participants of the workshops and community-wide initiatives conducted by CIC and CIMT for the contribution of knowledge to this evolving methodological framework. Author information * References * Acknowledgments * Author information Affiliations * Bristol-Myers Squibb, Wallingford, Connecticut, USA. * Axel Hoos * Cancer Immunotherapy Consortium (CIC; formerly Cancer Vaccine Consortium) of the Cancer Research Institute, New York, New York, USA. * Axel Hoos & * Jill O'Donnell-Tormey * Department of Medicine, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany. * Cedrik M Britten * Ribological GmbH, Mainz, Germany. * Cedrik M Britten * Association for Cancer Immunotherapy (CIMT), Mainz, Germany. * Cedrik M Britten & * Christoph Huber * Center for Translational Oncology and Immunology (TRON), Mainz, Germany. * Christoph Huber * Cancer Research Institute (CRI), New York, New York, USA. * Jill O'Donnell-Tormey Competing financial interests A.H. is an employee of Bristol-Myers Squibb (BMS), a pharmaceutical company and holds stock in BMS. C.M.B. has 50% employment at Ribological (Mainz, Germany), which is a company developing vaccines to treat cancer. C.H. is cofounder and supervisory board member of Ganymed Pharmaceuticals and BioNtech (Mainz, Germany), both biotech companies. Corresponding author Correspondence to: * Axel Hoos Author Details * Axel Hoos Contact Axel Hoos Search for this author in: * NPG journals * PubMed * Google Scholar * Cedrik M Britten Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Huber Search for this author in: * NPG journals * PubMed * Google Scholar * Jill O'Donnell-Tormey Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Pharmacogenetics and the immunogenicity of protein therapeutics
  - Nat Biotechnol 29(10):870-873 (2011)
  Nature Biotechnology | Opinion and Comment | Correspondence Pharmacogenetics and the immunogenicity of protein therapeutics * Chen Yanover1 * Nisha Jain2 * Glenn Pierce3 * Tom E Howard4 * Zuben E Sauna5 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:870–873Year published:(2011)DOI:doi:10.1038/nbt.2002Published online13 October 2011 To the Editor: The development of anti-drug antibodies (ADAs) to therapeutic proteins can lead to adverse events and also make a biologic less effective for its intended use. Immunogenicity assessments are now critical for the development, regulatory licensure and use of biologics and it has been argued that it is highly unlikely that regulatory approval would be granted for a biologic without an assessment of its immunogenicity1. The development of ADAs does not necessarily affect the safety and/or efficacy of a protein therapeutic and thus risk-based approaches are generally advocated to evaluate the clinical consequences2. For example, although therapies that involve replacement of proteins that are lacking or nonfunctional in patients have had spectacular results in the clinical management of many chronic diseases, such therapies are particularly prone to have adverse consequences as a result of so-called neutralizing ADAs3. Several reviews have previously catalogued the product and pa! tient-related risk factors for immunogenicity (refs. 4,5 and references therein and Supplementary Fig. 1). View full text Figures at a glance * Figure 1: Schematic of a proposed decision tree for the evaluation of immunogenicity in individual patients or populations. (i) Genotype the patient's endogenous protein (factor VIII for hemophilia A patients). Increasingly, therapeutic proteins are of human origin and manufactured using recombinant DNA technology and thus have a single defined sequence. Where multiple products are available for the same protein, the different products may have slightly different sequences (as is the case with factor VIII). This information can be used to identify those regions of the infused protein likely to be identified as foreign by a particular patient. Even so, not all individuals can present the same foreign peptide on the antigen-presenting proteins (Supplementary Fig. 1b). (ii) High-resolution HLA typing of individual patients can be used to determine whether (and with what affinity) the foreign peptides derived from the infused protein bind the patient's MHC class II molecules. Ex vivo T-cell proliferation assays, using the patient's peripheral blood mononuclear cells, can be used to determine whether ! the peptides that can potentially bind to the patient's MHC class II molecules actually stimulate a T-cell response. The illustration shows that the same set of peptides bind some MHC class II molecules and not others. (iii) The data accumulated in steps 1 and 2 for a population can be used to identify T-cell epitopes that bind to MHC class II molecules that represent a substantial segment of the population or those that are unique to some ethnicities or populations (Supplementary Fig. 1c). The latter can be used to design personalized therapies that could limit the incidence of immunogenicity in susceptible populations. * Figure 2: Estimating potential ADA responses to factor VIII in individual patients. () Percentile ranks for the binding of overlapping 15-mer peptides covering the entire factor VIII primary sequence to the HLA allele DRB1*1501 were determined (2,326 peptides for the mature factor VIII). The affinity of each of these peptides for the DRB1*1501 allele was computed and presented as a percentile binding rank using the consensus method14 (http://tools.immuneepitope.org/analyze/html/mhc_II_binding.html). The percentile rank for individual algorithms is generated by comparing the peptide's binding affinity (in nM) to that of 5 million random peptides from the SWISSPROT database; the consensus score is the median of the scores obtained by the different algorithms. In this scale, a lower percentile rank indicates higher binding affinity. The percentile binding ranks of all 15-mer peptides derived from the factor VIII protein are depicted as gray dots (left y axis). We have depicted the peptides with percentile rank < 4 (that is, peptides derived from the wild-type ! factor VIII sequence that bind to DRB1*1501 with high affinity) as colored squares (right y axis). These are further classified as low to intermediate (green), high (blue) and very high (red) affinity binding peptides. The position of each square or dot on the factor VIIII sequence represents a 15-mer peptide with the amino acid at that location at the center of the peptide (that is, the 8th amino acid). The peptides that are predicted to bind with very high affinity are clustered in six hot-spots, identified with red numbered circles and are listed in the inset. Each hot-spot represents a region of the factor VIII polypeptide found to contain several 15-mer peptides that bind with very high affinity. We determined whether individuals with missense mutations (that is, point mutations that did not result in a stop codon) in these six hot-spots were represented in the hemophilia ADB database. There have been reports of missense mutations in four of the six hot-spots. The freq! uency of inhibitor development among these individuals is indi! cated in the lower panel of the table. NR, not reported, () The overall fraction of MHC-II molecules that bind each wild-type peptide with high affinity (low percentile binding rank), termed the 'immunogenicity score' (Supplementary Note). Peptides that incorporate Y2105 (left) and R2150 (middle) show high immunogenicity scores but the same is not true of peptides that incorporate W2229 (right). Mutations at all three positions result in moderate hemophilia A and a relatively high proportion of patients with these mutations develop inhibitory antibodies. () Heat map depicting the affinities of individual MHC-II molecules (y axis) to wild-type peptides (x axis) from regions of factor VIII spanning the three highly recurrent hemophilia A–causing missense mutations analyzed in . The consensus percentile ranks used in generating all figures were obtained using version 2.3 of the predictor tool. 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 * Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. * Chen Yanover * Clinical Review Branch, Division of Hematology, Center for Biologics Evaluation and Research, Food and Drug Administration, Bethesda, Maryland, USA. * Nisha Jain * Biogen Idec Hemophilia, Waltham, Massachusetts, USA. * Glenn Pierce * Department of Pathology and Laboratory Medicine, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California, USA. * Tom E Howard * Laboratory of Hemostasis, Division of Hematology, Center for Biologics Evaluation and Research, Food and Drug Administration, Bethesda, Maryland, USA. * Zuben E Sauna Competing financial interests G.P. is an employee of BiogenIDEC. Corresponding author Correspondence to: * Zuben E Sauna Author Details * Chen Yanover Search for this author in: * NPG journals * PubMed * Google Scholar * Nisha Jain Search for this author in: * NPG journals * PubMed * Google Scholar * Glenn Pierce Search for this author in: * NPG journals * PubMed * Google Scholar * Tom E Howard Search for this author in: * NPG journals * PubMed * Google Scholar * Zuben E Sauna Contact Zuben E Sauna Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Figures 1 and 2 and Supplementary Note (175K) C.Y. analyzed the data, generated Figure 2 and contributed to the writing of the manuscript. G.P. wrote the section on the clinical development and regulatory requirements for developing a personalized approach to protein replacement therapy. T.E.H. and N.J. provided the discussion of the clinical and regulatory issues, respectively. Z.E.S. was responsible for conceptualizing this project and overall writing of the manuscript. Additional data
• Wanted: bioprospecting consultants
  - Nat Biotechnol 29(10):873-875 (2011)
  Article preview View full access options Nature Biotechnology | Opinion and Comment | Correspondence Wanted: bioprospecting consultants * Kazuo N Watanabe1, 2 * Guat Hong Teh3 * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:873–875Year published:(2011)DOI:doi:10.1038/nbt.2001Published online13 October 2011 To the Editor: The Convention on Biological Diversity (CBD) was set up with the aim of preserving biological diversity. One part of that goal is to implement fair and equitable sharing of the benefits arising from the use of genetic resources, which after 10 years of deliberations finally took shape in the agreement of the Nagoya Protocol last October1. The first meeting of the CBD's Intergovernmental Committee for The Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization took place in Montreal from June 6–10. This meeting discussed several recommendations for implementing the Nagoya Protocol, including the operation of the Access and Benefit-sharing Clearinghouse; capacity building and development and human and institutional capacities in developing countries; and cooperative procedures and institutional mechanisms to promote compliance with the Protocol and address cases of noncompliance. The fact is, however, that the somewhat ambiguous language of the Nagoya Protocol presents several hurdles to any company or individual seeking to legitimately collect and invest in the development of products based on natural resources. Together with the proliferation of overlapping treaties and agreements and the involvement of an increasingly complex patchwork of international agencies, bioprospecting now represents a daunting legal challenge for any entity seeking to access the genetic resources of a particular country. For these reasons, we believe there is an urgent need for consultants to facilitate partnerships and foster trust among players in the bioprospecting process. Last year's Nagoya Protocol found an historic consensus on four key issues in access and benefit sharing: first, the extent to which past access in a particular territory can affect benefit sharing (Preamble and Article 3); second, the extent to which commercial and noncommercial uses of genetic resources translate to fair and equitable benefit sharing over the diversity of genetic resources (Articles 5 and 8); third, how derivatives of genetic resources can be defined and the extent to which those derivatives are included under the access and benefit-sharing framework and that framework is put into practice (Articles 2 and 6); and fourth, the mechanisms by which individual countries not only provide authorization on access and benefit sharing through specific national agencies (Article 13) but also set up checkpoints to monitor trafficking of genetic resources in compliance with domestic legislation and regulatory requirements (Articles 15 and 17). For this consensus to be achieved, however, rather ambiguous wording needed to be introduced into the protocol. For instance, it is unclear whether Article 17, which relates to the monitoring of formal trafficking of genetic resources, calls for compulsory establishment of a regulatory system or more arbitrary responses by competent authorities within the nation in question. It seems that many nations providing genetic resources could be uncertain about sharing their resources with recipient countries without a better defined arrangement. We believe this ambiguity will be detrimental to both users and providers of genetic resources in the long term. One reason the ambiguity is harmful is that it provides an opportunity for free-riding and encourages unlawful behavior by individuals, research institutions and companies. Such acts serve only to increase the tension between developed and developing nations and ultimately may threaten the foundations of open science. The uncertainty also discourages industries—such as the pharmaceutical, biotech, seed and agriculture industries—that rely on natural resources for the development of new products derived from collecting and investing in the development of products based on such resources. Those companies that aspire to do things the right way face challenges on several fronts: they often are confronted by allegations from third parties that they have misappropriated genetic resources (biopiracy); they may lack the relevant expertise and tools to navigate the complex legal territory of access and benefit sharing; they may have only minimal experience in practical skills, such as negotiation with local and international bodies; and they may face difficulties in identifying experts for professional advice. Access and benefit-sharing regulations may also compromise public health efforts, such as acquisition of emerging infectious, human-disease pathogens for basic public health research. This was seen in efforts to rapidly obtain and transfer avian influenza strain H5N1 samples from infected patients at sites of outbreak (mainly in developing countries) to the global medical research communities (mainly in developed countries). Negotiations on access and benefit sharing took center stage instead of discussions about mechanisms to ensure prompt access to the samples in order to prevent the possible spread of a human pandemic. As information associated with genetic resources also falls under the remit of access and benefit-sharing regulations, red tape associated with bioprospecting may also encumber genomics-type research. Restrictions on access and burdensome requirements for benefit sharing also serve to hinder industrial pursuit of natural targets that may provide starting points for medical products against public health needs. Lastly, academia—perhaps the least equipped stakeholder for navigating the access and benefit-sharing framework— is also likely to be negatively affected by the language in the current protocol. Noncommercial uses of genetic resources are subject to access and benefit-sharing regulations; indeed, many countries do not make the distinction between noncommercial and commercial uses2, even though simplified procedures have been requested by many nations and international organizations. If the access and benefit-sharing protocol wasn't enough, those seeking to tap into a country's genetic resources must contend with rules for intellectual property (IP) on genetic resources, which for the past decade has been overseen by the World Intellectual Property Organization (WIPO; http://www.wipo.int/tk/en/genetic/). Although WIPO and CBD have attempted to harmonize oversight, as yet, there is no integration of WIPO IP rules and access and benefit sharing. What's more, several other instruments on genetic resources have proliferated over the past decade, including the Agreement on Trade-Related Aspects of Intellectual Property Rights (negotiated primarily by ministries of trade); the International Treaty on Plant Genetic Resources for Food and Agriculture (negotiated primarily by ministries of agriculture) and the Cartagena Protocol on Biosafety (negotiated primarily by ministries of science and technology). One should bear in mind that the CBD was negotiated under t! he aegis of the United Nations Environment Program, which brought together the ministries of the environment. All of this has resulted in a patchwork of regulatory requirements that must be navigated by those who wish to prospect for genetic resources, those who grant access to such genetic resources, and those whose duty is to implement the regulatory mechanisms to oversee the process. In this context, we feel there is an urgent need for reengagement of public and private sector participants in the processes on access and benefit sharing. In particular, we believe that consulting expertise is crucial to create trust and build skill sets between partners, with the aim of encouraging collaborations to implement access and benefit sharing in support of global R&D. The idea of creating a facilitation or mediation mechanism to foster partnership and create trust among players in the bioprospecting process is not new. In 2002, Switzerland presented to the CBD the results of a feasibility study on the creation of a voluntary3 "comprehensive, independent and neutral mediation service between the parties to the negotiation" that would "aim to ensure that the views and interests of all stakeholders are represented and that solutions, which meet the needs of all parties involved, are found." At the time, this idea was dismissed because the stakeholders involved, including players in both the public and private sectors, feared that such a mediation process would incur further transaction costs and make bioprospecting less economically attractive. We submit that the previous rejection of the mediation mechanism stems from the concern that a formal mediating body at the international level would further complicate matters; it is not an indication of a lack of interest in professional entities that would perform such a service. We also think that a market-led mediation mechanism is preferable to that originally proposed because the latter would likely be unable to serve as a truly independent and neutral body for parties who are attempting to negotiate for access by offering monetary and nonmonetary returns—two contrasting interests that would require bargaining and sophistication in negotiation skills. The nature of such negotiations is that it should be driven by parties who will be directly affected by the outcome of the deal-making, rather than by an outsider who may not be directly affected by the conclusion of such a process. With this in mind, we propose that a better solution would be to encourage the creation of market-driven consulting services that provide professional advice to governments, companies, public research institutions, individual scientists and others, without conflict of interest; this would ensure that participants build capacity and receive advice in a relationship of trust and confidence. To provide such a service, the consultancy would need to be equipped with the necessary legal, scientific, technological and marketing skills to improve the capacity of its 'clients' in a way that encourages rather than detracts from engaging in the activity of bioprospecting. Personnel trained in law (particularly IP rights and biodiversity laws), biological sciences and business development would be important to ensure that such businesses establish their professional credibility in the market. It would also be essential that these services have an understanding and appreciation of the various users and providers, and the needs of different industries, so that the advice provided is pragmatic and useful. Specialists would also be needed with expertise in specific regions, such as Japan4 and Himalayan countries5. 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 Gene Research Center, University of Tsukuba, Japan. * Kazuo N Watanabe * The Institute of Advanced Studies, United Nations University, Yokohama, Japan. * Kazuo N Watanabe * Wong, Teh & Sharzila, Advocates & Solicitors, Kuala Lumpur, Malaysia. * Guat Hong Teh Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Kazuo N Watanabe or * Guat Hong Teh Author Details * Kazuo N Watanabe Contact Kazuo N Watanabe Search for this author in: * NPG journals * PubMed * Google Scholar * Guat Hong Teh Contact Guat Hong Teh Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Evergreening: a common practice to protect new drugs
  - Nat Biotechnol 29(10):876-878 (2011)
  Nature Biotechnology | Feature | Patents Evergreening: a common practice to protect new drugs * Kate S Gaudry1Journal name:Nature BiotechnologyVolume: 29,Pages:876–878Year published:(2011)DOI:doi:10.1038/nbt.1993Published online13 October 2011 The common strategy of evergreening using patents and other exclusivity periods likely contributes to the total incentives that justify a pharmaceutical company's investment in a new drug. View full text Figures at a glance * Figure 1: Characteristics of patent exclusivities associated with NDAs. () Percentage of NDAs associated with one or more patents. Percentage of all NDAs approved within the identified year for which one or more patents were identified under 21 CFR § 355(b)(1)(G) or 21 CFR § 355(c)(2) as claiming the NDA's drug or a method of using the drug. () Number of NDA-associated patents. For each NDA, the total number of patents identified to the FDA as claiming the NDA's drug or a method of using the drug was determined. NDAs not associated with any patents were excluded, and the number of patents were then averaged across the remaining applications approved within each year between 2000 and 2010. () Maximum remaining patent term after approval. For each NDA, I determined the latest expiration date across all of the patents identified as claiming the NDA's drug or method of using the drug. The remaining total patent term was defined as the time between the NDA approval date and this expiration date. NDAs not associated with any patents were excluded, a! nd the remaining terms were averaged across all applications approved within each year between 2000 and 2010. Error bars in and show the s.e.m. * Figure 2: Characteristics of FDA-approval exclusivities associated with NDAs. () Percentage of NDAs associated with FDA-approval exclusivity periods. Percentage of all NDAs approved within the identified year and having one or more FDA-approval exclusivity periods. () Number of NDA-associated FDA-approval exclusivity periods. For each NDA, I determined the total number of FDA-approval exclusivity periods associated with the NDA. NDAs not associated with any FDA-approval exclusivities were excluded, and the exclusivity-period numbers were then averaged across the remaining applications approved within each year from 2000 to 2010. () Maximum approval-related exclusivity terms. For each NDA, I identified the expiration of each FDA-approval exclusivity period received. The maximum approval-related exclusivity term was defined as the time between an NDA's approval and the latest approval-related exclusivity-period expiration. NDAs not associated with any FDA-approval exclusivities were excluded, and the maximum approval-related exclusivity terms were avera! ged across all applications approved within each year between 2000 and 2010. Error bars in and show the s.e.m. 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 * Kate S. Gaudry is a recent graduate from Harvard Law School. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Kate S Gaudry Author Details * Kate S Gaudry Contact Kate S Gaudry Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Recent patent applications in drug screening
  - Nat Biotechnol 29(10):879 (2011)
  Article preview View full access options Nature Biotechnology | Feature | Patents Recent patent applications in drug screening Journal name:Nature BiotechnologyVolume: 29,Page:879Year published:(2011)DOI:doi:10.1038/nbt.2007Published online13 October 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.
• New fluorescent probes for super-resolution imaging
  - Nat Biotechnol 29(10):880-881 (2011)
  Article preview View full access options Nature Biotechnology | News and Views New fluorescent probes for super-resolution imaging * Joshua C Vaughan1 * Xiaowei Zhuang1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:880–881Year published:(2011)DOI:doi:10.1038/nbt.1997Published online13 October 2011 Fatigue-resistant, photoswitchable fluorescent proteins facilitate sub-diffraction-limit imaging of living cells with low light intensity. 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 * Joshua C. Vaughan and Xiaowei Zhuang are at Harvard University and Howard Hughes Medical Institute, Cambridge, Massachusetts, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Xiaowei Zhuang Author Details * Joshua C Vaughan Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaowei Zhuang Contact Xiaowei Zhuang Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Tracking down the human myelinating cell
  - Nat Biotechnol 29(10):881-883 (2011)
  Article preview View full access options Nature Biotechnology | News and Views Tracking down the human myelinating cell * Robert H Miller1 * Paul J Tesar2 * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:881–883Year published:(2011)DOI:doi:10.1038/nbt.2004Published online13 October 2011 A new strategy for isolating oligodendrocyte progenitor cells from the human brain may advance the goal of therapeutic remyelination. 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 * Robert H. Miller is at the Center for Translational Neuroscience, Department of Neurosciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA. * Paul J. Tesar is at the Department of Genetics, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Robert H Miller or * Paul J Tesar Author Details * Robert H Miller Contact Robert H Miller Search for this author in: * NPG journals * PubMed * Google Scholar * Paul J Tesar Contact Paul J Tesar Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• RNA lights up
  - Nat Biotechnol 29(10):883-884 (2011)
  Article preview View full access options Nature Biotechnology | News and Views RNA lights up * John S Mattick1 * Michael B Clark1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:883–884Year published:(2011)DOI:doi:10.1038/nbt.2003Published online13 October 2011 A new method to genetically tag RNA for fluorescence imaging in live cells simplifies imaging of cellular RNAs. 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 * John S. Mattick and Michael B. Clark are at the Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * John S Mattick Author Details * John S Mattick Contact John S Mattick Search for this author in: * NPG journals * PubMed * Google Scholar * Michael B Clark Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE
  - Nat Biotechnol 29(10):886-891 (2011)
  Nature Biotechnology | Computational Biology | Analysis Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE * Peng Qiu1, 2 * Erin F Simonds3 * Sean C Bendall3 * Kenneth D Gibbs Jr3 * Robert V Bruggner3 * Michael D Linderman4 * Karen Sachs3 * Garry P Nolan3 * Sylvia K Plevritis1 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:886–891Year published:(2011)DOI:doi:10.1038/nbt.1991Received10 January 2011Accepted31 August 2011Published online02 October 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 The ability to analyze multiple single-cell parameters is critical for understanding cellular heterogeneity. Despite recent advances in measurement technology, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system. To objectively uncover cellular heterogeneity from single-cell measurements, we present a versatile computational approach, spanning-tree progression analysis of density-normalized events (SPADE). We applied SPADE to flow cytometry data of mouse bone marrow and to mass cytometry data of human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. We demonstrate that SPADE is robust to measurement noise and to the choice of cellular markers. SPADE facilitates the analysis of cellular heterogeneity, the identification of cell types and comparison of functional markers in re! sponse to perturbations. View full text Figures at a glance * Figure 1: Flowchart of SPADE and SPADE analysis of a simulated data set. (i) A simulated two-parameter flow cytometry data set, with one rare population and three abundant populations. (ii) Result of density-dependent down-sampling of the original data. (iii) Agglomerative clustering result of the down-sampled cells. Adjacent clusters are drawn in alternating colors. (iv) Minimum spanning tree that connects the cell clusters. (v) Colored SPADE trees. Nodes are colored by the median intensities of protein markers of cells in each node, allowing visualization of the behaviors of the two markers across the entire heterogeneous cell population. * Figure 2: SPADE applied to mouse bone marrow flow cytometry data. () Known hematopoietic hierarchy in mouse bone marrow. () SPADE tree derived from the mouse bone marrow data. (–) Trees colored by the median intensity of one individual marker. () Traditional gating analysis on the mouse bone marrow data. () For each gated population, one SPADE tree was drawn, where each node was colored according to the percentage of gated cells in that node. Thus, the darker regions of each tree represent which part of the tree is populated by the cells in the corresponding gate. This comparison shows the concordance between SPADE and gating results. * Figure 3: SPADE applied to human bone marrow data of 30 experiments with two overlapping staining panels and multiple experimental conditions. () Experiment and staining panel design. () SPADE tree derived from this data set. The SPADE tree was annotated according to its colored versions based on the 13 core surface markers. CMP, common myeloid progenitor; MPP, multipotent progenitor. * Figure 4: SPADE tree colored by two NK-specific markers CD7 and CD16, which were not used to derive the SPADE tree. The color patterns indicate that the nodes contained within the dark black boundary are NK cells. * Figure 5: SPADE trees that describe the cell type–dependent behavior of functional markers in response to perturbations. () After stimulation with TNF, phosphorylated MAPKAPK2 was observed in myeloid and NK cell types, but not in other cell types. () After stimulation with LPS, degradation of total IκBα was restricted to the monocytoid lineage. () TPO-induced phosphorylated STAT5 was observed in HSCs and CD123++, but not in other cell types. () GM-CSF–induced phosphorylation of pSyk was observed only in myelocytes. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Radiology, Stanford University, Stanford, California, USA. * Peng Qiu & * Sylvia K Plevritis * Department of Bioinformatics and Computational Biology, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, USA. * Peng Qiu * Department of Microbiology and Immunology, Stanford University, Stanford, California, USA. * Erin F Simonds, * Sean C Bendall, * Kenneth D Gibbs Jr, * Robert V Bruggner, * Karen Sachs & * Garry P Nolan * Computer Systems Laboratory, Stanford University, Stanford, California, USA. * Michael D Linderman Contributions P.Q., G.P.N. and S.K.P. conceived the study and developed the method. E.F.S., S.C.B. and K.D.G.Jr. performed mass and flow cytometry experiments, and participated in the biological interpretation. P.Q., R.V.B., M.D.L. and K.S. performed robustness analysis of the method. P.Q., E.F.S., S.C.B., K.D.G.Jr., G.P.N. and S.K.P. wrote the manuscript and developed the figures. Competing financial interests A patent for the SPADE algorithm has been applied for on behalf of Stanford University. Corresponding author Correspondence to: * Peng Qiu Author Details * Peng Qiu Contact Peng Qiu Search for this author in: * NPG journals * PubMed * Google Scholar * Erin F Simonds Search for this author in: * NPG journals * PubMed * Google Scholar * Sean C Bendall Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth D Gibbs Jr Search for this author in: * NPG journals * PubMed * Google Scholar * Robert V Bruggner Search for this author in: * NPG journals * PubMed * Google Scholar * Michael D Linderman Search for this author in: * NPG journals * PubMed * Google Scholar * Karen Sachs Search for this author in: * NPG journals * PubMed * Google Scholar * Garry P Nolan Search for this author in: * NPG journals * PubMed * Google Scholar * Sylvia K Plevritis Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (10M) Supplementary Sections 1–8 Zip files * Supplementary Data 1 (350K) simulated fcs file * Supplementary Data 2 (26M) Qiu_SPADE_MouseBM.fcs * Supplementary Data 3 (520K) Additional data
• Direct lineage conversions: unnatural but useful?
  - Nat Biotechnol 29(10):892-907 (2011)
  Nature Biotechnology | Research | Review Direct lineage conversions: unnatural but useful? * Thomas Vierbuchen1 * Marius Wernig1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:892–907Year published:(2011)DOI:doi:10.1038/nbt.1946Published online12 October 2011 Abstract * Abstract * Author 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 Classic experiments such as somatic cell nuclear transfer into oocytes and cell fusion demonstrated that differentiated cells are not irreversibly committed to their fate. More recent work has built on these conclusions and discovered defined factors that directly induce one specific cell type from another, which may be as distantly related as cells from different germ layers. This suggests the possibility that any specific cell type may be directly converted into any other if the appropriate reprogramming factors are known. Direct lineage conversion could provide important new sources of human cells for modeling disease processes or for cellular-replacement therapies. For future applications, it will be critical to carefully determine the fidelity of reprogramming and to develop methods for robustly and efficiently generating human cell types of interest. View full text Figures at a glance * Figure 1: Epigenetic models of development and reprogramming. During development, cells are gradually restricted in their developmental potential (left). It is believed that this irreversible restriction is accompanied and caused by the progressive acquisition of epigenetic modifications (represented as accumulating black stripes in bars) that help to stabilize cell fate decisions and to restrict the adoption of inappropriate fates. The pluripotent state is characterized by a highly 'open' chromatin configuration, which is thought to permit differentiation to a variety of cell types. In one model (model A), reprogramming to a pluripotent state (by nuclear transfer, cell fusion or defined transcription factors) occurs through stepwise erasure of epigenetic marks associated with differentiation (red arrows), allowing cells to regain the open chromatin state and, by default, pluripotency. Alternatively (model B), the pluripotent state can be thought of as a defined and actively regulated epigenetic state rather than as an epigenetically e! rased space. This model suggests that the reprogramming factors actively establish the pluripotent chromatin state (red arrow), and that reprogramming represents an acquisition of pluripotent characteristics (red bars) rather than a loss of epigenetic lineage-restriction (green bars). In this model, inducing pluripotent cells is not considered fundamentally different than inducing other defined cell types, which implies that it should be possible to convert one differentiated cell type into another (blue bars) with the right combination of factors. * Figure 2: Various modes of induced cell fate changes. () Dedifferentiation: reversion to a less differentiated state. Examples include iPS cell reprogramming and loss of Pax5 in mature B cells. () Transdetermination: conversion between two closely related progenitor cells that share a direct common progenitor. Most gain-of-function experiments interrogating lineage-determining factors during embryonic development fall into this category. () Transdifferentiation: direct fate switch between two distinct cell types. Examples include lineage conversion of mature hematopoietic cell types, conversion of exocrine to endocrine pancreatic cells and conversion of fibroblasts into cardiac cells, skeletal myocytes, neurons or hepatocytes. () Directly induced differentiation: direct conversion studies suggest that it might be possible to directly induce a more differentiated cell type without passing through the corresponding intermediate progenitor state. For example, MyoD1 expression in human ES cells rapidly generates multinucleated myot! ubes271. Similarly, forced expression of iN cell reprogramming factors in pluripotent human cells rapidly generates neurons30, 170. * Figure 3: Potential mechanism of the stepwise activation of silent genes by reprogramming factors. () How can a transcription factor or a combination of transcription factors modify gene expression at epigenetically silenced loci? The various repressive marks are represented with red objects of different shapes (left) on DNA (blue line) or nucleosomes (blue cylinders). Green objects represent active chromatin marks (right). Dark green circles represent lineage reprogramming factors that promote gene transcription in a permissive chromatin state. () The repressed chromatin state is likely to be more dynamic than classically assumed. Epigenetic marks may stochastically fluctuate between active and repressive states, with the majority of marks being repressed at any given time point. During cell division there is also a potential window for epigenetic plasticity as unmodified histones are incorporated into duplicated strands of DNA. () The stochastic loss of repressive modifications or the sliding and/or displacement of nucleosomes may allow transcription factors to weakly b! ind DNA and access their cognate binding sites. These interactions may interfere with the stochastic fluctuations and allow recruitment of additional coactivators and/or histone-modifying enzymes to this regulatory region, thereby stabilizing transcription factor binding and eventually leading to transcriptional activation. () The newly activated genes may code for endogenous reprogramming factors or other transcription factors that could promote activation of the novel transcriptional program through a positive feedback loop. This would activate a self-maintaining transcriptional program, and the exogenous reprogramming factors would no longer be required to maintain the new cell lineage identity. Author information * Abstract * Author information Affiliations * Institute for Stem Cell Biology and Regenerative Medicine and Department of Pathology, Stanford University School of Medicine, Stanford, California, USA. * Thomas Vierbuchen & * Marius Wernig Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Marius Wernig Author Details * Thomas Vierbuchen Search for this author in: * NPG journals * PubMed * Google Scholar * Marius Wernig Contact Marius Wernig Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Performance comparison of exome DNA sequencing technologies
  - Nat Biotechnol 29(10):908-914 (2011)
  Nature Biotechnology | Research | Analysis Performance comparison of exome DNA sequencing technologies * Michael J Clark1, 4 * Rui Chen1, 4 * Hugo Y K Lam1 * Konrad J Karczewski1 * Rong Chen2 * Ghia Euskirchen1, 3 * Atul J Butte2 * Michael Snyder1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:908–914Year published:(2011)DOI:doi:10.1038/nbt.1975Received16 May 2011Accepted18 August 2011Published online25 September 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 Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. We present a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. Our results suggest that the Nimblegen platform, which is the only one to use high-density overlapping baits, covers fewer genomic regions than the other platforms but requires the least amount of sequencing to sensitively detect small variants. Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina captures untranslated regions, which are not targeted by the Nimblegen and Agilent platforms. We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect addi! tional small variants missed by WGS. View full text Figures at a glance * Figure 1: Exome enrichment designs include different biochemical methods, bait lengths, quantity and overlap of baits and number of bases targeted. () Bait design details for each commercial platform. () Venn diagram showing the overlap of targeted genome regions for all three platforms. () Venn diagram showing coverage of RefSeq coding exons and overlap between platforms. (,) Same as , but for Ensembl CDS exons and RefSeq UTR exons respectively. * Figure 2: Efficiency trends by platform. () Efficiency visualized as the percent of total targeted bases covered at particular depths. Inset: zoomed view of top left corner of the graph. (–) The percent of targeted bases covered at >10-fold, >20-fold and >30-fold read depth, respectively, at increasing read count thresholds. (–) The total number of bases covered at >10-fold, >20-fold and >30-fold read depth, respectively, at increasing read count thresholds. * Figure 3: Off-target enrichment and GC bias. () Off-target enrichment by platform is represented by total number of on-target (green) and off-target (gray) post-alignment reads from data sets normalized to 80M reads total. (,) The percent of on-target and off-target reads that overlap RepeatMasker entries () and known segmental duplications (). (–) Density plot shows the correlation between mean read depth across targeted regions and GC content in the Agilent exome sequencing data (), Nimblegen () and Illumina (). GC content across every target region was determined by dividing the number of G and C bases by the total number of bases in the target region. Mean read depth was determined across each target region independently. These plots were generated with smoothScatter from the Bioconductor package "geneplotter" (http://www.bioconductor.org/). * Figure 4: SNV trends by platform. Sensitivity toward SNVs is compared between each platform at increasing read counts. () Total number of SNVs detected at increasing read count thresholds. Sensitivity increases at higher read counts, particularly for the lower efficiency platforms. () SNVs detected in bases targeted by all three platforms. Nimblegen detects the most SNVs at all read counts because it is the most efficient. There is <2% increase in total variants detected for all platforms past 50M reads. () SNVs detected in RefSeq coding exons. These curves match the shared interval curves very closely because the genomic region shared by all three platforms is made up almost entirely by the RefSeq coding exons. () SNVs detected in RefSeq UTRs. UTRs are generally only targeted by the Illumina platform, so it detects far more in the UTRs at all read counts. () SNVs detected in Ensembl CDS. The Nimblegen and Illumina curves are very similar to their RefSeq coding curves in . The Agilent curve is shifted upward! s compared to its RefSeq coding curve because Agilent targets a large segment (1.4 Mb) of Ensembl CDS missed by the other two platforms. * Figure 5: Sensitivity toward indels compared between each platform at increasing read counts. Indel sensitivity may be more intimately tied to factors such as bait length and density compared with SNV sensitivity. () Total number of indels detected at increasing read count thresholds. As with SNVs, sensitivity increases at higher read counts. Agilent detects the highest quantity at lower read counts because its baits appear more robust toward indels than Illumina's. () Indels detected in bases targeted by all three platforms. Nimblegen detects the most indels at all read counts because it is the most efficient. Very few indels are detected in the shared interval because it is mostly made up of coding exons, which have a strong bias against indels. () Indels detected in RefSeq coding exons. These curves match the shared interval curves from b closely, much like for SNVs. () Indels detected in RefSeq UTRs. Again, Illumina detects far more of these because it is the only platform that specifically targets UTRs. () Indels detected in Ensembl CDS. Agilent detects the most! indels in Ensembl CDS due to a combination of the additional 1.4 Mb of targeted Ensembl CDS bases and its high sensitivity toward indels. * Figure 6: SNVs detected uniquely by exome sequencing or WGS, but not both. A standard WGS experiment at 35× mean genomic coverage was compared to exome sequencing experiments on each platform at 50M reads yielding exome target coverage of 30× for Illumina, 60× for Agilent and 68× for Nimblegen. SNVs were called in the WGS and then restricted to the regions targeted by each platform for comparison. () SNVs called in Agilent target regions by exome sequencing and WGS plotted as a function of coverage in exome sequencing versus coverage in WGS. Gray dots represent SNVs detected by both exome sequencing and WGS. Light blue dots represent SNVs uniquely called by exome sequencing. Red dots represent SNVs uniquely called by WGS. Lines represent the linear regression of the corresponding points. (,) The same plot as for , but for Nimblegen and Illumina, respectively. For all three exome sequencing platforms, SNVs detected uniquely by exome sequencing had lower than average coverage in WGS. SNVs detected uniquely by WGS were often in targets with zero o! r very low coverage by exome sequencing. () Venn diagram of SNVs detected by Agilent exome sequencing and WGS across Agilent targets. SNVs detected by both are in the green section. True-positive exome sequencing–specific SNVs are divided into novel (yellow) and known (red) slices. True-positive WGS-specific SNVs are divided into novel (orange) and known (blue) slices. False positives are in brown. (,) Same as , but for Nimblegen () and Illumina (), respectively. F.P., false positives. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Sequence Read Archive * SRA040093 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Michael J Clark & * Rui Chen Affiliations * Department of Genetics, Stanford University School of Medicine, Stanford, California, USA. * Michael J Clark, * Rui Chen, * Hugo Y K Lam, * Konrad J Karczewski, * Ghia Euskirchen & * Michael Snyder * Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA. * Rong Chen & * Atul J Butte * Center for Genomics and Personalized Medicine, Stanford University, Stanford, California, USA. * Ghia Euskirchen & * Michael Snyder Contributions M.S. and R.C. conceived and planned the study. R.C. performed the experiments. G.E. provided sequencing services. M.J.C. conducted the data analysis. R.C. and M.S. both contributed to the data analysis and discussion. H.Y.K.L. and M.J.C. analyzed the whole genome data. K.J.K., R.C. and A.J.B. created the disease/trait SNP database and analyzed our data against it. M.J.C., R.C. and M.S. prepared the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Michael Snyder Author Details * Michael J Clark Search for this author in: * NPG journals * PubMed * Google Scholar * Rui Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Hugo Y K Lam Search for this author in: * NPG journals * PubMed * Google Scholar * Konrad J Karczewski Search for this author in: * NPG journals * PubMed * Google Scholar * Rong Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Ghia Euskirchen Search for this author in: * NPG journals * PubMed * Google Scholar * Atul J Butte Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Snyder Contact Michael Snyder Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Tables 1–5 and Supplementary Figures 1–3 Zip files * Supplementary Data 1. (6M) SNVs detected by exome-seq with three platforms. * Supplementary Data 2. (799K) Indels detected by exome-seq with three platforms. Additional data
• Efficient de novo assembly of single-cell bacterial genomes from short-read data sets
  - Nat Biotechnol 29(10):915-921 (2011)
  Nature Biotechnology | Research | Article Efficient de novo assembly of single-cell bacterial genomes from short-read data sets * Hamidreza Chitsaz1, 6 * Joyclyn L Yee-Greenbaum2, 6 * Glenn Tesler3 * Mary-Jane Lombardo2 * Christopher L Dupont2 * Jonathan H Badger2 * Mark Novotny2 * Douglas B Rusch4 * Louise J Fraser5 * Niall A Gormley5 * Ole Schulz-Trieglaff5 * Geoffrey P Smith5 * Dirk J Evers5 * Pavel A Pevzner1 * Roger S Lasken2 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:915–921Year published:(2011)DOI:doi:10.1038/nbt.1966Received21 December 2010Accepted09 August 2011Published online18 September 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 Whole genome amplification by the multiple displacement amplification (MDA) method allows sequencing of DNA from single cells of bacteria that cannot be cultured. Assembling a genome is challenging, however, because MDA generates highly nonuniform coverage of the genome. Here we describe an algorithm tailored for short-read data from single cells that improves assembly through the use of a progressively increasing coverage cutoff. Assembly of reads from single Escherichia coli and Staphylococcus aureus cells captures >91% of genes within contigs, approaching the 95% captured from an assembly based on many E. coli cells. We apply this method to assemble a genome from a single cell of an uncultivated SAR324 clade of Deltaproteobacteria, a cosmopolitan bacterial lineage in the global ocean. Metabolic reconstruction suggests that SAR324 is aerobic, motile and chemotaxic. Our approach enables acquisition of genome assemblies for individual uncultivated bacteria using only short r! eads, providing cell-specific genetic information absent from metagenomic studies. View full text Figures at a glance * Figure 1: Assembling single-cell reads using Velvet-SC. () Coverage varies widely along the genome, between 1× and 12×. Reads (short thin colored lines) and potential contigs (thick lines) are positioned along the genome, with a box around the reads supporting each contig. There are two potential contigs to choose from in the middle, differing by a single nucleotide (C versus T): a green contig with coverage 6.4×, and a blue contig with coverage 1×. With a fixed coverage threshold of 4×, Velvet would delete the low-coverage blue and purple contigs, and then merge the high-coverage red and green contigs into a contig much shorter than the full genome. Velvet-SC instead starts by eliminating sequences of average coverage 1×, which only removes the blue contig. () The other contigs are combined into a single contig of average coverage 9×. The purple region is salvaged by Velvet-SC because it was absorbed into a higher coverage region as coverage threshold increased. Velvet-SC repeats this process with a gradually increasing l! ow-coverage threshold. () A portion of the de Bruijn graph for the contigs described in . The black circles are the 'vertices' and represent 5-mer strings derived from the reads, which are indicated by colored lines alongside the chains of vertices, including a blue read with an erroneous T. The lines between the vertices are termed 'edges' and represent the overlaps between the 5-mers. The edges are directed from left to right in this example. The read with the C/T mismatch results in two alternative paths for assembly, both with five intermediate vertices. The lower of the two paths arises from the erroneous blue read and has coverage 1×; it is the only part of the graph eliminated by Velvet-SC, leaving a single chain of vertices that gives a single contig for the entire genome. See Supplementary Figure 3 for an example of the condensing of contigs. An example of Velvet-SC handling of a chimeric read is presented in Supplementary Figure 4. * Figure 2: Comparison of contigs generated by Velvet versus EULER+Velvet-SC for single-cell E. coli lane 1. (–) Contigs are those presented in Table 1 and are ordered from largest to smallest number of bases. The y axis shows the cumulative length (), the cumulative number of genes () and the cumulative number of operons in the contigs (). EULER+Velvet-SC improves upon Velvet in all three plots. () Average read coverage over a 1,000-bp window (top, log scale), Velvet contigs (middle) and EULER+Velvet-SC contigs (bottom) mapped along the E. coli reference genome, with vertical staggering to help visualize small contigs. Contigs in blue or green match between the assemblies. Contigs in red or orange differ between the assemblies; they either have substantially different lengths, are broken into a different number of contigs, or are present in one assembly but missing in the other. * Figure 3: A 16S maximum likelihood tree of Deltaproteobacterial 16S sequences including SAR324_MDA (red). Sequences with species identification are from representative Deltaproteobacterial reference genomes in GenBank. The environmental 16S sequences (designated uncultured SAR324 or uncultured Deltaproteobacteria) were retrieved from GenBank based on their accession numbers (see Fig. S3 of ref. 30). The sequences were aligned using MOTHUR38. The tree was inferred using the nucleotide maximum likelihood feature of PAUP* 4.0b10 (ref. 39). Branches drawn in thick lines are clades with bootstrap support of 75% or greater. Scale at bottom of figure indicates the branch length associated with 0.1 substitutions per position. Sequences present on fosmids with extensive nucleotide similarity to the SAR324_MDA assembly are indicated (red star), as is a SAR324 fosmid (yellow star) encoding CoxL homologs also present in the SAR324_MDA assembly (Supplementary Fig. 13). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * AGAU00000000 * PRJNA71321 Sequence Read Archive * SRA043956 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Hamidreza Chitsaz & * Joyclyn L Yee-Greenbaum Affiliations * Department of Computer Science, University of California, San Diego, La Jolla, California, USA. * Hamidreza Chitsaz & * Pavel A Pevzner * J. Craig Venter Institute, San Diego, California, USA. * Joyclyn L Yee-Greenbaum, * Mary-Jane Lombardo, * Christopher L Dupont, * Jonathan H Badger, * Mark Novotny & * Roger S Lasken * Department of Mathematics, University of California, San Diego, La Jolla, California, USA. * Glenn Tesler * J. Craig Venter Institute, Rockville, Maryland, USA. * Douglas B Rusch * Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterfield, Nr Saffron Walden, Essex, UK. * Louise J Fraser, * Niall A Gormley, * Ole Schulz-Trieglaff, * Geoffrey P Smith & * Dirk J Evers Contributions All authors analyzed data. H.C. and G.T. wrote software. M.N., J.L.Y.-G., M.-J.L. and L.J.F. performed wet lab experiments. Illumina sequencing was performed at Illumina Cambridge Ltd. O.S.-T. analyzed sequencing data at Illumina. H.C., J.L.Y.-G., G.T., C.L.D., M.-J.L., L.J.F., N.A.G., P.A.P. and R.S.L. wrote the manuscript. H.C., G.T., M.-J.L., C.L.D., J.H.B., D.B.R. and N.A.G. created figures and tables. R.S.L. and M.-J.L. supervised the JCVI group. P.A.P. and G.T. supervised the UCSD group. N.A.G. and D.J.E. supervised the Illumina group. G.P.S. initiated the Illumina-JCVI collaboration. Competing financial interests L.J.F., N.A.G., O.S.-T., G.P.S. and D.J.E. are employees of Illumina, the commercial source of Illumina sequencing, which is evaluated in this manuscript. Corresponding author Correspondence to: * Roger S Lasken Author Details * Hamidreza Chitsaz Search for this author in: * NPG journals * PubMed * Google Scholar * Joyclyn L Yee-Greenbaum Search for this author in: * NPG journals * PubMed * Google Scholar * Glenn Tesler Search for this author in: * NPG journals * PubMed * Google Scholar * Mary-Jane Lombardo Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher L Dupont Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan H Badger Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Novotny Search for this author in: * NPG journals * PubMed * Google Scholar * Douglas B Rusch Search for this author in: * NPG journals * PubMed * Google Scholar * Louise J Fraser Search for this author in: * NPG journals * PubMed * Google Scholar * Niall A Gormley Search for this author in: * NPG journals * PubMed * Google Scholar * Ole Schulz-Trieglaff Search for this author in: * NPG journals * PubMed * Google Scholar * Geoffrey P Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Dirk J Evers Search for this author in: * NPG journals * PubMed * Google Scholar * Pavel A Pevzner Search for this author in: * NPG journals * PubMed * Google Scholar * Roger S Lasken Contact Roger S Lasken Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Tables 1–5, Supplementary Methods, Supplementary Data 3 and Supplementary Figures 1–13 Other * Supplementary Data 1 (4M) Velvet-SC source code * Supplementary Data 2 (135K) EULER-SR Error correction source code Additional data
• Comparative genomic analysis of the thermophilic biomass-degrading fungi Myceliophthora thermophila and Thielavia terrestris
  - Nat Biotechnol 29(10):922-927 (2011)
  Nature Biotechnology | Research | Article Comparative genomic analysis of the thermophilic biomass-degrading fungi Myceliophthora thermophila and Thielavia terrestris * Randy M Berka1, 15 * Igor V Grigoriev2, 15 * Robert Otillar2 * Asaf Salamov2 * Jane Grimwood3 * Ian Reid4 * Nadeeza Ishmael4 * Tricia John4 * Corinne Darmond4 * Marie-Claude Moisan4 * Bernard Henrissat5 * Pedro M Coutinho5 * Vincent Lombard5 * Donald O Natvig6 * Erika Lindquist2 * Jeremy Schmutz3 * Susan Lucas2 * Paul Harris1 * Justin Powlowski4 * Annie Bellemare4 * David Taylor4 * Gregory Butler4 * Ronald P de Vries7, 8 * Iris E Allijn7 * Joost van den Brink7 * Sophia Ushinsky4 * Reginald Storms4 * Amy J Powell9 * Ian T Paulsen10 * Liam D H Elbourne10 * Scott E Baker11 * Jon Magnuson11 * Sylvie LaBoissiere12 * A John Clutterbuck13 * Diego Martinez6, 14 * Mark Wogulis1 * Alfredo Lopez de Leon1 * Michael W Rey1 * Adrian Tsang4, 15 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:922–927Year published:(2011)DOI:doi:10.1038/nbt.1976Received16 May 2011Accepted18 August 2011Published online02 October 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 Thermostable enzymes and thermophilic cell factories may afford economic advantages in the production of many chemicals and biomass-based fuels. Here we describe and compare the genomes of two thermophilic fungi, Myceliophthora thermophila and Thielavia terrestris. To our knowledge, these genomes are the first described for thermophilic eukaryotes and the first complete telomere-to-telomere genomes for filamentous fungi. Genome analyses and experimental data suggest that both thermophiles are capable of hydrolyzing all major polysaccharides found in biomass. Examination of transcriptome data and secreted proteins suggests that the two fungi use shared approaches in the hydrolysis of cellulose and xylan but distinct mechanisms in pectin degradation. Characterization of the biomass-hydrolyzing activity of recombinant enzymes suggests that these organisms are highly efficient in biomass decomposition at both moderate and high temperatures. Furthermore, we present evidence sugge! sting that aside from representing a potential reservoir of thermostable enzymes, thermophilic fungi are amenable to manipulation using classical and molecular genetics. View full text Figures at a glance * Figure 1: Genome organization of M. thermophila and T. terrestris. The six chromosomes of T. terrestris are mapped to genomic regions from M. thermophila (shown as colored blocks in far-right lane). Only major synteny blocks are represented. For each T. terrestris chromosome, left-most lane shows G+C content, second lane from left shows repetitive elements and third lane from left shows regions with high gene density. * Figure 2: Analysis of transcription profiles. () Expression of CAZymes genes of the thermophiles cultured on glucose, alfalfa straw and barley straw. Gene activity is presented as percentage of total CAZymes gene activity of the three culture conditions of each organism. For the present analysis, cellulases include endoglucanases and cellobiohydrolases from GH5, GH6, GH7, GH12 and GH45; xylanases refer to GH10 and GH11 endoxylanases; arabinanases are endoarabinanases and arabinosidases from GH43, GH51 and GH62; mannanases are GH5 and GH26 endomannanases; and pectinases include polygalacturonases, rhamnogalacturonases, pectin lyases and pectin esterases from GH28, PL1, PL3, PL4, CE8 and CE12. () Transcript profiles of GH61 orthologs in M. thermophila and T. terrestris. The homologs of GH61 of M. thermophila and T. terrestris are organized in clades as shown in Supplementary Figure 6. Gene activity is presented as percentage of total CAZymes gene activity of the three culture conditions of each organism. Genes of several ! clades (e.g., K, O, R, S and T) are not upregulated in any of the growth conditions. None of the genes encoding GH61 proteins are upregulated during growth on glucose (Supplementary Tables 5–7). * Figure 3: Release of reducing sugars from alfalfa straw by crude extracellular enzymes from thermophilic and nonthermophilic fungi. The crude extracellular enzymes from the fungi cultured on alfalfa straw were used for hydrolysis. The hydrolysis reactions were performed at the temperatures indicated. The final protein concentrations in the reaction mixtures were: Chaetomium globosum, 439 μg/ml; Myceliophthora thermophila, 422 μg/ml; Thielavia terrestris, 362 μg/ml; and Trichoderma reesei, 524 μg/ml. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * CP003002 * CP003008 * CP003009 * CP003014 Gene Expression Omnibus * GSE27323 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Randy M Berka, * Igor V Grigoriev & * Adrian Tsang Affiliations * Novozymes, Inc., Davis, California, USA. * Randy M Berka, * Paul Harris, * Mark Wogulis, * Alfredo Lopez de Leon & * Michael W Rey * US Department of Energy Joint Genome Institute, Walnut Creek, California, USA. * Igor V Grigoriev, * Robert Otillar, * Asaf Salamov, * Erika Lindquist & * Susan Lucas * HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA. * Jane Grimwood & * Jeremy Schmutz * Centre for Structural and Functional Genomics, Concordia University, Montreal, Quebec, Canada. * Ian Reid, * Nadeeza Ishmael, * Tricia John, * Corinne Darmond, * Marie-Claude Moisan, * Justin Powlowski, * Annie Bellemare, * David Taylor, * Gregory Butler, * Sophia Ushinsky, * Reginald Storms & * Adrian Tsang * Architecture et Fonction des Macromolécules Biologiques, CNRS/Universités de Provence/Université de la Mediterranée, Marseille, France. * Bernard Henrissat, * Pedro M Coutinho & * Vincent Lombard * Department of Biology, University of New Mexico, Albuquerque, New Mexico, USA. * Donald O Natvig & * Diego Martinez * CBS-KNAW Fungal Biodiversity Centre, Utrecht, The Netherlands. * Ronald P de Vries, * Iris E Allijn & * Joost van den Brink * Microbiology and Kluyver Centre for Genomics of Industrial Fermentation, Utrecht University, Utrecht, The Netherlands. * Ronald P de Vries * Sandia National Laboratory, Albuquerque, New Mexico, USA. * Amy J Powell * Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia. * Ian T Paulsen & * Liam D H Elbourne * Fungal Biotechnology Team, Pacific Northwest National Laboratory, Richland, Washington, USA. * Scott E Baker & * Jon Magnuson * McGill University and Génome Québec Innovation Centre, Montreal, Canada. * Sylvie LaBoissiere * University of Glasgow, Glasgow, UK. * A John Clutterbuck * Present address: Broad Institute of MIT & Harvard, Cambridge, Massachusetts USA. * Diego Martinez Contributions The final text of the manuscript was written by R.M.B. and A.T., and reviewed by I.V.G.; who together also coordinated the overall analysis. I.V.G. coordinated both genome projects at the Joint Genome Institute. R.M.B. prepared the genomic DNA of T. terrestris and T.J. the DNA of M. thermophila. A.T. coordinated the transcriptome and exo-proteome work, and analyzed the transcriptomes. S.L. and E.L. led genome and cDNA sequencing. J.G. and J.S. finished and assembled both genomes. R.O. and A.S. annotated and analyzed the genomes, synteny and GC content. I.R. processed the RNA-Seq data and analyzed the cell wall proteins. N.I. coordinated the sample preparation for transcriptome analysis and analyzed the lignocellulolytic proteins. B.H., P.M.C. and V.L. performed the comparative analysis of the carbohydrate-active proteins. C.D. conducted the enzymatic hydrolysis of straws and M.-C.M. prepared the samples for transcriptome and exo-proteome analysis. D.O.N. analyzed the mating ! types and phylogeny of thermophilic fungi. E.L. coordinated the cDNA synthesis and EST analysis. A.B. coordinated the cloning and expression of xylanase genes. D.T. characterized the biochemical properties of the xylanases. R.P. de V., I.E.A, and J. van den B. examined the growth on different substrates. P.H. analyzed the GH61 proteins and J.P. membrane biogenesis. G.B. analyzed the secretomes. S.U. and R.S. analyzed the chromatin structure and dynamics. A.J.P. examined melanin pigment biogenesis. I.T.P. and L.D.H.E. analyzed transporters. S.E.B. analyzed secondary metabolism. J.M. examined oxidative stress. M.W. reviewed proteases and peptidases. S.L. examined the exo-proteomes. A.J.C. looked for repeat-induced polymorphisms. D.M. contributed computational tools for viewing T. terrestris transcriptome data. A.L.de L. and M.W.R. examined oxidoreductases and chitinases, respectively. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Adrian Tsang Author Details * Randy M Berka Search for this author in: * NPG journals * PubMed * Google Scholar * Igor V Grigoriev Search for this author in: * NPG journals * PubMed * Google Scholar * Robert Otillar Search for this author in: * NPG journals * PubMed * Google Scholar * Asaf Salamov Search for this author in: * NPG journals * PubMed * Google Scholar * Jane Grimwood Search for this author in: * NPG journals * PubMed * Google Scholar * Ian Reid Search for this author in: * NPG journals * PubMed * Google Scholar * Nadeeza Ishmael Search for this author in: * NPG journals * PubMed * Google Scholar * Tricia John Search for this author in: * NPG journals * PubMed * Google Scholar * Corinne Darmond Search for this author in: * NPG journals * PubMed * Google Scholar * Marie-Claude Moisan Search for this author in: * NPG journals * PubMed * Google Scholar * Bernard Henrissat Search for this author in: * NPG journals * PubMed * Google Scholar * Pedro M Coutinho Search for this author in: * NPG journals * PubMed * Google Scholar * Vincent Lombard Search for this author in: * NPG journals * PubMed * Google Scholar * Donald O Natvig Search for this author in: * NPG journals * PubMed * Google Scholar * Erika Lindquist Search for this author in: * NPG journals * PubMed * Google Scholar * Jeremy Schmutz Search for this author in: * NPG journals * PubMed * Google Scholar * Susan Lucas Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Harris Search for this author in: * NPG journals * PubMed * Google Scholar * Justin Powlowski Search for this author in: * NPG journals * PubMed * Google Scholar * Annie Bellemare Search for this author in: * NPG journals * PubMed * Google Scholar * David Taylor Search for this author in: * NPG journals * PubMed * Google Scholar * Gregory Butler Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald P de Vries Search for this author in: * NPG journals * PubMed * Google Scholar * Iris E Allijn Search for this author in: * NPG journals * PubMed * Google Scholar * Joost van den Brink Search for this author in: * NPG journals * PubMed * Google Scholar * Sophia Ushinsky Search for this author in: * NPG journals * PubMed * Google Scholar * Reginald Storms Search for this author in: * NPG journals * PubMed * Google Scholar * Amy J Powell Search for this author in: * NPG journals * PubMed * Google Scholar * Ian T Paulsen Search for this author in: * NPG journals * PubMed * Google Scholar * Liam D H Elbourne Search for this author in: * NPG journals * PubMed * Google Scholar * Scott E Baker Search for this author in: * NPG journals * PubMed * Google Scholar * Jon Magnuson Search for this author in: * NPG journals * PubMed * Google Scholar * Sylvie LaBoissiere Search for this author in: * NPG journals * PubMed * Google Scholar * A John Clutterbuck Search for this author in: * NPG journals * PubMed * Google Scholar * Diego Martinez Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Wogulis Search for this author in: * NPG journals * PubMed * Google Scholar * Alfredo Lopez de Leon Search for this author in: * NPG journals * PubMed * Google Scholar * Michael W Rey Search for this author in: * NPG journals * PubMed * Google Scholar * Adrian Tsang Contact Adrian Tsang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Tables 1–4, 10–22, Supplementary Methods, Supplementary Notes and Supplementary Figures 1–9 Excel files * Supplementary Tables (556K) Supplementary Tables 5–9, and 23–25 Additional data
• Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding
  - Nat Biotechnol 29(10):928-933 (2011)
  Nature Biotechnology | Research | Article Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding * Rong Lu1 * Norma F Neff2 * Stephen R Quake2 * Irving L Weissman1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:928–933Year published:(2011)DOI:doi:10.1038/nbt.1977Received02 May 2011Accepted19 August 2011Published online02 October 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 Disentangling cellular heterogeneity is a challenge in many fields, particularly in the stem cell and cancer biology fields. Here we demonstrate how to combine viral genetic barcoding with high-throughput sequencing to track single cells in a heterogeneous population. We use this technique to track the in vivo differentiation of unitary hematopoietic stem cells (HSCs). The results are consistent with single-cell transplantation studies but require two orders of magnitude fewer mice. In addition to its high throughput, the high sensitivity of the technique allows for a direct examination of the clonality of sparse cell populations such as HSCs. We show how these capabilities offer a clonal perspective of the HSC differentiation process. In particular, our data suggest that HSCs do not equally contribute to blood cells after irradiation-mediated transplantation, and that two distinct HSC differentiation patterns co-exist in the same recipient mouse after irradiation. This tech! nique can be applied to any virus-accessible cell type for both in vitro and in vivo processes. View full text Figures at a glance * Figure 1: Experimental workflow. A DNA barcode consists of a common 6-bp library ID at the 5′ end followed by a random 27-bp cellular barcode. In the figure, different colors represent different barcode sequences. A lentiviral vector delivers a large library of barcodes into a small number of cells such that each cell receives a unique barcode. Barcodes replicate with the cells in the recipient mice after transplantation. Afterwards, the progeny of the donor cells are harvested. Barcodes are recovered from the genomic DNA using PCR and analyzed using high-throughput sequencing (Illumina GA II). The 6-bp library ID helps to identify barcodes in the sequencing result. Identical 33-bp barcodes are combined allowing for mismatches and indels up to 2 bp in total. The barcodes are then compared across different cell populations that originate from the same starting cell population. * Figure 2: DNA barcode library and delivery. () Barcode copy numbers from a lentiviral library. Additional lentiviral libraries are shown in Supplementary Figure 1, together with the negative controls demonstrating the level of background noise for this experiment. () Histogram showing the number of barcode(s) that each HSC clone received after infection. Ninety-five HSC clones were examined in total. This distribution fits a normal distribution shown in Supplementary Figure 3. () Monte Carlo simulation of the null hypothesis that >95% of the barcodes represent single cells. The P value is plotted against the size of the cell population whose barcodes are recovered in the result. * Figure 3: Background noise sequences. () Background noise sequences without the expected 6-bp library IDs. Sequences with identical 6 bp at the 5′ end are clustered. Mock barcode libraries are constructed from clustered sequences whose initial 6 bp are not among the expected library IDs. Mock barcodes from 20 mock barcode libraries are plotted as one line to demonstrate their copy number distribution. Different lines display the mock barcode libraries with different sizes. () Log-scale plot of barcode copy numbers in HSCs and in B cells from one irradiated mouse transplanted with 1,000 donor HSCs. Each dot represents a distinct barcode. Barcodes with copy numbers <1,000 appear randomly in the two cell populations whereas barcodes with copy numbers >10,000 form a distinct pattern. Red lines illustrate background thresholds as calculated by our algorithm. * Figure 4: Lineage bias of HSC differentiation after irradiation. Triangle plots8 show the relative proportion of barcodes in granulocytes (Gr), B cells (B) and CD4+ T cells (CD4T) 22 weeks after lethal irradiation–mediated transplantation. Each dot within the triangle represents a distinct barcode. Bigger and darker dots represent more abundant barcodes. The distance of a dot to the three vertices of the triangle is inversely correlated with the relative abundance of the barcode within the particular cell populations. For example, if a barcode is only found in one cell population, the dot is plotted at the corresponding vertex; if a barcode appears equally in all three populations, the dot is plotted in the middle of the triangle. () Barcodes from seven mice are plotted in one triangle. The barcodes from each mouse are represented by a particular shape: circle, square, triangle pointing up, triangle pointing down, diamond, pentagon and octagon. () Each triangle plot depicts a single mouse. Distinct barcode groups are highlighted with bl! ue and orange ellipses. Plots for all the seven mice are shown in Supplementary Figure 7. * Figure 5: Clonal correlations of hematopoietic populations. Pearson correlation coefficients of barcode representations (copy numbers) are calculated to quantify the clonal correlations. The colors are assigned based on the mean correlations from seven mice. Raw data for individual mouse are shown in Supplementary Table 4. () Clonal correlations of extracted hematopoietic populations. () Clonal correlations of the hematopoietic populations compared with HSCs. () Clonal correlations of the hematopoietic populations compared with granulocyte/monocytic progenitor (GMP). Pearson correlations coefficient values are labeled for MEP and CLP to highlight the difference. (,) The circles and arrows are arranged based on the general model of hematopoiesis to depict the developmental relationships of the hematopoietic populations4, 5, 24, 46, 47. HSC, hematopoietic stem cell; MPP/Flk2−, Flk2− multipotent progenitor; MPP/Flk2+, Flk2+ multipotent progenitor; GMP, granulocyte/monocytic progenitor; MEP, megakaryotic/erythroid progenitor; CLP, co! mmon lymphocyte progenitor; Gr, granulocyte; B, B cell; CD4T, CD4+ T cells; CD8T, CD8+ T cells. Author information * Abstract * Author information * Supplementary information Affiliations * Institute for Stem Cell Biology and Regenerative Medicine and the Ludwig Center, School of Medicine, Stanford University, Stanford, California, USA. * Rong Lu & * Irving L Weissman * Department of Bioengineering and Howard Hughes Medical Institute, Stanford University, Stanford, California, USA. * Norma F Neff & * Stephen R Quake Contributions R.L. and I.L.W. designed the experiments. R.L. performed the experiments. N.F.N. and S.R.Q. set up and carried out the high-throughput sequencing. R.L. analyzed the data and wrote the manuscript. All authors edited the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Rong Lu or * Irving L Weissman Author Details * Rong Lu Contact Rong Lu Search for this author in: * NPG journals * PubMed * Google Scholar * Norma F Neff Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen R Quake 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 Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Tables 1–4 and Supplementary Figures 1–7 Zip files * Supplementary Data (765K) Additional data
• CD140a identifies a population of highly myelinogenic, migration-competent and efficiently engrafting human oligodendrocyte progenitor cells
  - Nat Biotechnol 29(10):934-941 (2011)
  Nature Biotechnology | Research | Article CD140a identifies a population of highly myelinogenic, migration-competent and efficiently engrafting human oligodendrocyte progenitor cells * Fraser J Sim1, 2, 3 * Crystal R McClain1 * Steven J Schanz1 * Tricia L Protack1 * Martha S Windrem1 * Steven A Goldman1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:934–941Year published:(2011)DOI:doi:10.1038/nbt.1972Received22 February 2011Accepted11 August 2011Published online25 September 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 Experimental animals with myelin disorders can be treated by transplanting oligodendrocyte progenitor cells (OPCs) into the affected brain or spinal cord. OPCs have been isolated by their expression of gangliosides recognized by mAb A2B5, but this marker also identifies lineage-restricted astrocytes and immature neurons. To establish a more efficient means of isolating myelinogenic OPCs, we sorted fetal human forebrain cells for CD140a, an epitope of platelet derived growth factor receptor (PDGFR)α, which is differentially expressed by OPCs. CD140a+ cells were isolated as mitotic bipotential progenitors that initially expressed neither mature neuronal nor astrocytic phenotypic markers, yet could be instructed to either oligodendrocyte or astrocyte fate in vitro. Transplanted CD140a+ cells were highly migratory and robustly myelinated the hypomyelinated shiverer mouse brain more rapidly and efficiently than did A2B5+cells. Microarray analysis of CD140a+ cells revealed overex! pression of the oligodendroglial marker CD9, suggesting that CD9+/CD140a+ cells may constitute an even more highly enriched population of myelinogenic progenitor cells. View full text Figures at a glance * Figure 1: CD140a/PDGFRα identifies a proliferating OPC in fetal cortex and intermediate zone. CD140a+ cells were found in the cortical mantle of 22 week g.a. human fetal brain. () All identifiable CD140a+ cell bodies co-expressed the oligodendrocyte lineage transcription factor OLIG2. () Consistent with an early neural progenitor phenotype, CD140a+ cells within the intermediate zone co-expressed the progenitor-expressed transcription factor SOX2. () A proportion of CD140a+ cells co-labeled with KI67 antibody, a marker of cells in active cell cycle. The main panel shows a confocal z-stack (CD140a, red; KI67, green); the inset shows fluorophore-specific single optical sections of the imaged cell. () A low-power schematic reconstruction of the distribution of CD140a+ cells in a section of 18 week g.a. forebrain, showing the broad dispersal of these cells through the intermediate zone and cortical mantle. CTX, cortex; IZ, intermediate zone; VZ, ventricular zone. Scale bar, 20 μm. * Figure 2: CD140a/PDGFRα recognizes a population of cells in the fetal brain that accumulates with gestational age in the intermediate zone and cortex. Flow cytometry was used to determine the relative abundance of CD140+ cells in the fetal human germinal zones and overlying intermediate zone and cortex. (–) Typical CD140a cytometry of a 21 week g.a. fetal cortical/intermediate zone dissociate. Limited nonspecific staining using a phycoerythrin (PE)-conjugated isotype control (); the same dissociate stained using PE-conjugated anti-CD140a. CD140a+ cells were uncommon in the second trimester intermediate zone and cortex before 16 weeks g.a. (); their incidence increased thereafter with gestational age (n = 29) (). () In contrast, the incidence of CD140a+ cells remained relatively constant throughout the second trimester in the VZ/SVZ (n = 10). () A superimposition of all CD140a incidence data, as multiple regression lines, including whole forebrain as well as dissected VZ/SVZ and intermediate zone/cortex. * Figure 3: CD140a/A2B5/PSA-NCAM cytometry. Fetal dissociates were immunomagnetically selected on the basis of PSA-NCAM antigenicity. (–) PSA-NCAM− cells were subject to two-color FACS for CD140a and A2B5 using PE- and allophycocyanin (APC)-conjugated antibodies, respectively. Positive selection gates were defined using fluorescence-minus-one controls by substitution of either CD140a () or A2B5 () antibodies with a matched isotype control–conjugated antibody. A2B5 and CD140a/PDGFRα-specific antibodies were combined in . A large proportion of CD140a+ cells co-expressed A2B5 (). () The proportion of CD140a+/PDGFRα+ cells in each A2B5/PSA-NCAM sorted fractions (n = 4, 19–22 weeks g.a.). The PSA-NCAM−/A2B5+ fraction contained significantly more CD140a+ cells than unsorted dissociate (one-way ANOVA followed by Dunnett's multiple comparison test, *P < 0.05). () Each sorted fraction was cultured in T3/0.5% PD-FBS media for 7 d and assessed for the immature oligodendrocyte antigen O4. CD140a+ cells from each A2B5/! PSA-NCAM fraction gave rise to a higher proportion of O4+ oligodendrocytes than matched CD140a− cells (n = 3 samples). Error bars indicate s.e.m. * Figure 4: CD140a+ cells mature primarily as oligodendrocytes but can be maintained as bipotential progenitors. Sorted CD140a+ cells were plated onto substrate and allowed to differentiate after removal of the exogenous growth factors PDGF AA and FGF2. () By 4 d after FACS, cells showed the characteristic morphology of immature oligodendrocytes and expressed the sulfatide antigen O4. () The proportion of O4+ oligodendrocytes was determined at 4 d in vitro, after removal of PDGF AA and FGF2. Virtually no O4-defined oligodendrocytes were found in CD140a− cultures; in contrast, ~40% of CD140a+ cells expressed O4 by that point. () 7 d post-sort some oligodendrocytes had matured further, with elaborate oligodendrocyte profiles stained with O1 antibody. () CD140a+/PDGFRα+ cells were cultured for 7 d in the presence of PDGF-AA and FGF-2 (20 ng/ml each), then immunophenotyped. Under these conditions, CD140a+ cells continued to express A2B5, whereas <10% expressed O4. In contrast, the CD140a−/PDGFRα− fraction comprised primarily βIII-tubulin+ neurons. Scale bars, 10 μm. Error bars in! dicate s.e.m. ***, P < 0.001; **P < 0.01 (two-tailed t-test). * Figure 5: CD140a+ cells efficiently myelinate shiverer axons. Human fetal CD140a+ OPCs were transplanted into the hypomyelinated forebrain of immunosuppressed shiverer mice. () At 8 weeks after injection, a fraction of human cells recognized by anti-human nuclear antigen (hNA) had differentiated into myelinating oligodendrocytes expressing the myelin protein gene MBP. (,) Consistent with the time course of human myelination, a large proportion of transplanted human CD140a+ cells (red) remained as NG2-expressing OPCs at 8 weeks after implantation (), whereas a minor fraction differentiated as astrocytes, as immunolabeled by GFAP (). () Quantification of human CD140a+ cell fate, at 8 weeks after implantation (n = 3). Scale bars, 20 μm. Error bars indicate s.e.m. * Figure 6: CD140a+ OPCs myelinate more effectively compared with A2B5+ OPCs. () Computer-assisted drawings of 14-μm sections taken at 0.67-mm intervals throughout the forebrain of a 12-week-old shiverer × rag2-null mouse, transplanted bilaterally in the corpus callosum with 100,000 CD140a+ cells. Each red dot represents an individual cell labeled with anti-human nuclear antigen. () The corpus callosum of an engrafted shiverer mouse at 12 weeks, stained for MBP, showing substantial donor-derived myelin. () A photomicrograph of the corpus callosum and fimbria in another engrafted mouse. () An individual oligodendrocyte, stained for anti-human nuclear antigen (red). (,) Ensheathment of host mouse axons (neurofilament, green) at 12 weeks by CD140a+ () or A2B5+ () human fetal cells, showing the more rapid and robust axonal myelination by CD140a+ cells. (,) Sections of a CD140a+ cell–engrafted shiverer callosum at 12 weeks, immunostained for MBP, human GFAP and human nuclear antigen, showing robust production of hGFAP+ astrocytes as well as MBP+ oligod! endrocytes. Scale bars: , 500 μm; , 200 μm; , 10 μm; ,, 20 μm. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE29368 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA. * Fraser J Sim, * Crystal R McClain, * Steven J Schanz, * Tricia L Protack, * Martha S Windrem & * Steven A Goldman * Department of Neurosurgery, University of Rochester Medical Center, Rochester, New York, USA. * Fraser J Sim & * Steven A Goldman * Department of Pharmacology, State University of New York at Buffalo, Buffalo, New York, USA. * Fraser J Sim Contributions F.J.S. directed both the in vitro experiments and genomics analysis; C.M. planned and performed the in vitro studies with F.J.S., and conducted the assessment of OPC ontogeny; S.S. performed the transplants of A2B5+ and CD140+ cells into shiverer mice; T.L.P. assisted F.J.S. and C.M. in the in vitro studies and FACS analysis; M.S.W. directed the comparative assessment of myelination by A2B5 and CD140a cells in vivo; S.A.G. co-designed the experiments, co-analyzed the data with F.J.S. and M.S.W. and wrote the paper together with the co-authors. Competing financial interests S.A.G. and F.J.S. have a patent application pending on the use of CD140a-sorted oligodendrocyte progenitor cells in therapeutic remyelination. Corresponding authors Correspondence to: * Fraser J Sim or * Steven A Goldman Author Details * Fraser J Sim Contact Fraser J Sim Search for this author in: * NPG journals * PubMed * Google Scholar * Crystal R McClain Search for this author in: * NPG journals * PubMed * Google Scholar * Steven J Schanz Search for this author in: * NPG journals * PubMed * Google Scholar * Tricia L Protack Search for this author in: * NPG journals * PubMed * Google Scholar * Martha S Windrem Search for this author in: * NPG journals * PubMed * Google Scholar * Steven A Goldman Contact Steven A Goldman Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (14M) Supplementary Tables 1–3 and Supplementary Figs. 1–5 Additional data
• A reversibly photoswitchable GFP-like protein with fluorescence excitation decoupled from switching
  - Nat Biotechnol 29(10):942-947 (2011)
  Nature Biotechnology | Research | Article A reversibly photoswitchable GFP-like protein with fluorescence excitation decoupled from switching * Tanja Brakemann1, 6 * Andre C Stiel1, 6 * Gert Weber2 * Martin Andresen1 * Ilaria Testa1 * Tim Grotjohann1 * Marcel Leutenegger1 * Uwe Plessmann3 * Henning Urlaub3, 4 * Christian Eggeling1 * Markus C Wahl2 * Stefan W Hell1 * Stefan Jakobs1, 5 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:942–947Year published:(2011)DOI:doi:10.1038/nbt.1952Received12 April 2011Accepted20 July 2011Published online11 September 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 Photoswitchable fluorescent proteins have enabled new approaches for imaging cells, but their utility has been limited either because they cannot be switched repeatedly or because the wavelengths for switching and fluorescence imaging are strictly coupled. We report a bright, monomeric, reversibly photoswitchable variant of GFP, Dreiklang, whose fluorescence excitation spectrum is decoupled from that for optical switching. Reversible on-and-off switching in living cells is accomplished at illumination wavelengths of ~365 nm and ~405 nm, respectively, whereas fluorescence is elicited at ~515 nm. Mass spectrometry and high-resolution crystallographic analysis of the same protein crystal in the photoswitched on- and off-states demonstrate that switching is based on a reversible hydration/dehydration reaction that modifies the chromophore. The switching properties of Dreiklang enable far-field fluorescence nanoscopy in living mammalian cells using both a coordinate-targeted and ! a stochastic single molecule switching approach. View full text Figures at a glance * Figure 1: Properties of Dreiklang. () Scheme depicting Dreiklang's switching modality. () Normalized absorbance (solid black line), fluorescence emission (dashed green line) and fluorescence excitation (dotted red line) spectra of the (fluorescent) equilibrium-state Dreiklang at pH 7.5. (,) Switching curves of Dreiklang's fluorescence recorded on colonies of living E. coli. Off- and on-switching was performed with near-UV (405 nm) and UV light (365 nm), respectively, and fluorescence read-out with green light (515 nm). The respective irradiation scheme is indicated on top of the graphs by the colored bars. () One switching cycle. Fluorescence was continuously recorded. () Twenty consecutive switching cycles. Fluorescence was recorded when the cells were irradiated with green light only. () Irradiation-dependent changes in Dreiklang absorbance. Absorbance spectra obtained at the indicated time points during switching of equilibrium-state Dreiklang (pH 7.5) into the off-state by irradiation with 405 nm. () Irra! diation-independent changes in Dreiklang fluorescence due to the thermal equilibration from the off-state into the fluorescent equilibrium state. After off-switching, fluorescence was recorded at 25 °C under constant irradiation with 515 nm (black line) or by consecutive 20-ms pulses of 515 nm light in 60 s intervals (red dots). The similar curves demonstrate that 515 nm light does not photoswitch Dreiklang. Inset: relaxation half-time from the off- into the equilibrium-state as a function of temperature. The data were obtained on purified Dreiklang (pH 7.5) (circles) or on living cells expressing Dreiklang targeted to the ER (squares). Red line: single exponential fit to the data obtained on purified protein. * Figure 2: Molecular basis of Dreiklang photoswitching. () Dreiklang in the fluorescent equilibrium-state (top), the nonfluorescent off-state (middle) and the fluorescent on-state (bottom). Left, top: representative Dreiklang protein crystal. Left, bottom: proposed chemical structure of the chromophore. Central: details of the X-ray structures (PDB IDs: 3ST2, 3ST3, 3ST4, respectively, top to bottom). Shown is the chromophore (carbon, magenta/gray; oxygen, red; nitrogen, blue). In the equilibrium-state and the on-state, water Wata (magenta sphere) is additionally displayed. Final 2Fo–Fc electron densities are contoured at the 1σ level. The off-state and the on-state structures have been successively recorded on the same protein crystal. Right: representative deconvoluted ESI-MS spectra of Dreiklang photoswitched in solution and measured under native conditions. () Overall Dreiklang ribbon structure displayed in two orthogonal views. () Chromophore and immediate surrounding of on-state Dreiklang (magenta) and GFP (PDB: 1EMA25) (! cyan). The Van-der-Waals' radii of important atoms are indicated by spheres to highlight structural restraints. The chromophores are depicted as ball and stick whereas the surrounding amino acid residues are shown in the stick representation. () Superimposed representations of the Dreiklang hydrogen bond network in the (fluorescent) equilibrium- and the off-states. Equilibrium-state carbons, magenta; off-state carbons, gray; oxygen, red; nitrogen, blue. Important water molecules are shown as magenta (equilibrium-state) and gray (off-state) spheres. Inset: hydrogen bond network in GFP. * Figure 3: Applications of Dreiklang. () 'PacMan' movie. Thirty-three individual images were written successively at the same position of a polyacrylamide-Dreiklang layer. Before writing each new frame, all molecules were photoswitched to the on-state. Shown are the first and the thirty-third frame (see also Supplementary Movie 1). Scale bar, 100 μm. () Switching of various Dreiklang fusion proteins in living Vero cells (from left to right, on, off, etc.). From top to bottom: Dreiklang-MAP2, Dreiklang-α-tubulin, mito-Dreiklang, Dreiklang-Histone2B. Fluorescence was excited with green light (495 nm); switch-off (light blue arrowheads): near-UV (420 nm); switch-on (violet arrowheads): UV-light (360 nm). () FRAS with Dreiklang. Dreiklang was targeted to the ER in living Vero cells. Images from top to bottom: overview; before switching; immediately after switching Dreiklang off in region of interest (ROI)-i; and at the end of the measurement (65 s after switching). Graphs on the right: the plotted fluorescence sig! nals were collected within the indicated ROIs during 20 repetitions of the same FRAS experiment on a single cell (ROI-i: in this region Dreiklang was selectively switched off prior to the measurement; ROI-ii: in the same cell, showing the flow of switched-off Dreiklang molecules into this region; ROI-iii: in the neighboring cell). Shown are raw data. The red line marks the mean values at each time point, demonstrating the reduction of statistical noise. Scale bars in and , 10 μm. * Figure 4: Super-resolution microscopy of living PtK2 cells using Dreiklang. () Cells expressing Dreiklang-Map2 imaged both conventionally (left) and by super-resolution microscopy based on single-molecule stochastic switching (center). () Keratin19-Dreiklang expressed in living cells and imaged both confocally (left) and in the RESOLFT mode (spatially targeted switching) (center). Right: magnifications of the regions indicated in the main images. Scale bars, 1 μm (middle, left), 250 nm (right). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Protein Data Bank * 3ST2 * 3ST3 * 3ST4 * 3ST2 * 3ST3 * 3ST4 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Tanja Brakemann & * Andre C Stiel Affiliations * Max Planck Institute for Biophysical Chemistry, Department of NanoBiophotonics, Göttingen, Germany. * Tanja Brakemann, * Andre C Stiel, * Martin Andresen, * Ilaria Testa, * Tim Grotjohann, * Marcel Leutenegger, * Christian Eggeling, * Stefan W Hell & * Stefan Jakobs * Freie Universität Berlin, Institut für Chemie und Biochemie, AG Strukturbiochemie, Berlin, Germany. * Gert Weber & * Markus C Wahl * Max Planck Institute for Biophysical Chemistry, Bioanalytical Mass Spectrometry, Göttingen, Germany. * Uwe Plessmann & * Henning Urlaub * University Medical Center Göttingen, Department of Clinical Chemistry, Bioanalytics, Göttingen, Germany. * Henning Urlaub * University of Göttingen Medical School, Göttingen, Germany. * Stefan Jakobs Contributions G.W., M.A. and I.T. contributed equally to this work. C.E., S.W.H. and S.J. conceived the project. T.B., A.C.S., G.W., M.A., I.T., T.G., M.L. and U.P. performed all experiments. I.T. recorded the super-resolution images. Data analysis was done by T.B., A.C.S., G.W., M.A., I.T., T.G., M.L., H.U., C.E., M.C.W., S.W.H. and S.J. The manuscript was written by S.W.H. and S.J. All authors discussed the results and commented on the manuscript. Competing financial interests A patent application concerning the protein Dreiklang has been filed. Corresponding authors Correspondence to: * Stefan W Hell or * Stefan Jakobs Author Details * Tanja Brakemann Search for this author in: * NPG journals * PubMed * Google Scholar * Andre C Stiel Search for this author in: * NPG journals * PubMed * Google Scholar * Gert Weber Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Andresen Search for this author in: * NPG journals * PubMed * Google Scholar * Ilaria Testa Search for this author in: * NPG journals * PubMed * Google Scholar * Tim Grotjohann Search for this author in: * NPG journals * PubMed * Google Scholar * Marcel Leutenegger Search for this author in: * NPG journals * PubMed * Google Scholar * Uwe Plessmann Search for this author in: * NPG journals * PubMed * Google Scholar * Henning Urlaub Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Eggeling Search for this author in: * NPG journals * PubMed * Google Scholar * Markus C Wahl Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan W Hell Contact Stefan W Hell Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Jakobs Contact Stefan Jakobs Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Tables 1,2 and Supplementary and Figures 1–17 Movies * Supplementary Movie 1 (1.4M) Animated sequence of 33 individual images as shown in Figure 3a. * Supplementary Movie 2 (14M) Animated sequence of 100 consecutive switching cycles of vimentin-Dreiklang in PtK2 cells, as shown in Supplementary Figure 13. Additional data
• A global need for women's biotech leadership
  - Nat Biotechnol 29(10):948-949 (2011)
  Nature Biotechnology | Careers and Recruitment A global need for women's biotech leadership * Laurel Smith-Doerr1 * Gintare Kemekliene2 * Rita Teutonico3 * Lene Lange4 * Lydia Villa-Komaroff5 * Line Matthiessen-Guyader2 * Fiona Murray6 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:948–949Year published:(2011)DOI:doi:10.1038/nbt.1998Published online13 October 2011 Increasing women's participation in leadership of biotech policy making, funding, research and implementation will strengthen the race to solve global problems. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Laurel Smith-Doerr is at Boston University, Department of Sociology, Boston, Massachusetts, USA; * Gintare Kemekliene and Line Matthiessen-Guyader are at the European Commission—DG Research, Brussels, Belgium; * Rita Teutonico is at the National Science Foundation, Directorate for Social, Behavioral and Economic Sciences, Arlington, Virginia, USA; * Lene Lange is at the Copenhagen Institute of Technology, Aalborg University, Ballerup, Denmark; * Lydia Villa-Komaroff is at CytonomeST, Boston, Massachusetts, USA; * Fiona Murray is at the MIT Sloan School of Management, Cambridge, Massachusetts, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Laurel Smith-Doerr Author Details * Laurel Smith-Doerr Contact Laurel Smith-Doerr Search for this author in: * NPG journals * PubMed * Google Scholar * Gintare Kemekliene Search for this author in: * NPG journals * PubMed * Google Scholar * Rita Teutonico Search for this author in: * NPG journals * PubMed * Google Scholar * Lene Lange Search for this author in: * NPG journals * PubMed * Google Scholar * Lydia Villa-Komaroff Search for this author in: * NPG journals * PubMed * Google Scholar * Line Matthiessen-Guyader Search for this author in: * NPG journals * PubMed * Google Scholar * Fiona Murray Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• People
  - Nat Biotechnol 29(10):950 (2011)
  Article preview View full access options Nature Biotechnology | Careers and Recruitment | People People Journal name:Nature BiotechnologyVolume: 29,Page:950Year published:(2011)DOI:doi:10.1038/nbt.2006Published online13 October 2011 (right) will leave his position as founding executive director of the Genome Institute of Singapore to become president and CEO of The Jackson Laboratory (Bar Harbor, ME, USA) as of January 2012. He succeeds , who departs for the National Institute of Environmental Health Sciences where he will serve as deputy director. Formerly scientific director of the National Cancer Institute's division of clinical sciences, Liu was recruited to run GIS in 2001. He is also a two-term president of the Human Genome Organization. Leo Holt, chair of The Jackson Laboratory board of trustees said, "The Jackson Laboratory is a dynamic pivot point at the intersection of mammalian and human genetics. [Ed Liu's] talents run broad and deep, and his leadership is a great addition to the team that leads the search for tomorrow's cures." has been appointed chairman and CEO, and has been named president and chief administrative officer of Neurologix (Fort Lee, NJ, USA). Both Adams and Koven also join the company's board of directors, with Adams assuming the role of chairman. Previously, Adams served as president and CEO of Inspire Pharmaceuticals and Sepracor. Acorda Therapeutics (Hawthorne, NY, USA) has named as chief medical officer, succeeding . Carrazana has over 20 years of experience in the pharma industry and clinical practice. Most recently, he was director of the Epilepsy Center of Excellence at the Miami Veterans' Administration Hospital and associate professor of neurology at the University of Miami Miller School of Medicine. Prior to this, he held various leadership roles at Novartis, including vice president, global head of the established medicines development franchise. Silence Therapeutics (London) has announced the appointment of as CEO. Christély is a 20-year veteran of corporate and business development and finance, having served as CFO, COO and CEO of Atugen and senior vice president and CFO at OXO Chemie. He currently serves as nonexecutive chairman of the supervisory board of Müller-Spreer. He will be based at Silence's facility in Berlin. The Biotechnology Industry Organization (Washington) has selected as senior vice president, international affairs. He previously served as deputy vice president, international affairs at the Pharmaceutical Research & Manufacturers of America and as deputy assistant for the Asia-Pacific region in the Office of the US Trade Representative. XOMA (Berkeley, CA, USA) has announced the resignation of as CEO, president and chairman of the board. , a current board member, has been appointed as interim CEO. He has previously served as COO and CFO of Aryx Therapeutics and CFO of Genset. A search has been initiated for a permanent CEO. In addition, , XOMA's lead independent director, has been named chairman of the board. Five Prime Therapeutics (S. San Francisco, CA, USA) has announced the election of to its board of directors. Jensen most recently served as corporate senior vice president and general manager, R&D for Japan and Asia/Pacific at Schering-Plough. He currently serves on the boards of Acorda Therapeutics and BioCryst Pharmaceuticals. has been appointed as CEO and a member of the board of directors of Myrexis (Salt Lake City, UT, USA). He joined the company in February 2009 as CFO and treasurer, rising to the position of interim president and CEO. Previously, he was president and CEO of Iomed. Additionally, Myrexis has named as CFO. She had served as vice president, finance and human resources since June 2010. OXiGENE (S. San Francisco, CA, USA) has announced the appointment of and the impending retirements of and from its board of directors. McMahon currently serves as senior vice president of R&D and head of the oncology innovative medicines unit for AstraZeneca. He has held various roles at Pfizer, Pharmacia, Sandoz and SUGEN. Shiebler and Kessel will serve the remainder of their current terms on the board but will not stand for reelection at OXiGENE's annual stockholder meeting this Fall. Thrasos (Montreal) has announced the appointment of as chief medical officer. Orfanos has over 25 years of experience in strategy development and executive and operational management in the healthcare industry, as a principal in his own consulting firm and as executive vice president, strategic planning and scientific affairs at Neurochem. Orion Genomics (St. Louis) has named vice president of bioinformatics. Smith brings over 20 years of experience in the biotech and bioinformatics field, most recently as head of consulting firm Genesmith Informatics. He previously served as vice president of bioinformatics at NimbleGen Systems and has worked at Millipore, Genetics Computer Group and the Harvard Genome Laboratory. 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