Hot off the presses! Mar 01 Nat Biotech

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Latest Articles Include:

• Realigning interests
  - Nat Biotech 29(3):171 (2011)
  Nature Biotechnology | Editorial Realigning interests Journal name:Nature BiotechnologyVolume: 29,Page:171Year published:(2011)DOI:doi:10.1038/nbt.1829Published online09 March 2011 Fifteen years after Nature Biotechnology was launched, the old paradigms in life science commercialization are no longer tenable. It's time to realign the interests of companies, patients and payors so that innovation is prioritized. View full text Additional data
• Fate of novel painkiller mAbs hangs in balance
  - Nat Biotech 29(3):173-174 (2011)
  Nature Biotechnology | News Fate of novel painkiller mAbs hangs in balance * Ken Garber1Journal name:Nature BiotechnologyVolume: 29,Pages:173–174Year published:(2011)DOI:doi:10.1038/nbt0311-173Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Targeting pain with anti-nerve growth factor antibodies. Inflammation produces several inflammatory factors, most notably nerve growth factor, which sensitize nerve cells by acting on their cognate receptors and activating signal transduction. These activated pathways phosphorylate transient receptor potential (TRP) channels, which alter their trafficking and reduce the membrane's threshold, resulting in an increased excitability of pain neurons. Image courtesy of Nat. Rev. Drug. Disc. (, 55–56, 2009). A major new class of pain medications suffered a severe setback in December when the US Food and Drug Administration (FDA) placed a hold on most clinical trials for experimental therapies targeting nerve growth factor (NGF). These biologics were poised to be the first important new class of drugs for general pain since the prototype non-steroidal anti-inflammatory drug (NSAID), aspirin, came into general use at the end of the nineteenth century. "We've had over a hundred years without having really a major new pain drug," says Thomas Schnitzer, a professor of medicine at Northwestern University in Chicago. With this latest stumbling block, the fate of anti-NGF painkillers hangs in the balance. New York–based Pfizer leads the quest for novel painkillers with tanezumab (PF-4383119), a humanized monoclonal antibody (mAb) that blocks NGF. Preclinical models of pain suggest that this mAb is equally or more efficacious than opiates or NSAIDs. Tanezumab was originally discovered by Genentech spin-off Rinat of South San Francisco. The antibody passed to Pfizer in 2006 when the pharma giant acquired Rinat. But tanezumab's steady progress faltered last summer when some individuals in phase 3 osteoarthritis trials developed cases of joint damage. Sixteen of them needed surgery to replace joints when they developed progressively worsening osteoarthritis with evidence of bone necrosis inferred from radiographic images. The FDA responded by placing on hold phase 3 trials testing Pfizer's NGF inhibitor in osteoarthritis and some other pain indications in June and July. Then in December, an additional case of joint failure cropped up, suggesting problems with the entire class of drugs. The FDA did not release information on which drug caused the additional case, yet it still decided to extend the hold to other companies developing competing NGF-targeting antibodies (Table 1). Table 1: Selected anti-NGF antibodies in clinical development for pain Full table But according to insiders, anti-NGF antibodies are far from dead. Pfizer's tanezumab phase 3 studies involved >10,000 patients, with four trials now complete. And though at least six other trials have been terminated, the company is not yet giving up. "From Pfizer's perspective, no causal relationship has been established between tanezumab and the reported adverse events," says company spokesperson MacKay Jimeson. Pfizer's phase 2 trials in cancer pain have been allowed to proceed. Other companies investing in NGF painkillers are also cautiously optimistic. "We plan to continue working with the regulators, such as the FDA, to try to understand whether and where there is sufficient risk-benefit ratio for this class of drugs to be used," says George Yancopoulos, CSO of Regeneron of Tarrytown, New York. "And whether there really is any class effect that might be causing these problems." Regeneron has brought its anti-NGF antibody REGN475/SAR164877, generated using t! he company's VelocImmune technology (mice in which the murine variable regions have been replaced with their human heavy and light chain counterparts), into phase 2 trials, in partnership with Sanofi-aventis of Paris. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Ann Arbor, Michigan * Ken Garber Author Details * Ken Garber Search for this author in: * NPG journals * PubMed * Google Scholar
• Novel agents combined get own guidance
  - Nat Biotech 29(3):174 (2011)
  Nature Biotechnology | News Novel agents combined get own guidance Journal name:Nature BiotechnologyVolume: 29,Page:174Year published:(2011)DOI:doi:10.1038/nbt0311-174Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Studio Heinemann/Westend61/Newscom Drug combinations gain regulatory path. Companies welcome the draft guidance published by the US Food and Drug Administration (FDA) clarifying the regulatory issues involved in developing novel, experimental drugs used as combinations. Recognizing that there are occasions when co-developing two or more investigational agents may provide significant therapeutic advantages, the FDA issued a public call for comments. Fifteen firms and organizations including Celgene of Summit, New Jersey, MedImmune of Gaithersburg, Maryland, the Melanoma Research Alliance and the Biotechnology Industry Organization submitted responses. "These comments were considered in the development of the draft guidance," says Crystal Rice, a spokesperson for the FDA. Until this draft guidance was published, companies were forging their own regulatory paths for the co-development of investigational drugs. Because many large companies already have a number of such combinations in early clinical trial testing (Nat. Biotechnol.28, 765–766, 201! 0), the opportunity to receive consistent advice from the regulators has been particularly well received. However, Rice explains that the guidance does not describe a one-size-fits-all development program for combination therapies. She acknowledges that the amount and types of clinical data needed and appropriate study designs will vary depending on the nature of the combination being developed, the disease and other factors. "The FDA anticipates that the finer details of individual development programs will usually be worked on a case-by-case basis," says Rice. Importantly, the new guidance (http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM236669.pdf) does not apply to already marketed drugs in fixed-dose combinations or to the development of an investigational drug and an approved drug. "Historically, the independent contribution of each participating drug in a combination needed to have been characterized beyond reasonable dou! bt, which often led sponsors to combine novel drugs with regis! tered standards of care," says Andrew Hughes, global clinical vice president of early oncology development at AstraZeneca. Instead, "the guidance document facilitates the earlier clinical appraisal of promising combinations of two unregistered drugs," adds Hughes, for instance, in vivo and in vitro evidence to support the biological rationale for a particular combination. For AstraZeneca, the FDA's input is timely because they have just announced a strategic alliance with Cancer Research UK to take combinations of experimental cancer drugs into early phase clinical trials. Bethan Hughes View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Dreamboat sinks prospects for fast approval of inhaled insulin
  - Nat Biotech 29(3):175-176 (2011)
  Nature Biotechnology | News Dreamboat sinks prospects for fast approval of inhaled insulin * Jim Kling1Journal name:Nature BiotechnologyVolume: 29,Pages:175–176Year published:(2011)DOI:doi:10.1038/nbt0311-175Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. MannKind Thumb-sized device. MannKind's inhaled insulin product, here shown with Dreamboat dispenser, suffered a surprise setback. In a move that could spell the end of a longstanding dream of inhaled insulin, in January the US Food and Drug Administration (FDA) issued a complete response letter to Valencia, California–based MannKind, asking for more data on its inhaled insulin product Afrezza. Specifically, the agency requested more information on the bioequivalence of a second-generation inhaler device, known as Dreamboat, to the MedTone inhaler used in clinical trials. After initially putting a brave face on the development, the company announced plans to lay off 179 employees, 41% of its workforce, during a quarterly earnings call on February 10. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Bellingham, Washington * Jim Kling Author Details * Jim Kling Search for this author in: * NPG journals * PubMed * Google Scholar
• Courts back Prometheus IP
  - Nat Biotech 29(3):176 (2011)
  Nature Biotechnology | News Courts back Prometheus IP * Michael FranciscoJournal name:Nature BiotechnologyVolume: 29,Page:176Year published:(2011)DOI:doi:10.1038/nbt0311-176aPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. In a ruling closely watched by developers of companion diagnostics, the US Court of Appeals for the Federal Circuit recently concluded that two methods for determining the optimal dosage of drugs to treat autoimmune diseases are patentable. The December 17, 2010, ruling reaffirmed the court's earlier decision in Prometheus Labs. Inc. v. Mayo Collaborative Services. Prometheus Laboratories of San Diego sued the Mayo Clinic for patent infringement when the medical group applied an in-house diagnostic test instead of sending samples to Prometheus. The Mayo Clinic claimed the process of giving a drug, observing its effects and adjusting the dosage is an abstract idea that was around before Prometheus patented the test. But the Federal Circuit upheld the patent. Then soon after the Supreme Court's Bilski v. Kappos decision (Nat. Biotechnol., 767, 2010), in which the court determined that the 'machine-or-transformation' test was only one of the considerations for an invention's pa! tentability, it vacated the Federal Circuit's ruling and ordered the court to issue a new one. Prometheus argued the Bilski decision did not merit a reversal, as the tests "involve a particular transformation of a patient's body and bodily sample and use particular machines to determine metabolite concentrations in a bodily sample." The court came back with the same decision—good news for companies wanting to develop and patent companion diagnostic tests. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Michael Francisco Search for this author in: * NPG journals * PubMed * Google Scholar
• Accelerated approvals examined
  - Nat Biotech 29(3):176 (2011)
  Nature Biotechnology | News Accelerated approvals examined * Emma DoreyJournal name:Nature BiotechnologyVolume: 29,Page:176Year published:(2011)DOI:doi:10.1038/nbt0311-176bPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. The US Food and Drug Administration (FDA) is seeking to improve the much-criticized accelerated approval program by reviewing six drugs approved under this pathway. The agency's Oncologic Drugs Advisory Committee (ODAC) held a meeting on February 8 to scrutinize Eli Lilly's Erbitux (cetuximab), GlaxoSmithKline's Bexxar (tositumomab) and Arranon (nelarabine); Genzyme's Clolar (clofarabine), Amgen's Vectibix (panitumumab) and Novartis' Gleevec (imatinib). The committee's intention was to analyze the process that brought these drugs to market without full confirmation that they are safe and effective. ODAC concluded that to grant accelerated approval, the agency should require a randomized trial, which could measure a surrogate endpoint. The panel also proposed that at the time of gaining accelerated approval, two randomized controlled trials should be under way. "The real issue is that lots of drugs are approved that are not terribly efficacious," argues Laurence Baker, ch! airman of the Southwest Oncology Group, Ann Arbor, Michigan, who was not on the panel. Recently, for instance, the agency withdrew the breast cancer indication for Avastin (bevacizumab),given accelerated approval in 2008, after studies found the drug did not provide asurvival advantage (Nat. Biotechnol.29, 3–15, 2011). View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Emma Dorey Search for this author in: * NPG journals * PubMed * Google Scholar
• Biosimilars encircle Rituxan, US debates innovator exclusivity
  - Nat Biotech 29(3):177-178 (2011)
  Nature Biotechnology | News Biosimilars encircle Rituxan, US debates innovator exclusivity * Karen Carey1Journal name:Nature BiotechnologyVolume: 29,Pages:177–178Year published:(2011)DOI:doi:10.1038/nbt0311-177Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Genentech Biosimilars producers are keen to bite into Rituxan's $6.6 billion global market. Sandoz, the generic drugs unit of Basel's Novartis, announced in January that it has begun a phase 2 rheumatoid arthritis trial with its own version of blockbuster monoclonal antibody (mAb) Rituxan (MabThera, rituximab). It joins Teva Pharmaceuticals, of Petach Tikva, Israel, and Spectrum Pharmaceuticals, of Irvine, California, both of whom are also working on versions of the anti-CD20 chimeric mAb approved for chronic lymphocytic leukemia, non-Hodgkin's lymphoma and rheumatoid arthritis. The progress of these biosimilar versions of Rituxan will be closely monitored by biotech innovators, particularly the rapidity with which they proceed through the review process. At $6.6 billion in 2010 sales, Rituxan is the largest revenue-producing biologic yet to come into the crosshairs of biosimilar developers. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * York, Pennsylvania * Karen Carey Author Details * Karen Carey Search for this author in: * NPG journals * PubMed * Google Scholar
• NCI revamps trials
  - Nat Biotech 29(3):178 (2011)
  Nature Biotechnology | News NCI revamps trials * Nidhi SubbaramanJournal name:Nature BiotechnologyVolume: 29,Page:178Year published:(2011)DOI:doi:10.1038/nbt0311-178aPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. The National Cancer Institute (NCI) is restructuring its long-established clinical trials program to take advantage of new understanding in molecular oncology and improvements in clinical trial design. The NCI's clinical trial Cooperative Group program's nine groups will be consolidated into four entities. "As we start defining illness based on molecular or genetic signatures, we start homing into more specific patient populations, which require screening for larger populations," says Jan Buckner, professor of oncology at Mayo Clinic in Rochester, Minnesota, and the chair of the North Central Cancer Treatment Group. The NCI's Cooperative Group program was founded over 50 years ago and involves more than 3,100 institutions. The organizational changes follow a NCI-requested report released last April by the Institute of Medicine (IOM), of Washington, DC. Efficiency will be boosted by revamping informational technology infrastructure, outfitting all groups with a uniform in! formation system and seamless sharing of information, sample banks and databases. One of the major goals is to speed up the time taken to approve and initiate phase 2 and phase 3 clinical trials. "We desperately want to get new treatments out to cancer patients, and do this in the most expeditious and safe way possible," says James Doroshow, director of the Division of Cancer Treatment and Diagnosis at NCI in Bethesda, Maryland. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Nidhi Subbaraman Search for this author in: * NPG journals * PubMed * Google Scholar
• Yardsticks for R&D
  - Nat Biotech 29(3):178 (2011)
  Nature Biotechnology | News Yardsticks for R&D * Nidhi SubbaramanJournal name:Nature BiotechnologyVolume: 29,Page:178Year published:(2011)DOI:doi:10.1038/nbt0311-178bPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Two nonprofits—the Critical Path Institute (C-Path), based in Tucson, and the Clinical Data Interchange Standards Consortium (C-DISC) of Round Rock, Texas—are teaming up to set common standards for companies to report clinical data on diseases considered major public health challenges. The aim is to quicken R&D efforts and potentially facilitate the evaluation of new therapies at the US Food and Drug Administration (FDA). "Most companies are recognizing greater efficiency when we all call an apple an apple," says Raymond Woosley, C-Path's president and CEO. The data standards are intended as useful guidelines rather than mandates. C-Path and C-DISC built a database for Alzheimer's disease, launched in June 2010, as part of C-Path's Coalition Against Major Diseases project, and data from 4,000 patients have now been mapped to the standard. The joint effort will now be expanded to include data on amyotrophic lateral sclerosis, Huntington's disease, multiple sclerosis, ! lung cancer and diabetes. Standardized data would allow regulators to compare clinical data results across trials and across companies. ShaAvhree Buckman, Director of the Office of Translational Sciences at the FDA's Center for Drug Evaluation and Research (CDER) welcomes these data standards, as they capitalize on work already set in motion by existing groups. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Nidhi Subbaraman Search for this author in: * NPG journals * PubMed * Google Scholar
• Industry exhales as USDA okays glyphosate-resistant alfalfa
  - Nat Biotech 29(3):179-181 (2011)
  Nature Biotechnology | News Industry exhales as USDA okays glyphosate-resistant alfalfa * Emily Waltz1Journal name:Nature BiotechnologyVolume: 29,Pages:179–181Year published:(2011)DOI:doi:10.1038/nbt0311-179aPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Jason Lugo/istockphoto Planting glyphosate-resistant alfalfa has resumed following the USDA's January decision. US farmers can again plant genetically engineered alfalfa following a decision in January by the US Department of Agriculture (USDA). The ruling, which follows a tumultuous debate and four-year US court-imposed ban, comes as a relief to the agricultural biotech industry. The agency was proposing to place geographic restrictions on planting in response to organic growers' requests. This alternative was only narrowly averted and could have set sweeping regulatory precedents. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Additional data Affiliations * Nashville, Tennessee * Emily Waltz Author Details * Emily Waltz Search for this author in: * NPG journals * PubMed * Google Scholar
• DuPont swallows Danisco
  - Nat Biotech 29(3):179 (2011)
  Nature Biotechnology | News DuPont swallows Danisco * Nidhi SubbaramanJournal name:Nature BiotechnologyVolume: 29,Page:179Year published:(2011)DOI:doi:10.1038/nbt0311-179bPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Early in January, agricultural biotech giant DuPont of Wilmington, Delaware, agreed to purchase Danish enzyme maker Danisco, based in Copenhagen, for $5.8 billion. The deal has not been finalized, but speculation about the potential consequences of this buyout is rippling through the Danish biotech sector. "We've sold one of our national treasures," says Claus Felby, a professor of wood and biomass technology at the University of Copenhagen. Biotech researchers like Birger Moller, professor of plant biochemistry at the University of Copenhagen, fear that if DuPont decides to move Danisco's manufacturing to the US, this may put an end to an era of fruitful collaboration between industry and basic research in the country. Equally, DuPont's interest in Danisco could send a message about the value of Danish biotech. "It indicates we're sitting on a gold mine here," says Moller. In another recent transaction, Danish enzyme manufacturer Novozymes bought Darmstadt, Germany�! ��based Merck's bioagricultural science unit for $275 million. Merck's divested Crop Bioscience, which makes inoculants for plant health, is a strong strategic fit for the Danish biotech located in Bagsvaerd. The companies expect to close the deal by May, pending regulatory approval. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Nidhi Subbaraman Search for this author in: * NPG journals * PubMed * Google Scholar
• Alzheimer's genetic map
  - Nat Biotech 29(3):179 (2011)
  Nature Biotechnology | News Alzheimer's genetic map * Nidhi SubbaramanJournal name:Nature BiotechnologyVolume: 29,Page:179Year published:(2011)DOI:doi:10.1038/nbt0311-179cPublished online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Research groups across France, the UK and US are pooling their resources to create the biggest genetic information bank on Alzheimer's disease. Researchers participating in the International Genomics of Alzheimer's Project (IGAP) will compare the genomic data of 20,000 individuals with 30,000 controls. Members of the project include the European Alzheimer's Disease Initiative, led by the Institute Pasteur de Lille and Lille University, the Genetic and Environmental Risk in Alzheimer's Disease group from Cardiff, UK, the Heart and Aging Research in Genomic Epidemiology, Boston University and the Alzheimer's Disease Genetics Consortium at the University of Pennsylvania School of Medicine, Philadelphia. "This is the first time, internationally, we've all gotten together," says Gerard Schellenberg, director of the Philadelphia-based team and professor of pathology and laboratory medicine, University of Pennsylvania Medical School. Each institute will carry out its own associ! ation analysis, and those statistics pooled into a meta analysis, says Schellenberg. With almost 50,000 individuals, and drawing on results from the 1000 Genome Project, the IGAP aims to deepen understanding of the molecular basis of rare variants of the disease, Schellenberg says, and identify genetic risk factors for the disease. IGAP's meeting and analysis costs are currently supported by the Alzheimer's Association of Chicago, and Foundation Plan Alzheimer, of Paris. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Nidhi Subbaraman Search for this author in: * NPG journals * PubMed * Google Scholar
• Video games played with live organisms
  - Nat Biotech 29(3):181 (2011)
  Nature Biotechnology | News Video games played with live organisms Journal name:Nature BiotechnologyVolume: 29,Page:181Year published:(2011)DOI:doi:10.1038/nbt0311-181Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. 'Biotic games' that mimic classic video games have been devised by Ingmar Riedel-Kruse and his team at Stanford. Single-celled organisms are placed in a microfluidics chamber with a microscope camera to track their movements. The image is overlaid on a game board. In PAC-mecium (pictured) the player guides paramecia up and down by changing the chamber's electrical field with a joystick. Paramecia gain points for gobbling yeast cells, and avoiding a computer-animated fish. There's Biotic Pinball, POND PONG and Ciliaball. Riedel-Kruse hopes these biotech games could become part of biology studies and contribute to crowd-sourcing and research. http://news.stanford.edu/news/2011/january/biotic-video-games-011211.html View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Gary Pisano
  - Nat Biotech 29(3):183 (2011)
  Nature Biotechnology | News | Profile Gary Pisano Journal name:Nature BiotechnologyVolume: 29,Page:183Year published:(2011)DOI:doi:10.1038/nbt.1817Published online09 March 2011 The author of the landmark book Science Business: the Promise, the Reality and the Future of Biotech discusses key challenges in life science commercialization. View full text Additional data
• Stelios Papadopoulos
  - Nat Biotech 29(3):184 (2011)
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• Paul Keckley
  - Nat Biotech 29(3):185 (2011)
  Nature Biotechnology | News | Profile Paul Keckley Journal name:Nature BiotechnologyVolume: 29,Page:185Year published:(2011)DOI:doi:10.1038/nbt.1827Published online09 March 2011 The executive director of the Deloitte Center for Healthcare Solutions discusses how the changing policy and reimbursement environment is likely to affect the biotech and pharmaceutical sectors. View full text Additional data
• Merv Turner
  - Nat Biotech 29(3):186 (2011)
  Nature Biotechnology | News | Profile Merv Turner Journal name:Nature BiotechnologyVolume: 29,Page:186Year published:(2011)DOI:doi:10.1038/nbt.1811Published online09 March 2011 An industry veteran talks about the challenges facing a world-leading pharmaceutical corporation. View full text Additional data
• Anthony Coyle
  - Nat Biotech 29(3):187 (2011)
  Nature Biotechnology | News | Profile Anthony Coyle Journal name:Nature BiotechnologyVolume: 29,Page:187Year published:(2011)DOI:doi:10.1038/nbt.1821Published online09 March 2011 The man spearheading Pfizer's Centers for Therapeutic Innovation (CTI) initiative outlines how his company hopes to spur academia collaborations. View full text Additional data
• Elias Zerhouni
  - Nat Biotech 29(3):188 (2011)
  Nature Biotechnology | News | Profile Elias Zerhouni Journal name:Nature BiotechnologyVolume: 29,Page:188Year published:(2011)DOI:doi:10.1038/nbt.1825Published online09 March 2011 The former National Institutes of Health (NIH) director lays out the numerous challenges facing the translation of academic discoveries. View full text Additional data
• Edison Liu
  - Nat Biotech 29(3):189 (2011)
  Nature Biotechnology | News | Profile Edison Liu Journal name:Nature BiotechnologyVolume: 29,Page:189Year published:(2011)DOI:doi:10.1038/nbt.1824Published online09 March 2011 The executive director of the Genome Institute of Singapore surveys the changing global landscape of healthcare provisioning. View full text Additional data
• Greg Winter
  - Nat Biotech 29(3):190 (2011)
  Nature Biotechnology | News | Profile Greg Winter Journal name:Nature BiotechnologyVolume: 29,Page:190Year published:(2011)DOI:doi:10.1038/nbt.1815Published online09 March 2011 The inventor of humanized monoclonal antibodies and cofounder of Cambridge Antibody Technology, Greg Winter, muses on the future of antibody therapeutics and UK life science innovation. View full text Additional data
• Lee Hood
  - Nat Biotech 29(3):191 (2011)
  Nature Biotechnology | News | Profile Lee Hood Journal name:Nature BiotechnologyVolume: 29,Page:191Year published:(2011)DOI:doi:10.1038/nbt.1809Published online09 March 2011 Lee Hood outlines his vision of personalized medicine for the next 10 years. View full text Additional data
• Robert Weinberg
  - Nat Biotech 29(3):192 (2011)
  Nature Biotechnology | News | Profile Robert Weinberg Journal name:Nature BiotechnologyVolume: 29,Page:192Year published:(2011)DOI:doi:10.1038/nbt.1814Published online09 March 2011 A decade after publishing the seminal "The hallmarks of cancer" paper in Cell with Doug Hanahan, Robert Weinberg reflects on where we stand in the fight against cancer. View full text Additional data
• Arnold Demain
  - Nat Biotech 29(3):193 (2011)
  Nature Biotechnology | News | Profile Arnold Demain Journal name:Nature BiotechnologyVolume: 29,Page:193Year published:(2011)DOI:doi:10.1038/nbt.1810Published online09 March 2011 A trailblazer in the field of antibiotics reflects on natural product discovery in the genomic age. View full text Additional data
• Irv Weissman
  - Nat Biotech 29(3):194 (2011)
  Nature Biotechnology | News | Profile Irv Weissman Journal name:Nature BiotechnologyVolume: 29,Page:194Year published:(2011)DOI:doi:10.1038/nbt.1816Published online09 March 2011 An authority on hematopoiesis talks about the difficulties encountered in commercializing stem cell therapies. View full text Additional data
• Barbara Mazur
  - Nat Biotech 29(3):195 (2011)
  Nature Biotechnology | News | Profile Barbara Mazur Journal name:Nature BiotechnologyVolume: 29,Page:195Year published:(2011)DOI:doi:10.1038/nbt.1812Published online09 March 2011 A research leader at a major agrochemical company comments on the application of biotechnologies in commercial crop science. View full text Additional data
• Lee Lynd
  - Nat Biotech 29(3):196 (2011)
  Nature Biotechnology | News | Profile Lee Lynd Journal name:Nature BiotechnologyVolume: 29,Page:196Year published:(2011)DOI:doi:10.1038/nbt.1813Published online09 March 2011 Reflecting on progress in the bioenergy sector, Lee Lynd considers the prospects of producing liquid biofuels on a scale sufficient to impact energy challenges. View full text Additional data
• Fresh from the biologic pipeline—2010
  - Nat Biotech 29(3):197-200 (2011)
  Nature Biotechnology | News | News Feature Fresh from the biologic pipeline—2010 * Jim Kling1Journal name:Nature BiotechnologyVolume: 29,Pages:197–200Year published:(2011)DOI:doi:10.1038/nbt.1793Published online09 March 2011 Apart from a drug produced in rabbits, 2010 was in some ways an unremarkable year for biologic drugs coming onto the market. Emphasis on safety may be keeping the reins on new product registrations for some time to come. Jim Kling reports. View full text Additional data Affiliations * Bellingham, Washington * Jim Kling Author Details * Jim Kling Search for this author in: * NPG journals * PubMed * Google Scholar
• The power of many
  - Nat Biotech 29(3):201-203 (2011)
  Nature Biotechnology | News | News Feature The power of many * Clare Sansom1Journal name:Nature BiotechnologyVolume: 29,Pages:201–203Year published:(2011)DOI:doi:10.1038/nbt.1792Published online09 March 2011 Applications of crowdsourcing in commercial biotech remain few and far between, but the approach is proving increasingly popular for solving challenges in basic research. Clare Sansom reports. View full text Additional data Affiliations * London & Cambridge * Clare Sansom Author Details * Clare Sansom Search for this author in: * NPG journals * PubMed * Google Scholar
• Divining the path to a successful European exit
  - Nat Biotech 29(3):205-207 (2011)
  
• Strengths and limitations of the federal guidance on synthetic DNA
  - Nat Biotech 29(3):208-210 (2011)
  Nature Biotechnology | Opinion and Comment | Correspondence Strengths and limitations of the federal guidance on synthetic DNA * Laura Adam1 * Michael Kozar1 * Gaelle Letort1 * Olivier Mirat1 * Arunima Srivastava1 * Tyler Stewart1 * Mandy L Wilson1 * Jean Peccoud1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:208–210Year published:(2011)DOI:doi:10.1038/nbt.1802Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. To the Editor: The December issue included a report summarizing the first reactions of the gene synthesis industry to the publication of the US government Screening Framework Guidance for Providers of Synthetic Double-Stranded DNA1. Some of the questions raised by the federal guidance had already been exposed in your columns2, 3, but none of these previous comments relied on a bioinformatics analysis of the screening protocol proposed by the US government. Here we present the preliminary results of an implementation of this protocol with the hope of documenting the strengths and limitations of the federal guidance. This document outlines a minimal DNA sequence screening protocol that providers of gene synthesis4 services are encouraged to follow before fulfilling an order. The objective of the protocol is to identify sequences of concern of any length that are specific to 'select agents or toxins' (SAT) listed on the National Select Agent Registry (http://www.selectagents.gov/). It starts by translating the nucleotide sequence ordered by the customers into each of six possible reading frames. Both the nucleotide and amino acid sequences must then be divided into fragments that are individually aligned against GenBank using a local sequence alignment algorithm. Alignment results are interpreted using the 'best match' criterion, a procedure designed to identify sequences specific to SATs without relying on a curated database of sequences of concern. Although the federal guidance gives a general method for the automatic identification of potentially dangerous sequences, few instructions are given concerning the exact implementation of the method. Here we describe an interpretation of the method that is amenable to implementation in software (Fig. 1). The input DNA sequence to be screened first undergoes a six-frame translation. The resulting six-amino-acid sequences and the two original DNA sequences corresponding to the two strands of the query sequence are then divided into 66 amino acids (aa) and 200-bp fragments, respectively. When the sequence length is not a multiple of 200 bp or 66 aa, a new subsequence is created using the last 200 bp or 66 aa of the sequence. This subsequence overlaps the last subsequence resulting from the initial fragmentation, but it ensures that the entire sequence is screened. Figure 1: Sequence screening algorithm. The query sequence first undergoes a six-frame translation, then the amino acid sequences and nucleotide sequences are fragmented into the appropriate size. The subsequences are then aligned using BLAST against GenBank and the nature of the best matches is determined. If there is no best match but there are sequences of concern with query coverage >50%, then the alignment extension occurs. The algorithm is repeated on the extended sequences to determine whether original query sequence is a hit to a SAT. * Full size image (102 KB) * Figures/tables index All of these fragments are then analyzed individually to determine if they should be flagged. They are first aligned against GenBank using BLAST5. The best matches are extracted among the BLAST results by selecting the alignments with the highest percent identity over the entire 200-bp fragment (query coverage of 100%). To determine if a best match corresponds to a SAT, the information in the GenBank reference page is cross-referenced with a keyword list. For toxins, keywords include alternative names of the toxin, the names of enzymes that are associated with the production and function of the toxin, and the names of organisms that uniquely produce the toxin. For organisms and viruses, keywords include alternative species names, the names of diseases associated with the entries and any toxins or pathogenic agents uniquely produced by the entry. Two keyword lists were developed. The restricted keyword list has 86 records, whereas the extended keyword list has 340 keywords. I! f every best match is to a SAT, then the fragment is considered a hit. 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 * Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, USA. * Laura Adam, * Michael Kozar, * Gaelle Letort, * Olivier Mirat, * Arunima Srivastava, * Tyler Stewart, * Mandy L Wilson & * Jean Peccoud Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jean Peccoud Author Details * Laura Adam Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Kozar Search for this author in: * NPG journals * PubMed * Google Scholar * Gaelle Letort Search for this author in: * NPG journals * PubMed * Google Scholar * Olivier Mirat Search for this author in: * NPG journals * PubMed * Google Scholar * Arunima Srivastava Search for this author in: * NPG journals * PubMed * Google Scholar * Tyler Stewart Search for this author in: * NPG journals * PubMed * Google Scholar * Mandy L Wilson Search for this author in: * NPG journals * PubMed * Google Scholar * Jean Peccoud Contact Jean Peccoud Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Partnering Brazilian biotech with the global pharmaceutical industry
  - Nat Biotech 29(3):210-211 (2011)
  Nature Biotechnology | Opinion and Comment | Correspondence Partnering Brazilian biotech with the global pharmaceutical industry * Luiz A B de Castro1Journal name:Nature BiotechnologyVolume: 29,Pages:210–211Year published:(2011)DOI:doi:10.1038/nbt.1801Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. To the Editor: Previous descriptions of the Brazilian health biotech sector in this journal1, 2 have highlighted several challenges to sustainable development, including inefficient interactions between the public and private sectors1, a lack of venture financing1 and a paucity of legal incentives to encourage commercialization of the region's rich biodiversity2. Here we would like to emphasize the importance of another issue that prevents Brazilian biotech enterprises from successfully bringing innovative drugs to market—the lack of local partnerships between small and large companies and the poor level of collaboration between Brazilian companies and multinational pharmaceutical companies that can accelerate late-stage clinical development. One illustration of the behavior of the local health biotech sector is the lack of interaction between the two main industry associations in the country—the National Association of Pharmaceutical Laboratories (ALANAC; http://www.alanac.org.br) and the Brazilian Research-Based Pharmaceutical Manufacturers Association (Interfarma; http://www.interfarma.org.br). This weakens the Brazilian industry by preventing both collaboration and pooling of complementary scientific and financial resources that might otherwise bankroll innovative drug development. Most local companies are insufficiently capitalized to carry out innovative R&D activity in the area of biopharmaceuticals, let alone invest over a billion dollars to fund the core process from target discovery to a regulatory approval or registration. As a result of the weakness of the pharmaceutical sector, not one blockbuster drug has been developed in Brazil throughout its history. Moreover, many ALANAC member companies are o! pting to produce less R&D-intensive products, such as generics, instead of innovative drugs. Against this background, the Brazilian government has implemented several initiatives to create a local environment that is more conducive to innovative product development, thereby enriching the pool of partnering opportunities for pharmaceutical companies. In 2004, the 'Innovation Law' (Law 10,973)1 was introduced to encourage the sharing of intellectual property and other resources between public and private entities and allow direct support of R&D activities in private enterprises. Although the number of Brazilian biomedical inventions licensed at the US Patent & Trademark Office (Washington, DC) has doubled over the past two decades, it is still only a small number (http://www.uspto.gov/web/offices/ac/ido/oeip/taf/cst_utl.pdf). The situation in Brazil is complicated further by the country's cumbersome patenting process. Under Patent Law 9,279, the National Institute of Industrial Property can grant a pharmaceutical patent related to a product only after agreement has been obtained from Brazil's National Health Surveillance Agency. This rule makes the Brazilian process longer and more unwieldy than that in any other territory in the world. Even so, progress in fostering an innovation- and enterprise-friendly environment is being made. Two laws for creating favorable fiscal incentives for R&D investment (the 'Asset Law'; Law 11,196) and income tax exemptions for enterprises involved in R&D (Law 11,487) were introduced in 2005 and 2007, respectively. Although these laws had only a minor impact initially, in 2008 the income tax deduction derived from Law 11,196 amounted to ~0.05% of Brazilian gross domestic product (http://www.mct.gov.br). Even greater benefits could potentially be accrued if Law 11,487 could be extended to private enterprises, rather than applied solely to public research institutions, as it does at present. More recently, the launch of the Brazilian Technology System (SIBRATEC3) has facilitated the identification and development of promising compounds in academia. In this scheme, government funding is used to support preclinical and phase 1 clinical research of certain compounds selected by specialists from academic laboratories (Fig. 1). It is hoped that these activities will complement and synergize with the activities of the small number of private contract research organizations in Brazil that carry out clinical work. Indeed, there are clear examples of companies in the ALANAC group that are now attracted to developing new drugs. Such initiatives are critical to move lead molecules to a stage of validation where the pharmaceutical industry is willing to license in, or collaborate in the development of, a molecule. Figure 1: Model system to foster partnership in the Brazilian pharmaceutical sector. CRO, Consultative Research Organization; Sc&T, Science and Technology. * Full size image (80 KB) Domestic Brazilian pharmaceutical companies, as mentioned previously, are in general not financially capable of performing clinical testing alone, particularly phase 2 and 3 trials. To address this problem, the Brazilian government is actively funding pharmaceutical enterprises to propel compounds into early trials through a competitive system called 'subvenção'. In addition, foreign venture capital funds specialized in biotech are now setting up in Brazil to further contribute to this role and grow the national health biotech industry. For example, San Francisco—headquartered Burrill and Company is now fully operational in the country, with a $150 million life science venture fund slated to launch early this year. 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 * Brazilian Academy of Sciences, Rio de Janeiro, Brazil. * Luiz A B de Castro Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Luiz A B de Castro Author Details * Luiz A B de Castro Contact Luiz A B de Castro Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Survival and growth of Arabidopsis plants given limited water are not equal
  - Nat Biotech 29(3):212-214 (2011)
  Nature Biotechnology | Opinion and Comment | Correspondence Survival and growth of Arabidopsis plants given limited water are not equal * Aleksandra Skirycz1, 2, 5, 6 * Korneel Vandenbroucke1, 2, 4, 5, 6 * Pieter Clauw1, 2 * Katrien Maleux1, 2 * Bjorn De Meyer1, 2 * Stijn Dhondt1, 2 * Anna Pucci1, 2, 4 * Nathalie Gonzalez1, 2 * Frank Hoeberichts1, 2 * Vanesa B Tognetti1, 2 * Massimo Galbiati3 * Chiara Tonelli3 * Frank Van Breusegem1, 2 * Marnik Vuylsteke1, 2 * Dirk Inzé1, 2 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:212–214Year published:(2011)DOI:doi:10.1038/nbt.1800Published online09 March 2011 To the Editor: Although drought tolerance is a central concern of plant research, the translatability for crop improvement is relatively low. Here we report on a major contributing factor to this lack of success. Drought tolerance is predominately scored based on an improved survival rate under lethal conditions that, as demonstrated by our study, does not predict superior growth performance and, thus, biomass yield gain, under moderate drought often encountered in the field. Drought tolerance is a major subject of trait research for agbiotech companies and thousands of academic papers have been published on the topic. Consequently, there is a plethora of reports on improved drought tolerance, mainly in the model plant Arabidopsis thaliana1. Classic genetic engineering approaches involve target genes that function in mechanisms used by plants to avoid and/or tolerate drought, such as stomatal conductance or osmolyte production2. Such genes, frequently identified through expression profiling, include signaling components and downstream effector genes. However, despite the apparent success of stress research on model plants, rarely are the findings applied to improve crops. Only a few genes have been characterized that enhance stress tolerance in model plants or crops leading to increased yields3, 4, 5, 6 and the molecular mechanisms through which they work remain only partly understood. One of the key reasons relates to the genetic and physiologic! al differences between model and crop species. In Arabidopsis research, drought tolerance is assessed predominantly under quite severe conditions in which plant survival is scored after a prolonged period of soil drying. However, in temperate climates, limited water availability rarely causes plant death, but restricts biomass and seed yield. To study the relation between survival and biomass gain under drought, we analyzed the growth of transgenic Arabidopsis plants with increased tolerance to lethal stress in a mild stress assay. An extensive literature screen was conducted to identify Arabidopsis genes that, in gain- or loss-of-function situations, confer stress tolerance in Arabidopsis, without growth penalty under control conditions. Although drought and osmotic stresses were prioritized, other related ones, including salt, heat and oxidative stresses, were considered as well. The final selection consisted of 25 genes, which we designate 'stress tolerance genes' (STGs), involved in diverse aspects of stress toleranc! e and in a wild-type Columbia-0 (Col-0) background (Table 1, Supplementary Table 1). back to article Table 1: STG lines tested show no significant genotype-specific responses to the imposed drought stress, either combined or across all the time points. Gene identifierGene symbolExperimentLineBiological functionSurvivalP-value (genotype control conditions)P-value (genotype drought conditions)Mean percent reduction ± s.e.m.a aMean ± s.e.m. percent reduction of rosette size by drought measured 10 days into the treatment. bSignificant (P < 0.01) decrease of rosette area of the STG compared with the wild type under control or drought condition. View full text Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Primary authors * These authors contributed equally to this work. * Aleksandra Skirycz & * Korneel Vandenbroucke Affiliations * Department of Plant Systems Biology, VIB, Ghent, Belgium. * Aleksandra Skirycz, * Korneel Vandenbroucke, * Pieter Clauw, * Katrien Maleux, * Bjorn De Meyer, * Stijn Dhondt, * Anna Pucci, * Nathalie Gonzalez, * Frank Hoeberichts, * Vanesa B Tognetti, * Frank Van Breusegem, * Marnik Vuylsteke & * Dirk Inzé * Department of Plant Biotechnology and Genetics, Ghent University, Ghent, Belgium. * Aleksandra Skirycz, * Korneel Vandenbroucke, * Pieter Clauw, * Katrien Maleux, * Bjorn De Meyer, * Stijn Dhondt, * Anna Pucci, * Nathalie Gonzalez, * Frank Hoeberichts, * Vanesa B Tognetti, * Frank Van Breusegem, * Marnik Vuylsteke & * Dirk Inzé * Dipartimento di Scienze Biomolecolari e Biotecnologie, Università degli Studi di Milano, Milano, Italy. * Massimo Galbiati & * Chiara Tonelli * Present address: Bayer Crop Science, Ghent, Belgium * Korneel Vandenbroucke & * Anna Pucci * Current address: Dipartimento di Agrobiologia e Agrochimica, Università degli Studi della Tusc(K.V.); Dipartimento di Agrobiologia e Agrochimica, Universita degli Studi della Tuscia, Viterbo, Italy (A.P.). * Aleksandra Skirycz & * Korneel Vandenbroucke Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Dirk Inzé Author Details * Aleksandra Skirycz Search for this author in: * NPG journals * PubMed * Google Scholar * Korneel Vandenbroucke Search for this author in: * NPG journals * PubMed * Google Scholar * Pieter Clauw Search for this author in: * NPG journals * PubMed * Google Scholar * Katrien Maleux Search for this author in: * NPG journals * PubMed * Google Scholar * Bjorn De Meyer Search for this author in: * NPG journals * PubMed * Google Scholar * Stijn Dhondt Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Pucci Search for this author in: * NPG journals * PubMed * Google Scholar * Nathalie Gonzalez Search for this author in: * NPG journals * PubMed * Google Scholar * Frank Hoeberichts Search for this author in: * NPG journals * PubMed * Google Scholar * Vanesa B Tognetti Search for this author in: * NPG journals * PubMed * Google Scholar * Massimo Galbiati Search for this author in: * NPG journals * PubMed * Google Scholar * Chiara Tonelli Search for this author in: * NPG journals * PubMed * Google Scholar * Frank Van Breusegem Search for this author in: * NPG journals * PubMed * Google Scholar * Marnik Vuylsteke Search for this author in: * NPG journals * PubMed * Google Scholar * Dirk Inzé Contact Dirk Inzé Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1.4M) Supplementary Methods, Supplementary Table 1 and Supplementary Figures 1–6 Additional data * Journal home * Current issue * For authors * Subscribe * E-alert sign up * RSS feed Science jobs from naturejobs * Research Professorship "Clinical Epidemiology / Public Health" (W2) * Friedrich-Schiller-Universitat Jena * Jena, Germany * Scientific Programmer - Resequencing Informatics * European Bioinformatics Institute * Cambridge, United Kingdom * Fellowships * The Institute of Cancer Research (ICR) * London, United Kingdom * Post a free job * More science jobs Open innovation challenges * Preserving Cell Viability at Positive Temperatures Deadline:May 05 2011Reward:$50,000 USD The Seeker is looking for a method of preservation of cell viability for primary eukaryotic cells fo… * Delayed Release Formulation for Aqueous Protein Solution Deadline:Apr 02 2011Reward:$40,000 USD A delayed release technology is required for a boosting agent that would allow the simultaneous deli… * Powered by: * More challenges Top content Emailed * Biotechnology, development, and the Web Nature Biotechnology 01 Oct 1997 * Asia calls for united approach to commerce Nature Biotechnology 01 Oct 1999 * Public biotech 2009—the numbers Nature Biotechnology 13 Oct 2010 * Malaysia seeks biotech partners Nature Biotechnology 01 Apr 2009 * Toolkit for evaluating genes required for proliferation and survival using tetracycline-regulated RNAi Nature Biotechnology 05 Dec 2010 View all Downloaded * A high-quality catalog of the Drosophila melanogaster proteome Nature Biotechnology 22 Apr 2007 * Regulation of transcription by unnatural amino acids Nature Biotechnology 16 Jan 2011 * Generation of anterior foregut endoderm from human embryonic and induced pluripotent stem cells Nature Biotechnology 27 Feb 2011 * Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Nature Biotechnology 02 May 2010 * Efficient construction of sequence-specific TAL effectors for modulating mammalian transcription Nature Biotechnology 19 Jan 2011 View all Blogged * Generation of induced pluripotent stem cells without Myc from mouse and human fibroblasts Nature Biotechnology 30 Nov 2007 * Induction of pluripotent stem cells by defined factors is greatly improved by small-molecule compounds Nature Biotechnology 22 Jun 2008 * Live cell imaging distinguishes bona fide human iPS cells from partially reprogrammed cells Nature Biotechnology 11 Oct 2009 * Cell type of origin influences the molecular and functional properties of mouse induced pluripotent stem cells Nature Biotechnology 19 Jul 2010 * Cloud computing and the DNA data race Nature Biotechnology 01 Jul 2010 View all * Nature Biotechnology * ISSN: 1087-0156 * EISSN: 1546-1696 * About NPG * Contact NPG * RSS web feeds * Help * Privacy policy * Legal notice * Accessibility statement * Terms * Nature News * Naturejobs * Nature Asia * Nature EducationSearch:Go © 2011 Nature Publishing Group, a division of Macmillan Publishers Limited. 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• Biomedical technology and the clinic of the future
  - Nat Biotech 29(3):215 (2011)
  Nature Biotechnology | Opinion and Comment | Commentary Biomedical technology and the clinic of the future Journal name:Nature BiotechnologyVolume: 29,Page:215Year published:(2011)DOI:doi:10.1038/nbt.1796Published online09 March 2011 Technology pioneers trade views with a clinician and an entrepreneur on the likely impact of large-scale systems technology in healthcare. View full text Additional data
• POINT: Are we prepared for the future doctor visit?
  - Nat Biotech 29(3):215-218 (2011)
  Nature Biotechnology | Opinion and Comment | Commentary POINT: Are we prepared for the future doctor visit? * Stephen H Friend1 * Trey Ideker2 * AffiliationsJournal name:Nature BiotechnologyVolume: 29,Pages:215–218Year published:(2011)DOI:doi:10.1038/nbt.1794Published online09 March 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Imagine the following visit to the doctor's office, which, although fictitious, is based on technologies that are emerging or already available. A patient, Jane Doe, enters the clinic for a routine physical exam. Today, at least seven parameters would be registered upon her admittance: sex, age, height, weight, temperature, pulse rate and blood pressure (itself a pair of values). But in the future when Jane registers, this set of routine measurements will have expanded enormously (Table 1). Table 1: Current and emerging genomic technologies for network medicine Full table * Figures/tables index Tomorrow's routine checkup Either on this visit or a previous one, Jane's full genome has been sequenced, noninvasively, using a buccal swab. At the same time, and optionally on every visit, the nurse has sampled and sequenced the metagenome of the microbiome pool resident in the patient's mucosal and gastrointestinal cavities, providing a detailed characterization of the population of microbes commensal with the human host. Messenger RNA, microRNA, proteome and metabolome profiles may be gathered from urine and, if necessary, whole blood and other tissues. Finally, in addition to height and weight, a large panel of physiological parameters and images is monitored, capturing detailed information about respiration, endocrine function, cardiac and brain activity, and so on. Another key development that will transform Jane's visit to the clinic is deeper data integration. All of the newly gathered information are banked in a unified electronic medical record, which uses a relational database to establish cross-references among the different data types. The new information augments the history of data gathered on previous visits, including all medical treatments and outcomes accumulated over the patient's lifetime. Crucially, the new data are then integrated with a library of biological network models spanning multiple levels and scales (Fig. 1). First is the network of functional and molecular interactions—a.k.a. the molecular wiring diagram—providing a modular, hierarchical and executable view1 of the cellular processes underlying human health and disease. Such networks are being assembled from diverse large- and small-scale experiments performed over decades of systems biology and biomedical research, providing an up-to-date representation of current knowledge in the field2, 3. A second type of network model will represent the relevant nosology, which maps relationships between diseases based on their similarities in etiology, pathogenesis and symptoms. Related to this will be another network—that of pharmacologic treatments, which provides rich information about the different protocols and drugs that are available along with their quantitative inter-relationships. One more im! portant network will be the patient's extended social network and pedigree, which will be available along with references to the integrated medical records of friends and relatives. This social network documents significant personal relationships in Jane's life, weighted by importance and, subject to privacy concerns, gathered from social networking websites, personal address books, geographical co-location data, as well as cell phone and e-mail usage. The pedigree provides a complementary set of social relationships that have a genetic basis. Figure 1: Layers of genomic and network-based information in integrative healthcare. The future primary care physician may need to cope with a staggering array of integrated patient data including genome sequences and biological networks. Access to the full electronic medical record (far left) will provide data at the level of genome sequence (lower left), pedigree and social network (lower center), nosology of disease (far right) and molecular network modules (center). The module 3b.AF8001D is represented as a map of functional interactions among protein complexes, with red nodes indicating proteins for which significant genetic variants were identified. Integrative analysis of these data and model simulation yields a patient prognostic report (lower right). Sequence view is adapted from the UC Santa Clara Genome Browser (http://genome.ucsc.edu/). Network views are from Cytoscape (http://www.cytoscape.org/). * Full size image (216 KB) * Figures/tables index The benefits of these network models to Jane are severalfold. First, they integrate an array of different lines of evidence for health or disease, enabling the formulation of compound biomarkers that are combinations or functions of many simultaneous readouts. Such compound biomarkers can be more robust than biomarkers based on individual genes, proteins or metabolites4. Second, the networks provide a natural interpretation of the mechanisms behind Jane's present and future conditions, in contrast to current biomarkers that often have little relation to the actual cause of disease. Third, Jane's data and outcomes can be dynamically analyzed and reintegrated to improve the network models themselves. Thus, the impact of a network can increase over time along with the coverage and accuracy of the information it captures. For this reason, all of these network models have been developed using an online public 'commons', which is open-access, crowd-sourced and hosted by a neutral ! party. The commons serves as a platform for sharing biomedical data, models and tools, including results from extensive clinical trials, ample proteomic and genomic information, proper curation with standard annotations and full assurance that all of the information will remain in the public domain without the constraints of intellectual property (IP). The commons is also a portal by which federal regulators monitor drugs, since, in this future world, therapies are evaluated predominantly by patient-driven trials after their initial approval as safe compounds. On the basis of Jane's integrated data, multiple indicators are triggered that she is at moderate risk factor 12.7 for breast cancer. The molecular network model indicates both common and rare variants in genes within module 3b.AF8001D, a tumor suppressor module involved in DNA repair and cell cycle checkpoints, resulting in a quantitative decrease in its simulated functional output, which is corroborated by the mRNA and protein expression profiling data. In addition, the system predicts greater than average activation of a key onco-module involved in cell proliferation, which triggers a warning on the nurse's information management console. The entire pattern of network module activity is cross-referenced to the nosology, highlighting a web of diseases for which Jane is at risk and with tubular carcinoma type IIa3 as the most likely outcome. Type IIa3 is a tumor substratification of the future, which can only be identified using molecular profiling data in conjunction with ! a network model. Jane's integrated pedigree shows that, although no immediate family members have been diagnosed with similar diseases, two family members at network distances 2 and 3, respectively, have had breast and ovarian cancer. The history for these individuals shows that both were initially placed on preventative treatment with the compound 'aleamed A' but switched to 'aleamed B' after experiencing deleterious side effects, including severe depression. Although Jane's genome sequence places her only at moderate risk for depression, this trait is strongly enriched among the social network of her immediate friends—a finding that raises Jane's own depression risk factor5. Thus, aleamed B is recommended as the initial course of action for Jane, or related protocols as indicated by the network of treatments. Technological possibility or political and social pipe dream? What are the barriers to making this scenario a reality? Technologies, such as genome sequencing and molecular profiling, are here now (Table 1). The required network models—representing connections at the molecular, social, chemical and disease levels—are also available in various forms, although their coverage is far from complete. Clearly, using network maps to develop therapies will require representations of disease that go far beyond the classic biopathway maps so vaunted today. It will require pathophysiological maps that highlight the protein targets lacking in redundancy, such that when altered by drugs these targets modify disease. In turn, these maps will need to highlight unforeseen secondary effects of modifying each potential target. Assembling and interpreting such integrative network maps will also require that we populate patient records with genotypic and phenotypic changes at scales far beyond our capabilities today. It will require a new class of primary care physician who is proficient in biostatistics, the various data types, networks and modes of integration, and the contribution of each of these components to the overall disease risk and treatment plan. Presently, some of the most forward-looking tests are provided by direct-to-consumer personalized genetics companies6, but a key challenge faced by such companies is how to provide suitable education to the patient without physician guidance. However, the proposal we make here is that the most challenging hurdles that will keep this reality from occurring may not be related to technology or education but will be social and political in nature. We acknowledge that the complex technology and informatics methods that will need to be developed will require massive efforts extending over more than just a few years. At the same time, we anticipate that overcoming the accompanying social and political hurdles will be the more vexing problems, as they will involve addressing issues such as how we will need to work together, how we will need to reward individuals and what we will value. First and foremost, the future of biomedicine will require that the data are generated and used in a sustainable way. Currently, we fund researchers to perform large clinical studies as if they were indigenous hunter-gatherers. The assumption is that these individuals must not only generate large data sets but should also zealously defend their right to use the data to deliver conclusions that develop the careers of themselves and their laboratories. The data, when finally made available, are often not formatted in a way that is accessible for other investigators to use further, other than as a conclusion. It is as if the patient, who is the actual donor and owner of their data, is sidelined by the biomedical institutions that take on a paternalistic ownership role. Should it be a surprise that this situation typically places the institution's interests and incentives in control of how the data are distributed? Another driver of current behavior within our medical-industrial complex is the publisher, who wishes to charge for access to the results wrapped within the paper, because this paper is the main scientific currency with which authors are recognized. How can we expect researchers to share their insights before they have written papers, if there are no means to provide them recognition for the actual work itself, including their models and representations of disease? Because the models will require massive amounts of data, building these models will require data sharing in ways that issues of privacy and IP typically obstruct. Dealing with these issues effectively will require that the patients with disease be highly visible. If patients come to better understand the Byzantine cloistering of data that is prevalent today, they will likely demand a shift in culture to one that places the impact squarely on patients, not on the careers of academic investigators. In a more positive frame, there is enormous potential for the coming tsunami of clinical-genomic data to fundamentally improve the process of developing therapies, which has been atrociously ineffective7. Most necessary, we posit, will be to establish a shared infrastructure for the data, tools and models needed to evolve our understanding of disease and its treatment (that is, the online public commons featured in Jane Doe's visit to the doctor described above). Such a platform must grant unrestricted use of data to develop therapies, and it will benefit greatly from public-private partnerships. One powerful example of such a partnership within the realm of drug discovery is the Structural Genomics Consortium (SGC) led by Aled Edwards and Chas Bountra8. Now 6 years old, this consortium has stimulated sharing of data and models to the extent that the majority of crystal structures solved today no longer have IP attached to them. This is an important example of how a domain of scientific discovery has been transformed—from the traditional assumption that solving structures of targets is a competitive proprietary benefit, to the modern realization that such competitive activities end up crippling all parties because each effort is only a small piece of the whole and has access to only a fraction of the data. Since its inception with a focus on crystal structures, SGC has diversified to tackle other components of basic drug discovery, such as the generation of chemical probes, guided by the same open-access, IP-free philosophy. A second example of real data sharing is the Coalition Against Major Diseases9, which has worked to provide open access to clinical trial data from Alzheimer's and other neurological disorders. Patient-led clinical trials, such as those facilitated by PatientsLikeMe or the Life Raft Group, are also a promising direction, provided certain challenges can be met, such as the establishment of appropriate controls. Beyond these needs, it will be essential that information technology companies be shown what a key role they will have in hosting massive amounts of biomedical data and resources in 'the cloud'. An additional interconnected hurdle relates to the legal friction that the integration of clinical and genomic data will spawn. The desire to capture economic benefits from potential discoveries associated with the data and resulting integrative network models will, if not kept in check, lead to layered legal ownership constraints that could cripple sharing. Avoiding this paralysis will require cooperation among academic institutions, nonprofit foundations, government funders and journals, which set many of the current research rules and reward structures. If we are going to be able to guide the future care of Jane Doe, we will need to engage in "institutional analysis" akin to that described by Elinor Ostrum, who won the 2009 Nobel Prize in Economic Sciences10. Within the institution of academic research, the most important cultural issues are recognition and reward. We will need to develop robust ways to recognize scientists for their work before, and independent of, publication of journal articles. For example, if we were able to publish models of disease that could be cited by others, then academic institutions might be willing to grant tenure based on the citation impact associated with the models themselves. Similarly, funding agencies might judge potential grantees by the impact of their disease models and, in parallel, set standards for how grantees should share data and models in publicly accessible ways. Such mechanisms could speed the transition to a world in which public access to data and models, as ingredient! s for future experiments, is not the exception but the rule. It also would greatly help if others were to follow the example set by the Wellcome Trust (London), which has opened discussions about standard legal tools that enable disease-to-therapy projects within an IP-free zone11. Here, too, patients as advocates will need to harness their energy and visibility as we navigate the delicate path to robust public clinical-genomic data access while protecting key issues of patient privacy. Conclusions In summary, the technologies are here that will entirely transform healthcare. For that reason, it is vitally important that we now focus on realigning the cultural and institutional incentives driving researchers, academic institutions and publishers. The way forward is at least threefold. First, to engage the patients, who must demand methods for data sharing that move past current privacy issues; second, to promote open-access platforms for sharing of data, models and tools; and third, to reward scientists for publication of models, not papers. If these challenges can be met, the future promises to be a world of healthcare honed by data collected from a vast majority of patients being treated in real time. At the same time, the world of drug discovery will no longer be filled by the top ten pharmaceutical giants of the present day. Instead, these titans will be complemented by a distributed chain of groups who each build a given tool, reagent or product—much closer to the archipelago of software engineers that currently provide applications for iPhones. It is indeed possible that certain forces—in pharma, in insurance or in hospital administrations—will be aligned against this view. Nonetheless, the tasks described are not impossible, especially if we the people—as citizens, as scientists and as patients—are willing to experiment with how we work together. Don't doubt that the technology will be powerful enough to provide deep understandings. Do doubt whether we are willing to take the cultural and institutional steps to fundamentally change how we work together, and how we share the data and models that will be needed to take advantage of the upcoming opportunities. References * References * Acknowledgments * Author information * Fisher, J. & Henzinger, T.A.Nat. Biotechnol.25, 1239–1249 (2007). * ChemPort * ISI * PubMed * Article * Friend, S.H.Clin. Pharmacol. Ther.87, 536–539 (2010). * ChemPort * ISI * PubMed * Article * Chuang, H.Y., Hofree, M. & Ideker, T.Annu. Rev. Cell Dev. Biol.26, 721–744 (2010). * ChemPort * PubMed * Article * Ideker, T. & Sharan, R.Genome Res.18, 644–652 (2008). * ChemPort * ISI * PubMed * Article * Rosenquist, J.N., Fowler, J.H. & Christakis, N.A.Mol. Psych. published online, doi: doi:10.1038/mp.2010.13 (16 March 2010). * Article * Wagner, J.K.Am. J. Hum. Genet.87, 451–456 (2010). * ChemPort * ISI * PubMed * Article * David, E., Tramontin, T. & Zemmel, R.Nat. Rev. Drug Discov.8, 609–610 (2009). * ChemPort * ISI * PubMed * Article * Weigelt, J.EMBO Rep.10, 941–945 (2009). * ChemPort * ISI * PubMed * Article * Romero, K.et al. Clin. Pharmacol. Ther.86, 365–367 (2009). * ChemPort * ISI * PubMed * Article * Ostrum, E.Understanding Institutional Diversity (Princeton University Press, Princeton, NJ, USA, 2005). * Friend, S.H.Scientist24, 22–32 (2010). * Goodman, A.A.et al. Nature457, 63–66 (2009). * ChemPort * ADS * ISI * PubMed * Article Download references Acknowledgments * References * Acknowledgments * Author information We are grateful to G. Siuzdak and S. Choi for helpful comments on the manuscript. T.I. is a David and Lucille Packard Fellow and was funded by a grant from the US National Institutes of Health (RR031228). S.H.F. is funded in part by the National Cancer Institute Centers for Cancer Systems Biology (CCSB) Program and the State of Washington Life Sciences Discovery Fund. Author information * References * Acknowledgments * Author information Affiliations * Stephen H. Friend is at Sage Bionetworks, Seattle, Washington, USA. * Trey Ideker is in the Departments of Medicine and Bioengineering, University of California, La Jolla, California, USA, and at The Institute for Genomic Medicine, University of California, La Jolla, California, USA. or Competing financial interests The authors declare no competing financial interests. Author Details * Stephen H Friend Search for this author in: * NPG journals * PubMed * Google Scholar * Trey Ideker Contact Trey Ideker Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• COUNTERPOINT: Do not opine before it's time
  - Nat Biotech 29(3):218-219 (2011)
  Nature Biotechnology | Opinion and Comment | Commentary COUNTERPOINT: Do not opine before it's time * Isaac S Kohane1 * David M Margulies2 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:218–219Year published:(2011)DOI:doi:10.1038/nbt.1797Published online09 March 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Ms. Jane Janus stumbled into the office of Dr. Jill Askepulus pale and sweating. Before the administrative assistant could intercept the unfortunate woman, Dr. Askepulus took her friend by the arm and guided her to a soft landing on her office couch. When Jane had sufficiently recovered, Dr. Askepulus gently asked her what had happened. After a few quavering aborted attempts, she managed to whisper, "I know you warned me, but I went to the Network Integromics Clinic [NIC]." Jane was alternately glum and anxious. She explained to Jill that, of course, she knew she already had a risk of cancer because of her family history of ovarian and breast cancer, but then the NIC had shown her these complicated diagrams, which their physicians informed her demonstrated a high risk that required very close attention. They also had suggested a drug based on the genomic measurements taken at the NIC, which their models suggested could reduce her risk. Jill paused for a moment, then brought her electronic tablet over to the chair next to Jane and went over with her what appeared to be a prognostication of a track similar to those of hurricanes often seen on the video news. "Jane," she started, "given that you are a professor of mathematics, I figured you could appreciate this. Here," she said pointing to a 95% confidence interval, shaded in red, growing and broadening with age, "is the risk that we know you have and that increases with age for these various cancers. And here are the trajectories that are peeling away from the main risk trajectory under the influence of lifestyle choices, which you and I have already discussed. This broad trajectory in green is the estimated effect of the drug that they suggested to you, and some variations based on different predictive models of cancer based on your genetic markers. Jane stared for a minute at this display and remarked, "I see that I can change my risk somewhat! by lifestyle and I do see that this drug might be able to reduce the risk. But I was expecting that all these genomic and proteomic measurements were going to give me a much more accurate and personalized perspective of my medical future. They all seem to overlap a lot." Jill nodded, "They might be much more accurate one day soon, but we have had considerable challenges integrating these various clinical and experimental databases and results from other high-throughput data types to come up with a more accurate prognosis and individualized therapeutic decision-making. We will get there eventually, but the science still has to be worked out and frankly we need more research to be sure our models are accurate. Right now, let's make sure you understand the certainty or lack of it that comes from these various new data types. And let's weigh, with common sense, the preponderance of evidence to date. I could bore you with an accounting of untold suffering that occurred as a! result of an insufficiently informed use of tests such as pro! state specific antigen, mammograms or urinary screening for neuroblastoma. But I won't. Let's talk about how we are going to make the right decision for you, with you." An alternative view "Increased openness, transparency, data sharing and academic rewards for team and multidisciplinary behavior do not constitute the primary structural impediments to the translation of genomic measurements into safe clinical practice." The above slightly tongue-in-cheek sequel to the scenario proposed by Friend and Ideker is provided to emphasize where we believe the current challenges lie. To be sure, increased openness, transparency, data sharing and academic rewards for team and multidisciplinary behavior are important ingredients in developing a vibrant and productive biomedical discovery establishment. However, they do not constitute structural impediments to the translation of genome-scale measurements into safe clinical practice. Moreover, although we have a long way to go, historical trends point to steady progress towards openness and collaboration. This includes an ever-widening fraction of open-access publications with steadily rising impact, the opening to a world of researchers of cohort studies (e.g., the Framingham Study and the Gene Expression Omnibus storing the data of over half a million microarrays), each measuring tens of thousands of genes. It includes the evidence of the increased impact and frequency of large multinational studies with hundreds of authors; historic achievements such as trial registries like clinicaltrials.gov, which even now are being upgraded to include more primary data; multiple consumer-driven, data-sharing efforts, from the corporate, such as PatientsLikeMe, to purely voluntary and extensive social network support groups. Already, biomedical research groups are discussing publication formats that follow the lead of our colleagues in astronomy that include the fu! ll data within the publication document itself12. We can cheer on these efforts, but the translation of existing and future 'massively parallel' measurements to clinical-grade decision support and therapeutics remains a methodological and scientific challenge for which there has been far less progress than the sociological trends appropriately lauded by Friend and Ideker. More pressing challenges What are the components of this most pressing and thorny challenge in achieving meaningful, clinical-grade, integrative medicine that leverages the various data types enumerated by Friend and Ideker? First, we have to develop suitable technical methods and user interaction models to integrate the diverse data sources. Although there are isolated instances of integration of, for example, expression data with underlying pathways, or expression data in the context of specific somatic genome variation, there is no general purpose architecture or model for integrating the complexity of data types with physiology and anatomy over time. Second, we have to ensure that what we know is accurate. That is, we have to clean up our existing evidentiary knowledge base. For example, of the at least 150,000 genomic variants documented to have some import to disease, a substantial minority have not been reproduced or have been contradicted by subsequent reports. Third, we have to ensure that we know what is known. In the context of a medical education system that is already straining to keep physicians informed of best practices using only a few thousand clinical variables, the challenge of supporting sound and efficient decision-making in the context of millions of variants will require substantial progress in data reduction, user interfaces and automated support. Fourth, we have to know whether we can safely proceed to clinical decision-making from computer models that are not completely based on human clinical trials, randomized or observational. That is, can our models achieve the same mechanistic and predictive qualities as the Henderson-Hasselbalch equation for acid-base equilibrium, the Frank-Starling Curve for cardiac contractility or at least the Framingham cardiovascular risk scores? If not, are they only useful for hypothesis exploration rather than clinical care? Breakthroughs in both measurement and modeling technology may be required to achieve clinical-grade soundness of our models. Fifth, there will need to emerge regulatory clarity around the use of data displays of this complexity. Who will decide whether what we think we know is safe? What are the boundaries of the US Food and Drug Administration's (FDA) so-called 'IVDMIA' (in vitro diagnostic multivariate assay) threshold? How will the regulatory framework of the FDA and its international analogs cope with models as complex as those of in silico airplane design? Finally, how much better is our new knowledge than older knowledge? When is the incremental benefit of a genomic variant(s) or gene expression profile relative to a family history or classic histopathology insufficient and when does it add rather than subtract variance? If we are able to rationalize the selection of cancer chemotherapeutic agents by integrating information about responsiveness of cells with specific cell expression profiles, that would be an important 'emergent' benefit of deep integration. But it is important that we identify potential transformative benefits to focus and prioritize data integration efforts. The clinical perspective exemplified by these questions poses substantial challenges. We do not doubt that our biomedical research community is up to successfully addressing them, some even in the very near term. Like our colleagues, we are excited to be able to collaborate in integromic research that we are convinced will benefit many who suffer from disease. And like Friend and Ideker, we are optimistic that the trends to collaboration and transparency, already underway, can only help. References * References * Author information * Fisher, J. & Henzinger, T.A.Nat. Biotechnol.25, 1239–1249 (2007). * ChemPort * ISI * PubMed * Article * Friend, S.H.Clin. Pharmacol. Ther.87, 536–539 (2010). * ChemPort * ISI * PubMed * Article * Chuang, H.Y., Hofree, M. & Ideker, T.Annu. Rev. Cell Dev. Biol.26, 721–744 (2010). * ChemPort * PubMed * Article * Ideker, T. & Sharan, R.Genome Res.18, 644–652 (2008). * ChemPort * ISI * PubMed * Article * Rosenquist, J.N., Fowler, J.H. & Christakis, N.A.Mol. Psych. published online, doi: doi:10.1038/mp.2010.13 (16 March 2010). * Article * Wagner, J.K.Am. J. Hum. Genet.87, 451–456 (2010). * ChemPort * ISI * PubMed * Article * David, E., Tramontin, T. & Zemmel, R.Nat. Rev. Drug Discov.8, 609–610 (2009). * ChemPort * ISI * PubMed * Article * Weigelt, J.EMBO Rep.10, 941–945 (2009). * ChemPort * ISI * PubMed * Article * Romero, K.et al. Clin. Pharmacol. Ther.86, 365–367 (2009). * ChemPort * ISI * PubMed * Article * Ostrum, E.Understanding Institutional Diversity (Princeton University Press, Princeton, NJ, USA, 2005). * Friend, S.H.Scientist24, 22–32 (2010). * Goodman, A.A.et al. Nature457, 63–66 (2009). * ChemPort * ADS * ISI * PubMed * Article Download references Author information * References * Author information Affiliations * Isaac S. Kohane is at the Harvard Medical School Center for Biomedical Informatics and Children's Hospital Informatics Program, Boston, Massachusetts, USA. * David M. Margulies is at Correlagen Diagnostics Inc., Waltham, Massachusetts, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Isaac S Kohane Author Details * Isaac S Kohane Contact Isaac S Kohane Search for this author in: * NPG journals * PubMed * Google Scholar * David M Margulies Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Five more years of Nature Biotechnology research
  - Nat Biotech 29(3):221-227 (2011)
  Nature Biotechnology | Feature Five more years of Nature Biotechnology research * Monya Baker1 * Laura DeFrancesco2 * AffiliationsJournal name:Nature BiotechnologyVolume: 29,Pages:221–227Year published:(2011)DOI:doi:10.1038/nbt.1798Published online09 March 2011 Authors of the past five years' most highly cited research articles discuss their work and new directions in their respective areas. 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 * Monya Baker is Technology Editor for Nature and Nature Methods. * Laura DeFrancesco is Senior Editor at Nature Biotechnology. Author Details * Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar * Laura DeFrancesco Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Unsettled expectations: how recent patent decisions affect biotech
  - Nat Biotech 29(3):229-230 (2011)
  Nature Biotechnology | Feature | Patents Unsettled expectations: how recent patent decisions affect biotech * Brenda M Simon1 * Christopher T Scott1 * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:229–230Year published:(2011)DOI:doi:10.1038/nbt.1795Published online09 March 2011 A look back shows that broad patents are a thing of the past and biotech inventors face heightened requirements for patentability. 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 * Brenda M. Simon is at the Thomas Jefferson School of Law, San Diego, California, USA, and is a non-resident fellow at the Stanford University Center for Law and the Biosciences, Stanford, California, USA; * Christopher T Scott * Christopher T. Scott is at the Stanford University Center for Biomedical Ethics, Stanford, California, USA. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Brenda M Simon or * Christopher T Scott Author Details * Brenda M Simon Contact Brenda M Simon Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher T Scott Contact Christopher T Scott Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Recent patent applications in antibody fragments
  - Nat Biotech 29(3):231 (2011)
  Nature Biotechnology | Feature | Patents Recent patent applications in antibody fragments Journal name:Nature BiotechnologyVolume: 29,Page:231Year published:(2011)DOI:doi:10.1038/nbt.1819Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• IPSCs put to the test
  - Nat Biotech 29(3):233-235 (2011)
  Nature Biotechnology | News and Views IPSCs put to the test * Hyesoo Kim1 * Lorenz Studer1 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:233–235Year published:(2011)DOI:doi:10.1038/nbt.1805Published online09 March 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Analysis of a test set of cell lines shows that induced pluripotent stem cells perform as well as embryonic stem cells in differentiating to motor neurons. 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 * Hyesoo Kim and Lorenz Studer are at the Center for Stem Cell Biology and the Developmental Biology Program, Sloan-Kettering Institute, New York, New York, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Lorenz Studer Author Details * Hyesoo Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Lorenz Studer Contact Lorenz Studer Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Chemoproteomics quantifies complexity
  - Nat Biotech 29(3):235-236 (2011)
  Nature Biotechnology | News and Views Chemoproteomics quantifies complexity * Edward B Holson1 * Stuart L Schreiber1 * Affiliations * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:235–236Year published:(2011)DOI:doi:10.1038/nbt.1804Published online09 March 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. The affinities of small molecules for proteins in megadalton complexes can be measured by mass spectrometry. 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 * Edward B. Holson and Stuart L. Schreiber are at the Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Edward B Holson or * Stuart L Schreiber Author Details * Edward B Holson Contact Edward B Holson Search for this author in: * NPG journals * PubMed * Google Scholar * Stuart L Schreiber Contact Stuart L Schreiber Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Biomarkers in aggregate
  - Nat Biotech 29(3):236-237 (2011)
  Nature Biotechnology | News and Views Biomarkers in aggregate * Fred S Apple1Journal name:Nature BiotechnologyVolume: 29,Pages:236–237Year published:(2011)DOI:doi:10.1038/nbt.1803Published online09 March 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Implantable devices that measure the cumulative release of biomarkers promise new diagnostic options. 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 * Fred S. Apple is in the Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine and Hennepin County Medical Center, Minneapolis, Minnesota, USA. Competing financial interests F.S.A. has consulted for and received research grant funding for several biomarker companies that market the biomarkers discussed in the paper reviewed. These include Abbott Diagnostics, Beckman Coulter, Siemens, Ortho-Clinical Diagnostics, Radiometer, Roche, BRAHMS, Alere/Biosite and Response Biomedical. Corresponding author Correspondence to: * Fred S Apple Author Details * Fred S Apple Contact Fred S Apple Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• A modENCODE snapshot
  - Nat Biotech 29(3):238-240 (2011)
  Nature Biotechnology | News and Views A modENCODE snapshot * Markus Elsner1 * H. Craig Mak1 * AffiliationsJournal name:Nature BiotechnologyVolume: 29,Pages:238–240Year published:(2011)DOI:doi:10.1038/nbt.1806Published online09 March 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Since 2007 a consortium of research groups has been studying the genomes of two model organisms, the fruitfly Drosophila melanogaster and the nematode worm Caenorhabditis elegans, in a project called model organism encyclopedia of DNA elements (modENCODE)1. The latest results from this project were described recently in two papers in Science2, 3 and a suite of companion papers in Nature and Genome Research (http://blog.modencode.org/papers). The studies report both massive genome-scale data sets and analytic strategies for data integration. They substantially increase the annotated fractions of the fly and worm genomes and provide a wealth of data for understanding these model organisms and for developing new bioinformatic methods. Here we provide an overview of the data and some perspective from scientists on challenges for the field. The goal of modENCODE is to catalog sequence-based functional DNA elements in the fly and worm genomes. Such a catalog may be used to study regulatory networks and other emergent properties of the genomes, and, perhaps, to better understand the human genome. The project also seeks to generate experimental reagents for use by the research community. A summary of the new data sets is presented in Tables 1 and 2. To increase the number of functional genomic regions discovered, the studies analyzed organisms at different developmental stages. For the fly, ~700 data sets were generated from whole embryos, larvae and adult female and male insects as well as from a few cell lines and tissues. For the worm, ~240 data sets covered all major developmental stages along with some mutants, isolated tissues and animals exposed to pathogens. For both organisms, microarrays and sequencing were used to characterize gene expression, the binding sites of transcription factors and other proteins associated with DNA, origins of DNA replication, nucleosome turnover rates, salt-fractionated chromatin, the genomic locations of nucleosomes and the sites of different histone modifications. Box 1: Fruitfly modENCODE Full box Box 2: Nematode worm modENCODE Full box Looking forward, projects similar to modENCODE now seem feasible for studying other organisms and a broad range of biological problems. What will be the major challenges of such projects? Not sequencing, says Jun Wang, executive director of BGI in Shenzhen, China. He estimates that generating the equivalent of the fly modENCODE data set using today's technology could take less than 2 months, including less than a month for library construction and a month for sequencing (although in practice more time may be required if several replicates are necessary). The main technical barrier, he says, will be preparing large numbers of samples from different tissues, developmental stages and conditions. 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 * Associate Editors, Nature Biotechnology * Markus Elsner & * H. Craig Mak Author Details * Markus Elsner Search for this author in: * NPG journals * PubMed * Google Scholar * H. Craig Mak Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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
• Research highlights
  - Nat Biotech 29(3):241 (2011)
  Nature Biotechnology | Research Highlights Research highlights * Kathy Aschheim * Laura DeFrancesco * Markus Elsner * Peter Hare * Craig MakJournal name:Nature BiotechnologyVolume: 29,Page:241Year published:(2011)DOI:doi:10.1038/nbt.1822Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. Rumen metagenomics Jonas Lovaas Gjerstad The cost-effectiveness of biofuel may depend on the availability of better lignocellulolytic enzymes. An ideal source of these catalysts would be microbes in cow rumen, which digest complex plant polysaccharides with remarkable efficiency. Yet most members of the rumen microbiome defy culture. Hess et al. incubated nylon bags containing switchgrass, a promising energy crop, in the stomachs of fistulated cows for 72 h. Organisms adhering to the partially digested plant material were sequenced, yielding 268 Gbp of data and >2.5 million coding sequences. The authors identified >27,000 genes encoding putative carbohydrate-active enzymes, 43% of which are novel (having <50% identity to known proteins). Of 90 candidate gene products tested for activity, 51 were active on at least one of ten different substrates, including two potential biofuel feedstocks. Further analysis of this catalog of biomass-degrading enzymes may help to overcome a major bottleneck in biofuel production. (S! cience, 463–467, 2011) PH View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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 * Kathy Aschheim Search for this author in: * NPG journals * PubMed * Google Scholar * Laura DeFrancesco Search for this author in: * NPG journals * PubMed * Google Scholar * Markus Elsner Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Hare Search for this author in: * NPG journals * PubMed * Google Scholar * Craig Mak Search for this author in: * NPG journals * PubMed * Google Scholar
• David Haussler
  - Nat Biotech 29(3):243 (2011)
  Nature Biotechnology | Computational Biology | Profile David Haussler Journal name:Nature BiotechnologyVolume: 29,Page:243Year published:(2011)DOI:doi:10.1038/nbt.1808Published online09 March 2011 Human genome pioneer David Haussler talks about the evolving role of annotated data repositories. View full text Additional data
• Beyond natural antibodies: the power of in vitro display technologies
  - Nat Biotech 29(3):245-254 (2011)
  Nature Biotechnology | Research | Perspective Beyond natural antibodies: the power of in vitro display technologies * Andrew R M Bradbury1 * Sachdev Sidhu2 * Stefan Dübel3 * John McCafferty4 * Affiliations * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:245–254Year published:(2011)DOI:doi:10.1038/nbt.1791Published online09 March 2011 Abstract * Abstract * Accession codes * 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 In vitro display technologies, best exemplified by phage and yeast display, were first described for the selection of antibodies some 20 years ago. Since then, many antibodies have been selected and improved upon using these methods. Although it is not widely recognized, many of the antibodies derived using in vitro display methods have properties that would be extremely difficult, if not impossible, to obtain by immunizing animals. The first antibodies derived using in vitro display methods are now in the clinic, with many more waiting in the wings. Unlike immunization, in vitro display permits the use of defined selection conditions and provides immediate availability of the sequence encoding the antibody. The amenability of in vitro display to high-throughput applications broadens the prospects for their wider use in basic and applied research. View full text Figures at a glance * Figure 1: The unique capabilities of in vitro selection offer advantages over the immunization of animals for antibody generation. The direct coupling of the antibody and its encoding gene is characteristic of all display methodologies, including phage, yeast and ribosome display. Defined panning conditions with the desired buffer conditions, cofactors and competitors ensure that libraries can be screened using antigens with the desired conformation and biochemical properties to select for the requisite level of binder specificity and affinity. Binders can be selected sequentially, using different antigens to identify shared epitopes. The immediate availability of the antibody gene provides much additional value relative to antibodies obtained by immunizing animals. * Figure 2: In vitro selected antibodies can recognize minute differences in small molecules. () Antibodies against 6-monoacetylmorphine, the major heroin metabolite, do not recognize the closely related morphine154. () Many different antibodies have been selected and subsequently had both affinity and specificity matured to specifically recognize 17β-estradiol, testosterone and progesterone without cross-reacting with closely related steroids (Table 1). () Antibodies against proteins bearing sulfated tyrosine residues do not recognize proteins containing either tyrosine or tyrosine phosphate45, 46. * Figure 3: Mechanisms for blocking or activating receptor signaling using antibodies. The EGF receptor, a single transmembrane domain with multiple extracellular domains (ovals) with different functional domains, is used to exemplify mechanisms by which antibodies can block signaling by different classes of receptor. In this example, binding of ligand (green circle) occurs at domain 3, receptor dimerization occurs through domain 2 and interactions between domains 2 and 4 stabilize the 'closed' conformation of the receptor. (–) Antibodies can block signaling by binding to the ligand and preventing interaction with receptor (), binding the ligand-binding site of the receptor and preventing interaction with ligand (), preventing dimerization by binding the dimerization domain or sterically blocking the interaction () or stabilizing the closed conformation of the receptor (). () Activation can occur by binding the ligand-binding site typically with bivalent antibodies. * Figure 4: An engineered dual specificity synthetic Fab. The bH1 Fab binds to both Her2 (orange, Protein Data Bank (PDB) ID: 3BDY) and VEGF (red, PDB ID: 3BE1). The heavy and light chains of the Fab are colored cyan/gray or blue/black respectively, with the different colors derived from structures of bH1 binding to either Her2 or BEGF. Accession codes * Abstract * Accession codes * Author information Referenced accessions Protein Data Bank * 3BDY * 3BE1 * 3BDY * 3BE1 Author information * Abstract * Accession codes * Author information Affiliations * Los Alamos National Laboratory, Los Alamos, New Mexico, USA. * Andrew R M Bradbury * University of Toronto, Toronto, Ontario, Canada. * Sachdev Sidhu * Technical University Braunschweig, Braunschweig, Germany. * Stefan Dübel * University of Cambridge, Cambridge, UK. * John McCafferty Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Andrew R M Bradbury Author Details * Andrew R M Bradbury Contact Andrew R M Bradbury Search for this author in: * NPG journals * PubMed * Google Scholar * Sachdev Sidhu Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Dübel Search for this author in: * NPG journals * PubMed * Google Scholar * John McCafferty Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Chemoproteomics profiling of HDAC inhibitors reveals selective targeting of HDAC complexes
  - Nat Biotech 29(3):255-265 (2011)
  Nature Biotechnology | Research | Article Chemoproteomics profiling of HDAC inhibitors reveals selective targeting of HDAC complexes * Marcus Bantscheff1, 3 * Carsten Hopf1, 3 * Mikhail M Savitski1 * Antje Dittmann1 * Paola Grandi1 * Anne-Marie Michon1 * Judith Schlegl1 * Yann Abraham1 * Isabelle Becher1 * Giovanna Bergamini1 * Markus Boesche1 * Manja Delling1 * Birgit Dümpelfeld1 * Dirk Eberhard1 * Carola Huthmacher1 * Toby Mathieson1 * Daniel Poeckel1 * Valérie Reader2 * Katja Strunk1 * Gavain Sweetman1 * Ulrich Kruse1 * Gitte Neubauer1 * Nigel G Ramsden2 * Gerard Drewes1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:255–265Year published:(2011)DOI:doi:10.1038/nbt.1759Received18 November 2010Accepted17 December 2010Published online23 January 2011 Abstract * Abstract * Accession codes * 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 The development of selective histone deacetylase (HDAC) inhibitors with anti-cancer and anti-inflammatory properties remains challenging in large part owing to the difficulty of probing the interaction of small molecules with megadalton protein complexes. A combination of affinity capture and quantitative mass spectrometry revealed the selectivity with which 16 HDAC inhibitors target multiple HDAC complexes scaffolded by ELM-SANT domain subunits, including a novel mitotic deacetylase complex (MiDAC). Inhibitors clustered according to their target profiles with stronger binding of aminobenzamides to the HDAC NCoR complex than to the HDAC Sin3 complex. We identified several non-HDAC targets for hydroxamate inhibitors. HDAC inhibitors with distinct profiles have correspondingly different effects on downstream targets. We also identified the anti-inflammatory drug bufexamac as a class IIb (HDAC6, HDAC10) HDAC inhibitor. Our approach enables the discovery of novel targets and inh! ibitors and suggests that the selectivity of HDAC inhibitors should be evaluated in the context of HDAC complexes and not purified catalytic subunits. View full text Figures at a glance * Figure 1: Mapping of HDAC drug target complexes in chemical space and in proteome space. () Chemoproteomics competition binding assay to profile HDAC inhibitor target complexes in cell extract. (1) A probe matrix is generated by derivatizing sepharose with analogs of nonselective HDAC inhibitors (left, SAHA, right, givinostat). (2) Cell extract is incubated with vehicle or with drug over a range of concentrations. (3) The 'free' drug competes with the immobilized probes for drug-binding sites on target-protein complexes. White hexagon, inhibitor drug. (4) Captured proteins are trypsinized and each peptide mixture is tagged with a distinct isobaric tandem mass tag (TMT). (5) Tagged samples are pooled and analyzed by LC-MS/MS. Each peptide gives rise to six reporter signals in the MS/MS spectrum. (6) When free drug outcompetes protein capture, signal intensities relative to the vehicle control decrease for each peptide originating from this protein. Complexes formed by the target and associated proteins are defined by matching inhibition (IC50) curves. () Definiti! on of target protein complexes in biological space by quantitative co-IP. Data generated from the same cell extracts are used to deconvolute protein complexes formed around the drug target. * Figure 2: HDAC inhibitor drug targets and target complexes are defined by chemoproteomics profiling of drugs and compounds used as research tools. () Representative concentration-inhibition profiles of SAHA, BML-210 (aminobenzamide analog of SAHA), tacedinaline and romidepsin were determined in K562 cell extract as outlined in Figure 1. Inhibitors were pre-incubated with cell extracts at 4 °C before addition of the probe matrix, with the exception of the aminobenzamides BML-210 and tacedinaline, which were pre-incubated at 22 °C. Profiles are grouped in three plots for each inhibitor: HDACs (left), components of CoREST, NuRD, Sin3 and NCoR complexes (middle), and examples of other proteins either representing novel direct targets or complex components (right). Previously known complex associations are represented in a color code. Profiles of additional inhibitors are depicted in Supplementary Figure 3. () Bidirectional hierarchical clustering of the concentration-inhibition data for 16 inhibitors versus 1,251 proteins (each targeted by at least one inhibitor). Only the area of the clustering around HDACs is shown. Fo! r better comparison of selectivities, average pKdapp values were transformed into relative affinities scaling from 0 to 1 for each inhibitor. Statistically significant clusters are highlighted in blue and brown representing >95% and >99% unbiased bootstrap probability, respectively (Supplementary Fig. 7). * Figure 3: Deconvolution of protein complexes by co-IP analysis confirms the identification of novel HDAC complexes. () HDAC complexes identified by both chemoproteomics profiling and co-IP–MS/MS analysis of HDAC complexes. IPs were performed from K562 cells using antibodies for HDAC1, 2 and 3, known complex components (the CoREST subunit LSD1, the NuRD subunit MTA3, the Sin3 subunit SIN3A, and the NCoR-subunit TBL1XR1) and examples of novel HDAC interacting proteins. * denotes previously reported complex components not captured by the SAHA matrix. The color code indicates enrichment E of immunoprecipitated proteins as compared to mock-IP experiments (scales from −1 to 1, E = 0 denotes equal abundance, see Online Methods). () Examples of the quantitative mapping of immunoaffinity-purified protein complexes by MS/MS. Purifications conducted with two different antibodies each, and corresponding isotype controls, were combined after PAGE, trypsinization and isobaric tagging. Quantification data are shown as plots of relative enrichment in immunoprecipitates of Sin3 versus LSD1 (upper pane! l), and MTA3 versus TBL1XR1 (lower panel). Each square represents a protein with its size scaled according to the number of sequence-to-spectrum matches. () HDAC protein complexes in chemical and protein space. For each protein identified in chemoproteomics and co-IP experiments, enrichment in the IP samples is plotted against the average relative affinity data across all inhibitors tested. Target proteins are represented in red (class I HDACs), blue (CoREST components), green (NCoR components), purple (NuRD components), light blue (Sin3 components), pink (MiDAC components) and yellow (ELM-SANT proteins). The square size indicates the confidence of the interaction with the immunopurified protein complex (large squares: FDR < 0.05, medium-sized squares: 0.05 < FDR < 0.15, c.f. Supplementary Figs. 8 and 9 and Supplementary Table 4). * Figure 4: Class I HDACs and DNTTIP1 form a mitotic deacetylase complex (MiDAC). () Cell cycle-dependent association of DNTTIP1 with the SAHA probe matrix was probed by western blot analysis. Lanes 1–3; identical expression levels of DNTTIP1 and HDAC1 in HeLa cells treated with aphidicolin (induces G1/S-phase arrest), nocodazole (induces arrest in mitosis) or vehicle. Lanes 4–9; increased amounts of DNTTIP1 is captured by the SAHA matrix from nocodazole-treated cells (lanes 6, 7) compared to aphidicolin (lanes 4, 5) or vehicle (lanes 8, 9). () Deacetylase activity assay of immunoaffinity-precipitated HDAC complexes demonstrates increased mitotic activity of a DNTTIP1-containing complex (MiDAC) but not of LSD1 (CoREST), MTA3 (NuRD) and SIN3A (Sin3)-containing complexes. Values are displayed as relative fluorescence units (RFU ± s.d.; N = 3; *P < 0.001 (Student's t-test)). The fluorescence signal is reduced to background by 10 μM trichostatin A. * Figure 5: Differential effects of HDAC inhibitors on histone and tubulin acetylation. Immunofluorescence analysis of histone H3 (K9ac/K14ac) and tubulin acetylation in HeLa cells treated for 4 h with vehicle, SAHA (10 μM), tacedinaline (50 μM), PCI-24781 (20 μM), PCI-34051 (100 μM), romidepsin (1 μM) or valproate (2mM). () Mapping of histone acetylation in K562 cells treated with HDAC inhibitors by LC-MS/MS. Cells were treated with TSA (10 μM), SAHA (5 μM), PCI-24781 (2 μM), tacedinaline (50 μM), romidepsin (1 μM), PCI-34051 (20 μM), bufexamac (100 μM) or valproate (2 mM) for 6 h. Histones were extracted from cells and acetylated peptides were quantified after isobaric tagging. () Heat map showing abundance of peptides with single or multiple acetylated lysines as dependent on inhibitor treatment. () Abundance of differently modified variants of the Histone H3.3 peptide 9-17 and the fully acetylated H4-peptide 5-19. Triplicate experiments were performed and error bars represent s.e.m. (Supplementary Data Set 6). * Figure 6: The nonsteroidal anti-inflammatory drug bufexamac is a novel class IIb HDAC inhibitor. () Screen of a focused compound library against HDACs 1, 2, 3 and 6 using a chemoproteomics binding assay with the SAHA matrix in whole cell extract from Jurkat and Ramos cells. The plots outline inhibition relative to HDAC1 for HDAC6, HDAC3 and HDAC2, as quantified by antibodies on dot-blot arrays. The compound concentration was 10 μM and chemical structures of selective hit compounds are shown. () HDAC selectivity profile of bufexamac in K562 cells, measured as outlined in Figure 1. () Treatment of HeLa cells with bufexamac elicits hyperacetylation of tubulin, whereas treatment with the o-aminoanilide AA-2 leads to hyperacetylation of histones. Cultured cells were treated with vehicle or drug for 4 h, and cells were analyzed by immunofluorescence microscopy and by western blot analysis using antibodies for acetylated tubulin (EC50 = 2.9 μM) and acetylated histones H3 (K9) and H4 (K5), respectively. () Treatment of peripheral blood mononuclear cells with bufexamac inhibit! s the secretion of IFN-α (EC50 = 8.9 ± 4.9 μM, three independent experiments). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions GenBank * 15345–15472 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Marcus Bantscheff & * Carsten Hopf Affiliations * Cellzome AG, Heidelberg, Germany. * Marcus Bantscheff, * Carsten Hopf, * Mikhail M Savitski, * Antje Dittmann, * Paola Grandi, * Anne-Marie Michon, * Judith Schlegl, * Yann Abraham, * Isabelle Becher, * Giovanna Bergamini, * Markus Boesche, * Manja Delling, * Birgit Dümpelfeld, * Dirk Eberhard, * Carola Huthmacher, * Toby Mathieson, * Daniel Poeckel, * Katja Strunk, * Gavain Sweetman, * Ulrich Kruse, * Gitte Neubauer & * Gerard Drewes * Cellzome Ltd., Chesterford Research Park, Cambridge, United Kingdom. * Valérie Reader & * Nigel G Ramsden Contributions A.D., D.E., A.-M.M., and K.S. performed biochemical and cell biological experiments; V.R. synthesized and sourced compounds; D.P. performed the interferon assay; I.B. analyzed histone modifications; B.D., M.D. and M. Boesche prepared peptide samples and operated mass spectrometers; M. Bantscheff, M.M.S., T.M. and G.S. established and conducted mass spectrometry data handling processes; M.M.S., Y.A., C. Huthmacher and J.S. contributed data analysis and visualization; M. Bantscheff, C. Hopf, P.G. and G.D. analyzed data, planned and supervised experiments, and conceptualized the project; G.B., U.K., G.N. and N.G.R. contributed ideas and supported the work; and M. Bantscheff and G.D. wrote the paper. Competing financial interests The authors are employees of Cellzome AG or Cellzome UK Ltd. These companies funded the work. Corresponding authors Correspondence to: * Marcus Bantscheff or * Gerard Drewes Author Details * Marcus Bantscheff Contact Marcus Bantscheff Search for this author in: * NPG journals * PubMed * Google Scholar * Carsten Hopf Search for this author in: * NPG journals * PubMed * Google Scholar * Mikhail M Savitski Search for this author in: * NPG journals * PubMed * Google Scholar * Antje Dittmann Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Grandi Search for this author in: * NPG journals * PubMed * Google Scholar * Anne-Marie Michon Search for this author in: * NPG journals * PubMed * Google Scholar * Judith Schlegl Search for this author in: * NPG journals * PubMed * Google Scholar * Yann Abraham Search for this author in: * NPG journals * PubMed * Google Scholar * Isabelle Becher Search for this author in: * NPG journals * PubMed * Google Scholar * Giovanna Bergamini Search for this author in: * NPG journals * PubMed * Google Scholar * Markus Boesche Search for this author in: * NPG journals * PubMed * Google Scholar * Manja Delling Search for this author in: * NPG journals * PubMed * Google Scholar * Birgit Dümpelfeld Search for this author in: * NPG journals * PubMed * Google Scholar * Dirk Eberhard Search for this author in: * NPG journals * PubMed * Google Scholar * Carola Huthmacher Search for this author in: * NPG journals * PubMed * Google Scholar * Toby Mathieson Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel Poeckel Search for this author in: * NPG journals * PubMed * Google Scholar * Valérie Reader Search for this author in: * NPG journals * PubMed * Google Scholar * Katja Strunk Search for this author in: * NPG journals * PubMed * Google Scholar * Gavain Sweetman Search for this author in: * NPG journals * PubMed * Google Scholar * Ulrich Kruse Search for this author in: * NPG journals * PubMed * Google Scholar * Gitte Neubauer Search for this author in: * NPG journals * PubMed * Google Scholar * Nigel G Ramsden Search for this author in: * NPG journals * PubMed * Google Scholar * Gerard Drewes Contact Gerard Drewes Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information Zip files * Supplementary Data (16.5M) Supplementary Data Sets 1–6 PDF files * Supplementary Text and Figures (4M) Supplementary Tables 1–5, Supplementary Synthetic Procedures and Supplementary Figs. 1–10 Additional data
• Generation of anterior foregut endoderm from human embryonic and induced pluripotent stem cells
  - Nat Biotech 29(3):267-272 (2011)
  Nature Biotechnology | Research | Letter Generation of anterior foregut endoderm from human embryonic and induced pluripotent stem cells * Michael D Green1 * Antonia Chen1 * Maria-Cristina Nostro2 * Sunita L d'Souza1 * Christoph Schaniel1 * Ihor R Lemischka1 * Valerie Gouon-Evans1 * Gordon Keller2 * Hans-Willem Snoeck1 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:267–272Year published:(2011)DOI:doi:10.1038/nbt.1788Received05 November 2010Accepted25 January 2011Published online27 February 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Directed differentiation of human embryonic stem (hES) cells and human induced pluripotent stem (hiPS) cells captures in vivo developmental pathways for specifying lineages in vitro, thus avoiding perturbation of the genome with exogenous genetic material. Thus far, derivation of endodermal lineages has focused predominantly on hepatocytes, pancreatic endocrine cells and intestinal cells1, 2, 3, 4, 5. The ability to differentiate pluripotent cells into anterior foregut endoderm (AFE) derivatives would expand their utility for cell therapy and basic research to tissues important for immune function, such as the thymus; for metabolism, such as thyroid and parathyroid; and for respiratory function, such as trachea and lung. We find that dual inhibition of transforming growth factor (TGF)-β and bone morphogenic protein (BMP) signaling after specification of definitive endoderm from pluripotent cells results in a highly enriched AFE population that is competent to be patterned a! long dorsoventral and anteroposterior axes. These findings provide an approach for the generation of AFE derivatives. View full text Figures at a glance * Figure 1: Induction of AFE markers in NOGGIN/SB-431542-treated definitive endoderm. () Expression of FOXA2, MIXL1, SOX17, SOX2 and CDX2 mRNA during activin A–mediated induction of definitive endoderm in hES cells. Data expressed as quantification of mRNA normalized to β-ACTIN (also known as ACTB), scaled proportionally to maximum induction. Cytokines were added as indicated on top of the figure (bar). () Representative flow cytometric analysis of definitive endodermal markers CXCR4, C-KIT and EPCAM at day 5 of activin A induction. Two biologically independent experiments are shown. () Expression of FOXA2, SOX2, CDX2, PAX9 and TBX1 mRNA on day 9 in cultures treated on day 5 after induction of definitive endoderm (see upper left panel), with the factors listed in the lower left panel (n = 3 biological replicates; *, significantly different from all other conditions, P < 0.0001; one-way ANOVA). d0, prior to start of differentiation; d5, day 5. () Expression of SOX2 and PAX9 on day 9 in cultures treated on day 5, after induction of definitive endoderm, with ! NOGGIN/SB-431542 (SB) in the presence or absence of sFRP3 (*, P < 0.05, n = 3 biological replicates). () Expression of BRACHYURY and PAX6 mRNA at day 9 in hES cells differentiated as previously described to neurectoderm (day 1 addition of NOGGIN/SB-431542), or after induction of endoderm (endoderm induction until day 5, followed by addition of NOGGIN/SB-431542). For BRAYCHURY, day 3.5 hES cells exposed to activin A and undergoing gastrulation served as a positive control (*, P < 0.0001, n = 3 experiments consisting each of three biological replicates). () Expression of ODD1, CDX2, EVX1, CREB313, CEBPA, TBX1, PAX9, SOX2 and FGF8 mRNA in day 9 cultures treated in parallel with either NOGGIN/SB-431542 or cultured in hepatic conditions after induction of definitive endoderm until day 5 (n = 3 experiments consisting each of three biological replicates). * Figure 2: Immunofluorescence analysis of NOGGIN/SB-431542-treated definitive endoderm. () Immunofluorescence for FOXA2, SOX2, CDX2, PAX9, FOXG1 and TBX1 of day 9 in HES2 definitive endoderm cultures treated on day 5 with NOGGIN/SB-431542. Scale bar, 50 μm (upper); 100 μm (lower). () Expression of FOXA2 and SOX2 in HFD9 hiPS cultures in the same conditions. Scale bar, 25 μm. * Figure 3: Functional characteristics of NOGGIN/SB-431542-induced AFE cells. () H/E staining of a teratoma derived after 5 weeks from HES2 transplanted under the kidney capsule of NOD/SCIDIl2rg−/− mice. The three right-hand panels show neurectoderm (neural rosette), endoderm (intestinal epithelium) and mesoderm (cartilage), respectively. Scale bar, 50 μ. () H/E staining of a growth arising 5 weeks after transplantation of NOGGIN/SB-431542-induced AFE cells derived from HES2 cells under the kidney capsule of immunocompromised mice. Scale bar, 50 μm. () Immunofluorescence analysis of the tissue from stained for FOXA2, PAX9, AIRE and SFTPC. Scale bar, 50 μm. () Expression of SOX2, NKX2.1, NKX2.5, PAX1 and P63 in HES2-derived cells generated in the two conditions schematically represented on top of the panel (n = 6 culture wells from two independent experiments; *, significantly different from NOGGIN/SB-431542; P < 0.05) WKFBE: WNT3a, KGF, FGF10, BMP4 and EGF. () Expression of NKX2.1, NKX2.5 and PAX1 in HES2-derived cells generated in the three co! nditions schematically represented on top of the panel (n = 4 to 6 culture wells from three independent experiments, *, significantly different from the other conditions; P < 0.05). () Expression of FOXA2 (green) and SOX2 (red) 2 d after treatment of activin A–induced definitive endoderm with NOGGIN/SB-431542 (blue, DAPI). Scale bar, 50 μm. () Schematic overview of the efficiency of induction of ventral AFE. WKFBE: WNT3a, KGF, FGF10, BMP4 and EGF. () Immunofluorescence for NKX2.1 in differentiated HDF9 hiPS cells after sequential treatment with activin A, NOGGIN/SB-431542 and WKFBE according to the scheme in . Scale bar, 50 μm. * Figure 4: Induction of lung and pharyngeal pouch markers from ventral AFE generated in vitro. () Expression of PAX1, NKX2.1, FOXP2, GATA6 and FOXJ1 in HES2-derived cells generated in the two conditions schematically represented on top of the panel (n = 4 to six culture wells from three independent experiments, *, significantly different from WKFBE conditions; P < 0.05). WKFBE: WNT3a, KGF, FGF10, BMP4 and EGF. () Induction of SFTPC and GCM2 mRNA in ventralized AFE in the presence of factors indicated in the figure. Author information * Author information * Supplementary information Affiliations * Department of Gene and Cell Medicine and Black Family Stem Cell Institute, Mount Sinai School of Medicine, New York, New York, USA. * Michael D Green, * Antonia Chen, * Sunita L d'Souza, * Christoph Schaniel, * Ihor R Lemischka, * Valerie Gouon-Evans & * Hans-Willem Snoeck * Division of Stem Cell and Developmental Biology and McEwen Centre for Regenerative Medicine, Ontario Cancer Institute, Toronto, Ontario, Canada. * Maria-Cristina Nostro & * Gordon Keller Contributions M.D.G. performed all experiments with assistance of A.C. M.-C.N., V.G.-E., S.L.S. and G.K. advised and assisted with induction of definitive endoderm. S.L.S., I.R.L. and C.S. generated and characterized the hiPS lines, respectively. M.D.G. and H.-W.S. designed the experiments and wrote the manuscript. Competing financial interests A patent application filed with the US Patent and Trade Office by M.G. and H.W.S. on the work reported in this article is pending. Corresponding author Correspondence to: * Hans-Willem Snoeck Author Details * Michael D Green Search for this author in: * NPG journals * PubMed * Google Scholar * Antonia Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Maria-Cristina Nostro Search for this author in: * NPG journals * PubMed * Google Scholar * Sunita L d'Souza Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Schaniel Search for this author in: * NPG journals * PubMed * Google Scholar * Ihor R Lemischka Search for this author in: * NPG journals * PubMed * Google Scholar * Valerie Gouon-Evans Search for this author in: * NPG journals * PubMed * Google Scholar * Gordon Keller Search for this author in: * NPG journals * PubMed * Google Scholar * Hans-Willem Snoeck Contact Hans-Willem Snoeck Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figs. 1–3 and Supplementary Table 1 Additional data
• Implantable magnetic relaxation sensors measure cumulative exposure to cardiac biomarkers
  - Nat Biotech 29(3):273-277 (2011)
  Nature Biotechnology | Research | Letter Implantable magnetic relaxation sensors measure cumulative exposure to cardiac biomarkers * Yibo Ling1, 2, 3, 8 * Terrence Pong1, 4, 5, 8 * Christophoros C Vassiliou2, 3, 8 * Paul L Huang4, 6 * Michael J Cima3, 7 * Affiliations * Contributions * Corresponding authorJournal name:Nature BiotechnologyVolume: 29,Pages:273–277Year published:(2011)DOI:doi:10.1038/nbt.1780Received23 November 2010Accepted18 January 2011Published online13 February 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Molecular biomarkers can be used as objective indicators of pathologic processes. Although their levels often change over time, their measurement is often constrained to a single time point. Cumulative biomarker exposure would provide a fundamentally different kind of measurement to what is available in the clinic. Magnetic resonance relaxometry can be used to noninvasively monitor changes in the relaxation properties of antibody-coated magnetic particles when they aggregate upon exposure to a biomarker of interest. We used implantable devices containing such sensors to continuously profile changes in three clinically relevant cardiac biomarkers at physiological levels for up to 72 h. Sensor response differed between experimental and control groups in a mouse model of myocardial infarction and correlated with infarct size. Our prototype for a biomarker monitoring device also detected doxorubicin-induced cardiotoxicity and can be adapted to detect other molecular biomarkers w! ith a sensitivity as low as the pg/ml range. View full text Figures at a glance * Figure 1: Evidence of cardiac biomarker extravasation from serum to the subcutaneous space. () cTnI, myoglobin and CK-MB serum profiles after LAD ligation are within the range of literature results and confirm the validity of the MI model used. Approximately 0.5 ml of blood was drawn from each subject, the serum extracted by centrifugation and biomarker levels measured by ELISA at the indicated times after LAD ligation. Results are averages (n = 4), with error bars omitted for uncluttered visualization. (–) Three experimental conditions were imposed: control (sensor implantation only), sham (sensor implantation and thoracotomy only) and MI (sensor implantation, thoracotomy and LAD ligation). Each biomarker extravasates, with MI groups exhibiting significantly elevated concentrations, as compared to the corresponding control and sham groups. Presumably, implantation-induced injury caused the low initial cTnI in the setting of high initial myoglobin and CK-MB. The similarity between sham and control groups indicates that any thoracotomy-induced biomarker release is! not significantly 'visible' in the sensor implant site. Extravasate samples were obtained by flushing the flank with 1 ml PBS at the indicated times after LAD ligation and measured using ELISA. Values are normalized within each panel to the maximum measured concentration. Results are averages ± s.e.m. (n = 4, normalized); P < 0.05 is indicated by black asterisks between MI/sham, red asterisks between MI/control and green asterisks between sham/control. * Figure 2: Use of functionalized MRSw particles, encapsulated within discrete sensors and calibrated in vitro, to measure cumulative exposure to analyte in vitro. () The sensor consists of a reservoir containing MRSw particles enclosed by a size-exclusion membrane. T2 changes are produced when analytes diffuse across the membrane and initiate particle aggregation. (–) Sensor response as a function of analyte concentration was calibrated to match expected in vivo concentrations. The measurements were acquired after an incubation time of 72 h for cTnI and 24 h for myoglobin and CK-MB sensors to match the expected duration of elevation for the respective biomarkers. Results are averages ± 95% confidence intervals (n = 4). () Characterization of sensor saturation with exposure to constant concentration profiles. Devices were maintained in a constant concentration of myoglobin solution and the relaxation time T2 was measured every 20 min. The time to saturation depends on the concentration. All of the devices, with the exception of the control, show a similar response and saturate at the same T2 value. The total exposure of the device t! o myoglobin (measured in units of [μg·h/ml]) is defined as the area under the concentration versus time curve up until the measurement time. () Exposure to constant and temporal concentration profiles demonstrate that MRSw sensors function as dosimeters. Plot of T2 versus the constant exposure profiles obtained from are shown as curves. The symbols represent the average T2 of devices exposed to various temporal concentration profiles shown inset. The curves and symbols lie on top of each other, demonstrating that the response depends exclusively on exposure. Most points have deviations smaller than the symbol size. Measurements were made after several hours of incubation at zero concentration. * Figure 3: Sensor response differs markedly between MI and sham/control groups, and its magnitude correlates with the extent of infarction. () A T2 map (color bar on the right) superimposed on T2 -weighted images of myoglobin sensors demonstrates the feasibility of MRI-based in situ measurements after 24 h implantation with (MI) or without (control) concomitant LAD ligation at the time of sensor implantation. The images show that the sensors can be measured in either the axial or the transverse plane. () The T2 of explanted sensors, as measured by single-sided proton relaxometry (after 72 h implantation for cTnI and 24 h for myoglobin and CK-MB), from the MI group are significantly higher (* indicates P < 0.05 using the Wilcoxon rank-sum two-sided test) than from the control/sham groups for all three biomarkers. Increases in the T2 of myoglobin and CK-MB sensors for both control and sham groups were expected and consistent with the extravasation results. Results are averages ± 95% confidence intervals (n = 36; 6 sensors/subject and 6 subjects/group). (–) T2 change of the same explanted sensors from , if disag! gregated into the individual subjects and replotted as a function of infarct size, correlates positively with infarct size for all three cardiac biomarkers. The cumulative release of biomarkers from the infarcted myocardium generates the final T2 sensor value. This characteristic may contribute to the correspondence between sensor reading and infarct size. Results are averages ± 95% confidence intervals (n = 6 sensors/subject). * Figure 4: An implanted MRSw sensor device can detect the cardiotoxic effect of the chemotherapeutic drug doxorubicin in vivo. () Doxorubicin induces a significant (* indicates P < 0.05) increase in serum myoglobin (ELISA measurements). Results are averages ± 95% confidence intervals (n = 4). Wilcoxon rank-sum two-sided tests were used to test for statistical significance. () Myoglobin sensors explanted (after 72 h) from a doxorubicin-administered group show significant increases in T2 over those from a control group. Results are averages ± 95% confidence intervals (n = 16; 4 sensors/subject and 4 subjects/group). Author information Primary authors * These authors contributed equally to this work. * Yibo Ling, * Terrence Pong & * Christophoros C Vassiliou Affiliations * Harvard-MIT Division of Health Sciences & Technology, Cambridge, Massachusetts, USA. * Yibo Ling & * Terrence Pong * Department of Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Yibo Ling & * Christophoros C Vassiliou * The David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Yibo Ling, * Christophoros C Vassiliou & * Michael J Cima * Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA. * Terrence Pong & * Paul L Huang * School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA. * Terrence Pong * Cardiology Division, Harvard Medical School, Boston, Massachusetts, USA. * Paul L Huang * Department of Materials Science & Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Michael J Cima Contributions Y.L. initiated the project, designed and performed experiments, analyzed data and wrote the manuscript. T.P. conceived experiments, designed and performed animal experiments, analyzed data and wrote the manuscript. C.C.V. contributed ideas, performed experiments, analyzed data and wrote the manuscript. P.L.H. contributed to the design experiments related to clinical relevance, doxorubicin toxicity and myocardial infarction model. M.J.C. was the principal investigator; he initiated the project, conceived experiments and obtained funding. Competing financial interests M.J.C. is a director at T2 Biosystems, a company developing in vitro diagnostic assays. Corresponding author Correspondence to: * Michael J Cima Author Details * Yibo Ling Search for this author in: * NPG journals * PubMed * Google Scholar * Terrence Pong Search for this author in: * NPG journals * PubMed * Google Scholar * Christophoros C Vassiliou Search for this author in: * NPG journals * PubMed * Google Scholar * Paul L Huang Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Cima Contact Michael J Cima Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• A functionally characterized test set of human induced pluripotent stem cells
  - Nat Biotech 29(3):279-286 (2011)
  Nature Biotechnology | Research | Resources A functionally characterized test set of human induced pluripotent stem cells * Gabriella L Boulting1, 2, 3, 12 * Evangelos Kiskinis1, 2, 12 * Gist F Croft4, 5, 12 * Mackenzie W Amoroso4, 5, 12 * Derek H Oakley4, 5, 12 * Brian J Wainger6, 7, 8 * Damian J Williams9 * David J Kahler10 * Mariko Yamaki1, 2 * Lance Davidow2 * Christopher T Rodolfa3 * John T Dimos3, 11 * Shravani Mikkilineni2, 3 * Amy B MacDermott9 * Clifford J Woolf6, 7 * Christopher E Henderson4, 5 * Hynek Wichterle4, 5 * Kevin Eggan1, 2, 3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature BiotechnologyVolume: 29,Pages:279–286Year published:(2011)DOI:doi:10.1038/nbt.1783Received28 October 2010Accepted19 January 2011Published online03 February 2011Corrected online11 February 2011 Abstract * Abstract * Change history * 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 Human induced pluripotent stem cells (iPSCs) present exciting opportunities for studying development and for in vitro disease modeling. However, reported variability in the behavior of iPSCs has called their utility into question. We established a test set of 16 iPSC lines from seven individuals of varying age, sex and health status, and extensively characterized the lines with respect to pluripotency and the ability to terminally differentiate. Under standardized procedures in two independent laboratories, 13 of the iPSC lines gave rise to functional motor neurons with a range of efficiencies similar to that of human embryonic stem cells (ESCs). Although three iPSC lines were resistant to neural differentiation, early neuralization rescued their performance. Therefore, all 16 iPSC lines passed a stringent test of differentiation capacity despite variations in karyotype and in the expression of early pluripotency markers and transgenes. This iPSC and ESC test set is a robust! resource for those interested in the basic biology of stem cells and their applications. View full text Figures at a glance * Figure 1: Characterization of pluripotency in the test set of iPSC lines. iPSC colonies were morphologically identical to ESC colonies and expressed the pluripotency markers NANOG and TRA-1-60, unlike the patient fibroblasts from which they were derived. FB, fibroblasts. Scale bars, 200 μm. iPSC lines showed cell cycle profiles similar to those of ESCs and different from their parental fibroblasts. The percentage of cells at different stages of the cell cycle was determined by propidium iodide staining and flow cytometry. The percentage of cells in S, G2 and M phase was determined for each cell line and then averaged for each category. ***P < 0.001, mean ± s.d. Like ESCs, iPSC lines generated cell types of all three embryonic germ layers (endoderm, AFP; mesoderm, α-SMA; ectoderm, TUJ1) in vitro, as embryoid bodies (, EBs; scale bars, 100 μm), and when injected into mouse kidney capsules and allowed to form teratomas in vivo (; scale bars, 50 μm). Representative images of H&E-stained sections are shown for lines 11b and 27e. Glands and goble! t cells (endoderm), cartilage and muscle (mesoderm), pigmented neural epithelium and neural rosettes (ectoderm) are shown in the top and bottom panels, respectively, for both lines. Summary chart depicting assays by which iPSC lines in the test set were characterized. Pluripotency assays for 29A and B were previously published2. * Figure 2: iPSCs show similar capacity for directed motor neuron differentiation compared to ESCs. Protocol for directed differentiation of human stem cell lines into motor neurons. Cells were differentiated as embryoid bodies from day 0–29 in media formulations containing morphogens, including retinoic acid (RA), a small molecule agonist of the sonic hedgehog pathway (HAg) and neurotrophic factors BDNF, GDNF and CNTF. Embryoid bodies were dissociated and single cells plated for adherent culture on day 29. On day 32 cultures were analyzed. NIM, neural induction medium. Representative immunostaining results for iPSC (18c) and ESC (HuES-6) cultures show many ISL+ TUJ1+ motor neurons (scale bars, 50 μm). The percentage of all nuclei that were ISL+ was quantified from differentiations performed independently in the Eggan and PALS laboratories. Data sets from lines differentiated in both laboratories are compared here, are highly similar and have reproducible, characteristic percent ISL+ efficiencies. 29e and 27e did not differentiate efficiently in either laboratory. Hu-! 13, HuES-13; Hu-3, HuES-3. Efficiency of motor neuron differentiation was also measured by an alternative marker of motor neuron identity, HB9 (scale bars, 50 μm). Many ISL+ motor neurons were also ChAT+, indicating proper maturation toward a cholinergic transmitter phenotype (scale bar, 50 μm). iPSC lines from control and ALS patients differentiated into ISL+ motor neurons with similar efficiencies , as did ESCs and iPSCs . The percentages of HB9+ nuclei were compared for a subset of iPSC lines and HuES-13. Although comparisons again suggest donor- or line-specific differences, iPSC lines were overall equally capable of generating HB9+ motor neurons as HuES-13 (mean ± s.d.). Percent ISL+ data from both laboratories were pooled for each iPSC and ESC line, and comparisons between lines showed generally similar performance, with significant differences between iPSC line 18c and iPSC lines 11a and 11c (P < 0.05). Hu, HuES. * Figure 3: ESC- and iPSC-derived neurons are physiologically active. Images of iPSC 11a–derived neurons filled with Fura Red AM and Fluo-4 AM dyes. The Fura Red channel is shown. The field illustrated is that imaged in . Activity of labeled cells is represented in and . Scale bar, 100 μm. ISL immunostaining of 11a field in showing ISL+ neurons (star) and ISL- neurons (arrow). Spontaneous electrical activity in cultured iPSC-derived neurons visualized by a 'subtracted image' that shows the difference in pixel intensities between two images acquired 1.7 s apart in the Fluo-4 channel. Higher gray values represent increased pixel intensity. Identically exposed pseudocolored averages of ten Fluo-4 AM images taken during the control period before addition of kainic acid (KA) , after treatment with 100 μM KA , after washing following KA administration and after treatment with 50 μM KCl . Warmer colors represent increased fluorescence intensity. Plot of Fluo-4/Fura Red intensity ratio in the somata of the two cells indicated by the star and ! arrow in ; only starred cell shows spontaneous activity. Fluo-4/Fura Red intensity ratio of cells in during sequential administration of KA and KCl indicated by bars above graph. Examples of Fluo-4/Fura Red ratios from cell bodies of single spontaneously active cells in cultures of ESC RUES1–derived neurons, and iPSC 11a–, 18a–, 18c– and 27b–derived neurons as well as one example of a nonresponsive (NR), nonactive cell in an RUES1 culture. Response of cells in j to KA and KCl. Sample voltage-clamp traces from ESC and iPSC 18a–derived neurons. Blowup of an iPSC 27b–derived neuron recording reveals typical sodium currents (left), which are blocked by 500 nM TTX (right). Current-clamp recordings of single action potentials in ESC and iPSC 27b–derived neurons as well as multiple action potentials in an iPSC 18a–derived neuron. * Figure 4: Persistent transgene expression does not inhibit differentiation. qRT-PCR was used to measure relative levels of transcript from endogenous genes 'e' and viral transgenes 'v' of the reprogramming factors OCT4 and KLF4 in undifferentiated iPSCs and ESCs, and in day 32 neuron cultures. Transgene expression or silencing in the undifferentiated cells is maintained after differentiation. Relative levels in undifferentiated HuES-3 were set as 1. FB, fibroblasts. Day 32 motor neuron cultures were co-stained for ISL and OCT4. HuES-3– and iPSC 17a–derived cultures, which do not express viral OCT4, did not stain for OCT4. However, iPSC 15b–derived cultures, which do express viral OCT4, contained many OCT4+ ISL+ motor neurons and OCT4+ISL− cells. Arrow, OCT4+ ISL+; arrowhead, OCT4+ ISL−; chevron, OCT4− ISL+. Scale bars, 50 μm. * Figure 5: Suboptimal iPSC lines can be rescued using SMAD inhibition. During standard differentiation, iPSC lines 27e and 29e showed abnormal embryoid body morphology and survival compared to lines that behaved normally (HuES-3 and 29d shown); phase scale bar, 500 μm; DNA scale bar, 129 μm. Although embryoid bodies from iPSC line 11b had typical morphology, day 32 cultures showed decreased neuronal TUJ1 staining compared to all other normal lines (HuES-13 and iPSC 18a shown), scale bar, 129 μm. Representative phase and immunostaining images for previously defective iPSC lines 29e, 11b, and control ESC lines HuES-3 and HuES-3-hb9:GFP. Phase image scale bars are 500 μm, immunostaining image scale bars are 100 μm. Quantification of immunostaining in differentiated cultures derived from the three previously problematic iPSC lines (11b, 27e, 29e) and ESC controls; percentage of TUJ1+ cells ; percentage of ISL+ cells ; and percentage of HB9+ cells . Mean ± s.e.m. Change history * Abstract * Change history * Author information * Supplementary informationCorrigendum 11 February 2011In the version of this article initially published online, a funder was inadvertently omitted from the Acknowledgments. The error has been corrected for the print, PDF and HTML versions of this article. Author information * Abstract * Change history * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Gabriella L Boulting, * Evangelos Kiskinis, * Gist F Croft, * Mackenzie W Amoroso & * Derek H Oakley Affiliations * The Howard Hughes Medical Institute, Cambridge, Massachusetts, USA. * Gabriella L Boulting, * Evangelos Kiskinis, * Mariko Yamaki & * Kevin Eggan * Harvard Stem Cell Institute, Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA. * Gabriella L Boulting, * Evangelos Kiskinis, * Mariko Yamaki, * Lance Davidow, * Shravani Mikkilineni & * Kevin Eggan * Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA. * Gabriella L Boulting, * Christopher T Rodolfa, * John T Dimos, * Shravani Mikkilineni & * Kevin Eggan * Project A.L.S./Jenifer Estess Laboratory for Stem Cell Research, Columbia University, New York, New York, USA. * Gist F Croft, * Mackenzie W Amoroso, * Derek H Oakley, * Christopher E Henderson & * Hynek Wichterle * Departments of Pathology, Neurology and Neuroscience, Columbia University, Center for Motor Neuron Biology and Disease (MNC), and Columbia Stem Cell Initiative (CSCI), New York, New York, USA. * Gist F Croft, * Mackenzie W Amoroso, * Derek H Oakley, * Christopher E Henderson & * Hynek Wichterle * Program in Neurobiology and FM Kirby Neurobiology Center, Children's Hospital Boston, Boston, Massachusetts, USA. * Brian J Wainger & * Clifford J Woolf * Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, USA. * Brian J Wainger & * Clifford J Woolf * Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA. * Brian J Wainger * Departments of Physiology and Cellular Biophysics, and Neuroscience, Columbia University, New York, New York, USA. * Damian J Williams & * Amy B MacDermott * The New York Stem Cell Foundation, Inc. (NYSCF), New York, New York, USA. * David J Kahler * Present address: iPierian, Inc., South San Francisco, California, USA. * John T Dimos Contributions G.F.C., M.W.A. and D.H.O. maintained human fibroblasts. C.T.R. and J.T.D. reprogrammed all iPSC lines. G.L.B. and E.K. expanded all iPSC lines. G.L.B. and E.K. led and contributed equally to all other experiments and analyses in the Eggan laboratory. G.F.C., M.W.A. and D.H.O. led and contributed equally to all other experiments and analyses in the Project ALS laboratory. D.J.K. did FC analysis. A.B.M., D.J.W. and D.H.O. designed and carried out Ca2+ imaging. B.J.W., G.L.B. and C.J.W. did recordings. M.Y. assisted with teratomas. L.D. assisted with quantitative analysis. S.M. assisted with stem cell culture. G.L.B., E.K., K.E., G.F.C., M.W.A., D.H.O., C.E.H. and H.W. conceived the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Kevin Eggan or * Hynek Wichterle Author Details * Gabriella L Boulting Search for this author in: * NPG journals * PubMed * Google Scholar * Evangelos Kiskinis Search for this author in: * NPG journals * PubMed * Google Scholar * Gist F Croft Search for this author in: * NPG journals * PubMed * Google Scholar * Mackenzie W Amoroso Search for this author in: * NPG journals * PubMed * Google Scholar * Derek H Oakley Search for this author in: * NPG journals * PubMed * Google Scholar * Brian J Wainger Search for this author in: * NPG journals * PubMed * Google Scholar * Damian J Williams Search for this author in: * NPG journals * PubMed * Google Scholar * David J Kahler Search for this author in: * NPG journals * PubMed * Google Scholar * Mariko Yamaki Search for this author in: * NPG journals * PubMed * Google Scholar * Lance Davidow Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher T Rodolfa Search for this author in: * NPG journals * PubMed * Google Scholar * John T Dimos Search for this author in: * NPG journals * PubMed * Google Scholar * Shravani Mikkilineni Search for this author in: * NPG journals * PubMed * Google Scholar * Amy B MacDermott Search for this author in: * NPG journals * PubMed * Google Scholar * Clifford J Woolf Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher E Henderson Search for this author in: * NPG journals * PubMed * Google Scholar * Hynek Wichterle Contact Hynek Wichterle Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin Eggan Contact Kevin Eggan Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information Movies * Supplementary Video 1 (18.8M) Spontaneous activity in iPS 18c-derived motor neurons. PDF files * Supplementary Text and Figures (3.5M) Supplementary Tables 1–7, Supplementary Figs. 1–8 and Supplementary Methods Additional data
• A mentoring program for women scientists meets a pressing need
  - Nat Biotech 29(3):287-288 (2011)
  Nature Biotechnology | Careers and Recruitment A mentoring program for women scientists meets a pressing need * Masha Fridkis-Hareli1Journal name:Nature BiotechnologyVolume: 29,Pages:287–288Year published:(2011)DOI:doi:10.1038/nbt.1799Published online09 March 2011 An innovative program supports the career development of women scientists in academia and industry. 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 * Masha Fridkis-Hareli is president of the Massachusetts chapter of the Association for Women in Science (MASS-AWIS) and an associate scientific director at Taligen Therapeutics (acquired by Alexion Pharmaceuticals), Cambridge, Massachusetts, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Masha Fridkis-Hareli Author Details * Masha Fridkis-Hareli Contact Masha Fridkis-Hareli Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• People
  - Nat Biotech 29(3):290 (2011)
  Nature Biotechnology | Careers and Recruitment | People People Journal name:Nature BiotechnologyVolume: 29,Page:290Year published:(2011)DOI:doi:10.1038/nbt.1818Published online09 March 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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. AlloCure (Burlington, MA, USA) has announced the appointment of (below, right) as chief business officer. He joins the company with more than 20 years of experience in business development and corporate partnering for emerging pharmaceutical companies, most recently leading business development efforts at Vitae Pharmaceuticals. "Kevin Heyeck has a very impressive track record in business development, and he has been responsible for many major partnerships with large pharmaceutical and biotechnology companies worldwide," says AlloCure president and CEO Robert M. Brenner. "Kevin's arrival marks an important milestone in AlloCure's evolution as we advance into later stage clinical development and chart the course for future commercialization of our novel treatment for acute kidney injury." has been appointed chief medical officer and a member of the management board of Noxxon Pharma (Berlin). He joins the company from Focus Clinical Drug Development, where he served as CSO and managing director. Alios BioPharma (S. San Francisco, CA, USA) has named (right) to the position of chief medical officer. Brosgart joins Alios from Children's Hospital & Research Center (Oakland, CA, USA) where she served as senior vice president and chief medical officer. Previously, she served in several senior management roles at Gilead Sciences including vice president, public health and policy, vice president, clinical research and vice president, medical affairs. View full text Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Biotechnology for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Rent this article from DeepDyve * Login via Athens * Purchase a site license * Institutional access * 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